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The Journal of International Medical Research logoLink to The Journal of International Medical Research
. 2022 Sep 30;50(9):03000605221126880. doi: 10.1177/03000605221126880

Target temperature management versus normothermia without temperature feedback systems for out-of-hospital cardiac arrest survivors

Hui Jai Lee 1,2, Jonghwan Shin 1,2,, Kyoung Min You 1,2, Woon Yong Kwon 2,3, Kyung Su Kim 2,3, You Hwan Jo 2,4, Seung Min Park 2,4
PMCID: PMC9528025  PMID: 36177833

Abstract

Objective

The clinical benefit of automatic temperature control devices remains unclear. We investigated the outcomes of out-of-hospital cardiac arrest (OHCA) survivors who had undergone either target temperature management (TTM) with a temperature feedback system (TFS) or maintenance of normothermia without a TFS during post-resuscitation care.

Methods

This study was a retrospective analysis of a multicenter prospective cohort of OHCA survivors who had received postcardiac arrest care from August 2014 to December 2018. The overlap propensity score weighting method was applied for adjustment between groups.

Results

A total of 405 OHCA survivors were included. TTM with a TFS and normothermia without a TFS were applied to 318 and 87 patients, respectively. Fever events were more common in patients with normothermia without a TFS. After propensity score matching, no statistically significant differences were observed in the 1-month good neurologic outcome (odds ratio 0.99, 95% confidence interval [CI] 0.56–1.25) or survival rate (odds ratio 1.25, 95% CI 0.88–1.78).

Conclusion

No significant differences in the 1-month neurologic outcome were observed between patients receiving TTM with a TFS and those undergoing normothermia without a TFS.

Keywords: Out-of-hospital heart arrest, hypothermia, induced, treatment outcome, critical care, target temperature management, temperature feedback system

Introduction

Target temperature management (TTM) is the key component of modern postcardiac arrest care for comatose patients after successful resuscitation from cardiac arrest. After two large randomized controlled trials showed the benefits of hypothermia for out-of-hospital cardiac arrest (OHCA) survivors with a shockable rhythm, the Millennium guidelines suggested that temperature regulation or therapeutic hypothermia could improve neurological outcomes in patients with ischemic brain injury after cardiac arrest.13 During the nearly 20 intervening years, several preclinical and clinical studies have established the beneficial effects of therapeutic hypothermia. Accordingly, TTM has been recommended for most comatose patients after cardiac arrest.47 However, after a multicenter prospective trial using temperature-feedback devices showed no difference in neurologic outcome in patients randomized to target temperatures of 33°C versus 36°C, TTM procedures were changed and overall adherence to TTM wavered.5,810 Moreover, a recent TTM-2 trial comparing the use of TTM (33°C) with the maintenance of normothermia showed no difference in clinical outcomes. 11

Automated temperature control devices with a temperature feedback system (TFS) have several advantages including rapid induction of hypothermia, maintenance of a consistent temperature, and avoidance of fever or hypothermia overshooting. Thus, these devices are regarded as an important component of TTM.5,7,8 However, the clinical benefit of TFSs has not yet been fully evaluated and the evidence for their use is insufficient. 12

This study was conducted to assess whether TFSs provide any beneficial effect on neurological outcomes in OHCA patients.

Methods

Study design and setting

We conducted a retrospective analysis of prospectively registered data on OHCA patients who had undergone post-resuscitation care after the sustained return of spontaneous circulation (ROSC) in three hospitals between July 2014 and December 2018. All hospitals were tertiary university hospitals with an emergency department volume of approximately 60,000 (site A, south of Seoul), 90,000 (site B, Gyeonggi Province), and 70,000 (site C, north of Seoul) patients per year. All participating hospitals were equipped with facilities, equipment, and trained medical personnel to provide advanced cardiovascular life support and post-resuscitation care to OHCA patients. Prospective data on prehospital management, advanced cardiovascular life support, and postcardiac arrest care were previously collected in accordance with the standardized Utstein-style guidelines13,14 (ClinicalTrials.gov number, NCT03695718). All patient details were de-identified.

Participants

Comatose (Glasgow Coma Scale less than 8) OHCA survivors over the age of 18 years were included in the study. The exclusion criteria were as follows: 1) terminal illness or withdrawal of additive treatment after ROSC, 2) awake after ROSC, 3) active internal or external bleeding, 4) pregnancy, 5) hemodynamic instability (i.e., persistent shock despite adequate fluid resuscitation and vasopressor support), and 6) poor baseline functional status or cerebral performance category (CPC) 3 or less before cardiac arrest.

Treatment of postcardiac arrest patients was performed in accordance with each hospital’s treatment protocol and was based on international guidelines. 15 Core temperature, mainly of the esophagus or bladder, was monitored for all patients. TTM was defined as the application of an automatic TFS for the control of temperature during post-resuscitation care. A surface cooling device—the Artic Sun® Temperature Management System (Bard, Murray Hill, NJ, USA) or Blanketrol® (Cincinnati Sub Zero Products, LLC, Cincinnati, OH, USA)—was used for TTM with a TFS. The target temperature was maintained for 24 hours. Rewarming was actively performed at a rate of approximately 0.25°C to 0.5°C per hour. After rewarming, normothermia was maintained with surface cooling devices during the initial 72 hours. Occurrences of core temperatures over 38°C were regarded as fever events.

A strategy of normothermia maintenance with fever control was used if the patient’s caregivers did not consent—for cost or other reasons—to TTM with an automatic TFS. Acetaminophen or a cooling bag was applied at the treating clinician’s discretion.

The Institutional Review Board of Seoul Metropolitan Government - Seoul National University Boramae Medical Center, Seoul, Korea approved the study and all hospitals waived informed consent because only de-identified registry data were analyzed (24 September 2021, IRB No. 10-2021-106). This study was performed in accordance with the principles of the Declaration of Helsinki, and reporting conforms to the Strengthening the Reporting of Observational Studies in Epidemiology statement guidelines. 16

Statistical analysis

The primary outcome of a good CPC (i.e., CPC 1 or 2) at 1 month was compared between the groups. Subgroups were further identified based on initial rhythm, cause of arrest, or the presence of a witness during the arrest.

The Shapiro–Wilk test was used to evaluate the normality of the continuous variables. The continuous variables were expressed as the mean ± standard deviation or median and interquartile ranges, as appropriate. The Student’s t-test or Mann–Whitney U test was used, as appropriate. Categorical variables were presented as a frequency with the corresponding percentage and were compared using the chi-square test or Fisher’s exact test, as appropriate.

Because the application of TTM can be affected by the patient’s clinical condition and because the clinical parameters of the two groups were expected to be considerably different, the overlap propensity score weighting method was applied.17,18 A propensity score for receiving TTM was calculated from a multivariable logistic regression analysis incorporating the following variables: age, sex, baseline CPC, diabetes, hypertension, witnessed arrest, bystander cardiopulmonary resuscitation, initial shockable rhythm, prehospital ROSC, no flow time, low flow time, presence of ST-elevation myocardial infarction, emergency percutaneous coronary intervention, Sequential Organ Failure Assessment score, Acute Physiology And Chronic Health Evaluation II score, and the cause of cardiac arrest. Multiple imputations by chained equations were applied for missing values. Ten copies of the dataset were created and pooled results were calculated using Rubin’s rule. The results of the logistic regression analysis were presented as odds ratios (ORs) and 95% confidence intervals (CIs).

Modified Poisson regression was used to estimate adjusted relative risks (with 95% CIs) of fever events for a good outcome. The following variables were used for covariate adjustment: age, sex, baseline CPC, diabetes, hypertension, witnessed arrest, bystander cardiopulmonary resuscitation, initial shockable rhythm, prehospital ROSC, no flow time, low flow time, presence of ST-elevation myocardial infarction, emergency percutaneous coronary intervention, Sequential Organ Failure Assessment score, Acute Physiology And Chronic Health Evaluation II score, and the causes of cardiac arrest.

R version 3.6.2 (R Foundation for Statistical Computing, Vienna, Austria) was used for the statistical analysis. A P-value less than 0.05 was considered statistically significant.

Results

Enrolled patients

During the study period, 1045 patients received postcardiac arrest care and 405 were enrolled in the study (Figure 1). Among enrolled patients, 318 and 87 patients received TTM and underwent maintenance of normothermia strategy without a TFS, respectively. Several characteristics—such as no flow time and Sequential Organ Failure Assessment score—and some laboratory results differed. However, differences in functional outcomes were not observed between the groups (Table 1).

Figure 1.

Figure 1.

Enrollment of study patients.

OHCA: out-of-hospital cardiac arrest, DNAR: do not attempt resuscitation, CPC: cerebral performance category, ICU: intensive care unit, TTM: target temperature management, TFS: temperature feedback system.

Table 1.

Base characteristics of enrolled patients.

Normothermia TTM
(N = 87) (N = 318) P-value
Age, years 59.0 [49.5; 72.0] 58.5 [47.0; 74.0] 0.755
 Male 57 (65.5%) 224 (70.4%)
Baseline CPC >0.999
 1 67 (77.0%) 245 (77.0%)
 2 20 (23.0%) 73 (23.0%)
Initial body temperature, °C 35.8 [35.0; 36.0] 35.5 [34.9; 36.2] 0.400
Diabetes mellitus 21 (24.1%) 87 (27.6%) 0.609
Hypertension 27 (31.0%) 137 (43.5%) 0.049
Dyslipidemia 7 (8.0%) 23 (7.3%) 0.997
Witness arrest 68 (78.2%) 214 (67.3%) 0.069
Bystander CPR 46 (53.5%) 154 (48.6%) 0.493
Shockable rhythm 30 (34.5%) 96 (30.2%) 0.525
Prehospital defibrillation 32 (37.2%) 109 (35.0%) 0.808
Prehospital ROSC 27 (31.0%) 83 (26.3%) 0.454
No flow time 0.0 [0.0; 5.0] 3.0 [0.0; 8.0] 0.001
Low flow time 23.0 [12.0; 31.0] 24.0 [14.0; 32.0] 0.722
Emergency CAG 37 (42.5%) 113 (35.5%) 0.284
Emergency PCI 19 (21.8%) 50 (15.7%) 0.237
SOFA score 11.0 [8.0; 13.0] 9.0 [7.0; 12.0] 0.038
APACH II score 27.0 [20.0; 34.5] 28.0 [23.0; 32.0] 0.649
GCS 3.0 [3.0; 6.0] 3.0 [3.0; 4.0] 0.051
Laboratory results
 WBC 11.6 [8.4; 15.5] 13.7 [10.2; 18.9] 0.006
 Hemoglobin 12.3 [10.3; 14.3] 13.2 [11.1; 14.9] 0.045
 Platelet 175.0 [124.0; 237.0] 199.0 [152.0; 249.0] 0.067
 Na+ 139.0 [136.2; 142.4] 139.4 [136.0; 143.0] 0.862
 K+ 4.5 [3.7; 5.4] 4.2 [3.6; 5.2] 0.235
 Cl 104.0 [100.0; 109.0] 104.0 [100.3;108.0] 0.757
 TCO2 15.0 [12.0; 18.0] 15.6 [12.0; 19.0] 0.266
 Blood urea nitrogen 19.0 [14.0; 27.0] 19.0 [14.5; 27.5] 0.653
 Creatinine 1.4 [1.1; 2.1] 1.3 [1.0; 1.7] 0.323
 Total bilirubin 0.7 [0.5; 1.0] 0.7 [0.4; 0.9] 0.166
 Glucose 228.0 [163.0; 313.0] 251.0 [187.5; 329.5] 0.162
 AST 146.0 [69.0; 424.5] 167.5 [78.5; 411.0] 0.725
 ALT 84.0 [40.0;184.5] 106.0 [49.0; 256.5] 0.136
 PT/INR 1.3 [1.2; 2.0] 1.2 [1.1; 1.5] 0.002
 aPTT 47.3 [35.1;75.8] 38.0 [29.8; 54.8] 0.001
 C-reactive protein 0.3 [0.3; 5.2] 0.3 [0.1; 1.6] 0.004
 Troponin I 0.2 [0.0; 0.6] 0.1 [0.0; 1.2] 0.826
 NSE 37.6 [29.2; 57.1] 42.4 [31.0; 63.0] 0.445
 Lactate 11.9 [8.7; 15.8] 12.4 [9.5; 15.0] 0.936
Cardiac cause 44 (50.6%) 148 (46.5%) 0.071
Discharge CPC 4.0 [2.0; 5.0] 4.0 [3.0; 5.0] 0.549
1-month survival 39 (44.8%) 164 (51.6%) 0.320
1-month CPC 0.082
 1 20 (23.0%) 49 (15.4%)
 2 7 (8.0%) 27 (8.5%)
 3 3 (3.4%) 24 (7.5%)
 4 9 (10.3%) 64 (20.1%)
 5 48 (55.2%) 154 (48.4%)
Fever event
 Within 24 hours 18 (20.7%) 15 (4.7%) <0.001
 Within 72 hours 24 (27.6%) 58 (18.2%) 0.076

Data are n (%) or median [interquartile range].

TTM: target temperature management, CPC: cerebral performance category, CPR: cardiopulmonary resuscitation, ROSC: return of spontaneous circulation, CAG: coronary angiography, PCI: percutaneous coronary intervention, SOFA: Sequential Organ Failure Assessment Score, GCS: Glasgow Coma Scale, WBC: white blood cell count, AST: aspartate transaminase, ALT: alanine transaminase, PT/INR: prothrombin time/international normalized ratio, aPTT: activated partial thromboplastin time, NSE: neuron-specific enolase, APACHE: Acute Physiology And Chronic Health Evaluation.

Temperature changes

Core temperatures were higher in the normothermia without TFS group (Figure 2), and fever (i.e., body temperature ≥38°C) events were more frequent than in the TTM group during the initial 24 hours (18, 20.7% vs. 15, 4.7%, P < 0.001; Table 1, Supplemental Table).

Figure 2.

Figure 2.

Temperature of enrolled patients during initial 72 hours. Lines indicate the mean temperature of each group and shaded areas indicate the 2 SDs.

TTM: target temperature management, SD: standard deviation.

The number of patients experiencing a fever event within 72 hours did not differ statistically between the groups (24, 27.6% vs. 58, 18.2%). In the TTM group, 8 patients (15.4%) with a target temperature of 36°C and 50 patients (18.8%) with a target temperature less than 36°C experienced fever events (Table 1). Fever events during the initial 24 hours were not related to the outcome in either group. Fever events within 72 hours were more frequent in the good-outcome patients of the TTM group (Tables 2 and 3); however, this difference disappeared after adjustment (Table 3).

Table 2.

One-month neurological outcomes and fever events per group.

Normothermia without TFS
TTM with TFS
Good Bad P-value Good Bad P-value
Fever within 24 hours 6 (22.2%) 12 (20.0%) >0.999 5 (6.6%) 10 (4.1%) 0.570
Fever within 72 hours 9 (33.3%) 15 (25.0%) 0.586 28 (36.8%) 30 (12.4%) <0.001

Data are n (%).

TFS: temperature feedback system, TTM: target temperature management.

Table 3.

Relative risks of fever events for good outcome.

Fever within 24 hours
Fever within 72 hours
Unadjusted RR (95% CI) Adjusted RR (95% CI) Unadjusted RR (95% CI) Adjusted RR (95% CI)
Normothermia without TFS 1.10 (0.40–2.55) 1.81 (0.58–5.36) 1.31 (0.56–2.85) 1.89 (0.69 –5.30)
TTM with TFS 1.42 (0.50– 3.18) 0.89 (0.26–2.35) 2.61 (1.62–4.14) 1.43 (0.84–2.40)
Overall 1.35 (0.68– 2.41) 1.16 (0.55–2.18) 2.21 (1.46–3.28) 1.42 (0.91–2.18)

RR: relative risk, TFS: temperature feedback system, TTM: target temperature management, CI: confidence interval.

Propensity score matching

After propensity score weighting, a good CPC outcome at 1 month was not different between the groups (OR 0.99, 95% CI 0.56–1.25). Furthermore, no difference in survival was observed at 1 month (OR 1.25, 95% CI 0.88–1.78; Supplemental Figure).

Propensity-score-adjusted logistic regression analyses were conducted for several subgroups. No differences in outcome were observed between TTM and normothermia without a TFS for the various subgroups (Figure 3).

Figure 3.

Figure 3.

Subgroup analysis for 1-month good neurologic outcomes (odds ratios and 95% confidence intervals). The x-axis represents the log (10) scale of the odds ratio of good neurologic outcomes between the groups.

Furthermore, intergroup differences in 1-month functional outcomes were not observed in a sensitivity analysis after propensity weighting and removal of missing cases (OR 0.94, 95% CI 0.83–1.02).

Discussion

In our study, the neurological outcome of normothermia with a TFS did not differ from that of conventional TTM. Hyperthermia during postcardiac arrest care, especially within the first 72 hours, is believed to worsen brain injury. The use of temperature-management devices with a TFS has been encouraged for rapid induction, minimization of overcooling risk, and consistent temperature control.5,15 However, the beneficial effects of positive-feedback devices were never fully evaluated. A meta-analysis of randomized and non-randomized clinical trials showed a lower probability of unfavorable neurological outcomes when using a TFS. A difference in outcomes between with-TFS and without-TFS cohorts was observed in only one large-scale observational study and not in an analysis of exclusively randomized clinical trials. 12 Multivariable analyses revealed that only the use of invasive cooling methods—not external cooling devices—is related to good outcomes when compared with conventional cooling methods without a TFS.12,19 Given many clinical studies have not proved that invasive cooling devices are more effective than external cooling devices in improving functional outcomes or survival, the benefits of invasive cooling with a TFS versus conventional cooling without a TFS remain unclear.2022

Moreover, a recently published TTM-2 trial showed no differences in outcome between normothermia and hypothermia groups—a finding consistent with our results. However, whereas all patients in the normothermia group were treated with a cooling device in our study, only 46% of patients were treated with surface and intravascular cooling devices in the TTM-2 trial, which did not evaluate the TFS itself.

The results of a recent comprehensive meta-analysis further indicated no differences in neurological or survival outcomes between targeted hypothermia (32–34°C) and normothermia (≥36°C with fever control) for comatose OHCA patients. 23

The European Resuscitation Council–European Society of Intensive Care Medicine (ERC-ESCIM) guidelines still recommend TTM with a TFS. Active fever control with simple surface cooling using wet towels and ice can be considered in low-resource settings. 24 However, the evidence for active fever control without a TFS remains insufficient. Moreover, the results of the present study support the ERC-ESICM guidelines.

Consistent with the TTM-2 trial results, 20.7% of patients with normothermia without a TFS developed fever events during the initial 24 hours of our study. Fever is believed to worsen brain damage in various types of brain injury. Fever during post-resuscitation care is related to poor prognosis.25,26 Clinical practice has changed following the TTM trial; patients’ target and lowest temperatures have risen and fever events have increased. Nonetheless, changes in outcome have not been evident.5,9,2730 Similarly, in our study, although fever events during the initial 24 hours were more frequent in the normothermia without TFS group, no differences in outcomes were observed (Table 4).

Table 4.

Differences in characteristics between patients with good and bad outcomes.

Good outcome Bad outcome
(N = 103) (N = 302) P-value
Age, years 53.0 [44.5; 60.0] 64.0 [50.0; 75.0] <0.001
 Male 81 (78.6%) 200 (66.2%) 0.025
Baseline CPC <0.001
 1 93 (90.3%) 219 (72.5%)
 2 10 (9.7%) 83 (27.5%)
Initial body temperature, °C 36.0 [35.1; 36.6] 35.3 [34.7; 36.0] <0.001
Diabetes mellitus 14 (13.7%) 94 (31.3%) 0.001
Hypertension 39 (38.2%) 125 (41.7%) 0.622
Dyslipidemia 10 ( 9.8%) 20 ( 6.7%) 0.41
Witness arrest 89 (86.4%) 193 (63.9%) <0.001
Bystander CPR 67 (65.0%) 133 (44.3%) <0.001
Shockable rhythm 61 (59.2%) 65 (21.5%) <0.001
Prehospital defibrillation 71 (68.9%) 70 (23.8%) <0.001
Prehospital ROSC 68 (66.7%) 42 (14.0%) <0.001
No flow time 1.0 [0.0; 4.0] 3.0 [0.0; 8.0] <0.001
Low flow time 12.5 [9.0; 22.5] 26.0 [18.0; 35.0] <0.001
Emergency CAG 77 (74.8%) 73 (24.2%) <0.001
Emergency PCI 37 (35.9%) 32 (10.6%) <0.001
SOFA score 21.0 [16.0; 27.0] 29.0 [24.0; 34.0] <0.001
APACH II score 7.0 [5.0; 9.0] 10.0 [8.0; 13.0] <0.001
GCS 4.0 [3.0; 7.0] 3.0 [3.0; 3.0] <0.001
Laboratory results
 WBC 14.0 [10.2; 19.0] 13.2 [9.5; 18.4] 0.286
 Hemoglobin 14.4 [12.7; 15.4] 12.5 [10.4; 14.0] <0.001
 Platelet 227.0 [184.5; 271.0] 184.5 [138.0; 238.0] <0.001
 Na+ 139.0 [136.2; 141.3] 139.5 [136.0; 143.0] 0.097
 K+ 3.7 [3.3; 4.3] 4.5 [3.7; 5.4] <0.001
 Cl 104.0 [102.0; 107.6] 104.0 [100.0; 108.2] 0.738
 TCO2 16.0 [14.0; 19.0] 15.0 [11.9; 18.0] 0.001
 Blood urea nitrogen 17.0 [14.0; 21.0] 20.0 [15.0; 31.0] 0.002
 Creatinine 1.1 [0.9; 1.4] 1.4 [1.1; 1.9] <0.001
 Total bilirubin 0.6 [0.5; 0.9] 0.7 [0.4; 1.0] 0.904
 Glucose 228.0 [166.0; 276.0] 267.0 [187.5; 342.5] 0.003
 AST 133.0 [85.0; 248.0] 184.0 [72.0; 499.0] 0.03
 ALT 105.0 [54.0;192.0] 103.0 [46.0; 265.0] 0.687
 PT/INR 1.1 [1.0; 1.2] 1.3 [1.1; 1.7] <0.001
 aPTT 31.7 [27.4; 38.5] 44.5 [32.5; 66.8] <0.001
 C-reactive protein 0.3 [0.1; 0.3] 0.3 [0.2; 3.7] <0.001
 Troponin I 0.1 [0.0; 0.9] 0.2 [0.0; 1.1] 0.196
 NSE 38.2 [29.9; 50.9] 44.8 [30.4; 70.5] 0.024
 Lactate 9.3 [6.9; 14.6] 12.6 [9.7; 15.0] 0.01
Cardiac cause 88 (85.4%) 104 (34.4%) <0.001
Discharge CPC 2.0 [1.0; 2.0] 5.0 [4.0; 5.0] <0.001
Survival (28D) 103 (100.0%) 100 (33.1%) <0.001
CPC (28D) <0.001
 1 69 (67.0%) 0 (0.0%)
 2 34 (33.0%) 0 (0.0%)
 3 0 (0.0%) 27 (8.9%)
 4 0 (0.0%) 73 (24.2%)
 5 0 (0.0%) 202 (66.9%)
Fever event
 Within 24 hours 11 (10.7%) 22 (7.3%) 0.379
 Within 72 hours 37 (35.9%) 45 (14.9%) <0.001

Data are n (%) or median [interquartile range].

CPC: cerebral performance category, CPR: cardiopulmonary resuscitation, ROSC: return of spontaneous circulation, CAG: coronary angiography, PCI: percutaneous coronary intervention, SOFA: Sequential Organ Failure Assessment, GCS: Glasgow Coma Scale, WBC: white blood cell count, AST: aspartate transaminase, ALT: alanine transaminase, PT: prothrombin time, aPTT: activated partial thromboplastin time, NSE: neuron-specific enolase, APACHE: Acute Physiology And Chronic Health Evaluation.

Because of enhanced knowledge of postcardiac arrest pathophysiology, physicians’ responses have improved versus historical hypothermia practices. If adequate efforts toward achieving temperature control follow, the harmful effects of hyperthermia can be further minimized. 11 However, although a TFS can provide constant and convenient temperature control, it can cause complications necessitating expensive devices that incur additional costs. The average cost of TTM with a TFS was approximately USD 3,000 per patient in our centers during the study period. We believe that maintenance of normothermia without a TFS may be regarded as a temperature management option for post-resuscitation patients.

In our study, fever events were more common in good-outcome patients who underwent TTM with a TFS (Table 2). Thermal activity can be a sign of brain metabolic activity and preserved brain function. Preserving heat production ability during TTM is further related to good clinical outcomes.31,32 These phenomena may have affected our study results by masking the harmful effects of fever. However, heat production during the rewarming period was not related to clinical outcomes in a recent clinical study and most fever events developed after 24 hours in our study. 33

This study has several limitations. First, this was a retrospective analysis and treatment groups were not randomly selected or blinded. We attempted to overcome this limitation by using propensity score weighting; however, uncontrolled bias remains a possibility. Second, a small number of patients received TTM with a target temperature of 36°C because the clinical significance of the fever event was not fully evaluated given the limited number of patients. Third, long-term neurological outcomes were not evaluated in our study. Finally, the reasons for non-consent to TTM with a TFS were not recorded and matched for propensity analysis. This may have caused unadjusted differences in socioeconomic status between the groups.

Conclusion

No significant differences in the 1-month neurologic outcome were observed between patients receiving TTM with a TFS and those undergoing maintenance of normothermia without a TFS during post-resuscitation care.

Supplemental Material

sj-pdf-1-imr-10.1177_03000605221126880 - Supplemental material for Target temperature management versus normothermia without temperature feedback systems for out-of-hospital cardiac arrest survivors

Supplemental material, sj-pdf-1-imr-10.1177_03000605221126880 for Target temperature management versus normothermia without temperature feedback systems for out-of-hospital cardiac arrest survivors by Hui Jai Lee, Jonghwan Shin, Kyoung Min You, Woon Yong Kwon, Kyung Su Kim, You Hwan Jo, Seung Min Park in Journal of International Medical Research

Acknowledgement

The authors would like to thank the SNU CARE investigators for their contribution.

Footnotes

Author contributions: HJL: formal analysis, data curation, writing – original draft, and visualization; JS: conceptualization methodology, writing – original draft, review and editing, and supervision; KMY: resources, writing – review and editing; WYK: methodology and writing – review and editing; KSK: resources and writing – review and editing; YHJ: methodology and writing – review and editing; SMP: data curation and writing – review and editing.

Declaration of conflicting interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

The data that support the findings of this study are available on request from the corresponding author, JS, after IRB approval. The data are not publicly available given they contain information that could compromise the privacy of research participants.

ORCID iDs

Hui Jai Lee https://orcid.org/0000-0002-9064-4680

Seung Min Park https://orcid.org/0000-0002-3594-8403

Supplemental material

Supplemental material for this article is available online.

References

  • 1.Bernard SA, Gray TW, Buist MD, et al. Treatment of comatose survivors of out-of-hospital cardiac arrest with induced hypothermia. N Engl J Med 2002; 346: 557–563. 2002/02/22. DOI: 10.1056/NEJMoa003289. [DOI] [PubMed] [Google Scholar]
  • 2.The Hypothermia after Cardiac Arrest Study Group. Mild therapeutic hypothermia to improve the neurologic outcome after cardiac arrest. N Engl J Med 2002; 346: 549–556. 2002/02/22. DOI: 10.1056/NEJMoa012689. [DOI] [PubMed] [Google Scholar]
  • 3.American Heart Association. Part 6: Advanced Cardiovascular Life Support: 2020 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Circulation 2000; 102: I-166–I-171. DOI: doi:10.1161/circ.102.suppl_1.I-166. [Google Scholar]
  • 4.Panchal AR, Bartos JA, Cabañas JG, et al. Part 3: Adult Basic and Advanced Life Support: 2020 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation 2020; 142: S366–S468. 2020/10/22. DOI: 10.1161/cir.0000000000000916. [DOI] [PubMed] [Google Scholar]
  • 5.Taccone FS, Picetti E, Vincent JL. High Quality Targeted Temperature Management (TTM) After Cardiac Arrest. Crit Care 2020; 24: 6. 2020/01/08. DOI: 10.1186/s13054-019-2721-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Nolan JP, Sandroni C, Böttiger BW, et al. European Resuscitation Council and European Society of Intensive Care Medicine Guidelines 2021: Post-resuscitation care. Resuscitation 2021; 161: 220–269. 2021/03/29. DOI: 10.1016/j.resuscitation.2021.02.012. [DOI] [PubMed] [Google Scholar]
  • 7.Perman SM, Goyal M, Neumar RW, et al. Clinical applications of targeted temperature management. Chest 2014; 145: 386–393. 2014/02/05. DOI: 10.1378/chest.12-3025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Nielsen N, Wetterslev J, Cronberg T, et al. Targeted temperature management at 33°C versus 36°C after cardiac arrest. N Engl J Med 2013; 369: 2197–2206. 2013/11/19. DOI: 10.1056/NEJMoa1310519. [DOI] [PubMed] [Google Scholar]
  • 9.Bray JE, Stub D, Bloom JE, et al. Changing target temperature from 33°C to 36°C in the ICU management of out-of-hospital cardiac arrest: A before and after study. Resuscitation 2017; 113: 39–43. 2017/02/06. DOI: 10.1016/j.resuscitation.2017.01.016. [DOI] [PubMed] [Google Scholar]
  • 10.Hassager C, Nagao K, Hildick-Smith D. Out-of-hospital cardiac arrest: in-hospital intervention strategies. Lancet 2018; 391: 989–998. 2018/03/15. DOI: 10.1016/s0140-6736(18)30315-5. [DOI] [PubMed] [Google Scholar]
  • 11.Dankiewicz J, Cronberg T, Lilja G, et al. Hypothermia versus Normothermia after Out-of-Hospital Cardiac Arrest. N Engl J Med 2021; 384: 2283–2294. 2021/06/17. DOI: 10.1056/NEJMoa2100591. [DOI] [PubMed] [Google Scholar]
  • 12.Calabró L, Bougouin W, Cariou A, et al. Effect of different methods of cooling for targeted temperature management on outcome after cardiac arrest: a systematic review and meta-analysis. Critical Care 2019; 23: 285. DOI: 10.1186/s13054-019-2567-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Langhelle A, Nolan J, Herlitz J, et al. Recommended guidelines for reviewing, reporting, and conducting research on post-resuscitation care: the Utstein style. Resuscitation 2005; 66: 271–283. 2005/09/01. DOI: 10.1016/j.resuscitation.2005.06.005. [DOI] [PubMed] [Google Scholar]
  • 14.Perkins GD, Jacobs IG, Nadkarni VM, et al. Cardiac Arrest and Cardiopulmonary Resuscitation Outcome Reports: Update of the Utstein Resuscitation Registry Templates for Out-of-Hospital Cardiac Arrest: A Statement for Healthcare Professionals From a Task Force of the International Liaison Committee on Resuscitation (American Heart Association, European Resuscitation Council, Australian and New Zealand Council on Resuscitation, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation, Resuscitation Council of Southern Africa, Resuscitation Council of Asia); and the American Heart Association Emergency Cardiovascular Care Committee and the Council on Cardiopulmonary, Critical Care, Perioperative and Resuscitation. Resuscitation 2015; 96: 328–340. 2014/12/02. DOI: 10.1016/j.resuscitation.2014.11.002. [DOI] [PubMed] [Google Scholar]
  • 15.Callaway CW, Donnino MW, Fink EL, et al. Part 8: Post-Cardiac Arrest Care: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation 2015; 132: S465–S482. 2015/10/17. DOI: 10.1161/cir.0000000000000262. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med 2007; 147: 573–577. 2007/10/17. DOI: 10.7326/0003-4819-147-8-200710160-00010. [DOI] [PubMed] [Google Scholar]
  • 17.Desai RJ, Franklin JM. Alternative approaches for confounding adjustment in observational studies using weighting based on the propensity score: a primer for practitioners. Bmj 2019; 367: l5657. 2019/10/28. DOI: 10.1136/bmj.l5657. [DOI] [PubMed] [Google Scholar]
  • 18.Zhou T, Tong G, Li F, et al. PSweight: An R package for propensity score weighting analysis. arXiv preprint arXiv:201008893 2020. [Google Scholar]
  • 19.Kim KH, Shin SD, Song KJ, et al. Cooling methods of targeted temperature management and neurological recovery after out-of-hospital cardiac arrest: A nationwide multicenter multi-level analysis. Resuscitation 2018; 125: 56–65. 2018/02/08. DOI: 10.1016/j.resuscitation.2018.01.043. [DOI] [PubMed] [Google Scholar]
  • 20.De Fazio C, Skrifvars MB, Søreide E, et al. Intravascular versus surface cooling for targeted temperature management after out-of-hospital cardiac arrest: an analysis of the TTH48 trial. Crit Care 2019; 23: 61. 2019/02/24. DOI: 10.1186/s13054-019-2335-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Deye N, Cariou A, Girardie P, et al. Endovascular Versus External Targeted Temperature Management for Patients With Out-of-Hospital Cardiac Arrest: A Randomized, Controlled Study. Circulation 2015; 132: 182–193. 2015/06/21. DOI: 10.1161/circulationaha.114.012805. [DOI] [PubMed] [Google Scholar]
  • 22.Glover GW, Thomas RM, Vamvakas G, et al. Intravascular versus surface cooling for targeted temperature management after out-of-hospital cardiac arrest – an analysis of the TTM trial data. Crit Care 2016; 20: 381. 2016/11/27. DOI: 10.1186/s13054-016-1552-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Shrestha DB, Sedhai YR, Budhathoki P, et al. Hypothermia versus normothermia after out-of-hospital cardiac arrest: A systematic review and meta-analysis of randomized controlled trials. Ann Med Surg (Lond) 2022; 74: 103327. 2022/02/12. DOI: 10.1016/j.amsu.2022.103327. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Sandroni C, Nolan JP, Andersen LW, et al. ERC-ESICM guidelines on temperature control after cardiac arrest in adults. Intensive Care Med 2022; 48: 261–269. 2022/01/29. DOI: 10.1007/s00134-022-06620-5. [DOI] [PubMed] [Google Scholar]
  • 25.Bro-Jeppesen J, Hassager C, Wanscher M, et al. Post-hypothermia fever is associated with increased mortality after out-of-hospital cardiac arrest. Resuscitation 2013; 84: 1734–1740. 2013/08/07. DOI: 10.1016/j.resuscitation.2013.07.023. [DOI] [PubMed] [Google Scholar]
  • 26.Polderman KH. Induced hypothermia and fever control for prevention and treatment of neurological injuries. Lancet 2008; 371: 1955–1969. 2008/06/10. DOI: 10.1016/s0140-6736(08)60837-5. [DOI] [PubMed] [Google Scholar]
  • 27.Düggelin R, Maggiorini M, Voigtsberger S, et al. Increased protocol adherence and safety during controlled normothermia as compared to hypothermia after cardiac arrest. J Crit Care 2020; 63: 146–153. 2020/10/02. DOI: 10.1016/j.jcrc.2020.09.019. [DOI] [PubMed] [Google Scholar]
  • 28.Johnson NJ, Danielson KR, Counts CR, et al. Targeted Temperature Management at 33 Versus 36 Degrees: A Retrospective Cohort Study. Crit Care Med 2020; 48: 362–369. 2019/12/07. DOI: 10.1097/CCM.0000000000004159. [DOI] [PubMed] [Google Scholar]
  • 29.Abazi L, Awad A, Nordberg P, et al. Long-term survival in out-of-hospital cardiac arrest patients treated with targeted temperature control at 33 °C or 36 °C: A national registry study. Resuscitation 2019; 143: 142–147. 2019/08/31. DOI: 10.1016/j.resuscitation.2019.08.029. [DOI] [PubMed] [Google Scholar]
  • 30.Nolan JP, Orzechowska I, Harrison DA, et al. Changes in temperature management and outcome after out-of-hospital cardiac arrest in United Kingdom intensive care units following publication of the targeted temperature management trial. Resuscitation 2021; 162: 304–311. 2021/04/06. DOI: 10.1016/j.resuscitation.2021.03.027. [DOI] [PubMed] [Google Scholar]
  • 31.Murnin MR, Sonder P, Janssens GN, et al. Determinants of heat generation in patients treated with therapeutic hypothermia following cardiac arrest. J Am Heart Assoc 2014; 3: e000580. 2014/05/02. DOI: 10.1161/jaha.113.000580. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Uber AJ, Perman SM, Cocchi MN, et al. Increased Heat Generation in Postcardiac Arrest Patients During Targeted Temperature Management Is Associated With Better Outcomes. Crit Care Med 2018; 46: 1133–1138. 2018/04/06. DOI: 10.1097/ccm.0000000000003154. [DOI] [PubMed] [Google Scholar]
  • 33.Hoeyer-Nielsen AK, Holmberg MJ, Christensen EF, et al. Thermoregulation in post-cardiac arrest patients treated with targeted temperature management. Resuscitation 2021; 162: 63–69. 2021/02/15. DOI: 10.1016/j.resuscitation.2021.02.005. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

sj-pdf-1-imr-10.1177_03000605221126880 - Supplemental material for Target temperature management versus normothermia without temperature feedback systems for out-of-hospital cardiac arrest survivors

Supplemental material, sj-pdf-1-imr-10.1177_03000605221126880 for Target temperature management versus normothermia without temperature feedback systems for out-of-hospital cardiac arrest survivors by Hui Jai Lee, Jonghwan Shin, Kyoung Min You, Woon Yong Kwon, Kyung Su Kim, You Hwan Jo, Seung Min Park in Journal of International Medical Research

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author, JS, after IRB approval. The data are not publicly available given they contain information that could compromise the privacy of research participants.


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