The burden of traumatic brain injury from low-energy falls among patients from 18 countries in the CENTER-TBI Registry: A comparative cohort study

Fiona E Lecky; Olubukola Otesile; Carl Marincowitz; Marek Majdan; Daan Nieboer; Hester F Lingsma; Marc Maegele; Giuseppe Citerio; Nino Stocchetti; Ewout W Steyerberg; David K Menon; Andrew I R Maas; CENTER-TBI Participants and Investigators

doi:10.1371/journal.pmed.1003761

. 2021 Sep 14;18(9):e1003761. doi: 10.1371/journal.pmed.1003761

The burden of traumatic brain injury from low-energy falls among patients from 18 countries in the CENTER-TBI Registry: A comparative cohort study

Fiona E Lecky ^1,^2,^*, Olubukola Otesile ¹, Carl Marincowitz ¹, Marek Majdan ³, Daan Nieboer ⁴, Hester F Lingsma ⁴, Marc Maegele ⁵, Giuseppe Citerio ^6,⁷, Nino Stocchetti ^8,⁹, Ewout W Steyerberg ^4,¹⁰, David K Menon ¹¹, Andrew I R Maas ^12,¹³; CENTER-TBI Participants and Investigators^¶

Editor: Martin Schreiber¹⁴

¹Centre for Urgent and Emergency Care Research, Health Services Research Section, School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom

²Emergency Department, Salford Royal Hospital, Salford, United Kingdom

³Department of Public Health, University of Trnava, Trnava, Slovakia

⁴Department of Public Health, Erasmus University Medical Center, Rotterdam, Netherlands

⁵Institute for Research in Operative Medicine, Witten/Herdecke University, Köln, Germany

⁶Neurointensive Care, Azienda Socio Sanitaria Territoriale di Monza, Monza, Italy

⁷School of Medicine and Surgery, Università degli Studi di Milano–Bicocca, Milan, Italy

⁸Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy

⁹Neuroscience Intensive Care Unit, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Milan, Italy

¹⁰Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands

¹¹University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom

¹²Department of Neurosurgery, Antwerp University Hospital, Edegem, Belgium

¹³University of Antwerp, Edegem, Belgium

¹⁴Oregon Health and Science University, UNITED STATES

I have read the journal’s policy and the authors of this manuscript have the following competing interests: DM reports grants, personal fees and non-financial support from GlaxoSmithKline, grants and personal fees from NeuroTrauma Sciences, personal fees from Pfizer Ltd, personal fees from PressuraNeuro, grants and personal fees from Lantmannen AB, grants and personal fees from Integra, outside the submitted work;DM is an Academic Editor on PLOS Medicine’s editorial board. AM reports grants from European Union Framework 7, grants from Integra Life Sciences, grants from Hannelore Kohl Stiftung, grants from Neurotrauma Sciences, grants from BioDirection, during the conduct of the study; personal fees from PressuraNeuro, personal fees from Integra LifeSciences, personal fees from NeuroTrauma Sciences, outside the submitted work;. F L reports grants from EU Framework 7, during the conduct of the study; grants from Trauma Audit and Research Network, outside the submitted work; there are no other relationships or activities that could appear to have influenced the submitted work. There are no other author competing interests.

¶ Membership of CENTER-TBI Participants and Investigators is provided in the Acknowledgements.

^✉

* E-mail: f.e.lecky@sheffield.ac.uk

Roles

Fiona E Lecky: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing

Olubukola Otesile: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing

Carl Marincowitz: Conceptualization, Formal analysis, Methodology, Validation, Writing – review & editing

Marek Majdan: Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Daan Nieboer: Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Hester F Lingsma: Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Writing – review & editing

Marc Maegele: Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Giuseppe Citerio: Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Nino Stocchetti: Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Ewout W Steyerberg: Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Writing – review & editing

David K Menon: Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing – review & editing

Andrew I R Maas: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

Martin Schreiber: Academic Editor

PMCID: PMC8509890 PMID: 34520460

Abstract

Background

Traumatic brain injury (TBI) is an important global public health burden, where those injured by high-energy transfer (e.g., road traffic collisions) are assumed to have more severe injury and are prioritised by emergency medical service trauma triage tools. However recent studies suggest an increasing TBI disease burden in older people injured through low-energy falls. We aimed to assess the prevalence of low-energy falls among patients presenting to hospital with TBI, and to compare their characteristics, care pathways, and outcomes to TBI caused by high-energy trauma.

Methods and findings

We conducted a comparative cohort study utilising the CENTER-TBI (Collaborative European NeuroTrauma Effectiveness Research in TBI) Registry, which recorded patient demographics, injury, care pathway, and acute care outcome data in 56 acute trauma receiving hospitals across 18 countries (17 countries in Europe and Israel). Patients presenting with TBI and indications for computed tomography (CT) brain scan between 2014 to 2018 were purposively sampled. The main study outcomes were (i) the prevalence of low-energy falls causing TBI within the overall cohort and (ii) comparisons of TBI patients injured by low-energy falls to TBI patients injured by high-energy transfer—in terms of demographic and injury characteristics, care pathways, and hospital mortality. In total, 22,782 eligible patients were enrolled, and study outcomes were analysed for 21,681 TBI patients with known injury mechanism; 40% (95% CI 39% to 41%) (8,622/21,681) of patients with TBI were injured by low-energy falls. Compared to 13,059 patients injured by high-energy transfer (HE cohort), the those injured through low-energy falls (LE cohort) were older (LE cohort, median 74 [IQR 56 to 84] years, versus HE cohort, median 42 [IQR 25 to 60] years; p < 0.001), more often female (LE cohort, 50% [95% CI 48% to 51%], versus HE cohort, 32% [95% CI 31% to 34%]; p < 0.001), more frequently taking pre-injury anticoagulants or/and platelet aggregation inhibitors (LE cohort, 44% [95% CI 42% to 45%], versus HE cohort, 13% [95% CI 11% to 14%]; p < 0.001), and less often presenting with moderately or severely impaired conscious level (LE cohort, 7.8% [95% CI 5.6% to 9.8%], versus HE cohort, 10% [95% CI 8.7% to 12%]; p < 0.001), but had similar in-hospital mortality (LE cohort, 6.3% [95% CI 4.2% to 8.3%], versus HE cohort, 7.0% [95% CI 5.3% to 8.6%]; p = 0.83). The CT brain scan traumatic abnormality rate was 3% lower in the LE cohort (LE cohort, 29% [95% CI 27% to 31%], versus HE cohort, 32% [95% CI 31% to 34%]; p < 0.001); individuals in the LE cohort were 50% less likely to receive critical care (LE cohort, 12% [95% CI 9.5% to 13%], versus HE cohort, 24% [95% CI 23% to 26%]; p < 0.001) or emergency interventions (LE cohort, 7.5% [95% CI 5.4% to 9.5%], versus HE cohort, 13% [95% CI 12% to 15%]; p < 0.001) than patients injured by high-energy transfer. The purposive sampling strategy and censorship of patient outcomes beyond hospital discharge are the main study limitations.

Conclusions

We observed that patients sustaining TBI from low-energy falls are an important component of the TBI disease burden and a distinct demographic cohort; further, our findings suggest that energy transfer may not predict intracranial injury or acute care mortality in patients with TBI presenting to hospital. This suggests that factors beyond energy transfer level may be more relevant to prehospital and emergency department TBI triage in older people. A specific focus to improve prevention and care for patients sustaining TBI from low-energy falls is required.

In a cohort study, Fiona Lecky and colleagues investigate the factors associated with traumatic brain injury resulting from low energy falls compared with injuries from high energy transfer mechanisms among patients across Europe and Israel.

Author summary

Why was this study done?

Traumatic brain injury (TBI) poses a huge global disease burden, considered to mainly result from high-energy transfer mechanisms such as road traffic collisions, sports, falls from a height, and interpersonal violence.
People injured through low-energy transfer (ground- or low-level falls) are considered less likely to sustain significant TBI, so can be given lower priority for acute specialist care within emergency medical services (triage decisions).
Recent multinational studies challenge these assumptions by identifying falls as an important TBI causal mechanism—but these studies seldom describe fall height.
The lack of clarity concerning the low-energy TBI disease burden hampers effective prevention and clinical management.

What did the researchers do and find?

We studied 21,681 patients with TBI presenting to 56 hospital emergency departments across Europe and Israel using an efficient registry methodology enabling a real-world approach.
We found that the 40% of patients with TBI who were injured through low-energy falls were significantly older, more likely to be female, and more likely to be taking pre-injury drugs that prevent blood clotting than patients with TBI sustained through high-energy transfer.
Despite similar rates of significant injury on the CT brain scan and of dying in hospital, patients injured through low-energy falls were half as likely to receive critical care or emergency intervention compared to those injured by high-energy transfer.

What do these findings mean?

Low-energy falls contribute to a significant portion of the TBI disease burden, which will increase as the global population ages.
In older people, the assumption that energy transfer predicts brain injury severity and threat to life appears to lack validity.
Factors beyond energy transfer level may be more relevant to prehospital and emergency department TBI triage in older people. The appropriateness of providing less intensive acute hospital care after low-energy TBI requires further study.
Reduction of TBI disease burden requires specific prevention and therapy initiatives targeted at low-energy TBI.

Introduction

Traumatic brain injury (TBI) is a complex, imperfectly understood global disease [1], defined as ‘an alteration in brain function, or other evidence of brain pathology, caused by an external force’ [2]. This external force transfers mechanical energy to the brain to a degree that impairs its capacity for normal functioning, with the extent of injury varying with impact energy level [3–5]. Injury classification by energy transfer mechanism (high-energy transfer most commonly results from road traffic collisions, falling from a height, blunt assault, or contact sports while low-energy transfer results from low-level falls or those from a standing height [6–8]) has received broad attention in general trauma care and informs emergency medical service (EMS) on-scene trauma triage [3,8,9], with patients injured by high-energy transfer mechanisms being conveyed to higher levels of care within specialist trauma centres. High-energy transfer mechanisms are also the major focus of injury prevention and safety initiatives. This prioritisation is underpinned by an assumption that high-energy transfer is more likely to result in tissue damage that is potentially life-threatening or life-altering. Hence, the TBI disease burden is traditionally attributed to high-energy transfer mechanisms, with patients with TBI historically being described in terms of the presenting Glasgow Coma Scale (GCS; measure of consciousness level) [10] and head CT findings [11]—using International Classification of Diseases codes [12], the Abbreviated Injury Scale (AIS) [13], or the Marshall classification system [14]—rather than by energy transfer level.

Recent studies challenge the paradigm of prioritising high-energy transfer mechanisms as the best strategy for reducing TBI disease burden. Falls are now the leading cause of TBI in Europe and other high-income countries—particularly in older people [7,15–20]. Not only are older people more likely to sustain a low-level fall, but age-related changes to the brain and blood vessels increase the likelihood of a consequent significant intracranial injury and decrease recovery potential. However, most published TBI series do not differentiate high- from low-energy-transfer falls. A specific focus on low-energy TBI disease burden is required, and the appropriateness of current injury prevention, EMS, and trauma centre triage priorities should be addressed.

The CENTER-TBI (Collaborative European NeuroTrauma Effectiveness Research in TBI) Registry aims to address the entire spectrum of TBI to increase our understanding of the most complex disease in the most complex organ [21–23]. It was established alongside core data collection, aiming to capture ‘real world’ data in large numbers of individuals to inform improvements in clinical management and injury prevention [24].

The aim of this study is to assess the TBI disease burden attributable to low-energy mechanisms by determining the prevalence of low-energy transfer as a causal mechanism for TBI and comparing—by causal energy level—the demographic, injury, acute care pathway, and early outcome characteristics of patients with TBI who presented to CENTER-TBI Registry recruiting hospitals in Europe and Israel.

Methods

We established a prospective CENTER-TBI Registry in 56 participating centres across 18 countries (17 in Europe and Israel; S8 Table). The study enrolled patients presenting between 1 December 2014 and 31 January 2018 (S1 Fig). TBI patient advocacy groups contributed to study design and conduct through the study advisory board, facilitated by a dedicated section on the study website. We conducted a comparative cohort study between patients injured through low-energy falls and those injured by higher energy transfer mechanisms.

Inclusion and exclusion criteria

The CENTER-TBI Registry included patients of all ages with a suspected or clinical diagnosis of TBI in whom computed tomography (CT) brain scan was conducted [23]. There were no exclusion criteria for recruitment. In particular, the registry included patients with pre-existing cognitive impairment such as dementia, severely injured patients who died in the emergency department (ED) resuscitation room prior to imaging, and patients presenting more than 24 hours after injury. These 3 groups were excluded from recruitment to the separate CENTER-TBI core cohort study of 4,509 patients within study centres. Recruitment to the core and registry were mutually exclusive [24].

Data collection procedures for the CENTER-TBI Registry

Clinical data were collated over a 37-month period. No specific study interventions were performed. Study research teams were notified on arrival of eligible patients or identified these by screening their sites’ radiology imaging directories and ED records. Eligible patients’ registry variables were collated from the clinical record after the patient had been discharged (or died), and were entered into the electronic case report form. This registry methodology enabled data to be collected in batches to increase efficiency and reduce cost. Sampling was purposive; training was provided that study teams should include a representative sample of patients with TBI presenting within specific 24-hour periods (with the selected 24-hour periods covering equally the different weekdays and seasons of the year). No patient identifiers were stored. The CENTER-TBI Registry data are stored on a secure database, hosted by the International Neuroinformatics Coordinating Facility in Stockholm, Sweden. Data curation was conducted by the CENTER-TBI Registry Work Package lead centre (FEL and OO).

Case report form variables

We collected variables describing demographics (age and sex), pre-existing health status [25] including pre-injury anticoagulant and antiplatelet use, mechanism of injury, injury severity descriptors (GCS and AIS), presenting physiological vital signs (blood pressure, oxygen saturation, and pupillary responses), radiologically reported CT brain findings (classified as presence or absence of small or large epidural haematoma/acute subdural haematoma/brain contusion, subarachnoid haemorrhage, midline shift, basal cistern compression, and individual patient Marshall grading of CT findings [14]), processes of care (intubation status prior to arrival at study centre, method of referral to study centre [direct from scene versus secondary transfer from a referring hospital], time from study hospital arrival to CT brain scan, intensive care unit [ICU] admission, and key emergency interventions, i.e. craniotomy, intracranial pressure monitoring, decompressive craniectomy, external limb fixation, emergency laparotomy, thoracotomy, and extraperitoneal pelvic packing), and immediate outcome of care in terms of hospital mortality, length of stay (or time to death, where this occurred), and destination on discharge (own home, nursing home, another hospital, or rehabilitation centre). These variables were derived from the Utstein trauma template used for standard trauma registry collection across Europe, North America, and Australasia [26]. Patients were described in terms of 1 of 3 clinical care pathways after presentation, triage, and CT brain scan: discharge home or direct to the mortuary from the ED, admission to the hospital but not to the ICU, or admission to the ICU. A web-based data entry format was implemented.

Classification of patients by injury energy mechanism

TBI patients with the following mechanisms of injury were classified as having high-energy TBI: motor vehicle incidents, collisions involving bicycles and motorcycles, falls from a height, assaults, sports, and other high-energy transfer incidents; falls from a standing or low height were classified as low‐energy TBI [6–8].

Statistical analysis

Increased understanding of TBI disease burden through improved classification, and identification of effective care, are core objectives in the 2015 CENTER-TBI published protocol of the core and registry studies [23]. The protocol also specified the patient characteristic, care pathway, and outcome variables for collection within the registry that could best support these objectives [23]. The study objectives and analysis plan for determining the low-energy TBI disease burden were stimulated by publications [3,6,7,18] highlighting falls as an increasingly common mechanism causing TBI during and shortly after the completion of CENTER-TBI patient recruitment. The analysis plan was agreed on by the authors at a study meeting at the University of Antwerp in January 2019. We prespecified the energy transfer patient classification—informed by the literature (Fig 1); variables and statistical methods for comparison by energy transfer level are available in S1 Analysis Plan. The study analysis plan has not been modified since. The analysis was based on the CENTER-TBI Registry data version 2.0, downloaded from a data management tool, Neurobot (https://center-tbi.incf.org/).

Fig 1 — RTC, road traffic collision; TBI, traumatic brain injury.

We carried out comparative analysis by energy transfer level. Continuous and ordinal variables (age, time intervals, GCS, AIS [10,13], and Injury Severity Score (ISS) [27]) are presented as median and interquartile range (IQR), while categorical variables are presented as number and percentage. Chi-squared tests were used to compare categorical variables between low- and high-energy TBI categories, while non-parametric continuous and ordinal variables were compared using the Mann–Whitney test.

Analyses were performed using IBM Statistical Package for Social Sciences (SPSS) version 23, Microsoft Excel 2010, and RStudio (version 1.0.136).

An Excel radar plot compared the time of day of hospital arrival by energy transfer level; the arrival times of the overall cohort were also compared to those of patients with TBI submitted to the largest European trauma registry—the Trauma Audit and Research Network (https://www.tarn.ac.uk), which has Section 251 (Health Research Authority) approval for analysis of anonymised data. This facilitated appraisal of the purposive sampling strategy.

Ethics statement

The CENTER-TBI study (EC grant 602150) was conducted in accordance with all relevant laws of the European Union if directly applicable or of direct effect and all relevant laws of the country where the recruiting sites were located, including, but not limited to, relevant privacy and data protection laws and regulations, relevant laws and regulations on the use of human materials, and all relevant guidance relating to clinical studies at various times in force, including, but not limited to, the ICH Harmonised Tripartite Guideline for Good Clinical Practice (CPMP/ICH/135/95) and the World Medical Association Declaration of Helsinki.

Informed consent was not required as only administrative and routinely collected clinical data were accessed. However, national and local institutional review board approvals were obtained as per national guidelines. For example, within the UK, approval was obtained from the Health Research Authority.

Ethical approval was obtained for each recruiting site. The list of sites, ethical committees, approval numbers, and approval dates can be found at https://www.center-tbi.eu/project/ethical-approval.

This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 STROBE Checklist).

Results

Fifty-six study centres from 18 countries (17 European countries and Israel; S1 Table) enrolled 22,849 patients to the CENTER-TBI Registry (for cumulative recruitment over the study, see S1 Fig). A total of 21,681 TBI patients with known clinical care pathway and injury mechanism were included in the overall cohort for analysis (Fig 1), a median of 247 (IQR 63 to 473) from each centre.

Overall cohort

Patients enrolled into the CENTER-TBI Registry had a median age of 55 years (IQR 32 to 75 years) and a 61% (95% CI 60% to 62%) male preponderance; 55% (95% CI 54% to 56%) had pre-existing medical conditions, 12% (95% CI 11% to 13%) (n = 2,578) and 11% (95% CI 10% to 13%) (n = 2,466) were taking pre-injury anticoagulant or antiplatelet therapy. Overall, 82% (95% CI 81% to 82%) (n = 17,702) presented to the study hospital ED with mild TBI (GCS 13–15) (Table 1), with 89% (95% CI 89% to 90%) having normal pupillary responses. Overall, 8.4% (95% CI 7.1% to 9.6%) (n = 1,812) of patients arrived intubated, and 12% (95% CI 11% to 14%) (2,692) arrived as a result of a secondary transfer from a referring hospital. The radar plot of hospital arrival times demonstrated a post meridiem (PM) hospital arrival predominance within the overall study cohort similar to that of TBI patients submitted to the Trauma Audit and Research Network (S2 Fig). Patients presenting directly had CT brain imaging conducted a median (IQR) of 68 (34 to 141) minutes after ED arrival. The majority (57% [95% CI 56% to 58%]) were admitted to hospital, and 19% (95% CI 18% to 20%) to intensive care (an average of 2.5 hours after ED arrival). Overall, 31% (95% CI 30% to 32%) (n = 6,746) of patients had injuries on CT brain scan. The most common of these were subarachnoid haemorrhage, small cerebral contusion, and small subdural haematoma (Tables 2 and 3). Extracranial injuries were usually present in moderate severity (median extracranial ISS = 4), and 11% (95% CI 9.8% to 12%) of patients received key emergency interventions, with craniotomy (3.5% [95% CI 2.2% to 4.8%]) within 3 hours of ED arrival being the most common. Hospital mortality was 6.7%, (95% CI 5.4% to 8.0%), with 71% (95% CI 70% to 72%) of patients being discharged directly to their own home (Table 4).

Table 1. Demographics, injury mechanism, comorbidity, and presenting physiology of 21,681 TBI patients enrolled in the CENTER-TBI Registry.

Characteristic	Overall	High-energy TBI	Low-energy TBI	p-Value
Total	21,681	13,059 (60.2)	8,622 (39.8)
Demographic characteristics
Age (years), median (IQR)	55 (32–75)	42 (25–60)	74 (56–84)	<0.001^a
Age
Under 16 years	579 (2.7)	488 (3.7)	91 (1.1)	<0.001^b
16–64 years	12,782 (59.0)	9,934 (76.1)	2,848 (33.0)
65 years and over	8,317 (38.4)	2,635 (20.2)	5,682 (65.9)
Male
Overall	13,186 (60.8)	8,833 (67.6)	4,353 (50.5)	<0.001^b
Under 16 years	371 (64.1)	316 (64.8)	55 (60.4)	<0.001^b
16–64 years	8,831 (69.1)	7,044 (70.9)	1,787 (62.7)
65 years and over	3,982 (47.9)	1,472 (55.9)	2,510 (44.2)
Place of injury
Street/highway	7,324 (33.8)	6,328 (48.5)	996 (11.6)	<0.001^b
Home/domestic	8,295 (38.3)	2,860 (21.9)	5,435 (63.0)
Work/school	746 (3.4)	587 (4.5)	159 (1.8)
Sport/recreational	721 (3.3)	671 (5.1)	50 (0.6)
Public location	3,394 (15.7)	2,000 (15.3)	1,394 (16.2)
Other	735 (3.4)	308 (2.4)	427 (5.0)
Unknown	448 (2.1)	292 (2.2)	156 (1.8)
Missing	18 (0.1)	13 (0.1)	5 (0.1)
Pre-injury health status and medical history
Normal healthy patient	8,688 (40.1)	7,285 (55.8)	1,403 (16.3)	<0.001^b
Mild systemic disease	6,266 (28.9)	3,391 (26.0)	2,875 (33.3)
Severe systemic disease	5,105 (23.5)	1,569 (12.0)	3,536 (41.0)
Life-threatening disease	523 (2.4)	116 (0.9)	407 (4.7)
Taking anticoagulants	2,578 (11.9)	744 (5.7)	1,834 (21.3)	<0.001^b
Taking platelet aggregate inhibitors	2,466 (11.4)	783 (6.0)	1,683 (19.5)	<0.001^b
Taking both anticoagulants and platelet aggregate inhibitors	370 (1.7)	120 (0.9)	250 (2.9)	<0.001^b
Intracranial lesions and taking anticoagulants	580 (11.7)	207 (6.5)	373 (20.9)	<0.001^b
Intracranial lesions and taking platelet aggregate inhibitors	679 (13.7)	269 (8.5)	410 (23.0)	<0.001^b
Intracranial lesions and taking both anticoagulants and platelet aggregate inhibitors	114 (2.3)	37 (1.2)	77 (4.3)	<0.001^b
ED arrival physiology
GCS, median (IQR)^c	15 (14–15)	15 (14–15)	15 (14–15)	<0.001^a
GCS
Mild TBI (GCS 13–15)	17,702 (81.6)	10,270 (78.6)	7,432 (86.2)
Moderate TBI (GCS 9–12)	830 (3.8)	480 (3.7)	350 (4.1)
Severe TBI (GCS 3–8)	1,195 (5.5)	879 (6.7)	316 (3.7)
No sum	1,835 (8.5)	1,366 (10.5)	469 (5.4)
Hypoxia^c	287 (1.3)	183 (1.4)	104 (1.2)	0.219^b
Hypotension^c	434 (2.0)	322 (2.5)	112 (1.3)	<0.001^b
Pupillary reactivity^c				<0.001^b
Neither reacting	552 (2.5)	419 (3.2)	133 (1.5)
One reacting	483 (2.2)	313 (2.4)	170 (2.0)
Both reacting	19,409 (89.5)	11,694 (89.5)	7,715 (89.5)

Open in a new tab

Data are n (%) unless otherwise indicated.

^aBy Mann–Whitney test for non-parametric variable distributions.

^bBy chi-squared test.

^cMissing data percentage is 5.0%–10% for low- versus high-energy TBI comparison.

ED, emergency department; GCS, Glasgow Coma Score; IQR, interquartile range; TBI, traumatic brain injury.

Table 2. Imaging findings, injury severity, therapeutic interventions, and care pathways of 21,681 TBI patients enrolled in the CENTER-TBI Registry.

Outcome	Overall	High-energy TBI	Low-energy TBI	p-Value
Care pathway
Emergency department	9,286 (42.8)	5,511 (42.2)	3,775 (43.8)	0.021^a
Admission	8,224 (37.9)	4,365 (33.4)	3,859 (44.8)	<0.001^a
Intensive care unit	4,171 (19.2)	3,183 (24.4)	988 (11.5)	<0.001^a
CT characteristics
Abnormal CT	6,746 (31.1)	4,226 (32.4)	2,520 (29.2)	<0.001^a
Abnormal CT with intracranial lesion^b	4,959 (73.5)	3,177 (75.2)	1,782 (70.7)	<0.001^a
EDH—small^b	619 (9.2)	456 (10.8)	163 (6.5)	<0.001^a
EDH—large^b	239 (3.5)	175 (4.1)	64 (2.5)	0.001^a
ASDH—small^b	2,036 (30.2)	1,271 (30.1)	765 (30.4)	0.808^a
ASDH—large^b	983 (14.6)	520 (12.3)	463 (18.4)	<0.001^a
Contusions—small^b	2,449 (36.3)	1,698 (40.2)	751 (29.8)	<0.001^a
Contusions—large^b	567 (8.4)	404 (9.6)	163 (6.5)	<0.001^a
Compressed basal cisterns^b	791 (11.7)	548 (13.0)	243 (9.6)	<0.001^a
Midline shift^b	1,592 (23.6)	883 (20.9)	709 (28.2)	<0.001^a
Subarachnoid haemorrhage^b	3,509 (52.0)	2,397 (56.7)	1,112 (44.1)	<0.001^a
Marshall grading				<0.001^a
II—cisterns present with midline shift 0–5 mm and/or lesions present (high/mixed density < 25 cm); may include bone fragments	14,743 (68.6)	3,141 (24.3)	1,761 (20.5)
III—diffuse injury; cisterns compressed/absent with midline shift 0–5 mm (high/mixed density < 25 cm)	4,902 (22.8)	181 (1.4)	36 (0.4)
IV—diffuse injury; midline shift > 5 mm (high/mixed density < 25 cm)	217 (1.0)	107 (0.8)	94 (1.1)
V—surgically evacuated mass lesion	201 (0.9)	396 (3.0)	363 (4.2)
VI—non-evacuated mass lesion > 25 cm	759 (3.5)	401 (3.1)	266 (3.1)
Head/neck AIS, median (IQR)	2 (1–3)	2 (1–3)	1 (1–2)	<0.001^c
Cervical spine AIS, median (IQR)	0 (0–0)	0 (0–0)	0 (0–0)	<0.001^d
ISS, median (IQR)	9 (4–17)	9 (4–20)	6 (3–12)	<0.001^c
Extracranial ISS, median (IQR)	4 (1–9)	5 (1–13)	2 (0–8)	<0.001^c
Processes of care
Secondary referral—arrived from another hospital	2,692 (12.4)	1,720 (13.2)	972 (11.3)	<0.001^a
Length of stay (hours), median (IQR)	17 (3–137)	17 (3–137)	19 (4–137)	0.080
Arrived intubated	1,812 (8.4)	1,496 (11.5)	316 (3.7)	<0.001^a
Key interventions
At least 1 key emergency intervention	2,397 (11.1)	1,752 (13.4)	645 (7.5)	<0.001^a
Craniotomy	767 (3.5)	401 (3.1)	366 (4.2)	<0.001^a
ICP monitor insertion	753 (3.5)	609 (4.7)	144 (1.7)	<0.001^a
Decompressive craniectomy	275 (1.3)	201 (1.5)	74 (0.9)	<0.001^a
External limb fixation	293 (1.4)	276 (2.1)	17 (0.2)	<0.001^a
Other^e	445 (2.1)	369 (2.8)	76 (0.9)

Open in a new tab

Data are n (%) unless otherwise indicated.

^aLow- versus high-energy TBI comparison by chi-squared test.

^cBy Mann–Whitney test for non-parametric variable distributions.

^bDenominator is those with abnormal CT.

^dCervical spine injury present in 21.0% and 13.3% of high- and low-energy TBI cohorts, respectively.

^eIncludes external ventricular drainage, interventional radiology, damage control thoracotomy and laparotomy, and extraperitoneal pelvic packing.

AIS, Abbreviated Injury Scale; ASDH, acute subdural haematoma; CT, computed tomography; EDH, extradural haematoma; ICP, intracranial pressure; IQR, interquartile range; ISS, Injury Severity Score; TBI, traumatic brain injury.

Table 3. Median (interquartile range) times (in minutes) from arrival to imaging and key emergency interventions in study hospital (21,681 patients).

Time interval	Overall	High-energy TBI	Low-energy TBI	p-Value^a
Time to CT in non-transferred patients	68 (34–141)	54 (29–109)	99 (49–179)	<0.001
Time to ICU admission in non-transferred patients	151 (70–276)	152 (74–270)	150 (49–304)	0.632
Time to ICP monitor insertion	197 (87–485)	195 (89–472)	216 (77–568)	0.649
Time to craniotomy	142 (62–410)	115 (60–286)	190 (68–660)	<0.001
Time to decompressive craniectomy	165 (71–761)	129 (70–657)	235 (83–1,105)	0.098
Time to first extracranial emergency intervention	137 (59–284)	128 (59–267)	170 (60–717)	0.064

Open in a new tab

^aFrom Mann–Whitney comparisons of non-parametric variable distributions—high- versus low-energy TBI.

CT, computed tomography; ICP, intracranial pressure; ICU, intensive care unit; TBI, traumatic brain injury.

Table 4. Hospital mortality and discharge destination from study hospital (21,681 patients).

Outcome	Overall	High-energy TBI	Low-energy TBI	p-Value^a
Total	21,681	13,059 (60.2)	8,622 (39.8)
Hospital mortality	1,453 (6.7)	913 (7.0)	540 (6.3)	0.825
Discharged home	15,324 (70.7)	9,458 (72.4)	5,866 (68.0)	<0.001
Discharged to other hospital	2,151 (9.9)	1,351 (10.3)	800 (9.3)	0.010
Discharged to rehabilitation	1,221 (5.6)	776 (5.9)	445 (5.2)	0.015
Discharged to nursing home	1,122 (5.2)	289 (2.2)	833 (9.7)	<0.001

Open in a new tab

Data are n (%).

^aLow- versus high-energy TBI comparison by chi-squared test.

Comparisons by energy transfer mechanism

Patient characteristics and care pathway

Forty percent (95% CI 39% to 41%) (8,622) of the overall cohort were injured as a consequence of low-energy falls. Detailed comparisons of patient characteristics between patients injured by low-energy falls (LE cohort) versus those injured by high-energy transfer mechanisms (HE cohort) are provided in Tables 1 and 2. Road traffic collisions, falls from a height, and assaults were the predominant causal mechanisms in patients injured by high-energy transfer (Fig 1); the prevalence of low-energy transfer varied from 30% to 50% in most participating countries and recruiting centres (Figs 2 and S1).

Fig 2 — Colour shading as per key. Map from https://en.wikipedia.org/wiki/File:Europe_blank_map.png.

Patients sustaining TBI from low-energy falls were significantly older (median [IQR]: LE cohort, 74 [56 to 84] years, versus HE cohort, 42 [25 to 60] years; p < 0.001), with 66% (95% CI 65% to 67%) aged 65 years and over, and were less likely to be male (LE cohort, 51% [95% CI 49% to 52%], versus HE cohort, 67% [95% CI 66% to 69%]; p < 0.001) than patients injured by high-energy mechanisms. Patients injured by low-energy mechanisms were more likely to be injured at home (Table 1) and to arrive at the ED during daylight hours (S2 Fig). The low-energy TBI cohort had a significantly higher prevalence of pre-existing disease (LE cohort, 79% [95% CI 78% to 80%], versus HE cohort, 39% [95% CI 38% to 40%]; p < 0.001) and sole anticoagulant (LE cohort, 21% [95% CI 19% to 23%], versus HE cohort, 5.7% [95% CI 4.0% to 7.3%]; p < 0.001) or antiplatelet (LE cohort, 20% [95% CI 18% to 21%], versus HE cohort, 6.0% [95% CI 4.3% to 7.6%]; p < 0.001) usage than the high-energy TBI cohort, but were more likely to present with mild TBI (GCS 13–15; LE cohort, 86% [95% CI 85% to 87%], versus HE cohort, 79% [95% CI 78% to 79%]) and with normal pupils and vital signs (Table 1) than patients injured by high-energy mechanisms. These differences persisted within care pathways (Fig 3; S2 Table).

Fig 3 — The 3 care pathways are as follows: discharged or died in emergency department (ER; left column), admitted to ward but not receiving critical care in study hospital (ADM; central column), and admitted and received critical care in study hospital intensive care unit (ICU; right column). *Denominator is number of patients in energy transfer and care pathway cohort. CT, computed tomography; GCS, Glasgow Coma Score; TBI, traumatic brain injury.

Patients injured by low-energy falls were less likely to present to hospital intubated (LE cohort, 3.7 [95% CI 1.6% to 5.7%], versus HE cohort, 11% [95% CI 9.8% to 13.0%]; p < 0.001) or via a secondary transfer (LE cohort, 11% [95% CI 9.2% to 13.0%], versus HE cohort, 13% [95% CI 12% to 14%]; p < 0.001) and were more likely to have a delayed CT brain scan (median [IQR]: LE cohort, 99 [49 to 179] minutes after ED arrival, versus HE cohort, 54 [29 to 109] minutes; p < 0.001). The proportion of the LE cohort admitted to hospital was similar to that of the HE cohort (LE cohort, 56% [95% CI 55% to 58%], versus HE cohort, 58% [95% CI 57% to 59%]; p = 0.021), but the proportion receiving ICU care was half that of high-energy TBI patients (LE cohort, 11% [95% CI 9.4% to 13%], versus HE cohort, 24% [95% CI 23% to 26%]; p < 0.001), although times from arrival to ICU admission were similar. Patients in the low-energy TBI cohort had a similar hospital length of stay (median [IQR]: 19 [4 to 137] hours) to the high-energy TBI cohort (Tables 2 and 3).

Injury characteristics

In patients injured by low-energy falls, the proportion with abnormalities detected on CT scan (including skull fracture) (29% [95% CI 27% to 31%]) and the proportion of abnormal scans showing intracranial injury (70% [95% CI 69% to 73%]) were lower than those of patients injured by high-energy mechanisms (32% [95% CI 31% to 34%] and 75% [95% CI 74% to 77%], respectively; p < 0.001). Patients with intracranial injuries sustained through low-energy mechanisms were more likely to be taking anticoagulants, platelet aggregate inhibitors, or both (LE cohort, 21% [95% CI 17% to 25%], 23% [95% CI 19% to 27%], 4.3% [95% CI 0.0% to 8.8%], respectively, versus HE cohort, 6.5% [95% CI 3.2% to 9.9%], 8.5% [95% CI 5.1% to 12%], and 1.1% [95% CI 0.0% to 4.6%], respectively; p < 0.001). Rates of large acute subdural haematoma (LE cohort, 18% [95% CI 15% to 22%], versus HE cohort, 12% [95% CI 9% to 15%]; p < 0.001) and presence of midline shift (LE cohort, 28% [95% CI 25% to 31%], versus HE cohort, 21% [95% CI 18% to 24%]; p < 0.001)—as a proportion of patients with abnormalities on CT brain scan—were higher in the low-energy TBI cohort. However patients with low-energy injuries were significantly less likely to have small epidural haemorrhage (LE cohort, 6.5% [95% CI 2.7% to 10%], versus HE cohort, 11% [95% CI 7.9% to 14%]; p < 0.001), large epidural haemorrhage (LE cohort, 2.5% [95% CI 0.0% to 6.3%], versus HE cohort, 4.1% [95% CI 1.2% to 7.0%]; p < 0.001), small contusions (LE cohort, 30% [95% CI 27% to 33%], versus HE cohort, 40% [95% CI 38% to 43%]; p < 0.001), large contusions (LE cohort, 6.5% [95% CI 2.7% to 10%], versus HE cohort, 9.6% [95% CI 6.7% to 12.4%]; p < 0.001), subarachnoid haemorrhage (LE cohort, 44% [95% CI 41% to 47%], versus HE cohort, 57% [95% CI 55% to 59%]; p < 0.001), and basal cistern compression (LE cohort, 9.6% [95% CI 5.9% to 13.0%], versus HE cohort, 13% [95% CI 10% to 16%]; p < 0.001). They also had less severe extracranial injuries (median [IQR] extracranial ISS: LE cohort, 2 [0 to 8], versus HE cohort, 5 [1 to 13]; p < 0.001). The rate of small subdural haematoma in low-energy TBI patients was similar to that in high-energy TBI patients (30% [95% CI 27% to 33%]) (Table 2). The greatest relevant differences in Marshall CT grading were in rates of diffuse injury (III and IV; Table 2); diffuse injuries were 50% more common in the high-energy TBI cohort. Overall, the low-energy TBI cohort had a lower rate of key emergency intervention (LE cohort, 7.5% [95% CI 5.4% to 9.5%], versus HE cohort, 13% [95% CI 12% to 15%]; p < 0.001). This was observed for interventions associated with critical care (intracranial pressure monitoring and decompressive craniectomy) and extracranial injuries (external limb fracture fixation); however, the craniotomy rate was greater in the low-energy TBI cohort (LE cohort, 4.2% [95% CI 2.2% to 6.3%], versus HE cohort, 3.1% [95% CI 1.4% to 4.8%]; p < 0.001) (Table 2). In the low-energy TBI cohort, there was a greater time delay between arrival at the study hospital and the provision of emergency interventions such as craniotomy (Table 3); however, the time delay difference was only statically significant for patients receiving craniotomy.

Outcomes

Hospital mortality was similar in the high- and low-energy TBI cohorts (6.3% [95% CI 4.2% to 8.3%], versus 7.0% [95% CI 5.3% to 8.6%], respectively; p = 0.825); however, there was a greater time to death—from arrival in the study hospital—in low-energy TBI patients than in high-energy TBI patients (median [IQR]: 4 [1.6 to 11] versus 2 [0.7 to 7.5] days; p < 0.001). The rate of discharge home was lower (68% [95% CI 67% to 69%] versus 72% [95% CI 72% to 73%]; p < 0.001), and to nursing homes higher (9.7% [95% CI 7.7% to 12%] versus 2.2% [95% CI 0.9% to 3.9%]; p < 0.001), in the low-energy TBI cohort compared with the high-energy TBI cohort, with similar proportions referred for rehabilitation or transferred to other hospitals (Table 4). When care pathway was accounted for, mortality in the low-energy injury cohort was 6% higher in ICU patients (LE cohort, 22% [95% CI 17% to 28%], versus HE cohort, 16% [95% CI 13% to 20%]) and 4 times greater in admitted patients (LE cohort, 4.2% [95% CI 1.1 to 7.3%], versus HE cohort, 0.9% [95% CI 0.0% to 3.8%]; Fig 3).

The observed differences in rates of critical care admission, and the 4-fold greater in-hospital mortality rate in patients with low-energy TBI admitted to the ward, were unexpected and prompted exploratory assessment of the contribution of energy transfer level to likelihood of critical care/hospital admission and mortality—in risk-adjusted analyses that were not prespecified. The 50% reduction in likelihood of critical care provision for the low-energy TBI cohort persisted after variables influencing critical care admission decisions were adjusted for—adjusted odds ratio 0.46 (95% CI 0.43 to 0.50) to 0.77 (95% CI 0.53 to 1.12) after accounting for the interaction between age and energy transfer mechanism (S3 Table; S3 Fig). The multivariable logistic regression adjusted for demographics (age and sex), injury (ED arrival GCS and intubation status, ED pupillary responses, Marshall classification of CT findings, and AIS grading of extracranial injury severity), and comorbid status (pre-existing health and anticoagulation). A reduction in the likelihood of hospital admission was also observed for patients injured by low- when compared to high-energy transfer, albeit less so in older people (S4 Table; S4 Fig). In patients with TBI admitted to the ward or intensive care, the characteristics more often associated with patients injured by low-energy transfer (older age, pre-injury comorbidity and anticoagulation, and—in ward admissions—having non-evacuated mass lesion [Marshall VI]) were strong independent predictors of hospital mortality; after adjustment for these (and injury severity variables predicting hospital mortality after TBI [18]), low-energy transfer did not independently predict mortality (S5 and S6 Tables; S5 and S6 Figs). Non-evacuated intracranial mass lesions (Marshall VI) were present in 3.1% (n = 118) and 1.2% (n = 53) of ward admission patients injured by low- and high-energy transfer, respectively (p < 0.001).

Discussion

The CENTER-TBI Registry shows that at least 40% of TBI patients presenting to European and Israeli hospitals are injured by low-energy falls. Our results show that patients injured by low-energy transfer mechanisms (falls) and those injured by high-energy transfer mechanisms (mainly road traffic incidents) are very distinct subpopulations. To our knowledge, this is the first pan-Euro/Israeli study to identify and compare these 2 disease cohorts. Compared to the broader past literature, we observed a greater proportion of older adults (≥65 years old)—almost 39% of all patients presenting with TBI, as opposed to the 10% to 17% previously reported elsewhere [22,28]. This might be attributable to case ascertainment improvements following recommendations that all older head trauma and/or anticoagulated patients with TBI symptoms receive CT scanning, rather than only to ageing of the population [8,29].

We found that patients in the low-energy TBI cohort, compared with the high-energy TBI cohort, were on average 32 years older, more likely to be female, more than 3 times as likely to be taking pre-injury anticoagulant or platelet aggregate inhibitor medication, and less likely to be classified as moderately or severely injured (based on GCS). Nevertheless, both groups showed clinically similar rates of abnormality on CT scan (29% and 32%), acute hospital admission (58% for high energy, 56% for low energy), and hospital mortality (6.3% and 7.0%). However, the low-energy TBI cohort was 50% less likely to receive critical care (12% versus 24%) or emergency intervention (7.5% versus 13%).

Low-energy TBI cohort

Our finding that 40% of TBI patients presenting to European hospitals are injured by low-energy falls clearly demonstrates that this low-energy TBI cohort forms an important component of TBI and requires targeted prevention strategies [22,30]. Further, the specific features of this cohort have substantial implications for both clinical care and research. Sixty-six percent of patients injured by low-energy mechanisms are over 64 years of age—a common age cut-off in many clinical trials. Such disenfranchisement of older adults in clinical TBI research is inappropriate—on the contrary, dedicated studies are required [31].

Perhaps most importantly, our results suggest a need to review clinical care pathways and priorities for this group of patients. Our finding that the low-energy TBI cohort was 50% less likely to receive critical care (even after adjustment for age and comorbidity; S3 Table) or emergency intervention highlights an apparent ‘non-interventional’ approach towards patients injured by low-energy TBI across the continent. This was particularly evident in our post hoc analysis of the drivers of the 4-fold higher mortality rate in low-energy TBI patients admitted to the ward. This analysis showed that reduced rates of intervention (as evidenced by a higher incidence of non-evacuated mass lesions), in addition to age, anticoagulation use, and comorbidity, are explanatory low-energy-TBI-associated features, each independently predicting mortality in ward admissions (S5 Table; Fig 3). The lower critical care provision, and longer times from ED arrival to CT brain scan and emergency interventions, appear to implicitly reflect triage decisions. However, our analyses suggest that low-energy TBI patients do receive timely critical care when their presenting consciousness level is impaired (Table 3; Fig 3). The registry variables did not include ‘ceiling of care’; hence, it is uncertain whether the apparent non-intervention strategy for the low-energy TBI cohort reflects therapeutic nihilism approach.

The prevalence of TBI patients taking anticoagulant or/and antiplatelet medication within our study is much higher in the low-energy TBI cohort (44%) than the high-energy TBI cohort (13%), with a greater likelihood of hospitalisation. This reflects the high propensity of these patients with significant comorbidity and frailty to sustain TBI from low-level falls; age-related intracranial changes may also challenge assessment by allowing a higher GCS at presentation compared to younger patients with similar intracranial injury [32]. These findings point to the need for a holistic personalised medicine approach for TBI patients requiring multidisciplinary acute care. Such an approach addresses each patient’s pre-existing health issues, the specific brain injury sustained, and their interaction. Overall, there was a higher frequency of intracranial haemorrhage in patients taking antiplatelet medication than in patients taking anticoagulants. These results are in accordance with previous studies [3,32,33], and may possibly be explained by the fact that anticoagulant medication can (and should) be reversed, whilst antiplatelet medication cannot [34]. These findings indicate the need for imaging guidelines to give as much attention to antiplatelet therapy as to anticoagulation therapy. Our exploratory analyses (S5 and S6 Tables) suggest that specific features of the low-energy TBI cohort—having pre-existing health issues and taking anticoagulation medication—are strong independent predictors of hospital mortality in current-day practice. This signals a need to reassess TBI outcome prediction models, which were mostly developed on older data and did not include these factors and in which, importantly, older patients were underrepresented in the development population [22].

The observed equivalent hospital admission and mortality rates for patients injured by low- and high-energy transfer mechanisms challenge the generalisability of the current paradigm of trauma care systems to prioritise patients injured by high-energy mechanisms [8,9]. For older patients with TBI, the assumption that energy transfer is proportionate to severity of intracranial injury does not appear to be valid. A reappraisal of current injury prevention and clinical management policies is indicated [35].

Strengths and limitations

The CENTER-TBI Registry study had several strengths: the standardised and robust data collection system, large sample size from specialist neuroscience centres, likely representativeness of the study sample (as illustrated in S2 Fig), participation by a large number of hospitals from 18 countries (17 in Europe and Israel), and inclusion of all TBI severities and age groups. Fig 2 illustrates a considerable low-energy TBI disease burden across countries—the median (IQR) prevalence of low-energy TBI by centre was 36% (24% to 50%) (S1 Fig), suggesting our findings do not result from clustering of low-energy TBI patients in a few large centres or in specific countries. Indeed, as one might expect, the highest-recruiting centres had lower rates of patients injured by low-energy transfer—as study centres with larger catchment populations receive a greater proportion of their patients with TBI through EMS prehospital triage prioritisation of high-energy TBI [7,9,36]. The low-resource-intensive data collection for the registry has enabled the creation of a large dataset that includes patients with dementia and other causes of pre-existing cognitive impairment, characterised by validated energy transfer descriptions. The registry data may therefore be more generalisable to TBI populations across Europe—particularly those admitted to ward settings—than the core study.

Rates of disability beyond discharge were not available in the registry; however, the low rates of discharge home (68% in low-energy TBI and 72% in high-energy TBI) are consistent with the significant rates of post-discharge disability reported in the core study [24]. The registry did not record alcohol ingestion, which may contribute to both energy transfer cohorts (falls in the low-energy TBI cohort, and assaults and road traffic collisions in the high-energy TBI cohort). Our estimates for the study population may be subject to bias as a result of missing data and our purposive sampling strategy. The statistical power arising from the large sample size identified some clinically insignificant differences between the cohorts (proportions with ED pathway, abnormal CT, and intracranial injury) as statistically significant. Five percent of individuals in the registry were excluded because mechanism of injury was unknown; this may reflect the clinical reality of TBI patients being ‘found’ with impaired consciousness or amnesia and a lack of reliable incident witnesses. As a group, the demographic, injury, and outcome characteristics of those excluded suggest this group contained patients injured by high- and low-energy transfer (S7 and S8 Tables). The reality of injury incidents being unwitnessed—particularly in people falling whilst alone at home—means prehospital staff estimate fall height, resulting in possible misclassification; there is also some variation in classification of the height above ground that is considered low-energy transfer [3,8,9]. The CENTER-TBI study centres are generally specialist hospitals that receive a high proportion of TBI patients by secondary transfer or directly from the scene of EMS triage, bypassing closer non-specialist hospitals; these patients are generally high-energy TBI patients (Table 2; S1 Fig). Therefore, the proportion of patients with TBI injury by low-energy mechanisms across Europe may be greater than 40%; however, external validity is supported by CENTER-TBI hospital arrival times mirroring those from the Trauma Audit and Research Network (S2 Fig) [18,31]. Our analysis of factors explaining the increase in mortality (S5 and S6 Tables) in low-energy TBI ward and ICU admissions was not prespecified in our analysis plan and should be considered hypothesis-generating, requiring a specific ‘appropriate intervention’ a priori focus in future research.

Conclusions

Broad overall descriptions mask the heterogeneity of TBI as a disease. We present the largest standardised and consistently reported description of patients with TBI presenting to hospitals across Europe and Israel to our knowledge, highlighting 2 separate disease cohorts. Clinicians and trauma care systems need to recognise the potential for life-threatening TBI in patients injured by low-energy falls—particularly in alert older patients and those taking anticoagulant or antiplatelet medication. Our findings suggest that within the older cohort, TBI triage based on energy transfer may not inform risk of intracranial injury and hospital mortality. Further studies should test the justification for providing lower rates of critical care and emergency intervention for those injured by low-energy mechanisms. Reduction of the burden and impact of TBI can only be achieved through public health policies and guidelines targeted at the prevention and management of TBI resulting from both high- and low-energy mechanisms.

Supporting information

S1 Analysis Plan. The aim of this paper is to describe the demographic, injury, and clinical characteristics of high-energy and low-energy TBI patients who presented to 56 CENTER-TBI recruiting hospitals in Europe and Israel, including patients discharged from the emergency room (ER) after imaging.

(DOCX)

Click here for additional data file.^{(80.4KB, docx)}

S1 Fig. Cumulative monthly recruitment across 56 sites and prevalence of low-energy transfer injury mechanism in TBI patients in recruiting sites plotted by estimate precision (1/standard error).

(TIF)

Click here for additional data file.^{(2.3MB, tif)}

S2 Fig. Hospital arrival time by energy transfer level in CENTER-TBI Registry and Trauma Audit and Research Network (TARN).

(TIF)

Click here for additional data file.^{(1.3MB, tif)}

S3 Fig. Receiver operating characteristic (ROC) curve multivariable analysis of factors predicting ICU admission in 11,673* patients from the CENTER-TBI Registry.

*Excluding 9,286 patients who were discharged from or died in the ED and 722 with missing age/GCS sum score and/or extracranial injury details.

(TIF)

Click here for additional data file.^{(1.2MB, tif)}

S4 Fig. Receiver operating characteristic (ROC) curve multivariable analysis of factors predicting hospital admission in 18,035* patients from the CENTER-TBI Registry.

*Excluding patients who died in the ED (n = 69), arrived as secondary transfers (n = 2,706), or had missing age/CT.

(TIF)

Click here for additional data file.^{(1.2MB, tif)}

S5 Fig. Receiver operating characteristic (ROC) curve multivariable analysis of factors predicting in-hospital mortality in 7,792* ward admission patients from the CENTER-TBI Registry.

*Excluding 432 patients with missing GCS sum score and/or discharge status.

(TIF)

Click here for additional data file.^{(1MB, tif)}

S6 Fig. Receiver operating characteristic (ROC) curve multivariable analysis of factors predicting in-hospital mortality in 3,739* ICU admission patients from the CENTER-TBI Registry.

*Excluding 432 patients with missing GCS sum score/age and/or discharge status.

(TIF)

Click here for additional data file.^{(1.1MB, tif)}

S1 STROBE Checklist. STROBE statement—Checklist of items that should be included in reports of cohort studies.

(DOCX)

Click here for additional data file.^{(30.2KB, docx)}

S1 Table. Hospitals recruiting to the CENTER-TBI Registry.

(DOCX)

Click here for additional data file.^{(18.6KB, docx)}

S2 Table. Comparison of demographic and comorbid characteristics by energy transfer level and care pathway.

All within-pathway low- versus high-energy differences in age, sex, pre-existing health, and anticoagulant/antiplatelet medication were significant (p < 0.001). *ED = discharged or died in emergency department. **ADM = admitted to hospital but did not receive critical care in study hospital. ***ICU = admitted to hospital and received critical care in study hospital.

(DOCX)

Click here for additional data file.^{(15.2KB, docx)}

S3 Table. Multivariable analysis of factors (age, sex, pre-existing disease status, Marshall CT brain injury classification, CT abnormality, ED GCS and pupillary reactivity, presence of significant extracranial injury, presenting to ED intubated, and causal energy transfer mechanism and its interaction with age) predicting ICU admission in 11,673* patients from the CENTER-TBI Registry.

*Excluding 9,286 patients who were discharged from or died in ED and 722 with missing age/GCS sum score and/or extracranial injury details. AUC = 0.90. **AOR = 0.46 (95% CI 0.43 to 0.50) when same model omits age × energy transfer interaction—other variable AORs unchanged. CT, computed tomography; ED, emergency department; GCS, Glasgow Coma Score.

(DOCX)

Click here for additional data file.^{(19.9KB, docx)}

S4 Table. Multivariable analysis of factors (age, sex, pre-existing disease status, presence of CT brain abnormality, ED GCS < 15, presence of significant extracranial injury, presenting to ED intubated, and causal energy transfer mechanism and its interaction with age) predicting hospital admission in 18,035* patients from the CENTER-TBI Registry.

*Excluding patients who died in the ED (n = 69), arrived as secondary transfers (n = 2,706), or had missing age/CT abnormality/GCS sum score/extracranial injury (n = 873). GCS considered as binary category in accordance with guidance for hospital admission [8]. Area under receiver operating characteristic curve (AUC) = 0.81. AIS, Abbreviated Injury Scale; CT, computed tomography; ED, emergency department; GCS, Glasgow Coma Score.

(DOCX)

Click here for additional data file.^{(18.7KB, docx)}

S5 Table. Multivariable analysis of factors (age and sex and their interaction, pre-existing disease status, pre-injury anticoagulation status, Marshall CT brain injury classification, ED GCS and pupillary reactivity, presence of significant extracranial injury, and causal energy transfer mechanism and its interaction with age) predicting in-hospital mortality in 7,792* ward admission patients from the CENTER-TBI Registry.

*Excluding 432 patients with missing GCS sum score and/or discharge status. Area under receiver operating characteristic curve (AUC) = 0.92. AIS, Abbreviated Injury Scale; CT, computed tomography; ED, emergency department; GCS, Glasgow Coma Score.

(DOCX)

Click here for additional data file.^{(20.3KB, docx)}

S6 Table. Multivariable analysis of factors (age and sex and their interaction, pre-existing disease status, pre-injury anticoagulation status, Marshall CT brain injury classification, ED GCS and pupillary reactivity, presence of significant extracranial injury, and causal energy transfer mechanism and its interaction with age) predicting in-hospital mortality in 3,739* ICU admission patients from the CENTER-TBI Registry.

*Excluding 432 patients with missing GCS sum score/age and/or discharge status. Area under receiver operating characteristic curve (AUC) = 0.86. AIS, Abbreviated Injury Scale; CT, computed tomography; ED, emergency department; GCS, Glasgow Coma Score.

(DOCX)

Click here for additional data file.^{(18.9KB, docx)}

S7 Table. Demographics, injury mechanism, comorbidity-presenting physiology, and care pathway—Comparative analysis of the CENTER-TBI Registry high-energy, low-energy, and unknown-energy TBI cohorts.

GCS, Glasgow Coma Score. *ED = discharged from or died in the emergency department. **ADM = admitted to hospital but did not receive critical care in study hospital. ***ICU = admitted to hospital and received critical care in study hospital.

(DOCX)

Click here for additional data file.^{(18.7KB, docx)}

S8 Table. Imaging findings, injury severity, therapeutic interventions, discharge status—Comparative analysis of the CENTER-TBI Registry high, low and unknown energy transfer cohorts.

AIS, Abbreviated Injury Scale; ASH, acute subdural haematoma; CT, computed tomography; EDH, extradural haematoma; ICP, intracranial pressure; ISS, Injury Severity Score. **Denominator is those with abnormal CT brain scan.

(DOCX)

Click here for additional data file.^{(16.1KB, docx)}

S1 Text. Institutional affiliations of CENTER-TBI Participants and Investigators.

(DOCX)

Click here for additional data file.^{(20.2KB, docx)}

Acknowledgments

CENTER-TBI Participants and Investigators (see S1 Text for institutional affiliations 1–145): Cecilia Åkerlund¹, Krisztina Amrein², Nada Andelic³, Lasse Andreassen⁴, Audny Anke⁵, Anna Antoni⁶, Gérard Audibert⁷, Philippe Azouvi⁸, Maria Luisa Azzolini⁹, Ronald Bartels¹⁰, Pál Barzó¹¹, Romuald Beauvais¹², Ronny Beer¹³, Bo-Michael Bellander¹⁴, Antonio Belli¹⁵, Habib Benali¹⁶, Maurizio Berardino¹⁷, Luigi Beretta⁹, Morten Blaabjerg¹⁸, Peter Bragge¹⁹, Alexandra Brazinova²⁰, Vibeke Brinck²¹, Joanne Brooker²², Camilla Brorsson²³, Andras Buki²⁴, Monika Bullinger²⁵, Manuel Cabeleira²⁶, Alessio Caccioppola²⁷, Emiliana Calappi²⁷, Maria Rosa Calvi⁹, Peter Cameron²⁸, Guillermo Carbayo Lozano²⁹, Marco Carbonara²⁷, Simona Cavallo¹⁷, Giorgio Chevallard³⁰, Arturo Chieregato³⁰, Giuseppe Citerio^31,32, Hans Clusmann³³, Mark Coburn³⁴, Jonathan Coles³⁵, Jamie D. Cooper³⁶, Marta Correia³⁷, Amra Čović³⁸, Nicola Curry³⁹, Endre Czeiter²⁴, Marek Czosnyka²⁶, Claire Dahyot-Fizelier⁴⁰, Paul Dark⁴¹, Helen Dawes⁴², Véronique De Keyser⁴³, Vincent Degos¹⁶, Francesco Della Corte⁴⁴, Hugo den Boogert¹⁰, Bart Depreitere⁴⁵, Đula Đilvesi⁴⁶, Abhishek Dixit⁴⁷, Emma Donoghue²², Jens Dreier⁴⁸, Guy-Loup Dulière⁴⁹, Ari Ercole⁴⁷, Patrick Esser⁴², Erzsébet Ezer⁵⁰, Martin Fabricius⁵¹, Valery L. Feigin⁵², Kelly Foks⁵³, Shirin Frisvold⁵⁴, Alex Furmanov⁵⁵, Pablo Gagliardo⁵⁶, Damien Galanaud¹⁶, Dashiell Gantner²⁸, Guoyi Gao⁵⁷, Pradeep George⁵⁸, Alexandre Ghuysen⁵⁹, Lelde Giga⁶⁰, Ben Glocker⁶¹, Jagoš Golubovic⁴⁶, Pedro A. Gomez⁶², Johannes Gratz⁶³, Benjamin Gravesteijn⁶⁴, Francesca Grossi⁴⁴, Russell L. Gruen⁶⁵, Deepak Gupta⁶⁶, Juanita A. Haagsma⁶⁴, Iain Haitsma⁶⁷, Raimund Helbok¹³, Eirik Helseth⁶⁸, Lindsay Horton⁶⁹, Jilske Huijben⁶⁴, Peter J. Hutchinson⁷⁰, Bram Jacobs⁷¹, Stefan Jankowski⁷², Mike Jarrett²¹, Ji-yao Jiang⁵⁸, Faye Johnson⁷³, Kelly Jones⁵², Mladen Karan⁴⁶, Angelos G. Kolias⁷⁰, Erwin Kompanje⁷⁴, Daniel Kondziella⁵¹, Evgenios Kornaropoulos⁴⁷, Lars-Owe Koskinen⁷⁵, Noémi Kovács⁷⁶, Ana Kowark⁷⁷, Alfonso Lagares⁶², Linda Lanyon⁵⁸, Steven Laureys⁷⁸, Fiona Lecky^79,80, Didier Ledoux⁷⁸, Rolf Lefering⁸¹, Valerie Legrand⁸², Aurelie Lejeune⁸³, Leon Levi⁸⁴, Roger Lightfoot⁸⁵, Hester Lingsma⁶⁴, Andrew I. R. Maas⁴³, Ana M. Castaño-León⁶², Marc Maegele⁸⁶, Marek Majdan²⁰, Alex Manara⁸⁷, Geoffrey Manley⁸⁸, Costanza Martino⁸⁹, Hugues Maréchal⁴⁹, Julia Mattern⁹⁰, Catherine McMahon⁹¹, Béla Melegh⁹², David Menon⁴⁷, Tomas Menovsky⁴³, Ana Mikolic⁶⁴, Benoit Misset⁷⁸, Visakh Muraleedharan⁵⁸, Lynnette Murray²⁸, Ancuta Negru⁹³, David Nelson¹, Virginia Newcombe⁴⁷, Daan Nieboer⁶⁴, József Nyirádi², Otesile Olubukola⁷⁹, Matej Oresic⁹⁴, Fabrizio Ortolano²⁷, Aarno Palotie^95,96,97, Paul M. Parizel⁹⁸, Jean-François Payen⁹⁹, Natascha Perera¹², Vincent Perlbarg¹⁶, Paolo Persona¹⁰⁰, Wilco Peul¹⁰¹, Anna Piippo-Karjalainen¹⁰², Matti Pirinen⁹⁵, Horia Ples⁹³, Suzanne Polinder⁶⁴, Inigo Pomposo²⁹, Jussi P. Posti¹⁰³, Louis Puybasset¹⁰⁴, Andreea Radoi¹⁰⁵, Arminas Ragauskas¹⁰⁶, Rahul Raj¹⁰², Malinka Rambadagalla¹⁰⁷, Jonathan Rhodes¹⁰⁸, Sylvia Richardson¹⁰⁹, Sophie Richter⁴⁷, Samuli Ripatti⁹⁵, Saulius Rocka¹⁰⁶, Cecilie Roe¹¹⁰, Olav Roise^111,112, Jonathan Rosand¹¹³, Jeffrey V. Rosenfeld¹¹⁴, Christina Rosenlund¹¹⁵, Guy Rosenthal⁵⁵, Rolf Rossaint⁷⁷, Sandra Rossi¹⁰⁰, Daniel Rueckert⁶¹ Martin Rusnák¹¹⁶, Juan Sahuquillo¹⁰⁵, Oliver Sakowitz^90,117, Renan Sanchez-Porras¹¹⁷, Janos Sandor¹¹⁸, Nadine Schäfer⁸¹, Silke Schmidt¹¹⁹, Herbert Schoechl¹²⁰, Guus Schoonman¹²¹, Rico Frederik Schou¹²², Elisabeth Schwendenwein⁶, Charlie Sewalt⁶⁴, Toril Skandsen^123,124, Peter Smielewski²⁶, Abayomi Sorinola¹²⁵, Emmanuel Stamatakis⁴⁷, Simon Stanworth³⁹, Robert Stevens¹²⁶, William Stewart¹²⁷, Ewout W. Steyerberg^64,128, Nino Stocchetti¹²⁹, Nina Sundström¹³⁰, Riikka Takala¹³¹, Viktória Tamás¹²⁵, Tomas Tamosuitis¹³², Mark Steven Taylor²⁰, Braden Te Ao⁵², Olli Tenovuo¹⁰³, Alice Theadom⁵², Matt Thomas⁸⁷, Dick Tibboel¹³³, Marjolein Timmers⁷⁴, Christos Tolias¹³⁴, Tony Trapani²⁸, Cristina Maria Tudora⁹³, Andreas Unterberg⁹⁰, Peter Vajkoczy¹³⁵, Shirley Vallance²⁸, Egils Valeinis⁶⁰, Zoltán Vámos⁵⁰, Mathieu van der Jagt¹³⁶, Gregory Van der Steen⁴³, Joukje van der Naalt⁷¹, Jeroen T. J. M. van Dijck¹⁰¹, Thomas A. van Essen¹⁰¹, Wim Van Hecke¹³⁷, Caroline van Heugten¹³⁸, Dominique Van Praag¹³⁹, Thijs Vande Vyvere¹³⁷, Roel P. J. van Wijk¹⁰¹, Alessia Vargiolu³², Emmanuel Vega⁸³, Kimberley Velt⁶⁴, Jan Verheyden¹³⁷, Paul M. Vespa¹⁴⁰, Anne Vik^123,141, Rimantas Vilcinis¹³², Victor Volovici⁶⁷, Nicole von Steinbüchel³⁸, Daphne Voormolen⁶⁴, Petar Vulekovic⁴⁶, Kevin K. W. Wang¹⁴², Eveline Wiegers⁶⁴, Guy Williams⁴⁷, Lindsay Wilson⁶⁹, Stefan Winzeck⁴⁷, Stefan Wolf¹⁴³, Zhihui Yang¹¹³, Peter Ylén¹⁴⁴, Alexander Younsi⁹⁰, Frederick A. Zeiler^47,145, Veronika Zelinkova²⁰, Agate Ziverte⁶⁰, Tommaso Zoerle²⁷.

We gratefully acknowledge interactions and support from International Initiative for Traumatic Brain Injury Research funders and investigators. We are immensely grateful to our patients with TBI for helping us in our efforts to improve care and outcomes for TBI. We also acknowledge the contribution and expert advice of Dr Richard Jacques and Joanne Palfreman (University of Sheffield, UK) in conducting statistical analyses (RJ) and manuscript preparation (JP).

Role of Sponsor

Antwerp University Hospital is the study co-ordination centre and undertook the role of sponsor, ensuring research governance according to international standards across the 56 recruiting centres in study procedures, specifically for enrolling patients into the CENTER-TBI Registry and the storage and analysis of patient data.

Transparency statement

Fiona E. Lecky and Andrew I. R. Maas (the paper’s guarantors) affirm that the paper is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that there are no discrepancies from the study as originally planned.

Abbreviations

AIS: Abbreviated Injury Scale
CT: computed tomography
ED: emergency department
EMS: emergency medical service
GCS: Glasgow Coma Scale
ICU: intensive care unit
ISS: Injury Severity Score
TBI: traumatic brain injury

Data Availability

Data cannot be shared as the Consortium Agreement established between the CENTER TBI beneficiaries specifies the need for data access agreements with third parties. Proposals to access the study data, data dictionary, analytic code, and analysis scripts may be submitted online https://www.center-tbi.eu/data. Proposals are subject to review by the management committee. A Data Access Agreement is required, and all access must comply with regulatory restrictions imposed on the original study.

Funding Statement

CENTER-TBI was supported by the European Union 7th Framework program (EC grant 602150), recipient A.I.R. Maas. Additional funding was obtained from the Hannelore Kohl Stiftung (Germany) - recipient A.I.R. Maas, from OneMind (USA) - recipient A.I.R. Maas and from Integra LifeSciences Corporation (USA) - recipient A.I.R. Maas. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Foks KA, Cnossen MC, Dippel DWJ, Mass A, et al. Management of mild traumatic brain injury at the emergency department and hospital admission in Europe: a survey of 71 neurotrauma centers participating in the CENTER-TBI study. J Neurotrauma. 2017;34:2529–35. doi: 10.1089/neu.2016.4919 [DOI] [PubMed] [Google Scholar]
2.Menon DK, Schwab K, Wright DW, Mass A, Demographics and Clinical Assessment Working Group of the International and Interagency Initiative toward Common Data Elements for Research on Traumatic Brain Injury and Psychological Health. Position statement: definition of traumatic brain injury. Arch Phys Med Rehabil. 2010;91:1637–40. doi: 10.1016/j.apmr.2010.05.017 [DOI] [PubMed] [Google Scholar]
3.Vedin T, Svensson S, Edelhamre M, Karlsson M, et al. Management of mild traumatic brain injury—trauma energy level and medical history as possible predictors for intracranial haemorrhage. Eur J Trauma Emerg Surg. 2019;45(5):901–7. doi: 10.1007/s00068-018-0941-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Blyth BJ, Bazarian JJ. Traumatic alterations in consciousness: traumatic brain injury. Emerg Med Clin North Am. 2010;28(3):571–94. doi: 10.1016/j.emc.2010.03.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Russell R, Clasper J, Jenner B, Hodgetts TJ, Mahoney PF. Ballistic injury. BMJ. 2014;348:g1143. doi: 10.1136/bmj.g1143 [DOI] [PubMed] [Google Scholar]
6.Coats TJ, Lecky F. ‘Major trauma’: now two separate diseases? Emerg Med J. 2017;34:494. doi: 10.1136/emermed-2017-206788 [DOI] [PubMed] [Google Scholar]
7.Banerjee J, Baxter M, Coats T, Edwards A, et al. Major trauma in older people. Salford: Trauma Audit and Research Network; 2017. [cited 2021 Sep 9]. https://www.tarn.ac.uk/content/downloads/3793/Major%20Trauma%20in%20Older%20People%202017.pdf. [Google Scholar]
8.National Institute for Health and Care Excellence. Head injury: assessment and early management. Clinical guideline [CG176]. London: National Institute for Health and Care Excellence; 2014 [cited 2021 Sep 9]. https://www.nice.org.uk/guidance/cg176.
9.Rotondo MF, Cribari C, Smith RS, editors. Resources for optimal care of the injured patient. Chicago: American College of Surgeons; 2014. [cited 2021 Sep 9]. https://www.facs.org/-/media/files/quality-programs/trauma/vrc-resources/resources-for-optimal-care.ashx?la=en&hash=37FB4F37DCD6DE1B20969142B227FFDD729F0191. [Google Scholar]
10.Teasdale G, Jennett B. Assessment of coma and impaired consciousness. Lancet. 1974;2(7872):81–4. doi: 10.1016/s0140-6736(74)91639-0 [DOI] [PubMed] [Google Scholar]
11.National Institute for Health and Care Excellence. Head injury: triage, assessment, investigation and early management of head injury in infants, children and adults. Clinical guideline [CG56]. London: National Institute for Health and Care Excellence; 2007. [cited 2021 Sep 9]. https://www.nice.org.uk/guidance/cg56. [Google Scholar]
12.World Health Organization. ICD-10. International statistical classification of diseases and related health problems. 10th revision. Volume 1. Geneva: World Health Organization; 1992. [cited 2021 Sep 9]. https://apps.who.int/iris/handle/10665/228410. [Google Scholar]
13.Committee on Injury Scaling, Association for the Advancement of Automotive Medicine. The Abbreviated Injury Scale, 1990 revision. Chicago: Association for the Advancement of Automotive Medicine; 1990.
14.Marshall LF, Marshall SB, Klauber MR, Clark MV, et al. A new classification of head injury based on computerized tomography. J Neurosurg. 1991;75:S14–20. [Google Scholar]
15.Brazinova A, Rehorcikova V, Taylor MS, Bukova V, et al. Epidemiology of traumatic brain injury in Europe: a living systematic review. J Neurotrauma. 2021;38(10):1411–40. doi: 10.1089/neu.2015.4126 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Peeters W, Van den Brande R, Polinder S, Brazinova A, et al. Epidemiology of traumatic brain injury in Europe. Acta Neurochir (Wien). 2015;157:1683–96. doi: 10.1007/s00701-015-2512-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Moran CG, Lecky F, Bouamra O, Lawrence T, et al. Changing the system-major trauma patients and their outcomes in the NHS (England) 2008–17. EClinicalMedicine. 2018;2–3:13–21. doi: 10.1016/j.eclinm.2018.07.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Lawrence T, Helmy A, Bouamra O, Woodford M, et al. Traumatic brain injury in England and Wales: prospective audit of epidemiology, complications and standardised mortality. BMJ Open. 2016;6:e012197. doi: 10.1136/bmjopen-2016-012197 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Roozenbeek B, Maas AI, Menon DK. Changing patterns in the epidemiology of traumatic brain injury. Nat Rev Neurol. 2013;9:231–6. doi: 10.1038/nrneurol.2013.22 [DOI] [PubMed] [Google Scholar]
20.GBD 2016 Traumatic Brain Injury and Spinal Cord Injury Collaborators. Global, regional, and national burden of traumatic brain injury and spinal cord injury, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(1):56–87. doi: 10.1016/S1474-4422(18)30415-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Cnossen MC, Scholten AC, Lingsma HF, Synott A, et al. Adherence to guidelines in adult patients with traumatic brain injury: a living systematic review. J Neurotrauma. 2021;38(8):1072–85. doi: 10.1089/neu.2015.4121 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Maas AIR, Menon DK, Adelson PD, et al. Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research. Lancet Neurol. 2017;16(12):987–1048. doi: 10.1016/S1474-4422(17)30371-X [DOI] [PubMed] [Google Scholar]
23.Maas AI, Menon DK, Steyerberg EW, Citerio G, et al. Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI): a prospective longitudinal observational study. Neurosurgery. 2015;76:67–80. doi: 10.1227/NEU.0000000000000575 [DOI] [PubMed] [Google Scholar]
24.Steyerberg EW, Wiegers E, Sewalt C, Buki A, et al. The contemporary landscape of traumatic brain injury in Europe: case-mix, care pathways, and outcomes from the CENTER-TBI study. Lancet Neurol. 2019;18(10):923–34. [DOI] [PubMed] [Google Scholar]
25.American Society of Anaesthesiologists. ASA physical status classification system. Schaumburg (IL): American Society of Anaesthesiologists; 2020. [cited 2021 Sep 9]. https://www.asahq.org/standards-and-guidelines/asa-physical-status-classification-system. [Google Scholar]
26.Ringdal K, Coats TJ, Lefering R, Di Bartolomeo S, Steen PA, Røise O, et al. The Utstein template for uniform reporting of data following major trauma: a joint revision by SCANTEM, TARN, DGU-TR and RITG. Scan J Trauma Resusc Emerg Med. 2008;16:7. doi: 10.1186/1757-7241-16-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Baker SP, O’Neill B, Haddon W Jr, Long WB. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma Acute Care Surg. 1974;4(3):187–96. [PubMed] [Google Scholar]
28.Maas AI, Stocchetti N, Bullock R. Moderate and severe traumatic brain injury in adults. Lancet Neurol. 2008;7:728–41. doi: 10.1016/S1474-4422(08)70164-9 [DOI] [PubMed] [Google Scholar]
29.Hartholt KA, van Lieshout EM, Polinder S, Panneman MJM, et al. Rapid increase in hospitalizations resulting from fall-related traumatic head injury in older adults in The Netherlands 1986–2008. J Neurotrauma. 2011;8:739–44. doi: 10.1089/neu.2010.1488 [DOI] [PubMed] [Google Scholar]
30.Harvey LA, Close JC. Traumatic brain injury in older adults: characteristics, causes and consequences. Injury. 2012;43:1821–6. doi: 10.1016/j.injury.2012.07.188 [DOI] [PubMed] [Google Scholar]
31.Peters ME, Gardner RC. Traumatic brain injury in older adults: do we need a different approach? Concussion. 2018;3:CNC56. doi: 10.2217/cnc-2018-0001 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Kehoe A, Smith JE, Bouamra O, Edwards A, et al. Older patients with traumatic brain injury present with a higher GCS score than younger patients for a given severity of injury. Emerg Med J. 2016;3(6):381–5. doi: 10.1136/emermed-2015-205180 [DOI] [PubMed] [Google Scholar]
33.Murphy TE, Baker DI, Leo-Summers LS, Tinetti M. Trends in fall-related traumatic brain injury among older persons in Connecticut from 2000–2007. J Gerontol Geriatr Res. 2014;3(4):1000168. doi: 10.4172/2167-7182.1000168 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Baharoglu MI, Cordonnier C, Al-Shahi Salman R, de Gans K, Koopman MM, Brand A, et al. Platelet transfusion versus standard care after acute stroke due to spontaneous cerebral haemorrhage associated with antiplatelet therapy (PATCH): a randomised, open-label, phase 3 trial. Lancet. 2016;387(10038):2605–13. doi: 10.1016/S0140-6736(16)30392-0 [DOI] [PubMed] [Google Scholar]
35.Peterson AB, Kegler SR. Deaths from fall-related traumatic brain injury—United States, 2008–2017. MMWR Morb Mortal Wkly Rep. 2020;69:225–30. doi: 10.15585/mmwr.mm6909a2 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Cnossen MC, van der Brande R, Lingsma HF, Polinder S, Lecky F, Maas AIR, et al. Prehospital trauma care among 68 European neurotrauma centers: results of the CENTER-TBI Provider Profiling Questionnaires. J Neurotrauma. 2019;36:176–81. [DOI] [PubMed] [Google Scholar]

PLoS Med. doi: 10.1371/journal.pmed.1003761.r001

Decision Letter 0

Caitlin Moyer

27 Oct 2020

Dear Dr Lecky,

Thank you for submitting your manuscript entitled "Traumatic Brain Injury Disease Burden from low energy falls: Findings of the CENTER TBI Registry" for consideration by PLOS Medicine.

Your manuscript has now been evaluated by the PLOS Medicine editorial staff as well as by an academic editor with relevant expertise, and I am writing to let you know that we would like to send your submission out for external peer review.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

Please re-submit your manuscript within two working days, i.e. by .

Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. Once your manuscript has passed all checks it will be sent out for review.

Feel free to email us at plosmedicine@plos.org if you have any queries relating to your submission.

Kind regards,

Caitlin Moyer, Ph.D.,

Associate Editor

PLOS Medicine

PLoS Med. doi: 10.1371/journal.pmed.1003761.r002

Decision Letter 1

Caitlin Moyer

9 Apr 2021

Dear Dr. Lecky,

Thank you very much for submitting your manuscript "Traumatic Brain Injury Disease Burden from low energy falls: Findings of the CENTER TBI Registry" (PMEDICINE-D-20-05160R1) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to three independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We expect to receive your revised manuscript by Apr 30 2021 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

1. Competing Interests: Please add this statement to the manuscript's Competing Interests: "DM is an Academic Editor on PLOS Medicine's editorial board."

2. Data availability statement: Please revise the statement. a) If the data are freely or publicly available, note this and state the location of the data: within the paper, in Supporting Information files, or in a public repository (include the DOI or accession number).

b) If the data are owned by a third party but freely available upon request, please note this and state the owner of the data set and contact information for data requests (web or email address). Note that a study author cannot be the contact person for the data.

c) If the data are not freely available, please describe briefly the ethical, legal, or contractual restriction that prevents you from sharing it. Please also include an appropriate contact (web or email address) for inquiries (again, this cannot be a study author).

We suggest revising the note regarding data access as: “Data cannot be shared due to XXX. Proposals to access the study data, data dictionary, analytic code, and analysis scripts may be submitted online at https://www.center-tbi.eu/data. Proposals are subject to review by the management committee. A Data Access Agreement is required, and all access must comply with regulatory restrictions imposed on the original study.” or similar.

3. Abstract: Please structure your abstract using the PLOS Medicine headings (Background, Methods and Findings, Conclusions).

4. Abstract: Please quantify the main results (with 95% CIs and p values). In the last sentence of the Abstract Methods and Findings section, please describe the main limitation(s) of the study's methodology.

5. Abstract: Conclusions: Please address the study implications without overreaching what can be concluded from the data; beginning the section with the phrase "In this study, we observed ..." may be useful.

6. Author Summary: Thank you for including the summary box. Please reformat this into a short, bulleted, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information on Author Summary format: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

7. References: Please use square brackets for in-text citations, like this [1]. Please do not include spaces within brackets when listing multiple references [1-4].

8. Line numbers: Please include line numbers throughout text when re-submitting the document.

9. Methods: Page 7: Please include in the text, the 17 countries included. If possible, please include the information/distributions for the 56 participating centres as supporting information.

10. Methods: Page 8: It would be helpful to have more detail on the nature of the data collected: “We collected variables describing demographics (age & gender), pre-existing health status (https://www.asahq.org/standards-and-guidelines/asa-physical-status-classification-system), mechanism of injury, injury severity descriptors (Glasgow Coma Scale (GCS), Abbreviated Injury Scale (AIS)), presenting physiological vital signs, CT Brain findings, processes of care, and immediate outcome of care in terms of hospital mortality and destination on discharge (Tables 1-4). These variables were derived from the Utstein trauma template used for standard trauma registry collection across Europe, North America and Australasia.”

11. Methods: Page 9: Please note how you accounted for clustering at the country level (and center within country).

12. Methods: Page 9: Please explicitly indicate which analyses were done using chi-square, and which were done using Mann-Whitney tests, at least in the Table legends where the results are presented. And please clarify if all the continuous variables were non-parametric.

13. Methods: Did your study have a prospective protocol or analysis plan? Please state this (either way) early in the Methods section.

a) If a prospective analysis plan (from your funding proposal, IRB or other ethics committee submission, study protocol, or other planning document written before analyzing the data) was used in designing the study, please include the relevant prospectively written document with your revised manuscript as a Supporting Information file to be published alongside your study, and cite it in the Methods section. A legend for this file should be included at the end of your manuscript.

b) If no such document exists, please make sure that the Methods section transparently describes when analyses were planned, and when/why any data-driven changes to analyses took place.

c) In either case, changes in the analysis-- including those made in response to peer review comments-- should be identified as such in the Methods section of the paper, with rationale.

14. Methods: Page 10: Please revise the STROBE statement to: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."

15. Results: Page 11: Please define the abbreviations “PM” and “TARN” at first use.

16. Results: Page 11: Please clarify if the “Overall Cohort” results described and Table 1 pertain to the overall registry, or specifically those included in the study.

17. Results: Please provide 95% CIs and p values for all analyses described in the text.

18. Results: Page 18: The multivariable logistic regression here did not seem to be described in the Methods section. For the following result, please indicate the variables used in the adjustment: “The 50% reduction in likelihood of critical care provision for the low energy cohort persisted after demographic, injury and comorbid considerations were accounted for in multivariable logistic regression - Adjusted Odds Ratio (AOR) 0·46 (95% Confidence Interval (CI) (0·43-0·50), a reduction in the likelihood of hospital admission was also observed for patients injured by low energy transfer albeit less so in older people. In patients with TBI admitted to the ward and intensive care the characteristics of patients injured by low energy transfer ( older age, pre-injury comorbidity and anticoagulation, non-evacuated mass lesion – Marshall VI- in ward admissions) were strong independent predictors of hospital mortality; after adjustment for these low energy transfer did not independently predict mortality (suppl tables iv-vii); non-evacuated intracranial mass lesions were present in 3·1% (n=118) and 1·2% (n=53) of ward admission patients injured by low and high energy transfer.”

19. References: Please use the "Vancouver" style for reference formatting, and see our website for other reference guidelines https://journals.plos.org/plosmedicine/s/submission-guidelines#loc-references

20. Table 1: Please define all abbreviations in the legend (TBI, IQR).

21. Supporting information files: Please include both a descriptive title and legend for each figure/table of the supporting information. In particular, please provide a description for Supporting Information Figure S2.

22. Supporting information Tables S4, S5, S6, S7: In the legend please provide the variables used in the adjustment. Please also present the unadjusted results.

23. STROBE Checklist: Please reformat the checklist, using section and paragraph numbers to refer to locations within the text, rather than page numbers.

Comments from the reviewers:

Reviewer #1: The authors presented a well-constructed study addressing TBI Disease Burden focusing in low energy falls as mechanism of injury using data from the CENTER TBI registry. Whilst the data are interesting, they are very similar to those shown by a huge amount of studies evaluating geriatric TBI (actually, those patients who undergone low energy falls).

Since the study underscores that patients with low energy falls receive less invasive monitorization/treatments, it would be interesting to know how many of these patients had any limitation of life sustaining therapies. This would help to better characterize the population.

Minor comments:

Some references must be updated.

References are presented in different formats

Reviewer #2: "Traumatic Brain Injury Disease Burden from low energy falls: Findings of the CENTER TBI Registry" describes a comparative cohort study on the CENTER-TBI registry, involving over 21,000 patients presenting with traumatic brain injury (TBI) and indications for CT brain scan enrolled from 18 countries, from 2014 to 2018. The effect of various patient characteristics (both unadjusted and adjusted) is examined, for three clinical care pathways - emergency department (ED), admission to hospital but not ICU (ADM), and admission to the ICU (ICU). The main conclusion was that patients sustaining TBI comprise an important distinct demographic cohort, and that the level of energy transfer should not inform triage since it does not predict intracranial injury severity or threat to life.

While the scale of the registry and study is impressive, there are a number of issues that might be addressed:

1. Given the main recommendation of the study ("level of energy transfer should not inform triage"), it might be clarified as to the degree (if any) that level of energy transfer currently informs triage in the participating countries/hospital, cited guidelines ([8],[9]) notwithstanding.

In particular, while Table 1 affirms that level of energy transfer does not strongly predict intracranial injury severity (at least as measured by GCS), it can be observed that the care pathway distribution differs significantly between high and low energy TBI (24.4% ICU for high, versus 11.5% ICU for low). However, it is not certain whether this difference in clinical pathway is due to triaging on level of energy transfer in the first place, or due to other criteria. Indeed, it is mentioned that "most published TBI series do not differentiate high from low energy transfer falls" (Page 6). This might be clarified.

2. Additionally, one might suspect that injury events that are classified as high energy transfer (e.g. traffic collisions, falling from a height, etc) may be more likely to be triaged as ICU, at least partly due to accompanying critical injury to other organs/limbs (e.g. internal injury to core organs, broken arms/legs). It is unclear whether these possible non-brain/head injuries were record/accounted for in adjustments, from the patient characteristics presented in Table 1, despite possibly being a major factor in triage outcomes in practice. This might be clarified.

3. On Page 7, the Inclusion/Exclusion criteria might be made more consistent with Figure 1. In particular, it is stated that "...the Registry included patients with pre-existing cognitive impairment etc... these three groups were exclused from recruitment to the CENTER TBI core study", while Figure 1 appears to describe the bulk of the exclusions (1101 patients) as "missing and unknown mechanisms of injury". Terminology might be standardized between the main text and the flowchart figure, and it might be made more explicit in the figure as to what the registry includes (the initial 22,849 patients?) and where the recruitment to the core study is complete (the 21,681 patients?)

4. More generally, the existing triage criteria for assigning a patient to one of the three clinical pathways (ED, ADM, ICU; Page 8) might be explained in greater detail (partly alluded to in Point 1). If clinicians considered level of energy transfer as a criteria for triage, was it a major or minor criteria?

5. The purposive sampling procedure (Page 7) might be described in greater detail. How was it designed to produce a representative sample?

6. On Page 8, the ED clinical pathway is described as "either discharge or direct to the mortuary from the ED"; it might be clarified as to whether "discharge from the ED" in this case, is a full discharge from the hospital, or possibly to general admissions/the ICU.

7. More details on the multivariate analyses (as presented in Supplementary Tables V to VII) might be provided. In particular, how were the variables involved for each of these analyses selected, given that some available variables from Tables 1 & 2 appear to be omitted? p-values might also be included.

8. For EDGCS in Supplementary Tables V to VII, it appears presented as a binary category despite involving multiple groups/classes (as described in Table 1; contrast the Marshall Classification groups, which are analyzed individually). As such, the delineation of these groups/classes into a binary categorization might be described and justified.

9. Still on Supplementary Tables V to VII, an AUC value (e.g. AUC = 0.90) is mentioned for each table in its caption. If these AUCs pertain to each assumed logistic regression model in predicting ICU/mortality, it might be considered to also present the corresponding ROC curves.

10. A general reservation is that while the manuscript suggests that TBI triage on energy transfer does not inform risks of intracranial injury/hospital mortality and thus should be discarded, it does not appear to propose and justify a concrete alternative. In particular, the presented multivariate analyses would seem to have the potential to quantitatively suggest an alternative triage model (or risk score, since it is admitted in the limitations section that the analyses are post-hoc; therefore, the impact of improved triage is probably difficult to estimate). This might be considered by the authors.

11. There are a number of phrasing issues, e.g. the sentences "Injury classification by energy transfer mechanisms..."; "Patients injured by high energy mechanisms being conveyed..." (Page 5), "Forty percent (8622) of patients..." (Page 15), "significant longer term rates of disability..." (Page 22), etc.

Reviewer #3: Markus Skrifvars, University of Helsinki

Regarding the paper "Traumatic Brain Injury Disease Burden from low energy falls: Findings of the CENTER TBI Registry" submitted to PLOS Medicine. This a sub-study of the large TBI registry CENTER-TBI. This paper contains data from a large database/study with potential interest to the general medical audience. I have the following comments:

- The major aim of this study is to compare low and high energy trauma. Therefore it is paramount to include more precise information on how this classification was done. Perhaps include a Table with the different types of in the two groups? Was this classification done on site? Was there any data validation between centers in order to make sure that different centers scored this the same way? Of course one may debate whether a low velocity car accident or bicycle accident (with a helmet) is different from a fall from standing were the energy on the head may be substantial.

- The manuscript mentions that patients with a suspected or confirmed TBI who had a CT brain done were included. Did there need to be a clear presented history of a trauma? I refer to the elderly patient who is found at home without any clear evidence of what has happened. Continuing on from this do you have information on how many of the abnormal CT brain findings were unexpected? Again many of these patients will have an unclear event history with many factors making the diagnostic work up more difficult (intoxiocations, seazures, cardiac arrhythmias etc.).

- One would intuitively think that the use of "not for ICU", DNR and other treatment limitations would impact the admission of the elderly patients with multiple comorbidities to ICU. Is this information included in the registry?

- I would personally like to see the results of a multivariable model predicting outcome including high/low energy. This could even be done for only the patients with an abnormal CT scan. The key question is, if you look at two similar abnormal CT scans will the outcome be different if they are the result of a high or low energy? When you have the abnormal CT in front of you what are the factors that drive admission to ICU? I suspect it is age.

- Continuing on from the previous point. I would be interested to know if one ends up in the ICU does it then make any difference for outcome (survival, neurological outcome) if the energy was high or low?

- Do you have information about frailty and functional capacity? Again I suspect that this piece of information will drive the decision on further care.

- In the first sentence of the discussion there is a statement that 40% of patients with TBI have a low energy injury pattern. Does this comparison also include those with a negative CT brain? Perhaps state more specifically about numbers in those with a CT brain confirmed TBI?

- You mention in the discussion that the low-energy patients may be receive less intense care. This may be the case but is this the results of the injury being of low energy or the fact that these patients are not perceived to benefit from these interventions? Unless you present data that many of these "low energy" patients experience late deterioration with emergency surgery and ICU admission this may not be completely supported by your data.

- The European map with differences in incidence of low energy TBI is intriguing. However, this is not discussed in the manuscript. Were the centers included in the CENTER-TBI study of comparable enabling the drawing of such a Figure? Indeed one would like to see the equivalent of a 95% confidence interval in the colors. This is of course not possible but somehow certainly of these findings must be presented.

- Do you have information on how many patients were intoxicated? Again data suggests the association between alcohol/drugs and TBI from low-energy trauma.

- In the discussion the authors state that anti-platelet medication effects cannot be reversed. How the administration of platelets?

- The conclusion includes some ideas about the need for future studies especially regarding the need for more studies on the intensity of TBI care in low-energy cohort. Do we really think that it is the injury energy in itself that is driving care decisions and not the patient? I suspect that most clinicians make their decision on a combination of things with patient age, comorbidities and functional status being in focus. So unless the authors have compelling data that really challenges this, perhaps the conclusion should be softened.

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2021 Sep 14;18(9):e1003761. doi: 10.1371/journal.pmed.1003761.r003

Author response to Decision Letter 1

21 May 2021

Attachment

Submitted filename: CENTER TBI REGISTRY PAPER RESPONSE TO REVIEWERS.docx

Click here for additional data file.^{(44.8KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1003761.r004

Decision Letter 2

Caitlin Moyer

15 Jun 2021

Dear Dr. Lecky,

Thank you very much for submitting your revised manuscript "Traumatic Brain Injury Disease Burden from low energy falls: Findings of the CENTER TBI Registry" (PMEDICINE-D-20-05160R2) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to two of the original reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of the reviewer comments, we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

We expect to receive your revised manuscript by Jun 29 2021 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

We look forward to receiving your revised manuscript.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

1. Please completely address the points of the reviewers.

2. Data availability statement: Please remove the initial “Data sharing statement:” from this section.

3. Title: Please revise your title according to PLOS Medicine's style. Your title must be nondeclarative and not a question. It should begin with main concept if possible. "Effect of" should be used only if causality can be inferred, i.e., for an RCT. Please place the study design ("A randomized controlled trial," "A retrospective study," "A modelling study," etc.) in the subtitle (ie, after a colon).

We suggest: “Traumatic brain injury disease burden from low energy falls among patients from 17 countries from the CENTER-TBI Registry: A comparative cohort study” or similar, mentioning the design and setting.

4. Abstract: Please combine the Methods and Findings into a single section, with the main limitations as the final sentence of this section.

5. Abstract: Line 61-62: Please reword this sentence if possible, to clarify.

6. Abstract: Lines 65-76: Where the findings are reported, it is not completely clear that the first group is the low energy and the second is the high energy cohort. Please clarify this if possible.

7. Abstract: Line 71-72: Please clarify whether the finding of CT abnormalities was or was not significantly different between groups (p<0.001 is reported, where the text reports the groups were similar).

8. Abstract: Line 81-82: We suggest tempering this conclusion, given some of the limitations pointed out by the reviewer. “This suggests energy transfer level should no longer inform prehospital and emergency department TBI triage in older people.”

9. Author Summary: Please remove the “summary box” and please format using bullet points (we suggest 3-4 for each of the three sections). The third section should be titled “What do these findings mean?”

10. Author Summary: Please temper the second and third points of the “What do these findings mean” section, please interpret the study based on the results presented in the abstract, without overstating your conclusions.

11. Methods: Analysis Plan: Thank you for describing the analysis plan for your study. If feasible, please include a document version of the analysis plan as a supporting information file.

12. Results: For the “Comparisons by Energy Transfer mechanism” and “Injury characteristics” sections, please make it more clear in the text where possible, the nature of the two groups being compared (for example, where two sets of values refer to the low and high energy transfer groups, respectively).

13. Results: Line 314-317: Please clarify if these differences reached statistical significance (Table 2 seems to suggest they may). “In patients injured by low energy falls the proportion with abnormalities detected on CT scan (including skull fracture) and proportion of abnormal scans showing intracranial injury (29% (95% CI 27-31%) and 70% (95% CI 69-73%) was similar to that of patients injured by high energy mechanisms (32% (95% CI 31-34%) and 75% (95% CI 74-77%)).

14. Results: Line 342-344: Please clarify that for this finding, this was significant only for specific intervention (craniotomy) as shown in Table 3. “In the low energy cohort there was a greater time delay between arrival at the study hospital and the provision of emergency interventions such as craniotomy (Table 3).”

15. Results: Line 371-378: Please revise this sentence to clarify, or split into multiple sentences.

16. Discussion: Line 406: Please clarify this sentence to reflect the study findings. In your analysis, there seemed to be a significant differences in CT abnormality between the two groups, for example. You note later in the limitations section that these may not be clinically meaningful, but perhaps that could be expanded on/clarified here.

17. Conclusions: Line 511: Please modify this sentence with “...to our knowledge, the largest…” or similar wording.

18. Conclusions: Line 515: Please revise this sentence to temper the recommendations somewhat: Our findings suggest that within the older cohort, TBI triage based on energy transfer may not inform risk of intracranial injury and hospital mortality.”

19. Acknowledgements: Please remove the funding information from this section, and ensure all information is accurately entered into the Financial Disclosure and Competing Interests section of the manuscript submission form.

20. Page 28-29: Please remove the “Financial Disclosure” and “Competing Interests” sections from the main text of the manuscript- this information should be accurately entered into the manuscript submission form.

21. Line 583: List of The CENTER-TBI participants and investigators. Please include those who contributed to the work but do not meet our authorship criteria should be listed in the Acknowledgements with a description of the contribution. Authors are responsible for ensuring that anyone named in the Acknowledgements agrees to be named.

22. Figure 1: Please include a descriptive legend, including a definition of RTC.

23. Figure 2: Please confirm that the appropriate usage rights apply to the use of this map. Please see our guidelines for map images: https://journals.plos.org/plosmedicine/s/figures#loc-maps

24. Figure 3: Please include a legend, including definitions for all abbreviations used.

25. Table 2: Please clarify ASH vs ASDH in the table/legend.

26. Checklist: Please remove all references to page numbers.

Comments from the reviewers:

Reviewer #2: We thank the authors for addressing the previously raised points, and concerns over potential confounding on severity of extracranial injuries with reference to Supplemental Table V, which appears also updated with univariate odds from the previous revision (as is Supplemental Table IV).

1. It might however be explained as to why some values in the (updated) Supplemental Table V, appear different from the previous revision. For example, adjusted odds ratio for Significant Extracranial Injury is now 1.60 (1.40-1.82), while previously it was 1.59 (1.40-1.81). It might also be considered to explicitly state the baseline reference and condition being varied, for these tables (e.g. baseline being low energy, versus high energy)

2. The revised Results section states that "The 50% reduction in likelihood of critical care provision for the low energy cohort persisted after variables influencing critical care admission decisions were adjusted... Adjusted Odds Ratio (AOR) 0·46 (95% CI 0·43-0·50) - AOR 0.77 ( 95% CI 0.53-1.12) after accounting for the interaction between age and energy transfer mechanism (supplemental table v)". However, it is not clear where the initial 0.46 OR arises from, in the actual Supplemental Table V. The relevant univariate OR appears to be given as 0.36. This might be clarified.

3. The additional ROC curves provided as requested are appreciated. However, Supplemental Figure IV shows an AUROC = 0.9012, while its corresponding Supplemental Table V gives AUC = 0.91, which does not appear to correspond after rounding, unlike the other three figure/table pairs. This might be clarified.

4. It has been partly clarified that "Decisions on the care pathway for patients after the Emergency Department CT scan (decisions on discharge from hospital, or level of care for admitted patients) depend on imaging findings as well as the initial triage priority". Further specific details on the care pathways might be described, if possible.

5. The explanation for Point 8 on EDGCS as a binary category, might also be included in the manuscript or supplementary material in some capacity.

Reviewer #3: Markus Skrifvars University of Helsinki

Regarding the revised version of the paper "Traumatic Brain Injury Disease Burden from low 2 energy falls: Findings of the CENTER TBI Registry" submitted to Plos Medicine. The authors have revised their manuscript. The paper contains important information about the epidemiology if TBI care. However some of the conclusions made and recommendations are not completely supported by the data and further softening is in my mind required. From a societal/research perspective the key issue is the need to include these patients in TBI trials. My personal clinical take from this teh very risky patient group of; the elderly patient using anticoagulants/antiplatelet agents with low energy fall.

- In some parts of the manuscript I feel that there still is a suggestion that "low energy" in itself is the main reason why the patient does not receive ICU care For example on line 408-409 the authors state "However, the low energy cohort was 50% less likely to receive critical care (12% versus 24%) or emergency intervention (7·5% versus 13%)". I would suggest that one could also use the word "need" instead of "receive". I do not think that a study such as this can provide solid evidence that it is the injury mechanism in itself that prompted the neurosurgeon/neurointensivist NOT to admit the patient.

- Continuing from the previous comment, what do the authors suggest we should do in case of a low energy TBI patient with a GCS 14-15 patient and with a non-operatively managed injury on the CT scan? What is the ICU intervention that will make a difference?

- As the authors are comparing high and low energy falls it is quite clear that the reason the high energy group may have needed ICU care not due to their TBI but to other injuries. For example, how many were sedated/mechanically ventilated in the ED? It is quite clear that such a patient will go to the ICU no matter what?

- The statement in conclusion "This suggests energy transfer level should no longer inform prehospital and emergency department TBI triage in older people". This is a bit problematic I think. I think one can say based on these findings that a low energy level does not rule out significant TBI with high morbidity and mortality. But on the other hand, I do think that a significant injury mechanism must still be seen as a major contributor to morbidity and mortality and should treated as such. There is also the risk of multi-trauma. I would maintain that from the pre-hospital standpoint an elderly patient with a low energy fall is more likely to have a mild TBI/other pathology than one injured for example in a high speed traffic collision.

- It would be very interesting to the see the IMPACT risk in the high and low energy cohorts. In a simple model with the IMPACT risk included is the trauma energy a significant predictor of outcome? Is this the same in different age categories and based on use of antiplatelet agents.

- The authors mentions alcohol and drug intoxication as a challenge for pre-hospital TBI care. Can the authors perhaps provide a reference for this and slightly expand what they mean? Are intoxicated patients thought to have a more severe TBI or vice versa?

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2021 Sep 14;18(9):e1003761. doi: 10.1371/journal.pmed.1003761.r005

Author response to Decision Letter 2

18 Jul 2021

Attachment

Submitted filename: PLOS MED Responses to Editor and Reviewers.docx

Click here for additional data file.^{(31.7KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1003761.r006

Decision Letter 3

Caitlin Moyer

28 Jul 2021

Dear Dr. Lecky,

Thank you very much for re-submitting your manuscript "Traumatic Brain Injury Disease Burden from low energy falls:A comparative cohort study of patients from 18 countries - the CENTER TBI Registry." (PMEDICINE-D-20-05160R3) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by two reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

Please note, when your manuscript is accepted, an uncorrected proof of your manuscript will be published online ahead of the final version, unless you've already opted out via the online submission form. If, for any reason, you do not want an earlier version of your manuscript published online or are unsure if you have already indicated as such, please let the journal staff know immediately at plosmedicine@plos.org.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Aug 04 2021 11:59PM.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

------------------------------------------------------------

Requests from Editors:

1. Title: We suggest revising the title to: The burden of traumatic brain injury from low energy falls among patients from 18 countries in the CENTER TBI registry: A comparative cohort study”

2. Data availability statement: Please remove the opening set of quotation marks (“Data cannot be shared…).

3. Abstract: Lines 59-60: We suggest reformatting this sentence to clarify, and incorporating it into the following paragraph: “22782 eligible patients were enrolled, and study outcomes were analysed on 21681 TBI patients with known injury mechanism.”

4. Abstract: Line 72-73: Please clarify this sentence to make it clear it is the low energy group who were more likely to not receive critical care and emergency intervention.

5. Abstract: Line 79-81: We suggest revising to “...and further, our findings suggest that energy transfer level may not predict intracranial injury or acute care mortality in patients with TBI presenting to hospital. This suggests factors beyond energy transfer level may be more relevant to prehospital and emergency department TBI triage in older people.” or similar, depending on your meaning.

6. Author summary: Line 91: We suggest revising “are given lower priority” to “can be given lower priority” as it seems like this wouldn’t universally be the case depending on the circumstances.

7. Author summary: Line 101: We suggest revising to: “We found that the 40% of patients with TBI who were injured through low energy falls were significantly older…”

8. Author summary: Line 109-110: We suggest revising to “Low energy falls contribute to a significant portion of the TBI disease burden, which will increase…”

9. Author summary: Line 113-114: We suggest clarifying the wording here that the findings don’t necessarily indicate that fall energy level is not relevant to the triage process.

10. Introduction: Line 124-126: Please clarify to indicate that this is not an all-inclusive list of the sources of high and low energy transfer mechanisms “(High energy transfer resulting from road traffic collisions, falling from a height, blunt assault or contact sports while low energy transfer results from low level falls or those from a standing height [6,7,8])”

11. Introduction: Line 127-128: We suggest revising to: “informing Emergency Medical Service (EMS) on scene trauma triage [3,8,9], with patients injured by high energy transfer…”

12. Methods: Line 208: Please clarify if the energy mechanism classification list here is inclusive of all types of injuries presented.

13. Results: Line 334: Please fix the “s” typo in this sentence: “...was s lower than that of patients”

14. Results: Line 352: Please check if an end parenthesis is missing from: “(median (IQR) extracranial ISS; LE = 2 (0-8) versus HE = 5 (1-13) p<0.001.”

15. Results: Line 381-384: Please clarify the numbers associated with the high energy group in this sentence: “...6% higher in ICU patients (22% (95% CI 17-28%) versus 16 % (95% CI 13-20%)) 383 and four times greater in admitted patients (4.2% (95% CI 1.1–7.3%) versus 0·9% (95% CI 0.0 -3.8%)...”

16. Discussion: Line 407-408 and at Line 425: We suggest making the distinction between European hospitals and hospitals located in Israel. Please similarly adjust the language at line 410-411- “the first pan European study” as it is not clear if Israel is being considered as a European country.

17. Discussion: Line 411-413: Please revise this sentence to clarify if you mean that there are a greater proportion of older adults in the low energy fall cohort or among all of those presenting with TBI: “Compared to the broader past literature we observed a greater proportion of older adults (>65 years old)-almost 39% as opposed to 10-17% previously reported elsewhere [22,27].”

18. Discussion: Line 457: Please remove the superscript formatting applied to the word “and” in the sentence.

19. Discussion: Line 476: Please clarify, here and throughout, if there are 18 or 17 countries represented in the study.

20. Conclusions: Line 515-517 Please also change to “across Europe and Israel” or similar.

21. Page 33: Please remove the “Role of the funding source” section from the main manuscript, and ensure the information is accurately entered into the Financial Disclosures section of the manuscript submission system.

22. Page 33: Please remove the “Data sharing” section from the main manuscript, and ensure the information is accurately entered into the Data Availability section of the manuscript submission system.

23. Acknowledgements: We suggest listing all contributing members of the group, with affiliations, in a supporting information file. Or, including the names in the acknowledgements, but moving the affiliations to a supporting information file.

24. Figure 1: Please remove the extra paragraph symbols from the figure. If possible, please increase the font size, as it is difficult to read. Please include a brief descriptive legend. Please indicate the original sample of 22849 as those enrolled in the registry, and please clarify (here and or the first sentence of the results) why the number is different from the 22782 mentioned in the Results as enrolled in the Registry.

25. Figure 2: We suggest increasing the font size, if possible. Please also include a legend explaining the color map as it relates to low energy injury prevalence. Please note in the legend:

26. Figure 3: Please include a descriptive legend that describes what is illustrated in the figure.

27. Analysis Plan: We suggest renaming this file “S1 Analysis Plan” or similar. If possible, please note in the document that this describes a prospectively developed analysis plan for the project (as written it seems as if it is a preliminary report on the findings).

28. Supporting information files: Supplementary tables: Please provide a “clean” version of the document without markup. It was not clear which table went with which title/legend from tables 4-8. Please include the title and legend with each table individually.

29. Table 1: We suggest “no pre-existing medical conditions” or similar instead of “normal healthy patient” in the left column under Pre-Injury Health Status.

30. Supporting information files naming: You may use almost any description as the item name of your supporting information as long as it contains an "S" and number. For example, “S1 Appendix” and “S2 Appendix,” “S1 Table” and “S2 Table,” and so forth.

Please use whole numbers when naming your supporting information files. Combine separate parts (e.g., S1A and S1B Table) into one file (e.g. S1 Table) or rename with whole numbers (e.g., S1 and S2 Table).

Please match the names of your supporting information files with the supporting information captions within your manuscript. For example, a PDF file for “S2 Fig.” must be named “S2_fig.pdf”.

If you wish to refer to an element within a supporting information file, such as a table within a supporting text file, cite it in one of the following ways: “Table A in S1 Text,” “Table in S1 Table,” or “data in S1 Text.” Please do NOT cite it as “S1 Table in S1 Text.” This may lead to hyperlinking errors.

Comments from Reviewers:

Reviewer #2: We thank the authors for addressing the previous comments.

Reviewer #3: Markus Skrifvars, University of Helsinki

The authors have adressed my concerns and the paper has improved.

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2021 Sep 14;18(9):e1003761. doi: 10.1371/journal.pmed.1003761.r007

Author response to Decision Letter 3

3 Aug 2021

Attachment

Submitted filename: Responses to Requests from Editors.docx

Click here for additional data file.^{(20KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1003761.r008

Decision Letter 4

Caitlin Moyer

6 Aug 2021

Dear Dr Lecky,

On behalf of my colleagues and the Academic Editor, Martin Schreiber, I am pleased to inform you that we have agreed to publish your manuscript "The burden of Traumatic Brain Injury from low energy falls among patients from 18 countries in the CENTER TBI Registry: A comparative cohort study." (PMEDICINE-D-20-05160R4) in PLOS Medicine.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Once you have received these formatting requests, please note that your manuscript will not be scheduled for publication until you have made the required changes.

In the meantime, please log into Editorial Manager at http://www.editorialmanager.com/pmedicine/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process.

Please also complete these remaining editorial requests:

-Abstract: Line 52: Please revise to “56 acute trauma receiving hospitals across 18 countries (17 countries in Europe and Israel)” to avoid confusion between distribution of countries and the numbers of acute trauma centers.

-Methods: Line 190: Please cite the ASA Physical Status Classification System guidelines as a reference (in the reference list).

PRESS

We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with medicinepress@plos.org. If you have not yet opted out of the early version process, we ask that you notify us immediately of any press plans so that we may do so on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

(DOCX)

Click here for additional data file.^{(80.4KB, docx)}

S1 Fig. Cumulative monthly recruitment across 56 sites and prevalence of low-energy transfer injury mechanism in TBI patients in recruiting sites plotted by estimate precision (1/standard error).

(TIF)

Click here for additional data file.^{(2.3MB, tif)}

S2 Fig. Hospital arrival time by energy transfer level in CENTER-TBI Registry and Trauma Audit and Research Network (TARN).

(TIF)

Click here for additional data file.^{(1.3MB, tif)}

S3 Fig. Receiver operating characteristic (ROC) curve multivariable analysis of factors predicting ICU admission in 11,673* patients from the CENTER-TBI Registry.

*Excluding 9,286 patients who were discharged from or died in the ED and 722 with missing age/GCS sum score and/or extracranial injury details.

(TIF)

Click here for additional data file.^{(1.2MB, tif)}

S4 Fig. Receiver operating characteristic (ROC) curve multivariable analysis of factors predicting hospital admission in 18,035* patients from the CENTER-TBI Registry.

*Excluding patients who died in the ED (n = 69), arrived as secondary transfers (n = 2,706), or had missing age/CT.

(TIF)

Click here for additional data file.^{(1.2MB, tif)}

S5 Fig. Receiver operating characteristic (ROC) curve multivariable analysis of factors predicting in-hospital mortality in 7,792* ward admission patients from the CENTER-TBI Registry.

*Excluding 432 patients with missing GCS sum score and/or discharge status.

(TIF)

Click here for additional data file.^{(1MB, tif)}

S6 Fig. Receiver operating characteristic (ROC) curve multivariable analysis of factors predicting in-hospital mortality in 3,739* ICU admission patients from the CENTER-TBI Registry.

*Excluding 432 patients with missing GCS sum score/age and/or discharge status.

(TIF)

Click here for additional data file.^{(1.1MB, tif)}

S1 STROBE Checklist. STROBE statement—Checklist of items that should be included in reports of cohort studies.

(DOCX)

Click here for additional data file.^{(30.2KB, docx)}

S1 Table. Hospitals recruiting to the CENTER-TBI Registry.

(DOCX)

Click here for additional data file.^{(18.6KB, docx)}

S2 Table. Comparison of demographic and comorbid characteristics by energy transfer level and care pathway.

(DOCX)

Click here for additional data file.^{(15.2KB, docx)}

(DOCX)

Click here for additional data file.^{(19.9KB, docx)}

(DOCX)

Click here for additional data file.^{(18.7KB, docx)}

(DOCX)

Click here for additional data file.^{(20.3KB, docx)}

(DOCX)

Click here for additional data file.^{(18.9KB, docx)}

(DOCX)

Click here for additional data file.^{(18.7KB, docx)}

S8 Table. Imaging findings, injury severity, therapeutic interventions, discharge status—Comparative analysis of the CENTER-TBI Registry high, low and unknown energy transfer cohorts.

(DOCX)

Click here for additional data file.^{(16.1KB, docx)}

S1 Text. Institutional affiliations of CENTER-TBI Participants and Investigators.

(DOCX)

Click here for additional data file.^{(20.2KB, docx)}

Attachment

Submitted filename: CENTER TBI REGISTRY PAPER RESPONSE TO REVIEWERS.docx

Click here for additional data file.^{(44.8KB, docx)}

Attachment

Submitted filename: PLOS MED Responses to Editor and Reviewers.docx

Click here for additional data file.^{(31.7KB, docx)}

Attachment

Submitted filename: Responses to Requests from Editors.docx

Click here for additional data file.^{(20KB, docx)}

Data Availability Statement

[pmed.1003761.ref001] 1.Foks KA, Cnossen MC, Dippel DWJ, Mass A, et al. Management of mild traumatic brain injury at the emergency department and hospital admission in Europe: a survey of 71 neurotrauma centers participating in the CENTER-TBI study. J Neurotrauma. 2017;34:2529–35. doi: 10.1089/neu.2016.4919 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref002] 2.Menon DK, Schwab K, Wright DW, Mass A, Demographics and Clinical Assessment Working Group of the International and Interagency Initiative toward Common Data Elements for Research on Traumatic Brain Injury and Psychological Health. Position statement: definition of traumatic brain injury. Arch Phys Med Rehabil. 2010;91:1637–40. doi: 10.1016/j.apmr.2010.05.017 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref003] 3.Vedin T, Svensson S, Edelhamre M, Karlsson M, et al. Management of mild traumatic brain injury—trauma energy level and medical history as possible predictors for intracranial haemorrhage. Eur J Trauma Emerg Surg. 2019;45(5):901–7. doi: 10.1007/s00068-018-0941-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref004] 4.Blyth BJ, Bazarian JJ. Traumatic alterations in consciousness: traumatic brain injury. Emerg Med Clin North Am. 2010;28(3):571–94. doi: 10.1016/j.emc.2010.03.003 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref005] 5.Russell R, Clasper J, Jenner B, Hodgetts TJ, Mahoney PF. Ballistic injury. BMJ. 2014;348:g1143. doi: 10.1136/bmj.g1143 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref006] 6.Coats TJ, Lecky F. ‘Major trauma’: now two separate diseases? Emerg Med J. 2017;34:494. doi: 10.1136/emermed-2017-206788 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref007] 7.Banerjee J, Baxter M, Coats T, Edwards A, et al. Major trauma in older people. Salford: Trauma Audit and Research Network; 2017. [cited 2021 Sep 9]. https://www.tarn.ac.uk/content/downloads/3793/Major%20Trauma%20in%20Older%20People%202017.pdf. [Google Scholar]

[pmed.1003761.ref008] 8.National Institute for Health and Care Excellence. Head injury: assessment and early management. Clinical guideline [CG176]. London: National Institute for Health and Care Excellence; 2014 [cited 2021 Sep 9]. https://www.nice.org.uk/guidance/cg176.

[pmed.1003761.ref009] 9.Rotondo MF, Cribari C, Smith RS, editors. Resources for optimal care of the injured patient. Chicago: American College of Surgeons; 2014. [cited 2021 Sep 9]. https://www.facs.org/-/media/files/quality-programs/trauma/vrc-resources/resources-for-optimal-care.ashx?la=en&hash=37FB4F37DCD6DE1B20969142B227FFDD729F0191. [Google Scholar]

[pmed.1003761.ref010] 10.Teasdale G, Jennett B. Assessment of coma and impaired consciousness. Lancet. 1974;2(7872):81–4. doi: 10.1016/s0140-6736(74)91639-0 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref011] 11.National Institute for Health and Care Excellence. Head injury: triage, assessment, investigation and early management of head injury in infants, children and adults. Clinical guideline [CG56]. London: National Institute for Health and Care Excellence; 2007. [cited 2021 Sep 9]. https://www.nice.org.uk/guidance/cg56. [Google Scholar]

[pmed.1003761.ref012] 12.World Health Organization. ICD-10. International statistical classification of diseases and related health problems. 10th revision. Volume 1. Geneva: World Health Organization; 1992. [cited 2021 Sep 9]. https://apps.who.int/iris/handle/10665/228410. [Google Scholar]

[pmed.1003761.ref013] 13.Committee on Injury Scaling, Association for the Advancement of Automotive Medicine. The Abbreviated Injury Scale, 1990 revision. Chicago: Association for the Advancement of Automotive Medicine; 1990.

[pmed.1003761.ref014] 14.Marshall LF, Marshall SB, Klauber MR, Clark MV, et al. A new classification of head injury based on computerized tomography. J Neurosurg. 1991;75:S14–20. [Google Scholar]

[pmed.1003761.ref015] 15.Brazinova A, Rehorcikova V, Taylor MS, Bukova V, et al. Epidemiology of traumatic brain injury in Europe: a living systematic review. J Neurotrauma. 2021;38(10):1411–40. doi: 10.1089/neu.2015.4126 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref016] 16.Peeters W, Van den Brande R, Polinder S, Brazinova A, et al. Epidemiology of traumatic brain injury in Europe. Acta Neurochir (Wien). 2015;157:1683–96. doi: 10.1007/s00701-015-2512-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref017] 17.Moran CG, Lecky F, Bouamra O, Lawrence T, et al. Changing the system-major trauma patients and their outcomes in the NHS (England) 2008–17. EClinicalMedicine. 2018;2–3:13–21. doi: 10.1016/j.eclinm.2018.07.001 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref018] 18.Lawrence T, Helmy A, Bouamra O, Woodford M, et al. Traumatic brain injury in England and Wales: prospective audit of epidemiology, complications and standardised mortality. BMJ Open. 2016;6:e012197. doi: 10.1136/bmjopen-2016-012197 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref019] 19.Roozenbeek B, Maas AI, Menon DK. Changing patterns in the epidemiology of traumatic brain injury. Nat Rev Neurol. 2013;9:231–6. doi: 10.1038/nrneurol.2013.22 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref020] 20.GBD 2016 Traumatic Brain Injury and Spinal Cord Injury Collaborators. Global, regional, and national burden of traumatic brain injury and spinal cord injury, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(1):56–87. doi: 10.1016/S1474-4422(18)30415-0 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref021] 21.Cnossen MC, Scholten AC, Lingsma HF, Synott A, et al. Adherence to guidelines in adult patients with traumatic brain injury: a living systematic review. J Neurotrauma. 2021;38(8):1072–85. doi: 10.1089/neu.2015.4121 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref022] 22.Maas AIR, Menon DK, Adelson PD, et al. Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research. Lancet Neurol. 2017;16(12):987–1048. doi: 10.1016/S1474-4422(17)30371-X [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref023] 23.Maas AI, Menon DK, Steyerberg EW, Citerio G, et al. Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI): a prospective longitudinal observational study. Neurosurgery. 2015;76:67–80. doi: 10.1227/NEU.0000000000000575 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref024] 24.Steyerberg EW, Wiegers E, Sewalt C, Buki A, et al. The contemporary landscape of traumatic brain injury in Europe: case-mix, care pathways, and outcomes from the CENTER-TBI study. Lancet Neurol. 2019;18(10):923–34. [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref025] 25.American Society of Anaesthesiologists. ASA physical status classification system. Schaumburg (IL): American Society of Anaesthesiologists; 2020. [cited 2021 Sep 9]. https://www.asahq.org/standards-and-guidelines/asa-physical-status-classification-system. [Google Scholar]

[pmed.1003761.ref026] 26.Ringdal K, Coats TJ, Lefering R, Di Bartolomeo S, Steen PA, Røise O, et al. The Utstein template for uniform reporting of data following major trauma: a joint revision by SCANTEM, TARN, DGU-TR and RITG. Scan J Trauma Resusc Emerg Med. 2008;16:7. doi: 10.1186/1757-7241-16-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref027] 27.Baker SP, O’Neill B, Haddon W Jr, Long WB. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma Acute Care Surg. 1974;4(3):187–96. [PubMed] [Google Scholar]

[pmed.1003761.ref028] 28.Maas AI, Stocchetti N, Bullock R. Moderate and severe traumatic brain injury in adults. Lancet Neurol. 2008;7:728–41. doi: 10.1016/S1474-4422(08)70164-9 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref029] 29.Hartholt KA, van Lieshout EM, Polinder S, Panneman MJM, et al. Rapid increase in hospitalizations resulting from fall-related traumatic head injury in older adults in The Netherlands 1986–2008. J Neurotrauma. 2011;8:739–44. doi: 10.1089/neu.2010.1488 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref030] 30.Harvey LA, Close JC. Traumatic brain injury in older adults: characteristics, causes and consequences. Injury. 2012;43:1821–6. doi: 10.1016/j.injury.2012.07.188 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref031] 31.Peters ME, Gardner RC. Traumatic brain injury in older adults: do we need a different approach? Concussion. 2018;3:CNC56. doi: 10.2217/cnc-2018-0001 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref032] 32.Kehoe A, Smith JE, Bouamra O, Edwards A, et al. Older patients with traumatic brain injury present with a higher GCS score than younger patients for a given severity of injury. Emerg Med J. 2016;3(6):381–5. doi: 10.1136/emermed-2015-205180 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref033] 33.Murphy TE, Baker DI, Leo-Summers LS, Tinetti M. Trends in fall-related traumatic brain injury among older persons in Connecticut from 2000–2007. J Gerontol Geriatr Res. 2014;3(4):1000168. doi: 10.4172/2167-7182.1000168 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref034] 34.Baharoglu MI, Cordonnier C, Al-Shahi Salman R, de Gans K, Koopman MM, Brand A, et al. Platelet transfusion versus standard care after acute stroke due to spontaneous cerebral haemorrhage associated with antiplatelet therapy (PATCH): a randomised, open-label, phase 3 trial. Lancet. 2016;387(10038):2605–13. doi: 10.1016/S0140-6736(16)30392-0 [DOI] [PubMed] [Google Scholar]

[pmed.1003761.ref035] 35.Peterson AB, Kegler SR. Deaths from fall-related traumatic brain injury—United States, 2008–2017. MMWR Morb Mortal Wkly Rep. 2020;69:225–30. doi: 10.15585/mmwr.mm6909a2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pmed.1003761.ref036] 36.Cnossen MC, van der Brande R, Lingsma HF, Polinder S, Lecky F, Maas AIR, et al. Prehospital trauma care among 68 European neurotrauma centers: results of the CENTER-TBI Provider Profiling Questionnaires. J Neurotrauma. 2019;36:176–81. [DOI] [PubMed] [Google Scholar]

PERMALINK

The burden of traumatic brain injury from low-energy falls among patients from 18 countries in the CENTER-TBI Registry: A comparative cohort study

Fiona E Lecky

Olubukola Otesile

Carl Marincowitz

Marek Majdan

Daan Nieboer

Hester F Lingsma

Marc Maegele

Giuseppe Citerio

Nino Stocchetti

Ewout W Steyerberg

David K Menon

Andrew I R Maas

Roles

Abstract

Background

Methods and findings

Conclusions

Author summary

Why was this study done?

What did the researchers do and find?

What do these findings mean?

Introduction

Methods

Inclusion and exclusion criteria

Data collection procedures for the CENTER-TBI Registry

Case report form variables

Classification of patients by injury energy mechanism

Statistical analysis

Fig 1. Identification of patients injured by high- and low-energy transfer.

Ethics statement

Results

Overall cohort

Table 1. Demographics, injury mechanism, comorbidity, and presenting physiology of 21,681 TBI patients enrolled in the CENTER-TBI Registry.

Table 2. Imaging findings, injury severity, therapeutic interventions, and care pathways of 21,681 TBI patients enrolled in the CENTER-TBI Registry.

Table 3. Median (interquartile range) times (in minutes) from arrival to imaging and key emergency interventions in study hospital (21,681 patients).

Table 4. Hospital mortality and discharge destination from study hospital (21,681 patients).

Comparisons by energy transfer mechanism

Patient characteristics and care pathway

Fig 2. Prevalence of low-energy transfer as TBI causal mechanism in countries participating in the CENTER-TBI Registry.

Fig 3. High-energy and low-energy TBI patient characteristics compared within 3 care pathways.

Injury characteristics

Outcomes

Discussion

Low-energy TBI cohort

Strengths and limitations

Conclusions

Supporting information

Acknowledgments

Role of Sponsor

Transparency statement

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Caitlin Moyer

Roles

Decision Letter 1

Caitlin Moyer

Roles

Author response to Decision Letter 1

Decision Letter 2

Caitlin Moyer

Roles

Author response to Decision Letter 2

Decision Letter 3

Caitlin Moyer

Roles

Author response to Decision Letter 3

Decision Letter 4

Caitlin Moyer

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES