Abstract
Background
Predicting outcomes for out‐of‐hospital cardiac arrest (OHCA) patients remains challenging. We aimed to evaluate the association between the lactate/albumin ratio (LAR) upon hospital arrival and neurological outcomes in OHCA patients.
Methods
This multicenter, retrospective, nationwide observational study was based on data from the JAAM‐OHCA registry, including 28,098 adults with non‐traumatic OHCA from 140 emergency medical centers across Japan (June 2014 to December 2021). Receiver‐operating characteristic curves assessed the predictive ability of LAR, lactate, and albumin levels. A reference model based on age, sex, witnessed arrest, initial cardiac rhythm, and time from call to hospital arrival was compared with models including LAR, lactate, or albumin levels. The primary outcome was a favorable neurological outcome at 30 days, with a secondary outcome at 90 days. Subgroup analyses were conducted among admitted patients and those who received active post‐resuscitation treatments.
Results
Among the 28,098 patients, 1421 (5.1%) achieved favorable neurological outcomes at 30 days. We demonstrated that LAR had a significantly higher area under the curve than either lactate or albumin for predicting both 30‐ and 90‐day outcomes (all p < 0.001), and better predictive value than either marker when added to the reference model. However, in the subgroup analysis of admitted patients, the statistical difference between LAR and albumin was no longer apparent.
Conclusion
The lower LAR upon hospital arrival was independently associated with a favorable neurological outcome in OHCA patients. However, its utility may vary depending on patient background, and further studies are needed to establish its clinical relevance.
Keywords: Albumin, cardiac arrest, lactate, lactate‐to‐albumin ratio, post‐cardiac arrest syndrome
Predicting outcomes for out‐of‐hospital cardiac arrest remains a significant challenge. This study found that the lactate/albumin ratio was associated with better neurological outcomes compared with lactate or albumin alone.
INTRODUCTION
Out‐of‐hospital cardiac arrest (OHCA) is a leading cause of mortality globally, and patient survival after OHCA remains low. 1 Post‐cardiac arrest syndrome (PCAS) is a complex condition caused by ischemia–reperfusion associated with a systemic inflammatory response. 2 The inflammation, particularly in the cranial nerves, is closely related to prognosis; the cause of death for two‐thirds of patients who die following OHCA is neurological injury. 3 Thus, continuation of treatment in patients with OHCA who attain return of spontaneous circulation (ROSC) but with neurological injury is often controversial. However, it remains difficult to accurately predict the functional prognosis of hypoxic brain injury after cardiac arrest. 4 Moreover, current guidelines advise against predicting neurological outcomes within the first 72 h after cardiac arrest, and the best timing and methods remain uncertain. 5 Still, early indicators of prognosis may help guide treatment decisions and discussions with families.
The lactate level is a good marker of tissue hypoperfusion and can be easily measured. 6 The lactate level is associated with mortality and an unfavorable neurological outcome in patients after cardiac arrest. 7 , 8 However, the relationship between the initial lactate level and the clinical outcome in patients with cardiac arrest remains controversial. 9 Serum albumin has antioxidant and anti‐inflammatory effects, and a deficiency worsens the prognosis of various critical illnesses. 10 , 11 , 12 The albumin level has also been shown to be associated with prognosis in patients after cardiac arrest. 13 , 14 Since the lactate and albumin levels are independent measurements, combining them may be useful in further increasing the predictive value of the outcome of OHCA. Thus, the lactate/albumin ratio (LAR) may be a predictive marker in patients with OHCA.
Previous studies have shown that the LAR may be a marker for predicting the prognosis of patients after cardiac arrest. 15 , 16 , 17 However, these studies were limited to patients after in‐hospital cardiac arrest, those who attained ROSC, and those who were transported to a single hospital. In this study, we aimed to determine whether the LAR, calculated on hospital arrival, functions as a useful and reliable predictive biomarker of OHCA, regardless of the post‐arrival status.
MATERIALS AND METHODS
Study design, setting, and patients
This was a retrospective observational analysis of a nationwide hospital‐based prospective registry, conducted by the Japanese Association for Acute Medicine (JAAM‐OHCA registry). This registry collects pre‐hospital and in‐hospital data. Pre‐hospital data were collected by emergency medical service (EMS) personnel based on the internationally standardized Utstein style. 18 Japanese EMS personnel are not permitted to terminate resuscitation, except in cases of decapitation, incineration, decomposition, rigor mortis, or dependent cyanosis; they transport almost all patients with OHCA to a hospital. The physicians of each participating institution collected in‐hospital data using a standardized online form. The details of this registry have been described previously. 19 Members of the JAAM‐OHCA registry working group checked the data anonymity. This study included patients with non‐traumatic OHCA aged ≥18 years who were registered in the JAAM‐OHCA registry between June 1, 2014, and December 31, 2021. We excluded patients who received no resuscitation attempts at the hospital, did not have pre‐hospital data, had a traumatic etiology, had no blood tests conducted, or had no data on the first documented rhythm, time from emergency call to hospital arrival, or outcome. The study protocol was approved by the ethics committee of the Kyoto Prefectural University of Medicine (approval ID: ERB‐C‐650‐1) and the institutional review board of each participating hospital. The ethics committee waived the requirement for written informed consent.
Data collection and outcomes
The following data were collected from the JAAM‐OHCA registry: age, sex, bystander cardiopulmonary resuscitation (CPR), cause of cardiac arrest, witnessed cardiac arrest, first documented rhythm on EMS arrival, management in pre‐hospital and in‐hospital settings (defibrillation, epinephrine, percutaneous coronary intervention, target temperature management, and extracorporeal life support), laboratory data (lactate and albumin levels), and outcome data. As this observational study did not have a protocol for blood sampling, lactate and serum albumin levels were available only when physicians caring for patients with OHCA requested them to be measured in routine clinical settings. Therefore, all measured biomarker levels were known to the treating physician. Only the lactate and albumin levels that were measured for the first time after hospital arrival were analyzed. The primary outcome of this study was a 30‐day favorable neurological outcome. Favorable neurological outcomes were evaluated using the cerebral performance category (CPC) scale, which is defined by a scale of 1 or 2. 18 The secondary outcome was a 90‐day favorable neurological outcome.
Statistical analysis
We compared the patient characteristics, pre‐ and in‐hospital information, and outcomes (30‐day neurological outcomes categorized as CPC 1 or 2 and CPC 3–5), using the Kruskal–Wallis rank test for continuous variables and chi‐square or Fisher exact tests for categorical variables. All data are presented as the median and interquartile range (IQR). Receiver‐operating characteristic (ROC) curves were used to compare the ability of the LAR, the lactate level, and the albumin level to predict a favorable neurological outcome with the area under the curve (AUC). Youden's index was used to identify the optimal cutoff value for the LAR. We verified the improvement in the prediction model by adding the LAR to predict the clinical outcome using multivariable regression analysis. The reference prediction model was initially based on previous studies, including age, sex (male or female), witness cardiac arrest (yes or no), first documented rhythm on EMS arrival (shockable or non‐shockable), and the time from emergency call to hospital arrival. 20 , 21 We also adjusted for the presence or absence of active post‐resuscitation interventions in the multivariable analysis. To determine the improvement in the prediction model, the AUC of the reference model, reference model with the LAR added, reference model with the lactate level added, and reference model with the albumin level added were compared. DeLong's test or the Bootstrap test for two correlated ROC curves were performed to determine statistical significance. 22 For the standard Bootstrap method, there were 2000 times resampling. The net reclassification improvement (NRI) and integrated discrimination improvement (IDI) values were measured to confirm the improvement in the predictive ability of the reference model with the LAR added. In addition to the main analysis, we conducted subgroup analyses to further validate the robustness of our findings. Since outcomes can differ between cardiac and non‐cardiac etiologies, we performed a focused analysis on patients with cardiogenic OHCA. 1 Furthermore, the main analysis included patients whose resuscitation efforts were terminated in the emergency department and thus were not admitted. We recognized that combining these patients with those who were admitted could introduce substantial heterogeneity, making the interpretation and application of the findings difficult in real‐world settings. Therefore, we added an additional analysis limited to patients who were admitted to the intensive care unit or general ward after hospital arrival. However, acknowledging that heterogeneity may still exist even within this admitted cohort, we additionally performed a subgroup analysis limited to patients who received active treatments, such as extracorporeal life support, percutaneous coronary intervention, intra‐aortic balloon pumping, or targeted temperature management, since the presence or absence of active post‐resuscitation treatment after hospital arrival may have a significant impact on outcomes. 1
All p‐values were two‐sided, and the level of significance was set at 0.05. All statistical analyses were performed using EZR (version 1.54; Saitama Medical Center, Jichi Medical University, Saitama, Japan), which is a graphical user interface for R Statistical software version 3.6.2 (The R Foundation for Statistical Computing, Vienna, Austria). 23
RESULTS
A total of 81,234 patients with OHCA were registered during the study. After applying the exclusion criteria, 28,098 patients were eligible for analysis (Figure 1). The patient characteristics and pre‐ and in‐hospital information are presented in Table 1. There were 1421 patients (5.1%) with a 30‐day favorable neurological outcome and 26,677 patients (94.9%) with a 30‐day unfavorable neurological outcome (CPC 3–5). Blood test results, patient characteristics, and pre‐ and in‐hospital information differed according to the outcome. The median LAR of patients with a 30‐day favorable neurological outcome was 18.00 (IQR, 11.57–26.50), whereas the median LAR of patients with an unfavorable neurological outcome was 40.50 (IQR, 29.08–53.91).
FIGURE 1.
Patients of this study.
TABLE 1.
Patient characteristics and pre‐ and in‐hospital information.
| Variables | Total | Cerebral performance category 30 days | p‐value | |
|---|---|---|---|---|
| 1, 2 | 3–5 | |||
| N = 28,098 | N = 1421 | N = 26,677 | ||
| Men (%) | 17,178 (61.1) | 1095 (77.1) | 16,083 (60.3) | <0.001 |
| Age (median [IQR]) | 76.00 [65.00, 85.00] | 62.00 [50.00, 72.00] | 77.00 [66.00, 85.00] | <0.001 |
| Cause of event (%) | <0.001 | |||
| Cardiac | 15,675 (55.8) | 1241 (87.3) | 14,434 (54.1) | |
| Non‐cardiac | 12,423 (44.2) | 180 (12.7) | 12,243 (45.9) | |
| Pre‐hospital information | ||||
| Bystander witness (%) | 13,704 (48.8) | 1222 (86.0) | 12,482 (46.8) | <0.001 |
| Bystander CPR (%) | 13,511 (48.1) | 865 (60.9) | 12,646 (47.4) | <0.001 |
| Shock by public‐access AEDs (%) | 655 (2.3) | 296 (20.8) | 359 (1.3) | <0.001 |
| First documented rhythm at the scene (%) | ||||
| Ventricular fibrillation | 3112 (11.1) | 825 (58.1) | 2287 (8.6) | |
| Pulseless ventricular tachycardia | 56 (0.2) | 15 (1.1) | 41 (0.2) | |
| Pulseless electric activity | 7367 (26.2) | 208 (14.6) | 7159 (26.8) | |
| Asystole | 16,067 (57.2) | 38 (2.7) | 16,029 (60.1) | |
| Presence pulse | 1496 (5.3) | 335 (23.6) | 1161 (4.4) | |
| Epinephrine (%) | 9715 (34.6) | 168 (11.8) | 9547 (35.8) | <0.001 |
| Advanced airway management (%) | 24,620 (88.5) | 1076 (76.9) | 23,544 (89.1) | <0.001 |
| Defibrillation (%) | 4472 (19.3) | 949 (71.2) | 3523 (16.1) | <0.001 |
| EMS resuscitation times | ||||
| Call to contact with a patient (minutes) (median [IQR]) | 8.00 [7.00, 10.00] | 8.00 [6.00, 10.00] | 9.00 [7.00, 10.00] | <0.001 |
| Call to hospital arrive (minutes) (median [IQR]) | 34.00 [28.00, 41.00] | 30.00 [24.00, 38.00] | 34.00 [28.00, 41.00] | <0.001 |
| In‐hospital information | ||||
| First documented rhythm after hospital arrival (%) | ||||
| Ventricular fibrillation | 1448 (5.2) | 241 (17.0) | 1207 (4.5) | |
| Pulseless ventricular tachycardia | 107 (0.4) | 12 (0.8) | 95 (0.4) | |
| Pulseless electric activity | 6542 (23.3) | 109 (7.7) | 6433 (24.1) | |
| Asystole | 16,608 (59.1) | 42 (3.0) | 16,566 (62.1) | |
| Presence pulse | 3393 (12.1) | 1017 (71.6) | 2376 (8.9) | |
| Hospital admission | 9326 (33.2) | 1421 (100.0) | 7905 (29.6) | <0.001 |
| Extracorporeal life support (%) | 1758 (6.3) | 191 (13.4) | 1567 (5.9) | <0.001 |
| Percutaneous coronary intervention (%) | 1382 (4.9) | 522 (36.7) | 860 (3.2) | <0.001 |
| Intra‐aortic balloon pumping (%) | 1403 (5.0) | 307 (21.6) | 1096 (4.1) | <0.001 |
| Target temperature management (%) | 2285 (8.1) | 717 (50.5) | 1568 (5.9) | <0.001 |
| Laboratory data | ||||
| Lactate (mg/dL) (median [IQR]) | 120.60 [87.30, 157.00] | 68.00 [44.10, 98.00] | 123.00 [90.90, 160.00] | <0.001 |
| Albumin (g/dL) (median [IQR]) | 3.10 [2.70, 3.60] | 3.80 [3.50, 4.10] | 3.10 [2.70, 3.50] | <0.001 |
| LAR (median [IQR]) | 39.46 [27.64, 52.99] | 18.00 [11.57, 26.50] | 40.50 [29.08, 53.91] | <0.001 |
Note: Comparisons between the 2 groups were evaluated with Kruskal–Wallis tests for continuous variables and Fisher exact test for categorical variables.
Abbreviations: AED, automated external defibrillator; CPR, cardiopulmonary resuscitation; EMS, emergency medical services; IQR, interquartile range; LAR, lactate–albumin ratio.
The AUC for predicting a 30‐day favorable neurological outcome to discharge using the LAR was 0.83 (p < 0.001). The AUC of the LAR was significantly superior to that of the lactate level and the albumin level (both p < 0.001). The optimal cutoff value for the LAR using Youden's index was 26.64 (sensitivity, 75.5%; specificity, 79.7%) to predict a favorable neurological outcome (Figure 2). In the multivariate logistic regression model, the LAR was an independent prognostic indicator of neurological outcome (Table S1). The AUC of the reference model with LAR added was significantly higher than that of the reference model, the reference model with the lactate level added, and the reference model with the albumin level added (all p < 0.05) (Figure 3, Figure S1).
FIGURE 2.
ROC curves for predicting a 30‐day favorable neurological outcome after OHCA, comparing the LAR (A), the lactate level (B), and the albumin level (C) based on their AUCs. 95%CI, 95% confidence interval; AUC, area under the curve; LAR, lactate‐to‐albumin ratio; OHCA, out‐of‐hospital cardiac arrest; ROC, receiver‐operating characteristic.
FIGURE 3.
ROC curves for predicting a 30‐day favorable neurological outcome after OHCA, comparing the reference model alone, and the reference model with the addition of the LAR, the lactate level, or the albumin level. Reference model = age, sex, witnessed cardiac arrest, first documented rhythm on EMS arrival, time from emergency call to hospital arrival. 95%CI, 95% confidence interval; AUC, area under the curve; EMS, emergency medical services; LAR, lactate‐to‐albumin ratio; OHCA, out‐of‐hospital cardiac arrest; ROC, receiver‐operating characteristic.
In the subgroup analyses, results comparable to those of the main analysis were observed in patients with cardiogenic OHCA (Figure S2). Among admitted patients, the statistical significance between LAR and albumin was no longer apparent (p = 0.06), although a similar trend was noted, and significant differences emerged when comparing LAR with lactate and with the reference model (Figure S3). Furthermore, in those who received active treatments after hospital arrival following OHCA, consistent findings with the main analysis were noted (Figure S4). Furthermore, the addition of the LAR had a significantly positive IDI (IDI, 0.082; 95% confidence interval [CI], 0.075–0.089; p < 0.001) and NRI (NRI, 1.012; 95% CI, 0.967–1.057; p < 0.001) for the LAR in predicting a favorable neurologic outcome (both p < 0.001). This demonstrated that the LAR improved the ability to predict a favorable neurological outcome when added to the reference model (Table S2).
The AUC for predicting a 90‐day favorable neurological outcome using the LAR was higher than that using the lactate level or the albumin level (p < 0.001) (Figure 4). The AUC of the prediction model with the LAR added was significantly greater than the reference model, the reference model with the lactate level added, and the reference model with the albumin level added (all p < 0.05) (Figure 5).
FIGURE 4.
ROC curves for predicting a 90‐day favorable neurological outcome after OHCA, comparing the LAR (A), the lactate level (B), and the albumin level (C) based on their AUCs. 95%CI, 95% confidence interval; AUC, area under the curve; LAR, lactate‐to‐albumin ratio; OHCA, out‐of‐hospital cardiac arrest; ROC, receiver‐operating characteristic.
FIGURE 5.
ROC curves for predicting a 90‐day favorable neurological outcome after OHCA, comparing the reference model alone, and the reference model with the addition of the LAR, the lactate level, or the albumin level. Reference model = age, sex, witnessed cardiac arrest, first documented rhythm on EMS arrival, time from emergency call to hospital arrival. 95%CI, 95% confidence interval; AUC, area under the curve; EMS, emergency medical services; LAR, lactate‐to‐albumin ratio; OHCA, out‐of‐hospital cardiac arrest; ROC, receiver‐operating characteristic.
DISCUSSION
This study demonstrated that the LAR during early resuscitation was significantly associated with a favorable neurological outcome in patients with OHCA and showed better prognostic value than lactate or albumin alone. However, these differences became less pronounced in patients who received active treatments, and the difference between LAR and albumin was no longer significant in the admitted patient subgroup. These findings suggest that while LAR may be a useful adjunctive marker in prognostic assessment, it should not be used in isolation, and further validation is needed to establish its clinical relevance. Several previous studies have reported the effectiveness of the LAR in the clinical practice of patients with OHCA. 16 , 17 These studies validated the usefulness of the LAR as a prognostic factor for patients with OHCA. However, the previous studies had small sample sizes with short observation periods and only included patients with sustained ROSC; therefore, the external validation power was not strong. Our study was based on these previous studies and focused on including a large number of OHCA patients while taking into account post‐arrival interventions and patient status.
The pathophysiology of elevated lactate levels after cardiac arrest is complex and multifactorial. 24 Initial lactate elevation reflects tissue hypoperfusion and ischemia–reperfusion‐induced inflammation and can be improved with hemodynamic optimization. 25 However, sustained or rising lactate levels in later phases are often linked to organ failure and unfavorable outcomes. 26 High lactate levels have been associated with mortality and unfavorable neurological outcomes, though their early prognostic value after OHCA may be limited. 7 , 26 While early lactate reduction has been identified as an independent predictor of mortality, 25 the utility of lactate clearance as a resuscitation endpoint remains controversial due to its complex physiology 27 and the need for several hours of observation, which limits its practicality in early prognostic assessment. 25 , 27
Hypoalbuminemia has been associated with mortality in patients with various diseases. 12 , 28 Albumin has important physiological and pharmacological functions in inflammatory cascades 29 and can increase an anti‐inflammatory effect. 28 One of the essential factors of PCAS is the systemic ischemia–reperfusion response and subsequent systemic inflammatory immune response. Increased inflammation also causes vascular hyperpermeability, which can exacerbate tissue hypoperfusion. 30 Thus, the albumin level can be a biomarker for predicting outcomes in patients after cardiac arrest. 14 Hypoalbuminemia reduces oncotic pressure and can result in decreased intravascular volume and risk of inadequate blood flow to vital organs. Furthermore, serum albumin concentration generally decreases in both acute and chronic phases in accordance with disease severity. In particular, low serum albumin levels upon hospital arrival may be influenced by factors such as decreased hepatic synthesis due to chronic conditions like liver failure, increased catabolic rate, extravascular distribution, and exogenous loss. 14 , 29 Therefore, the serum albumin concentration at the time of hospital admission may reflect the presence of chronic comorbidities and the underlying disease status of the patient, and thus could be useful in predicting the clinical course after cardiac arrest. As lactate and albumin can compensate for each other's limitations, their combination as an inverse ratio may help capture trends in early hypoperfusion after OHCA and the subsequent course of PCAS.
In the subgroup of admitted patients, the statistical significance between LAR and albumin disappeared, possibly because patients who were able to be admitted after OHCA generally had more favorable outcomes than those who could not be admitted, and albumin levels tend to be preserved in patients with favorable prognoses, 14 thereby reducing the difference in prognostic value between the LAR and albumin markers. Additionally, compared to the total cohort, the overall AUC values were lower in both the active treatment and admitted patient groups, which may be explained by the increased proportion of favorable outcomes reducing intergroup variability and consequently lowering the discriminative power of the prediction models. Furthermore, the active treatments themselves may have had a strong influence on outcomes, possibly contributing to the decrease in AUC. On the contrary, the lack of statistical significance between LAR and albumin observed in the admitted patient subgroup suggests that the prognostic utility of LAR may depend on patient background characteristics. This finding differs from previous studies in which statistical significance was demonstrated among patients who had achieved ROSC, and therefore suggests that the clinical application of LAR requires cautious interpretation and further validation. 16 , 17
This study had several limitations. First, this registry did not provide medical, medication, or social histories, and these factors may have affected the outcomes. Therefore, the impact of covariates should be evaluated in future studies. Second, the protocol for the timing of blood tests was not standardized across institutions. Although both serum albumin and lactate levels are typically measured during the early resuscitation phase in clinical settings, variations in whether and when these tests were performed may have introduced some bias in the measurement of important variables. In particular, since albumin testing generally takes longer to produce results, it is possible that a certain number of patients underwent withdrawal of resuscitation before the test results were available. Therefore, the LAR may have limited utility as a decision‐making tool during the very early phase of resuscitation. However, considering that some time is typically required to complete initial assessments and interventions in the hospital setting, the LAR may still serve as a valuable supplementary tool in guiding further active treatment strategies. In fact, in the subgroup of patients who received active interventions, a trend similar to that seen in the overall analysis was observed in this study. Third, some patients were excluded because of missing data. This might have led to a bias in patient selection. Finally, this study was conducted in Japan, and whether the results can be applied to other countries requires examination.
CONCLUSION
In this nationwide retrospective observational study in Japan, we found that the lower LAR upon hospital arrival was independently associated with a favorable neurological outcome among patients with OHCA. In admitted patients, the difference between LAR and albumin was not significant, which may suggest that the utility of LAR varies depending on patient background. While LAR may serve as a helpful adjunctive marker for outcome prediction, further research is needed to confirm its clinical applicability.
FUNDING INFORMATION
This study was supported by Japan Society for the Promotion of Science KAKENHI (Grant Numbers 23KK0309 and 24K19500).
CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest.
ETHICS STATEMENT
Approval of the research protocol: The study protocol was approved by the ethics committee of the Kyoto Prefectural University of Medicine (approval ID: ERB‐C‐650‐1) and the institutional review board of each participating hospital.
Informed consent: The ethics committee waived the requirement for written informed consent.
Registry and the registration no. of the study/trial: Not applicable.
Animal studies: Not applicable.
Supporting information
Data S1.
ACKNOWLEDGEMENTS
We express our sincere gratitude to all EMS personnel and concerned physicians in Japan and to the Fire and Disaster Management Agency and Institute for Fire Safety and Disaster Preparedness of Japan for assisting in the establishment of the database based on the Utstein style. We would like to thank Editage (www.editage.jp) for English language editing. Dr. Ohta passed away suring the process of submitting the manuscript. He is listed as an author because he contributed to the writing manuscript and part of the revision.
Nakada K, Miyamoto Y, Kawama T, Hatakeyama T, Kitamura T, Ohta B, et al. Predictive effects of the lactate/albumin ratio on neurological outcomes in patients after out‐of‐hospital cardiac arrest. Acute Med Surg. 2025;12:e70082. 10.1002/ams2.70082
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the Japanese Association for Acute Medicine, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Data are, however, available from the authors upon reasonable request and with the permission of the Japanese Association for Acute Medicine.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1.
Data Availability Statement
The data that support the findings of this study are available from the Japanese Association for Acute Medicine, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Data are, however, available from the authors upon reasonable request and with the permission of the Japanese Association for Acute Medicine.