Skip to main content
NCBI home page
Annals of Medicine and Surgery logoLink to Annals of Medicine and Surgery
. 2026 Oct 6;88(11):7064–7069. doi: 10.1097/MS9.0000000000005675

Evaluating circulating lipids as biomarkers for the severity of traumatic brain injury: a prospective case-control study

Maryam Mehrpooya a, Mohammad S Khonji b, Zahra Sahraei c, Marjan Shariatpanahi d, Mohammad A Zare e, Azadeh Eshraghi f,g,*
PMCID: PMC13754341  PMID: 43017357

Abstract

Background:

The brain is rich in lipids, which play crucial roles in function and injury. Traumatic brain injury (TBI) triggers complex changes across lipid classes. While lipid profiles in stroke are well-studied, evidence regarding lipid alterations in TBI patients is limited.

Methods:

This prospective case-control study included 72 ICU patients with closed TBI aged over 15 years, admitted between September 2021 and March 2022, and 72 ICU patients without TBI as controls. Laboratory tests, including lipid profiles, were performed within 24 hours of admission. Glasgow Coma Scale (GCS) scores on Days 1 and 3 were used to assess consciousness and were compared with lipid levels. A P-value of <0.05 indicated statistical significance.

Results:

The average age was 45.5 ± 17.9 years in cases and 49.5 ± 13.1 years in controls (P > 0.05). Males comprised 83.3 and 75% of cases and controls, respectively (P > 0.05). GCS scores on Days 1 and 3 did not differ significantly between groups. Total cholesterol was significantly lower in TBI patients (163 ± 52.3 mg/dL) than in controls (185.4 ± 33.5 mg/dL, P = 0.003), and high-density lipoprotein (HDL) was also lower (34.6 ± 11.6 vs 49.3 ± 11.5 mg/dL, P ≤ 0.001). Triglycerides and low-density lipoprotein (LDL) levels showed no significant differences. No correlation was found between lipid levels and GCS.

Conclusion:

TBI patients show significant reductions in total cholesterol and HDL levels compared to controls, but lipid profiles do not correlate with consciousness levels.

Keywords: consciousness, Glasgow Coma Scale, intracranial hemorrhage, lipid profile, traumatic brain injury (TBI)

Introduction

Traumatic brain injury (TBI) is a major public health concern, with significant morbidity and mortality affecting millions of individuals worldwide. TBI can result from various external forces, leading to neurological impairment that demands comprehensive management strategies[1]. Although some changes have been observed in the epidemiology of this disease, such as delayed infliction, no significant improvement has been made in disease outcomes, including reductions in mortality and in the losses and problems stemming from trauma[2]. Therefore, determining predictive factors concerning patients’ outcomes and controlling them, if possible, can radically improve the condition of patients with TBI. The Glasgow Coma Scale (GCS) has significant limitations, prompting ongoing research to identify blood biomarkers for characterizing and stratifying patients with TBI to improve outcome predictions and refine clinical trials[3–5]. While substantial work has focused on protein biomarkers like neurofilament light chain (NFL), which indicates brain structural damage[6–8], less is known about the potential of lipid profiles as sensitive and reproducible indicators of injury severity. Given the brain’s high lipid content[9] and the alteration of lipid profiles following TBI, identifying a lipid signature in peripheral circulation could provide valuable insights into injury severity and prognosis shortly after injury[10].

HIGHLIGHTS

  • Serum total cholesterol and high-density lipoprotein (HDL) levels were significantly lower in patients with traumatic brain injury (TBI) than in non-TBI ICU controls.

  • No significant association was found between lipid profile parameters and Glasgow Coma Scale (GCS) scores.

  • The findings support further investigation of circulating lipid profiles in patients with TBI.

There are conflicting reports on the role of dyslipidemia in cerebrovascular disease[11,12]. Therefore, the correlation between serum lipid levels at the time of intracerebral hemorrhage (ICH) and patient outcome is still unclear. Several studies have shown that hypercholesterolemia is associated with a decreased risk of primary ICH and improved ICH outcomes[13,14].

For over 40 years, the GCS has been the standard scale against which the level of consciousness and the severity of patients with TBI are measured worldwide. This scale encompasses clinical examination of the patient’s eye, verbal, and motor responses. This tool is used for therapeutic and preventive interventions, as well as for patient transfer and triage[15,16]. The predictive significance of the GCS, alone or in combination with other scales, has drawn physicians’ attention when evaluating outcomes in patients with TBI[16].

In recent years, there has been special attention to metabolic disorders, such as the effects of lipid disorders on acute/critical injuries in critically and extremely critically ill patients, like those suffering from sepsis or septic shock [17,18], and in these patients, statin treatments reduce inflammatory severity and mortality stemming from sepsis [19,20]. Lipid disorders are another significant issue concerning patients suffering from brain injuries. In some case reports, serum cholesterol level decreases within just a few days after experiencing critical/acute ischemic brain strokes or hemorrhagic brain damage[21,22]. Some researchers suggest that low serum lipid levels, such as cholesterol, can increase the probability of ICH emergence[21–24]. Furthermore, some research advocates the preventive role of high cholesterol levels against ICH [25]. Bahado-Singh et al identified specific lipids, like phosphatidylcholine (PC) 34:4, in a serum metabolomic panel that differentiated TBI from controls within 24 hours post-injury in a mouse model[26]. Hogan et al identified a lipid panel, including free fatty acids (FFA) and sphingomyelin (SM), within the first week post-injury in rats with moderate TBI[27]. While Anyaegbu et al observed distinct lipid signatures in a rat model of repetitive mild TBI, including lysophospholipids and FFAs[28]. Additionally, Daley and colleagues reported a metabolomic panel in young athletes’ plasma 2–3 days after concussion, including several PC species, and further studies identified unique choline-containing lipid signatures in college athletes and injured patients within days after TBI[29].

Due to the high mortality and morbidity rates resulting from TBI, recognition of the factors affecting TBI emergence and development is important. According to research on lipid profiles, especially in the early stages of TBI, very few reports and little evidence have been published [30]. Our objective in this study is to examine serum lipid levels and their relation to reduced consciousness in patients with TBI. This study was conducted at a referral hospital for brain trauma. The findings of this research may provide additional evidence concerning lipid disorders in patients with TBI.

Methods

This prospective, population-based case-control study, consisting of 160 patients, was conducted at a referral hospital for brain trauma between September 2021 and March 2022. All patients admitted to the intensive care unit during the study period were randomly selected for inclusion in the study. Out of 160 patients, 72 with TBI (case group) and 72 without TBI (control group) met the inclusion criteria and were analyzed for further evaluation. Inclusion criteria were patients aged over 15 years who were admitted to the ICU, with a diagnosis of closed TBI (case group) or non-TBI (control group), and who had not used antihyperlipidemic agents for at least 1 month before admission. The exclusion criteria included open TBI; a medical history of neurological disorders; a history of antihyperlipidemic agent use; a history of familial hyperlipidemia; and unwillingness to participate in the study. The researchers visited the ICU ward of the hospital every 2 days and collected samples randomly, following the study guidelines. Demographic characteristic data for all participants were collected.

Blood samples were drawn from all subjects within the first 24 hours after admission. The blood samples were centrifuged at 3000 rpm for 10 minutes. Each serum sample was collected and frozen at −80°C prior to biochemical measurements.

The serum levels of total cholesterol, Low-density lipoprotein (LDL), High-density lipoprotein (HDL), and triglyceride (TG) were analyzed using an enzymatic method in the hospital laboratory. A TBA-FX8 biochemistry analyzer (Toshiba, Japan) was used during this study, and the corresponding results were recorded on the researcher’s checklist.

Determination of patients’ level of consciousness was based on the GCS[31]. The GCS is divided into five groups: 5 = good recovery, 4 = moderate disability, 3 = severe disability, 2 = persistent vegetative state, and 1 = death. The total GCS score is calculated by summing the scores from the three components, resulting in a score ranging from 3 to 15. The patients’ GCS scores were recorded, according to the physician’s assessment, during the first 24 hours of hospitalization and on the third day[31].

Data were analysed using IBM SPSS Statistics version 20.0 [32]. Quantitative data are presented as percentages and as mean ± standard deviation. To assess relatedness, the Pearson correlation was performed, and to compare groups, the t-test was performed. Findings were considered statistically significant at P < 0.05. The work was reported in accordance with the STROCSS criteria[33].

Sample size calculation

The sample size was calculated based on findings from a previous study by Togha et al[34], which evaluated the lipid profile in cerebrovascular accidents. Using a significance level (alpha) of 0.05 and a study power of 80%, their results indicated that the control group had lower LDL levels than ischemic patients (124.2 ± 38 vs. 146.8 ± 43). The final sample size was calculated using the formula N = 2(zα + z (1 − β))2 σ2/δ2, resulting in a required sample of 54 patients per group.

Outcome measurement

The primary objective of this study is to measure lipid profile levels in patients diagnosed with TBI and, consequently, determine their relationship to level of consciousness based on the GCS.

Results

During the study, 160 patients were evaluated for eligibility to participate in the intervention, and 144 patients were included based on the inclusion and exclusion criteria. In the case group, six individuals were excluded from the study due to death within the first 48 hours of treatment, and three of these patients had sustained open TBIs. Additionally, three patients from the control group and two from the case group had a history of stroke. Notably, one patient in each group had a history of antihyperlipidemic agent use. Patients were randomly assigned to the case (n = 72) and control (n = 72) groups. Data are shown in Figure 1. Patient characteristics are summarized in Table 1. The youngest and oldest participants were 16 and 86 years old respectively, and the mean age of participants was 47.5 years. On average, the TBI patients were 4 years younger than the control subjects, but this difference was not statistically significant (P = 0.1). Overall, 79.2% of participants across the case and control groups were men, and the remainder were women. The numbers of male participants in the case and control groups were 60 and 54, respectively (83.3 and 75%). There was no significant difference in sex distribution between the two groups.

Figure 1.

Figure 1.

Open in a new tab

Flow chart depicting patient selection.

Table 1.

Demographic data and lipid profiles of patients with TBI and the non-TBI group.

Variables TBI (n = 72) Control (n = 72) P-value
Age 45.5 ± 17.9 49.5 ± 13.1 0.1
Sex
 Male 60 (83.3) 54 (75) 0.2
 Female 12 (16.7) 18 (25)
Diabetes 7 (9.7) 10 (13.9) 0.4
Cardiovascular disease 4 (5.6) 4 (5.6) 1.0
Hypertension 14 (19.4) 12 (16.7) 0.7
Total Cholesterol (mg/dL) 163.2 ± 52.3 185.4 ± 33.5 0.003
TG (mg/dL) 139 ± 66.8 132.2 ± 59.4 0.5
LDL-C (mg/dL) 100.4 ± 36 101.7 ± 36 0.8
HDL-C (mg/dL) 34.6 ± 11.6 49.3 ± 11.5 0.001
Open in a new tab

Data are presented as mean ± SD, or number (%), where applicable. SD, standard deviation; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol. P-value <0.05 is not significant.

ICH, subdural hematoma (SDH), epidural hematoma (EDH), and subarachnoid hemorrhage (SAH), with a probability of 83.6%, are the most prevalent brain disorders (Table 2).

Table 2.

The distribution of cerebral and bony lesions in individuals with brain injury.

Injuries Type of injuries n (%)
Brain Injury Epidural hematoma (EDH) 11 (15.3)
Subdural hematoma (SDH) 12 (16.7)
Subarachnoid hemorrhage (SAH) 7 (9.7)
Intracerebral hemorrhage (ICH) 23 (31.9)
Combined traits of these disorders 19 (26.4)
Skull fracture 7 (9.9)
Basilar skull fracture 6 (8.5)
Open in a new tab

Data are presented as mean ± SD, or number (%), where applicable. SD: standard deviation.

The mean GCS values on the first and third days of admission were 8.6 and 8.4, respectively. There was no significant difference between the two groups’ GCS scores. Furthermore, the patients’ eye, verbal, and motor response scores did not suggest a significant difference on the aforementioned days (P > 0.05; Table 3).

Table 3.

The distribution of GCS scores in patients with Traumatic brain injury.

Variables Days of hospitalization Mean ± SD P-value
Total score of GCS On the first day 8.4 ± 3 0.3
On the third day 8.6 ± 3.1
Motor response On the first day 4.3 ± 1.4 0.4
On the third day 4.5 ± 1.4
Verbal response On the first day 1.7 ± 1.3 0.7
On the third day 1.7 ± 1.4
Eye response On the first day 2.6 ± 1.1 0.3
On the third day 2.8 ± 1.4
Open in a new tab

Data are presented as mean ± SD, or number (%), where applicable. GCS, Glasgow Coma Scale. SD, standard deviation.

The total cholesterol level in TBI patients was, on average, 22.2 mg/dL lower than that of the control group, and this substantial difference was statistically significant (P = 0.003). The TG level in TBI patients was, on average, 6.8 mg/dL higher than that of the control group, and this difference was not significant (P = 0.5). The LDL level in TBI patients was, on average, 1.3 mg/dL lower than that of the control group; however, this difference was not statistically significant (P = 0.8). In contrast, the HDL level in TBI patients was, on average, 10.9 mg/dL lower than that of the control group, and this difference was highly significant (P = ≤ 0.001).

In TBI patients, the GCS or its sub-scales were not meaningfully related to the aforementioned lipid variables on the first and third days of the traumatic experience (P > 0.05). In the case group, the GCS or its corresponding sub-scales on the first and third days of trauma, and the lipid variables of the case group, were not significantly related to brain disorder (P > 0.05; Table 4).

Table 4.

Association between lipid profile and GCS in patients with brain injuries on the first and third days of the injuries.

Lipid profile GCS on first day (R) P-value GCS on third day (R) P-value
Triglycerides (TG) −0.1 0.2 −0.2 0.2
LDL 0.03 0.8 0.01 0.9
Cholesterol −0.01 0.9 −0.04 0.7
HDL 0.04 0.7 0.1 0.4
Open in a new tab

R, Pearson’s correlation coefficient. P-value < 0.05 is not significant.

Discussion

The primary objective of this study is to measure the lipid profile levels of patients diagnosed with TBI and, consequently, determine their relationship with consciousness level based on the GCS. The results suggest that in these patients, despite significantly lower levels of total cholesterol and HDL compared to healthy subjects, the GCS score is irrelevant to their lipid profile. Very few reports and little evidence have been published on the assessment of lipid profile levels[35]. Due to similar acute neurological injuries, information and evidence on patients suffering from ischemic and hemorrhagic strokes can serve pathologically[36]. In Dhandapani’s research, the levels of total cholesterol, HDL, and LDL in patients diagnosed with SAH did not show a significant difference when compared with healthy subjects [37]. In another study conducted by Bharosay and colleagues on the prognostic effects of lipid profiles on the outcomes of ischemic and hemorrhagic strokes, patients suffering from stroke had significantly higher levels of total cholesterol, LDL, and TG in comparison to their counterparts in the control group; and like us, the HDL level of these patients was significantly lower than that of the control group[38]. Throughout their study comparing patients suffering from ICH and ischemic stroke with healthy subjects, Togha and his team found that the cholesterol level in ICH and ischemic patients was respectively higher and lower than its level in the control group; the HDL level in both stroke groups, ischemic and hemorrhagic, was significantly lower than that of the control group, conversely, the LDL level of both groups was higher than that of the control group, and only the TG level of the hemorrhagic stroke group was significantly lower than that of the control group[34]; their findings regarding total cholesterol and HDL correspond to both the findings of this study and the subgroup of TBI resulting in ICH. To sum up, according to these studies, variable lipid profile results are witnessed in patients suffering from non-TBI. Lipid profile alterations could result from the pathologic type of brain injury stemming from stroke and/or acute non-TBI.

Lipids in their various forms have a critical effect on the nervous system’s structure and function, and they constitute a significant portion of neurons’ structure, specifically the cell membranes; they act as secondary messengers and provide the energy used by brain tissues; metabolic disorders, oxidation, and the pro-inflammatory role of lipids have been recognized in various brain diseases, including acute/critical traumatic and non-traumatic injuries and neurodegenerative diseases [39]. In a lab simulation of TBI in rats and its subsequent histopathologic assessment, it was suggested that from the very first moments of trauma, metabolic lipid alterations emerge; an increase in free carboxylic acid levels and a fall in total cholesterol and phospholipid levels are among these metabolic lipid alterations[19]. Furthermore, cholesterol metabolic disorders and the consequent production of pro-inflammatory agents, combined with metabolic amino acid and carbohydrate disorders, have a significant impact on the abnormalities and disabilities in the aftermath of trauma [40] and on the mortality rate of these patients; in the large IPHS study conducted on 91 000 male and female subjects with no history of stroke, lower LDL levels were correlated with an increased probability of death from ICH[41]. The results of Rodriguez and his team’s research suggested that lower LDL levels were correlated with increased hematoma swelling volume in hemorrhagic stroke, neurological deterioration, and death within three months [24]. In Yang and his team’s multi-logistic analysis, patients experiencing ischemic stroke with lower LDL levels had a higher chance of hemorrhagic stroke [42]. In a study conducted by Thomas et al, it was concluded that certain lipids, particularly phospholipids such as lysophosphatidylcholines (LPCs), ether phosphatidylcholines (O-PCs), and SMs, were strongly and specifically associated with the severity of TBI, emerging as some of the most significant predictors of patient outcomes, and notably, the highest levels of these lipids were observed in patients with mild TBI, with levels decreasing as the severity of the injury increased[43].

Nessel et al suggest that changes in lipid levels within the central compartment may attract a compensatory influx of lipids from the peripheral compartment. This could explain the observed decreases in plasma LPCs and PCs over the first 3 days following injury[44]. Significant activation of phospholipases occurs within the first hour after TBI, as demonstrated in experimental models using mice and rats[45].

This cleavage of phospholipids releases FFAs and diacylglycerol (DAG). The intensity of this process correlates with clinical outcomes in humans, as cerebrospinal fluid (CSF) FFA levels measured within 2 days post-injury are inversely related to the Glasgow Outcome Score at hospital discharge[46]. Our study found no significant association between lipid profile and GCS scores on the first and third days following trauma in patients with brain injury.

The reason for the difference in lipid levels between TBI patients and the control group remains unclear; however, it may warrant further investigation as a potential area of concern. Generally, unlike the cited studies on stroke, in this study there was no significant association between lipid levels and brain injury. To reach a better conclusion concerning this correlation, more studies with larger sample sizes are needed.

GCS has a moderate correlation with TBI severity[47] and can predict the need for intubation in the emergency room, surgical interventions, and mortality in TBI patients[48]. To date, there are no available reports on the correlation between lipid profiles and level of consciousness in TBI patients. In the analysis of this study, the lipid variables did not show any correlation with the GCS scores during the first 3 days following trauma. Similarly, Ramirez[49] and his research team did not find a correlation between LDL levels and indicators of intracranial hemorrhage intensity, such as the NIH Stroke Scale and GCS scores. Ramirez’s findings align with those of the current study.

This research experienced some limitations and difficulties. The lack of prolonged lipid profile assessment and its relation to intra- and extra-hospital mortality rates and the aftermath of hospital discharge were among the limitations; addressing these, as well as the probable role of medical interventions to compensate for lipid profile alterations, could enhance the study’s value. Additionally, there was no multivariable analysis to adjust for potential confounders.

In this brief study, we observed that patients with TBI exhibited lower total cholesterol and HDL levels compared to healthy controls. While these findings suggest a potential correlation, it is important to interpret these results with caution. Further research is needed to validate these observations and explore their clinical significance. Future studies should investigate the effects of lipid profile changes before and after brain injury in relation to the severity of the injury. Additionally, studies should be conducted on larger and more diverse populations, including patients with various underlying medical conditions and demographic differences.

Acknowledgements

Not applicable.

Footnotes

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

Contributor Information

Maryam Mehrpooya, Email: m_mehrpooya2003@yahoo.com.

Mohammad S. Khonji, Email: m.saeid.khonji@gmail.com.

Zahra Sahraei, Email: zahra.sahraee@yahoo.com.

Marjan Shariatpanahi, Email: Shariatpanahi.m@iums.ac.ir.

Mohammad A. Zare, Email: mazare74@yahoo.com.

Azadeh Eshraghi, Email: aepharm@gmail.com.

Ethical approval

The study prospectively received approval from the hospital’s local ethics committee (IR.IUMS.FMD.REC 1396.9413708005) and was conducted in accordance with the Declaration of Helsinki and the ethical standards of the institutional and national research committees. The study was approved by the Ethics Committee of Iran University of Medical Sciences.

Consent

All patients gave informed consent to participate.

Sources of funding

The Iran University of Medical Sciences supported this research by providing the necessary funding and resources to complete it. However, the funding source had no role in the design, execution, analysis, interpretation, or writing of the study.

Author contributions

A.E. and M.M. contributed to the conceptualization, methodology, and writing of the original draft. A.E., M.K., and M.A.Z. were responsible for data collection and analysis. A.E., Z.S., and M.S. contributed to the interpretation of results and critical revision of the manuscript. A.E., M.K., and M.S. provided expertise in statistical analysis and reviewed the manuscript. All authors approved the final version for submission.

Conflicts of interest disclosure

The authors declare no conflicts of interest.

Research registration unique identifying number (UIN)

Researchregistry 11495, https://www.researchregistry.com/browse-theregistry#home.

Guarantor

The authors take full responsibility for the work and the conduct of the study.

Provenance and peer review

This manuscript was not invited. Not commissioned; externally peer-reviewed.

Data availability statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Governing declaration and use of AI

AI was not used in the research or manuscript development.

References

  • [1].Maas AIR, Menon DK, Manley GT, et al. Traumatic brain injury: progress and challenges in prevention, clinical care, and research. Lancet Neurol 2022;21:1004–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [2].Roozenbeek B, Maas A, Menon DK. Changing patterns in the epidemiology of traumatic brain injury. Nat Rev Neurol 2013;9:231–36. [DOI] [PubMed] [Google Scholar]
  • [3].Gan ZS, Stein SC, Swanson R, et al. Blood biomarkers for traumatic brain injury: a quantitative assessment of diagnostic and prognostic accuracy. Front Neurol 2019;10:446. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [4].Martinez BI, Stabenfeldt SE. Current trends in biomarker discovery and analysis tools for traumatic brain injury. J Biol Eng 2019;13:16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5].Slavoaca D, Muresanu D, Birle C, et al. Biomarkers in traumatic brain injury: new concepts. Neurol Sci 2020;41:2033–44. [DOI] [PubMed] [Google Scholar]
  • [6].Gaetani L, Blennow K, Calabresi P, et al. Neurofilament light chain as a biomarker in neurological disorders. J Neurol Neurosurg Psychiatry 2019;90:870–81. [DOI] [PubMed] [Google Scholar]
  • [7].Shahim P, Politis A, van der Merwe A, et al. Neurofilament light as a biomarker in traumatic brain injury. Neurology 2020;95:e610–e622. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [8].Thelin E, Al Nimer F, Frostell A, et al. A serum protein biomarker panel improves outcome prediction in human traumatic brain injury. J Neurotrauma 2019;36:2850–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [9].Svennerholm L, Boström K, Jungbjer B. Changes in weight and composition of major membrane components of human brain during the span of adult human life of Swedes. Acta Neuropathol 1997;94:345–52. [DOI] [PubMed] [Google Scholar]
  • [10].Nessel I, Michael-Titus AT. Lipid profiling of brain tissue and blood after traumatic brain injury: a review of human and experimental studies. Semin Cell Dev Biol 2021;112:145–56. [DOI] [PubMed] [Google Scholar]
  • [11].Siddeswari R, Manohar S, Sudarsi B, et al. Pattern of dyslipidemia in ischemic stroke. J Med Allied Sci 2015;5:26–29. [Google Scholar]
  • [12].Cai B, Peng L, Wang Z, et al. Association between serum lipid and hematoma expansion after spontaneous intracerebral hemorrhage in Chinese patients. J Stroke Cerebrovasc Dis 2020;29:104793. [DOI] [PubMed] [Google Scholar]
  • [13].Woo D, Kissela BM, Khoury JC, et al. Hypercholesterolemia, HMG-CoA reductase inhibitors, and risk of intracerebral hemorrhage, a case–control study. Stroke 2004;35:1360–64. [DOI] [PubMed] [Google Scholar]
  • [14].Chaoran M, Gurol E, Huang Z, et al. Low-density lipoprotein cholesterol and risk of intracerebral hemorrhage a prospective study. Neurology 2019;93:445–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [15].Heim C, Schoettker P, Spahn DR. Glasgow Coma Scale in traumatic brain injury. Anaesthesist 2004;53:1245–55. [DOI] [PubMed] [Google Scholar]
  • [16].Teasdale G, Maas A, Lecky F, et al. The Glasgow Coma Scale at 40 years: standing the test of time. Lancet Neurol 2014;13:844–54. [DOI] [PubMed] [Google Scholar]
  • [17].Wu A, Hinds CJ, Thiemermann C. High-density lipoproteins in sepsis and septic shock: metabolism, actions, and therapeutic applications. Shock 2004;21:210–21. [DOI] [PubMed] [Google Scholar]
  • [18].Jia L, Takahashi M, Morimoto H, et al. Changes in cardiac lipid metabolism during sepsis: the essential role of very low-density lipoprotein receptors. Cardiovasc Res 2006;69:545–55. [DOI] [PubMed] [Google Scholar]
  • [19].Kruger P, Fitzsimmons K, Cook D, et al. Statin therapy is associated with fewer deaths in patients with bacteraemia. Intensive Care Med 2006;32:75–79. [DOI] [PubMed] [Google Scholar]
  • [20].Novack V, Eisinger M, Frenkel A, et al. The effects of statin therapy on inflammatory cytokines in patients with bacterial infections: a randomized double-blind placebo controlled clinical trial. Intensive Care Med 2009;35:1255–60. [DOI] [PubMed] [Google Scholar]
  • [21].Segal AZ, Chiu RI, Eggleston-Sexton PM, et al. Low cholesterol as a risk factor for primary intracerebral hemorrhage: a case-control study. Neuroepidemiology 1999;18:185–93. [DOI] [PubMed] [Google Scholar]
  • [22].Mendez I, Hachinski V, Wolfe B. Serum lipids after stroke. Neurology 1987;37:507–11. [DOI] [PubMed] [Google Scholar]
  • [23].Ilie G, Boak A, Emerson M, et al. Prevalence and correlates of traumatic brain injuries among adolescents. JAMA 2013;309:2550–52. [DOI] [PubMed] [Google Scholar]
  • [24].Rodriguez-Luna D, Rubiera M, Ribo M, et al. Serum low-density lipoprotein cholesterol level predicts hematoma growth and clinical outcome after acute intracerebral hemorrhage. Stroke 2011;42:2447–52. [DOI] [PubMed] [Google Scholar]
  • [25].Thrift AG, McNeil JJ, Forbes A, et al. Risk factors for cerebral hemorrhage in the era of well-controlled hypertension. Stroke 1996;27:2020–25. [DOI] [PubMed] [Google Scholar]
  • [26].Bahado-Singh RO, Graham SF, Han B, et al. Serum metabolomic markers for traumatic brain injury: a mouse model. Metabolomics 2016;12:100. [Google Scholar]
  • [27].Hogan SR, Phan JH, Alvarado-Velez M, et al. Discovery of lipidome alterations following traumatic brain injury via high-resolution metabolomics. J Proteome Res 2018;17:2131–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [28].Anyaegbu CC, Szemray H, Hellewell SC, et al. Plasma lipid profiles change with increasing numbers of mild traumatic brain injuries in rats. Metabolites 2022;12:322. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [29].Daley M, Dekaban G, Bartha R, et al. Metabolomics profiling of concussion in adolescent male hockey players: a novel diagnostic method. Metabolomics 2016;12:1–9. [Google Scholar]
  • [30].Roux A, Muller L, Jackson SN, et al. Mass spectrometry imaging of rat brain lipid profile changes over time following traumatic brain injury. J Neurosci Meth 2016;272:19–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [31].Saatman KE, Duhaime A-C, Bullock R, et al. Classification of traumatic brain injury for targeted therapies. J Neurotrauma 2008;25:719–38. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [32].Field A. Discovering Statistics Using IBM SPSS Statistics. Sage; 2013. [Google Scholar]
  • [33].Agha RA, Mathew G, Rashid R, et al. Revised Strengthening the reporting of cohort, cross-sectional and case-control studies in surgery (STROCSS) Guideline: an update for the age of Artificial Intelligence. Prem J Sci 2025;10:100081. [Google Scholar]
  • [34].Togha M, Gheini MR, Ahmadi B, et al. Lipid profile in cerebrovascular accidents. Iran J Neurol 2011;10:1–4. [PMC free article] [PubMed] [Google Scholar]
  • [35].Demediuk P, Faden AI, Romhanyi R, et al. Traumatic brain injury in the rat: effects on lipid metabolism, tissue magnesium, and water content. J Neurotrauma 1988;5:105–19. [DOI] [PubMed] [Google Scholar]
  • [36].Adibhatla RM, Hatcher JF. Altered lipid metabolism in brain injury and disorders. Subcell Biochem 2008;49:241–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [37].Dhandapani S, Aggarwal A, Srinivasan A, et al. Serum lipid profile spectrum and delayed cerebral ischemia following subarachnoid hemorrhage: is there a relation? Surg Neurol Int 2015;6:543–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [38].Bharosay A, Bharosay VV, Bandyopadhyay D, et al. Effect of lipid profile upon prognosis in ischemic and haemorrhagic cerebrovascular stroke. Indian J Clin Biochem 2014;29:372–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [39].Adibhatla RM, Hatcher JF. Role of lipids in brain injury and diseases. Future Lipidol 2007;2:403–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [40].Yi L, Shi S, Wang Y, et al. Serum metabolic profiling reveals altered metabolic pathways in patients with post-traumatic cognitive impairments. Sci Rep 2016;6:21320. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [41].Noda H, Iso H, Irie F, et al. Low-density lipoprotein cholesterol concentrations and death due to intraparenchymal hemorrhage: the Ibaraki prefectural health study. Circulation 2009;119:2136–45. [DOI] [PubMed] [Google Scholar]
  • [42].Yang N, Lin M, Wang BG, et al. Low level of low-density lipoprotein cholesterol is related with increased hemorrhagic transformation after acute ischemic cerebral infarction. Eur Rev Med Pharmacol Sci 2016;20:673–78. [PubMed] [Google Scholar]
  • [43].Thomas A, Smith B, Johnson C. Serum metabolome associated with the severity of acute traumatic brain injury. Nat Commun 2022;13:2545. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [44].Nessel I, Whiley L, Dyall SC, et al. A plasma lipid signature in acute human traumatic brain injury: link with neuronal injury and inflammation markers. J Cereb Blood Flow Metab 2024;26:0271678X241276951. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [45].Homayoun P, Parkins NE, Soblosky J, et al. Cortical impact injury in rats promotes a rapid and sustained increase in polyunsaturated free fatty acids and diacylglycerols. Neurochem Res 2000;25:269–76. [DOI] [PubMed] [Google Scholar]
  • [46].Pilitsis JG, Coplin WM, O’Regan MH, et al. Free fatty acids in cerebrospinal fluids from patients with traumatic brain injury. Neurosci Lett 2003;349:136–38. [DOI] [PubMed] [Google Scholar]
  • [47].Grote S, Böcker W, Mutschler W, et al. Diagnostic value of the Glasgow Coma Scale for traumatic brain injury in 18,002 patients with severe multiple injuries. J Neurotrauma 2011;28:527–34. [DOI] [PubMed] [Google Scholar]
  • [48].Gill M, Windemuth R, Steele R, et al. A comparison of the Glasgow Coma Scale score to simplified alternative scores for the prediction of traumatic brain injury outcomes. Ann Emerg Med 2005;45:37–42. [DOI] [PubMed] [Google Scholar]
  • [49].Ramírez-Moreno JM, Casado-Naranjo I, Portilla JC, et al. Serum cholesterol LDL and 90-day mortality in patients with intracerebral hemorrhage. Stroke 2009;40:1917–20. [DOI] [PubMed] [Google Scholar]

Associated Data

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

Data Availability Statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Articles from Annals of Medicine and Surgery are provided here courtesy of Wolters Kluwer Health

RESOURCES