Clinical characteristics and Prognostic Factors of Elderly Heat Stroke in Chongqing: A Multicenter Retrospective Study

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Methods In this multicenter retrospective study, a total of 55 elderly patients with heat stroke from four hospitals in Chongqing, including Jiulongpo District People’s Hospital, Chongqing Emergency Medical Center, Chongqing Liangjiang New Area People’s Hospital, and the University Town Hospital affiliated to Chongqing Medical University were included from January 2022 to December 2024 and randomized to either improvement group or death group based on 28-day clinical outcomes, with clinical characteristics, organ dysfunction, and therapeutic interventions compared between the two groups. Normally distributed continuous variables were expressed as mean ± standard deviation and compared using the independent-samples t -test, whereas non-normally distributed variables were expressed as median (Q1, Q3) and compared using the Wilcoxon rank-sum test. Univariate and multivariate logistic regression analyses were performed to identify risk factors for mortality. Receiver operating characteristic (ROC) curves were used to evaluate sensitivity and specificity. All statistical analyses were two-sided, with P < 0.05 considered statistically significant. Results Among the 55 patients enrolled, 17 (30.9%) died within 28 days and 38 (69.1%) showed clinical improvement. There were no significant differences in age or sex between the two groups. Compared with the improvement group, the patients in the death group exhibited more severe multi-organ dysfunction on admission and significantly higher ( P < 0.05) initial and peak levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), serum creatinine (Scr), prothrombin time (PT), D-dimer, and myoglobin. The median dose of norepinephrine required was also markedly higher in the death group than in the improvement group (0.9 vs. 0.2 μg/kg/min, P < 0.001). The proportions of mechanical ventilation (100% vs. 47.4%) and continuous renal replacement therapy (CRRT) were significantly higher in the death group than in the improvement group ( P < 0.05). Severe hypoxemia (PaO₂/FiO₂ ≤ 200) was more common in the death group than in the improvement group (47.1% vs. 21.1%, P < 0.05). Heat stroke–induced coagulopathy (HIC) scores both at admission (median 4 vs. 3) and at peak were significantly higher in the death group than in the improvement group (median 5 vs. 4, P < 0.05). Univariate logistic regression showed that CRRT, low PaO₂/FiO₂, high vasopressor dose, elevated HIC scores, and increased AST, ALT, PT, and Scr levels were significantly associated with mortality. Multivariate logistic regression identified three independent risk factors for death: high HIC score at admission, elevated initial AST, and high peak Scr. ROC curve analysis demonstrated that the combined predictive value of these three indicators yielded an area under the curve (AUC) of 0.906. Conclusions Mortality in elderly heat stroke patients is closely associated with early multi-organ dysfunction. A high HIC score at admission, elevated initial AST levels, and increased peak serum creatinine are independent predictors of poor prognosis and may serve as valuable indicators for early risk stratification and clinical intervention. Elderly heat stroke Clinical characteristics Chongqing Multi-organ dysfunction HIC score Figures Figure 1 Figure 2 Figure 3 Introduction Heat stroke (HS) is a severe and life-threatening condition caused by thermal injury, characterized by central thermoregulatory failure following exposure to high environmental temperatures and/or strenuous physical activity. It results in a rapid elevation of core body temperature, accompanied by hot skin, altered consciousness, and multiple organ dysfunction [ 1 , 2 ]. Against the background of global climate change, the incidence of heat stroke has been increasing worldwide [ 3 , 4 ]. Elderly heat stroke (EHS) is classified as classic heat stroke (CHS) and is primarily caused by passive exposure to hot and humid environments, leading to an imbalance between heat production and heat dissipation. Compared with younger individuals, elderly patients often present with insidious prodromal symptoms, multiple comorbidities, rapid disease progression, and significantly higher mortality rates [ 5 ]. Age-related physiological decline, including impaired thermoregulation and reduced sweat gland function, combined with chronic diseases such as cardiovascular disease and diabetes, renders elderly individuals particularly vulnerable to heat injury [ 1 , 6 – 8 ]. Previous studies have reported that during summer heat waves, the incidence of CHS ranges from 17.6 to 26.5 per 100,000 population, with in-hospital mortality rates of 14%–65%, and ICU mortality exceeding 60% [ 9 , 10 ]. Mortality among elderly patients may exceed 50% [ 11 ]. Heat stroke also shows marked seasonal and regional variation [ 12 ], with especially high risks in hot and humid regions such as Chongqing [ 13 , 14 ]. Heat stroke progresses rapidly and is associated with high mortality, which correlates closely with the duration of hyperthermia [ 15 ]. Therefore, rapid and effective cooling is the cornerstone of treatment. However, no universally accepted diagnostic criteria for heat stroke currently exist, and diagnosis largely relies on clinical history and presentation [ 16 , 17 ]. Elderly patients often present with altered mental status, and a core temperature > 40°C may be absent, leading to frequent misdiagnosis as stroke, septic shock, or metabolic encephalopathy and consequent delays in treatment. With the accelerating aging population in China, the disease burden of EHS is increasing, yet systematic studies focusing on this population remain limited. Accordingly, early identification of high-risk EHS patients and timely intervention are crucial for improving outcomes. This study aimed to investigate the clinical characteristics and prognostic risk factors of heat stroke in elder patients so as to provide evidence for early diagnosis and precise treatment. Methods 2.1 Subjects In this multicenter retrospective study, a total of 55 elderly patients with heat stroke were enrolled from four hospitals in Chongqing between January 2022 and December 2024. This study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the Ethics Committee of Jiulongpo District People's Hospital (Approval No. 202501) and registered with the Chinese Clinical Trial Registry (ChiCTR305494). Due to the retrospective nature of the study, the requirement for informed consent was waived by the ethics committee. Patients were included in the study if they were aged ≥ 60 years with a medical history of exposure to high-temperature and/or high-humidity environments or strenuous physical activity plus and presented with at least one of the following yet without known cause: central nervous system dysfunction (e.g., coma, seizures, delirium, or behavioral abnormalities), core body temperature > 40°C, multiple organ dysfunction (involving ≥ 2 organs such as liver, kidney, skeletal muscle, or gastrointestinal tract), or severe coagulation disorder or disseminated intravascular coagulation (DIC). Patients were excluded if they had malignant hyperthermia, chronic liver disease, and or chronic renal insufficiency or if they had incomplete clinical data. 2.2 Study Design 2.2.1. monitoring method and timing The body temperature of the patients was measured immediately upon their presentation using infrared thermometer. If hyperthermia was detected, rectal temperature was measured for confirmation, and cooling measures were initiated immediately. Temperature was reassessed every 10 minutes during cooling. 2.2.2 Outcome Measures Baseline data included age, sex, body temperature, heat exposure etiology, level of consciousness, comorbidities, AST, ALT, Scr, creatine kinase, myoglobin, PT, D-dimer, oxygenation index, vasopressor dose (converted to norepinephrine equivalents), mechanical ventilation, CRRT, ICU length of stay, total hospital stay, and 28-day mortality. 2.3 Grouping and Treatment 2.3.1 Grouping Patients were randomized to either improvement group or a death group according to 28-day outcomes. 2.3.2 Treatment All of the enrolled patients received comprehensive treatment, including immediate cooling, fluid resuscitation with sodium-containing solutions, airway protection and oxygen therapy, sedation for seizures or agitation, continuous renal replacement therapy (CRRT) for acute kidney injury when indicated, and stress ulcer prophylaxis with nutritional support. For patients presenting with hyperthermia, cooling was initiated immediately through prompt removal from the hot environment, cold-water immersion or dousing, evaporative cooling with fanning, infusion of ice-cold saline, and the use of cooling blankets. Rapid fluid resuscitation was performed using sodium-containing solutions (e.g., normal saline or Ringer’s solution) as the preferred fluids; during the first hour on site, the infusion volume was 30 mL/kg or a total of 1,500–2,000 mL, with the volume of cold saline used for cooling included in the total fluid balance. Thereafter, fluid infusion rates were adjusted according to clinical responses, such as blood pressure, heart rate, and urine output, while avoiding fluid overload. Airway protection and oxygen therapy were provided as needed, and for most patients with heat stroke requiring airway protection, endotracheal intubation was performed as early as possible. In patients with seizures, anticonvulsant therapy was initiated on site, and sedative agents were administered to maintain adequate sedation; sedation was also provided for agitated patients. For patients with acute kidney injury, CRRT was selected based on the internal milieu status and myoglobin levels. Additionally, all patients received prophylaxis for stress-related ulcers and appropriate nutritional support. 2.4 Statistical Analysis Statistical analyses were performed using SPSS version 27.0. For continuous variables, normality was first assessed using the Shapiro–Wilk test. Normally distributed data are presented as the mean ± standard deviation and were compared between groups using the independent-samples t test. Non-normally distributed data are presented as the median (Q1, Q3) and were compared using the Wilcoxon rank-sum test. Categorical variables are expressed as frequencies (percentages) and were compared using the χ² test or Fisher’s exact test, as appropriate. To explore risk factors associated with poor outcomes in patients with exertional heat stroke (EHS), univariate logistic regression analyses were first performed to identify variables with statistical significance; these variables were then entered into a multivariate logistic regression model to identify independent risk factors. A backward stepwise regression approach was applied, with criteria for entry set at p 0.10. To further evaluate the predictive performance of each independent risk factor for poor outcomes, receiver operating characteristic (ROC) curves were constructed, and the area under the curve (AUC) with 95% confidence intervals was calculated, along with sensitivity and specificity. All statistical tests were two sided, and a P value < 0.05 was considered statistically significant. Results 3.1 General Characteristics As shown in Fig. 1 , a total of 82 patients with heat stroke were admitted to the ICU during the study period, of whom 62 met the inclusion criteria. Seven patients were excluded due to chronic liver disease (n = 2), chronic kidney disease (n = 1), or incomplete data (n = 4). Ultimately, 55 patients were included in the final analysis, including 38 patients (69.1%) in the improvementgroup and 17 patients (30.9%) in the death group. There were no statistically significant differences between the two groups in terms of age, sex, or age stratification ( p > 0.05). The improvementgroup included 38 patients (22 males and 16 females) with a mean age of 69 ± 10.751 years, whereas the death group comprised 17 patients (11 males and 6 females) with a mean age of 75 ± 10.56 years. Regarding comorbidities, 20 patients (52.6%) in the improvementgroup and 14 patients (82.4%) in the death group had at least one comorbidity, with a statistically significant difference between the groups ( p = 0.036). Analysis of the number of comorbidities showed that the proportions of patients with one and two comorbidities in the death group were 58.8% and 23.5%, respectively, both higher than those in the improvementgroup (34.2% and 10.5%, respectively); however, the overall distribution of comorbidity counts did not differ significantly between the two groups ( p > 0.05). In addition, there were no significant differences between the groups in initial body temperature, number of comorbidities, or etiological factors (Table 1 ). Table 1 Baseline characteristics. Variable Improvementgroup(n = 38) Death group (n = 17) Statistic p value Age (years) 69 ± 10.751 75 ± 10.56 t=-0.777 0.441 Age group (n, %) χ²=0.953 0.917 60–70 20(44.7) 6(35.3) 70–80 9(23.7) 6(29.4) 80–90 4(10.5) 3(17.6) ≥ 90 5(13.2) 2(11.8) Gender (n, %) χ²=0.227 0.634 Male 22(57.9) 11(64.7) Female 16(42.1) 6(35.3) Initial temperature (℃) 39.97 ± 1.07 40.49 ± 1.31 χ²=0.227 0.128 <40 22(59) 4(22.2) ≥ 40 15(41) 14(77.8) Comorbidity (n, %) χ²=4.396 0.036 Yes 20(52.6) 14(82.4) No 18(47.4) 3(17.6) Number of comorbidities (n, %) χ²=7.126 0.068 0 18(47.4) 3(17.6) 1 13(34.2) 10(58.8) 2 4(10.5) 4(23.5) Etiology n (%) χ² = 3.663 0.056 Outdoor heat exposure 11 (28.9) 1 (5.9) Hyperthermic environment 27 (71.1) 16 (94.1) 3.2 Organ Function Assessment The death group exhibited more severe multi-organ dysfunction than the improvementgroup. For liver function, both initial and peak aspartate aminotransferase (AST) levels were significantly higher in the death group [initial: 103 (36, 361) vs. 32 (20.75, 51), p = 0.002; peak: 166 (68, 457) vs. 53.5 (35.52, 117.25), p = 0.001], and similar increases were observed for initial and peak alanine aminotransferase (ALT) levels. Renal dysfunction was more pronounced in the death group, as reflected by significantly higher initial and peak serum creatinine levels. Coagulation abnormalities were also more severe in the death group, with significantly prolonged initial and peak prothrombin time (PT) and elevated initial and peak D-dimer levels. Regarding rhabdomyolysis, the death group had significantly higher initial and peak myoglobin levels, with the median initial level reaching 1,280 µg/L compared with 688.5 µg/L in the improvementgroup ( p = 0.024). In terms of circulatory function, the death group required significantly higher doses of norepinephrine [0.9 vs. 0.2 µg/(kg·min), p < 0.001]. No significant differences were observed in initial or peak creatine kinase levels between the two groups. Overall, significantly higher levels of AST, ALT, serum creatinine, PT, and D-dimer, as well as higher norepinephrine requirements, were observed in the death group than in the improvementgroup ( p < 0.05) (Table 2 ). Table 2 Initial and peak organ function assessment Variable Improve group (n = 38) Death group (n = 17) Z p value Liver AST (Initial,U/L) 32(20.75,51) 103(36,361) -3.143 0.002 AST (Peak,U/L) 53.5(35.52,117.25) 166(68,457) -3.343 0.001 ALT (Initial ,U/L) 41.5(22,59) 87(39,198) -2.587 0.010 ALT (Peak,U/L) 59(49.25,87.25) 110(67,256) -2.751 0.006 Renal Scr (Intial, µmol/L) 98(75.75,139.25) 182(125,198) -2.659 0.008 Scr (Peak, µmol/L) 112.5(75.75,189) 222(175,313) -3.297 0.001 Coagulation PT (Initial, S) 14.35(13.7,16.4) 17.9(15.7,21.4) -2.933 0.003 PT (Peak,S) 17.6(14.23,19.95) 22(17.1,35.1) -2.314 0.021 D-dimer (Initial, mg/L) 2.22(0.78,5.28) 10(4.09,10.63) -2.523 0.012 D-dimer (Peak, mg/L) 3.77(2,5.78) 10(5.21,16.2) -2.550 0.011 Heart CK (Initial, U/L) 300(76.05,1613.75) 635(6.31,1300) -0.091 0.927 CK (Peak, U/L) 514(103.5,1870.5) 866(101.27,1688) -0.319 0.750 MYO (Initial, µg/L) 688.5(241,1268.25) 1280(1000,1829) -2.261 0.024 MYO (Peak, µg/L) 1049.5(288.8,1923.5) 1994(1200,4000) -2.771 0.006 Circulation NE (µg/(kg.min)) 0.2(0,0.05) 0.9(0.5,1.2) -3.851 <0.001 AST: aspartate aminotransferase; ALT: alanine transaminase; Scr: serum reatinine; PT:prothrombin time; CK:creatine kinase; MYO:myohemoglobin; NE:noradrenaline. 3.3 Treatment and Outcomes The use of mechanical ventilation was significantly higher in the death group compared with the improvementgroup (100% vs. 47.4%, P < 0.001). Similarly, continuous renal replacement therapy (CRRT) was more frequently required in the death group (64.7% vs. 36.8%, P = 0.042). Severe hypoxemia, defined as PaO₂/FiO₂ ≤ 200, was significantly more common in the death group than in the improvementgroup (47.1% vs. 21.1%, P 0.05) (Table 3 ). Table 3 Outcome variables in the improvement group vs. the death group. Factor Improvement group (n = 38) Death group (n = 17) Statistic p value Mechanical ventilation, n (%) χ² = 14.060 300 6 (15.8) 0 (0.0) CRRT, n (%) χ² = 4.125 0.042 No 24 (63.2) 6 (35.3) Yes 13 (36.8) 11 (64.7) Length of ICU Stay (d) 6.05 ± 4.22 7.35 ± 7.56 t = -0.818 0.417 Length of Hospital Stay, (d) 9.92 ± 8.42 7.47 ± 7.53 t = 1.029 0.308 Etiology n (%) χ² = 3.663 0.056 Outdoor heat exposure 11 (28.9) 1 (5.9) Hyperthermic environment 27 (71.1) 16 (94.1) 3.4 Heat Stroke Coagulopathy (HIC) Score Significant differences were observed in both initial and peak HIC scores between the two groups. The median HIC score at admission was significantly higher in the death group than in the improvementgroup (4 vs. 3, P = 0.001). Furthermore, the peak HIC score during hospitalization was also higher in the death group than in the improvementgroup (5 vs. 4, P = 0.024) (Table 4, Fig. 2 ). Table 4 Heat stroke coagulopathy score. 3.5 Univariate Logistic Regression Analysis of Mortality Risk Factors Based on statistical results, laboratory indicators such as initial ST, peak AST, initial ALT, peak ALT, initial DD, peak DD, initial PT, peak PT, initial Scr, peak Scr, initial MYO, peak MYO, initial HIC, peak HIC, PO2/FIO2, and medical interventions like CRRT and vasopressors were selected for univariate logistic regression analysis. The statistical analysis revealed that CRRT, PO2/FIO2, vasopressors, initial HIC score, peak HIC score, peak PT, initial AST, peak AST, initial ALT, peak ALT, peak PT, and peak creatinine levels were significantly elevated in the death group than in the improvementgroup ( p < 0.05). These indicators may have significant clinical implications in predicting the prognosis of EHS. However, no significant differences were observed between the two group in other indicators such as D-dimer, myocardial enzymes, and admission creatinine levels ( p > 0.05). Table 5 Nivariate Logistic regression analysis for risk factors of death in CHS patients Factor B S.E. Waid P OR 95% CI Lower Upper CRRT 1.011 0.6 2.839 0.092 2.747 0.849 8.902 PO2/FIO2 0.021 0.008 6.775 0.009 1.0021 1.005 1.037 NE (µg/(kg.min)) -1.907 0.67 8.098 0.004 0.149 0.04 0.552 HIC (Intial, Score) -0.699 0.257 7.413 0.006 0.497 0.301 0.822 HIC (Peak, Score) -0.817 0.335 5.963 0.015 0.442 0.229 0.851 D-dimer (Initial, mg/L) 0.028 0.019 2.148 0.143 1.028 0.991 1.067 D-dimer (Peak, mg/L) 0.021 0.02 1.0095 0.095 1.021 0.982 1.062 PT (Initial ,S) 0.088 0.046 3.63 0.057 1.092 0.997 1.195 PT (Peak,S) 0.053 0.025 4.437 0.035 1.054 1.004 1.108 AST (Initial,U/L) 0.10 0.004 7.629 0.006 1.01 1.003 1.017 AST (Peak,U/L) 0.004 0.002 4.140 0.042 1.004 1.000 1.007 ALT (Initial ,U/L) 0.011 0.006 3.984 0.046 1.011 1 1.023 ALT (Peak,U/L) 0.004 0.002 3.996 0.046 1.004 1 1.009 Scr (Intial, µmol/L) 0.003 0.003 1.497 0.221 1.003 0.998 1.008 Scr (Peak, µmol/L) 0.005 0.002 4.47 0.034 1 1 1.01 MYO (Initial, µg/L) 0 0 1.239 0.266 1 1 1.001 MYO (Peak, µg/L) 0 0 1.726 0.189 1 1 1.001 CRRT: continuous renal replacement therapy; NE: noradrenaline; HIC: heat stroke coagulopathy score; PT: prothrombin time; AST: aspartate aminotransferase; ALT: alanine transaminase; Scr: serum reatinine; MYO: myohemoglobin. 3.6. Multivariate Logistic Regression Analysis of Risk Factors for Mortality To further identify independent risk factors for mortality in elderly heat stroke patients, variables with statistical significance from the univariate logistic regression analysis were included in the multivariate logistic regression analysis. A backward stepwise regression method was used, with an entry criterion of p 0.10. The final model included the initial HIC score, initial AST value, and peak serum creatinine (Scr) level. The results indicated that the initial HIC score, initial AST value, and peak Scr level are independent risk factors for mortality in elderly heat stroke patients. The ROC curve analysis showed that the initial HIC score, initial AST value, and peak Scr level have better predictive value for mortality (Table 5 , Fig. 3 ). Table 5 Univariate Logistic regression analysis for risk factors of death in CHS patients. Factor B S.E. Waid P OR 95% CI Lower Upper HIC (Intial, Score) 2.896 1.114 6.405 0.011 18.096 1.921 170.433 HIC (Peak, Score) -1.515 0.922 2.700 0.100 0.220 0.036 1.399 AST (Initial,U/L) 0.026 0.009 7.911 0.005 1.027 1.008 1.045 Scr (Peak,U/L) .015 0.006 6.898 0.009 1.015 1.004 1.027 HIC: heat stroke coagulopathy score; AST: aspartate aminotransferase; Scr: serum reatinine. Discussion Heat stroke represents the most severe form of heat-related illness, characterized by extreme hyperthermia and central nervous system dysfunction, with a high risk of mortality and disability [ 18 ]. It has a very high mortality and morbidity rate and is significantly influenced by seasonal and regional factors, particularly in "oven-like" Chinese cities such as Chongqing, Wuhan, and Nanjing [ 19 ]. Elderly individuals are especially vulnerable to heat stroke, with reported mortality rates exceeding 50%, largely due to age-related neuroendocrine dysregulation, impaired thermoregulation, and progressive decline in multi-organ functional reserve [ 20 , 21 ]. This is especially common in elderly individuals with poor health or those with chronic conditions such as cardiovascular disease, diabetes, and hypertension [ 22 ]. Consistent with our findings, the mortality rate in elderly heat stroke patients was 30.9%. Although there was no significant age difference between the two groups, the death group had a higher average age. Additionally, the number of comorbidities in the death group was significantly higher than in the improvement group, suggesting that elderly patients with underlying diseases are at higher risk for poor prognosis. Due to reduced multi-system reserve and chronic disease accumulation, elderly patients are more likely to develop multi-organ dysfunction syndrome under heat stress. The definition of heat stroke proposed in 2002 highlighted that the mechanism leading to multi-organ failure is multifactorial, involving a combination of cytotoxic effects from hyperthermia, coagulopathy, and systemic inflammatory response syndrome [ 23 ]. Organs such as the lungs, kidneys, liver, and coagulation system are particularly vulnerable. In heat stroke patients, the balance between heat production and dissipation is disrupted, leading to an excess of heat. This is further exacerbated by the increase in skin blood flow to promote heat dissipation, resulting in excessive blood storage and redistribution, which reduces gastrointestinal blood flow. This can damage intestinal tight junctions, allowing endotoxins to enter the bloodstream through the intestinal mucosa [ 24 ]. Due to the anatomical features of the portal venous system, these endotoxins first affect the liver, making it a key organ in heat stroke pathophysiology [ 25 ]. Additionally, the coagulopathy mechanism in heat stroke may involve fibrinolysis, manifesting as prolonged prothrombin time (PT), activated partial thromboplastin time (aPTT), increased D-dimer levels, reduced platelet count, and multi-organ dysfunction, reflected by elevated creatinine, creatine kinase, lactate dehydrogenase, and transaminases [ 26 ]. Furthermore, rhabdomyolysis, a hallmark of heat stroke, further exacerbates kidney injury [ 27 ]. In our study, the death group exhibited significantly higher levels of liver, kidney, coagulation, and muscle injury markers on admission and during hospitalization, especially AST, ALT, creatinine, PT, D-dimer, and myoglobin levels. Inflammation plays a key role in the development of MODS in heat stroke. Hyperthermia can disrupt immune system function, triggering systemic inflammation that directly or indirectly damages various cells and further induces systemic coagulopathy, bleeding, and tissue necrosis, with endothelial cells being the primary target of injury [ 28 ]. Our study also found that norepinephrine (NE) doses were significantly higher in the death group, indicating greater instability in circulatory function, which required higher doses of vasopressors for stabilization, a finding that suggests the severity of the systemic inflammatory response and endothelial damage. Moreover, acute respiratory distress syndrome (ARDS) is a common manifestation in heat stroke patients, caused by inflammatory alveolar-capillary leakage, surfactant dysfunction, and neutrophil infiltration [ 29 ]. In our study, the death group had a significantly higher rate of mechanical ventilation and CRRT use, along with poorer oxygenation, highlighting the critical role of respiratory support in the comprehensive treatment of elderly heat stroke patients. However, we found no significant differences in ICU and total hospital length of stay between the two groups, possibly due to the rapid progression and early death in the death group. Notably, we introduced the heat stroke coagulopathy (HIC) score and found it to be significantly associated with patient mortality. The death group had significantly higher HIC scores on admission and during hospitalization compared to the improvement group, suggesting that coagulopathy is not only a consequence of heat stroke but may also be a key factor in its pathogenesis. Heat stroke coagulopathy is a key diagnostic criterion for heat stroke and a major complication leading to heat stroke-related mortality [ 30 , 31 ]. The HIC score, as a tool integrating coagulation indicators, could serve as a useful clinical marker for early risk assessment and prognosis stratification [ 32 ]. Through multivariate logistic regression analysis, we further confirmed that the initial HIC score, initial AST value, and peak serum creatinine (Scr) level are independent risk factors for mortality in elderly heat stroke patients. For example, patients with an HIC score ≥ 4, significantly elevated AST levels, or rapid increases in creatinine should be considered high-risk and treated with early multi-organ support. This study focuses on the elderly, a high-risk group for heat stroke, and systematically explores their clinical features and prognostic factors within the regional climate context (Chongqing). It innovatively applies the HIC score to the prognosis evaluation of elderly heat stroke and clearly establishes its independent association with mortality risk. Additionally, clinical biomarkers such as initial AST values and peak Scr levels, which are easily accessible, were identified as risk factors with high clinical translation potential. However, this study has several limitations. First, the sample size is relatively small. Second, the retrospective design might involve inherent biases. Third, the data were collected from a single geographic region (Chongqing), which may limit the generalizability of the findings. Additionally, the limited data on elderly or very elderly patients may have further biased the results. To address these issues, future large-scale, multi-center, prospective studies are needed to validate these risk factors and explore their associations with treatment response and long-term prognosis. Declarations Funding Not applicable. Ethical statement This study was conducted in accordance with the Declaration of Helsinki. 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COMP G, PUGSLEY P. Heat Stroke Management Updates: A Description of the Development of a Novel In-Emergency Department Cold-Water Immersion Protocol and Guide for Implementation [J]. Ann Emerg Med. 2025;85(1):43–52. CRAMER M N, GAGNON D, LAITANO O, et al. Human temperature regulation under heat stress in health, disease, and injury [J]. Physiol Rev. 2022;102(4):1907–89. BRENNAN M, O’KEEFFE S T, MULKERRIN E C. Dehydration and renal failure in older persons during heatwaves-predictable, hard to identify but preventable? [J]. Age Ageing. 2019;48(5):615–8. SMITH C J, ALEXANDER L M, KENNEY WL. Nonuniform, age-related decrements in regional sweating and skin blood flow [J]. Am J Physiol Regul Integr Comp Physiol. 2013;305(8):R877–85. LEON L R, HELWIG BG. Heat stroke: role of the systemic inflammatory response [J]. Journal of applied physiology (Bethesda, Md: 1985), 2010, 109(6): 1980-8. BOUCHAMA A, KNOCHEL JP. Heat stroke [J]. N Engl J Med. 2002;346(25):1978–88. ZHANG Z, WU X. Heat stroke: pathogenesis, diagnosis, and current treatment [J]. Ageing Res Rev. 2024;100:102409. BOUCHAMA A, ABUYASSIN B, LEHE C, et al. Classic and exertional heatstroke [J]. Nat Reviews Disease Primers. 2022;8(1):8. XIANG C, GAO L, LIU X, et al. Advances in the comprehensive mechanisms, diagnosis, and treatment of heatstroke-induced coagulopathy [J]. Front Cell Dev Biology. 2025;13:1596039. TSUCHIDA T. TSUCHIDA T. Rapidly Progressive Disseminated Intravascular Coagulation (DIC) in Severe Fatal Heatstroke: A Diagnostic Challenge Despite Normal Initial Coagulation Tests [J]. Cureus, 2025, 17(3). IBA T, HELMS J, NAGAOKA I, et al. Sepsis and heatstroke: overlapping and distinct mechanisms of systemic inflammation [J]. Inflamm research: official J Eur Histamine Res Soc [et al]. 2025;74(1):173. LIU J, LI Q, ZOU Z, et al. The pathogenesis and management of heatstroke and heatstroke-induced lung injury [J]. Volume 13. Burns & Trauma; 2025. p. tkae048. MUSTAFA K Y, OMER O. Blood coagulation and fibrinolysis in heat stroke [J]. Br J Haematol. 1985;61(3):517–23. ENDO Y, INOKUCHI R, YAMAMOTO M, et al. Platelet dysfunction in heatstroke-induced coagulopathy: a retrospective observational study [J]. J Crit Care. 2025;85:154982. AL-MASHHADANI S A, GADER A G, AL HARTHI S, S, et al. The coagulopathy of heat stroke: alterations in coagulation and fibrinolysis in heat stroke patients during the pilgrimage (Haj) to Makkah [J]. Blood coagulation fibrinolysis: Int J haemostasis Thromb. 1994;5(5):731–6. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8939854","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":630972423,"identity":"f269cae6-2450-4854-b1c3-83aa71ffe908","order_by":0,"name":"Yu-Fan Ma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBACNvbmAwYf/0jw8DMcPkCcFj6eYwmFMxss5CQbjyUQp0VOIsfgM2dDhbHB4TMGRDqMIcdwM+MOicSZbWc+3njDYCen20BQy7Fi48IzEon9PGc3W85hSDY2O0BIC2PzNuMZbEBbZpzdJs3DcCBxG0EtzAzmv3mAWjbcf/OMSC1sLAbGvG0SxgYHzrARqYWHLcFwxhkJOcmGY8aWcwyI8Iv8/McHDD5U1IGi8uGNNxV2cgS1oAAJHiKjBlkLqTpGwSgYBaNgRAAAC6ZFFf3UDHkAAAAASUVORK5CYII=","orcid":"","institution":"Chongqing Jiulongpo District People's Hospital, Chongqing Medical University Affiliated University City Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yu-Fan","middleName":"","lastName":"Ma","suffix":""},{"id":630972424,"identity":"0b426f64-7560-445f-8f27-8f985e00de66","order_by":1,"name":"Xueshuang Gu","email":"","orcid":"","institution":"Chongqing Jiulongpo District People's Hospital, Chongqing Medical University Affiliated University City 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People's Hospital, Chongqing Medical University Affiliated University City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanlin","middleName":"","lastName":"Xiao","suffix":""},{"id":630972428,"identity":"27ba71c2-07f2-4d1f-8874-1fc5c5c593d6","order_by":5,"name":"Yuan Gong","email":"","orcid":"","institution":"Chongqing Jiulongpo District People's Hospital, Chongqing Medical University Affiliated University City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Gong","suffix":""},{"id":630972429,"identity":"f8c91c24-47be-4860-980d-c5e7ad2d0ba4","order_by":6,"name":"Jia cheng He","email":"","orcid":"","institution":"Chongqing Jiulongpo District People's Hospital, Chongqing Medical University Affiliated University City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jia","middleName":"cheng","lastName":"He","suffix":""},{"id":630972430,"identity":"622c35f1-9415-43f1-b51e-f2997728385f","order_by":7,"name":"Kaijing Xie","email":"","orcid":"","institution":"Chongqing Jiulongpo District People's Hospital, Chongqing Medical University Affiliated University City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kaijing","middleName":"","lastName":"Xie","suffix":""},{"id":630972431,"identity":"581ab47b-82d7-49b3-ab6b-0ff9f129bb3b","order_by":8,"name":"Cao Dan","email":"","orcid":"","institution":"Chongqing Jiulongpo District People's Hospital, Chongqing Medical University Affiliated University City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Cao","middleName":"","lastName":"Dan","suffix":""},{"id":630972432,"identity":"b00c673e-83ce-44b9-8ec4-fdff115b7c13","order_by":9,"name":"Fating Zhou","email":"","orcid":"","institution":"Chongqing Emergency Medical Center, Chongqing University Central Hospital.","correspondingAuthor":false,"prefix":"","firstName":"Fating","middleName":"","lastName":"Zhou","suffix":""},{"id":630972433,"identity":"ab84cafb-a816-443c-b5ec-aec06a0bd734","order_by":10,"name":"Tian Yongyang","email":"","orcid":"","institution":"Second Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Tian","middleName":"","lastName":"Yongyang","suffix":""},{"id":630972434,"identity":"34891eac-1a23-48c1-91d8-6059f830fe37","order_by":11,"name":"Zhang Xiaoyou","email":"","orcid":"","institution":"Chongqing Jiulongpo District People's Hospital, Chongqing Medical University Affiliated University City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhang","middleName":"","lastName":"Xiaoyou","suffix":""},{"id":630972435,"identity":"4937a85d-3d3d-4fe1-9bfc-f309bb383384","order_by":12,"name":"Jing Huidan","email":"","orcid":"","institution":"Chongqing Jiulongpo District People's Hospital, Chongqing Medical University Affiliated University City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Huidan","suffix":""}],"badges":[],"createdAt":"2026-02-22 14:53:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8939854/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8939854/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108391018,"identity":"2d21929d-f848-403d-879a-06804896f055","added_by":"auto","created_at":"2026-05-04 07:03:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":117892,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of classic heat stroke patients screening\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8939854/v1/d40579ebf50adc4cc2c0d92d.png"},{"id":108492765,"identity":"5d20eaf6-9444-47fa-adec-0a47c63a1003","added_by":"auto","created_at":"2026-05-05 09:58:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":140835,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of classic heat stroke patients screening\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8939854/v1/94a9c4d1750dd6f193f06255.png"},{"id":108391020,"identity":"1110a3b9-f908-4acf-9dc4-31abc77d4cda","added_by":"auto","created_at":"2026-05-04 07:03:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":245398,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves for AST Intial, Scr Peak, HIC Intial and combined diagnosis in the Death group\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8939854/v1/fa8b8f3ad3327637d2c8d26a.png"},{"id":108804144,"identity":"eda00214-62f1-4819-9833-5480253d5c5f","added_by":"auto","created_at":"2026-05-08 15:16:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1039466,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8939854/v1/3206ae16-5379-4dc8-8249-1dda400023ee.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical characteristics and Prognostic Factors of Elderly Heat Stroke in Chongqing: A Multicenter Retrospective Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHeat stroke (HS) is a severe and life-threatening condition caused by thermal injury, characterized by central thermoregulatory failure following exposure to high environmental temperatures and/or strenuous physical activity. It results in a rapid elevation of core body temperature, accompanied by hot skin, altered consciousness, and multiple organ dysfunction [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Against the background of global climate change, the incidence of heat stroke has been increasing worldwide [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eElderly heat stroke (EHS) is classified as classic heat stroke (CHS) and is primarily caused by passive exposure to hot and humid environments, leading to an imbalance between heat production and heat dissipation. Compared with younger individuals, elderly patients often present with insidious prodromal symptoms, multiple comorbidities, rapid disease progression, and significantly higher mortality rates [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Age-related physiological decline, including impaired thermoregulation and reduced sweat gland function, combined with chronic diseases such as cardiovascular disease and diabetes, renders elderly individuals particularly vulnerable to heat injury [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious studies have reported that during summer heat waves, the incidence of CHS ranges from 17.6 to 26.5 per 100,000 population, with in-hospital mortality rates of 14%\u0026ndash;65%, and ICU mortality exceeding 60% [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Mortality among elderly patients may exceed 50% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Heat stroke also shows marked seasonal and regional variation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], with especially high risks in hot and humid regions such as Chongqing [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHeat stroke progresses rapidly and is associated with high mortality, which correlates closely with the duration of hyperthermia [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, rapid and effective cooling is the cornerstone of treatment. However, no universally accepted diagnostic criteria for heat stroke currently exist, and diagnosis largely relies on clinical history and presentation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Elderly patients often present with altered mental status, and a core temperature\u0026thinsp;\u0026gt;\u0026thinsp;40\u0026deg;C may be absent, leading to frequent misdiagnosis as stroke, septic shock, or metabolic encephalopathy and consequent delays in treatment. With the accelerating aging population in China, the disease burden of EHS is increasing, yet systematic studies focusing on this population remain limited. Accordingly, early identification of high-risk EHS patients and timely intervention are crucial for improving outcomes. This study aimed to investigate the clinical characteristics and prognostic risk factors of heat stroke in elder patients so as to provide evidence for early diagnosis and precise treatment.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Subjects\u003c/h2\u003e \u003cp\u003eIn this multicenter retrospective study, a total of 55 elderly patients with heat stroke were enrolled from four hospitals in Chongqing between January 2022 and December 2024. This study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the Ethics Committee of Jiulongpo District People's Hospital (Approval No. 202501) and registered with the Chinese Clinical Trial Registry (ChiCTR305494). Due to the retrospective nature of the study, the requirement for informed consent was waived by the ethics committee. Patients were included in the study if they were aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years with a medical history of exposure to high-temperature and/or high-humidity environments or strenuous physical activity plus and presented with at least one of the following yet without known cause: central nervous system dysfunction (e.g., coma, seizures, delirium, or behavioral abnormalities), core body temperature\u0026thinsp;\u0026gt;\u0026thinsp;40\u0026deg;C, multiple organ dysfunction (involving\u0026thinsp;\u0026ge;\u0026thinsp;2 organs such as liver, kidney, skeletal muscle, or gastrointestinal tract), or severe coagulation disorder or disseminated intravascular coagulation (DIC). Patients were excluded if they had malignant hyperthermia, chronic liver disease, and or chronic renal insufficiency or if they had incomplete clinical data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Design\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. monitoring method and timing\u003c/h2\u003e \u003cp\u003eThe body temperature of the patients was measured immediately upon their presentation using infrared thermometer. If hyperthermia was detected, rectal temperature was measured for confirmation, and cooling measures were initiated immediately. Temperature was reassessed every 10 minutes during cooling.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Outcome Measures\u003c/h2\u003e \u003cp\u003eBaseline data included age, sex, body temperature, heat exposure etiology, level of consciousness, comorbidities, AST, ALT, Scr, creatine kinase, myoglobin, PT, D-dimer, oxygenation index, vasopressor dose (converted to norepinephrine equivalents), mechanical ventilation, CRRT, ICU length of stay, total hospital stay, and 28-day mortality.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Grouping and Treatment\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Grouping\u003c/h2\u003e \u003cp\u003ePatients were randomized to either improvement group or a death group according to 28-day outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Treatment\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAll of the enrolled patients received comprehensive treatment, including immediate cooling, fluid resuscitation with sodium-containing solutions, airway protection and oxygen therapy, sedation for seizures or agitation, continuous renal replacement therapy (CRRT) for acute kidney injury when indicated, and stress ulcer prophylaxis with nutritional support. For patients presenting with hyperthermia, cooling was initiated immediately through prompt removal from the hot environment, cold-water immersion or dousing, evaporative cooling with fanning, infusion of ice-cold saline, and the use of cooling blankets. Rapid fluid resuscitation was performed using sodium-containing solutions (e.g., normal saline or Ringer\u0026rsquo;s solution) as the preferred fluids; during the first hour on site, the infusion volume was 30 mL/kg or a total of 1,500\u0026ndash;2,000 mL, with the volume of cold saline used for cooling included in the total fluid balance. Thereafter, fluid infusion rates were adjusted according to clinical responses, such as blood pressure, heart rate, and urine output, while avoiding fluid overload. Airway protection and oxygen therapy were provided as needed, and for most patients with heat stroke requiring airway protection, endotracheal intubation was performed as early as possible. In patients with seizures, anticonvulsant therapy was initiated on site, and sedative agents were administered to maintain adequate sedation; sedation was also provided for agitated patients. For patients with acute kidney injury, CRRT was selected based on the internal milieu status and myoglobin levels. Additionally, all patients received prophylaxis for stress-related ulcers and appropriate nutritional support.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS version 27.0. For continuous variables, normality was first assessed using the Shapiro\u0026ndash;Wilk test. Normally distributed data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and were compared between groups using the independent-samples \u003cem\u003et\u003c/em\u003e test. Non-normally distributed data are presented as the median (Q1, Q3) and were compared using the Wilcoxon rank-sum test. Categorical variables are expressed as frequencies (percentages) and were compared using the χ\u0026sup2; test or Fisher\u0026rsquo;s exact test, as appropriate. To explore risk factors associated with poor outcomes in patients with exertional heat stroke (EHS), univariate logistic regression analyses were first performed to identify variables with statistical significance; these variables were then entered into a multivariate logistic regression model to identify independent risk factors. A backward stepwise regression approach was applied, with criteria for entry set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and for removal at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.10. To further evaluate the predictive performance of each independent risk factor for poor outcomes, receiver operating characteristic (ROC) curves were constructed, and the area under the curve (AUC) with 95% confidence intervals was calculated, along with sensitivity and specificity. All statistical tests were two sided, and a \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 General Characteristics\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, a total of 82 patients with heat stroke were admitted to the ICU during the study period, of whom 62 met the inclusion criteria. Seven patients were excluded due to chronic liver disease (n\u0026thinsp;=\u0026thinsp;2), chronic kidney disease (n\u0026thinsp;=\u0026thinsp;1), or incomplete data (n\u0026thinsp;=\u0026thinsp;4). Ultimately, 55 patients were included in the final analysis, including 38 patients (69.1%) in the improvementgroup and 17 patients (30.9%) in the death group.\u003c/p\u003e \u003cp\u003eThere were no statistically significant differences between the two groups in terms of age, sex, or age stratification (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The improvementgroup included 38 patients (22 males and 16 females) with a mean age of 69\u0026thinsp;\u0026plusmn;\u0026thinsp;10.751 years, whereas the death group comprised 17 patients (11 males and 6 females) with a mean age of 75\u0026thinsp;\u0026plusmn;\u0026thinsp;10.56 years. Regarding comorbidities, 20 patients (52.6%) in the improvementgroup and 14 patients (82.4%) in the death group had at least one comorbidity, with a statistically significant difference between the groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036). Analysis of the number of comorbidities showed that the proportions of patients with one and two comorbidities in the death group were 58.8% and 23.5%, respectively, both higher than those in the improvementgroup (34.2% and 10.5%, respectively); however, the overall distribution of comorbidity counts did not differ significantly between the two groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In addition, there were no significant differences between the groups in initial body temperature, number of comorbidities, or etiological factors (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImprovementgroup(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeath group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStatistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003e(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69\u0026thinsp;\u0026plusmn;\u0026thinsp;10.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u0026thinsp;\u0026plusmn;\u0026thinsp;10.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et=-0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003cp\u003e(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u0026sup2;=0.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(44.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80\u0026ndash;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003e(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u0026sup2;=0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(57.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16(42.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial temperature (℃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u0026sup2;=0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15(41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u0026sup2;=4.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(82.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18(47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of comorbidities (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u0026sup2;=7.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18(47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEtiology\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u0026sup2; = 3.663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutdoor heat exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperthermic environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (94.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Organ Function Assessment\u003c/h2\u003e \u003cp\u003eThe death group exhibited more severe multi-organ dysfunction than the improvementgroup. For liver function, both initial and peak aspartate aminotransferase (AST) levels were significantly higher in the death group [initial: 103 (36, 361) vs. 32 (20.75, 51), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002; peak: 166 (68, 457) vs. 53.5 (35.52, 117.25), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001], and similar increases were observed for initial and peak alanine aminotransferase (ALT) levels. Renal dysfunction was more pronounced in the death group, as reflected by significantly higher initial and peak serum creatinine levels. Coagulation abnormalities were also more severe in the death group, with significantly prolonged initial and peak prothrombin time (PT) and elevated initial and peak D-dimer levels. Regarding rhabdomyolysis, the death group had significantly higher initial and peak myoglobin levels, with the median initial level reaching 1,280 \u0026micro;g/L compared with 688.5 \u0026micro;g/L in the improvementgroup (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024). In terms of circulatory function, the death group required significantly higher doses of norepinephrine [0.9 vs. 0.2 \u0026micro;g/(kg\u0026middot;min), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001]. No significant differences were observed in initial or peak creatine kinase levels between the two groups. Overall, significantly higher levels of AST, ALT, serum creatinine, PT, and D-dimer, as well as higher norepinephrine requirements, were observed in the death group than in the improvementgroup (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInitial and peak organ function assessment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImprove group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeath group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003cp\u003e(Initial,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32(20.75,51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103(36,361)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003cp\u003e(Peak,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.5(35.52,117.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e166(68,457)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003cp\u003e(Initial ,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.5(22,59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87(39,198)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003cp\u003e(Peak,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59(49.25,87.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110(67,256)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScr\u003c/p\u003e \u003cp\u003e(Intial, \u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98(75.75,139.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e182(125,198)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScr\u003c/p\u003e \u003cp\u003e(Peak, \u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112.5(75.75,189)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e222(175,313)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoagulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePT\u003c/p\u003e \u003cp\u003e(Initial, S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.35(13.7,16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.9(15.7,21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePT\u003c/p\u003e \u003cp\u003e(Peak,S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.6(14.23,19.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(17.1,35.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer\u003c/p\u003e \u003cp\u003e(Initial, mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.22(0.78,5.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(4.09,10.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer\u003c/p\u003e \u003cp\u003e(Peak, mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.77(2,5.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(5.21,16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003cp\u003e(Initial, U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e300(76.05,1613.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e635(6.31,1300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003cp\u003e(Peak, U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e514(103.5,1870.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e866(101.27,1688)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMYO\u003c/p\u003e \u003cp\u003e(Initial, \u0026micro;g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e688.5(241,1268.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1280(1000,1829)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMYO\u003c/p\u003e \u003cp\u003e(Peak, \u0026micro;g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1049.5(288.8,1923.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1994(1200,4000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCirculation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNE\u003c/p\u003e \u003cp\u003e(\u0026micro;g/(kg.min))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.2(0,0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9(0.5,1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAST: aspartate aminotransferase; ALT: alanine transaminase; Scr: serum reatinine; PT:prothrombin time; CK:creatine kinase; MYO:myohemoglobin; NE:noradrenaline.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Treatment and Outcomes\u003c/h2\u003e \u003cp\u003eThe use of mechanical ventilation was significantly higher in the death group compared with the improvementgroup (100% vs. 47.4%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, continuous renal replacement therapy (CRRT) was more frequently required in the death group (64.7% vs. 36.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.042). Severe hypoxemia, defined as PaO₂/FiO₂ \u0026le; 200, was significantly more common in the death group than in the improvementgroup (47.1% vs. 21.1%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, no statistically significant differences were observed between the two groups in ICU length of stay or total hospital length of stay (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOutcome variables in the improvement group vs. the death group.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImprovement group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeath group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStatistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical ventilation,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u0026sup2; = 14.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaO₂/FiO₂\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e250.97\u0026thinsp;\u0026plusmn;\u0026thinsp;59.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e205.29\u0026thinsp;\u0026plusmn;\u0026thinsp;38.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;2.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e201\u0026ndash;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (52.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRRT,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u0026sup2; = 4.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of ICU Stay\u003c/p\u003e \u003cp\u003e(d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.05\u0026thinsp;\u0026plusmn;\u0026thinsp;4.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.35\u0026thinsp;\u0026plusmn;\u0026thinsp;7.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et = -0.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of Hospital Stay,\u003c/p\u003e \u003cp\u003e(d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.92\u0026thinsp;\u0026plusmn;\u0026thinsp;8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.47\u0026thinsp;\u0026plusmn;\u0026thinsp;7.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;1.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEtiology\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u0026sup2; = 3.663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutdoor heat exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperthermic environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (94.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Heat Stroke Coagulopathy (HIC) Score\u003c/h2\u003e \u003cp\u003eSignificant differences were observed in both initial and peak HIC scores between the two groups. The median HIC score at admission was significantly higher in the death group than in the improvementgroup (4 vs. 3, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). Furthermore, the peak HIC score during hospitalization was also higher in the death group than in the improvementgroup (5 vs. 4, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024) (Table\u0026nbsp;4, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;4\u003c/p\u003e \u003cp\u003eHeat stroke coagulopathy score.\u003c/p\u003e \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Univariate Logistic Regression Analysis of Mortality Risk Factors\u003c/h2\u003e \u003cp\u003eBased on statistical results, laboratory indicators such as initial ST, peak AST, initial ALT, peak ALT, initial DD, peak DD, initial PT, peak PT, initial Scr, peak Scr, initial MYO, peak MYO, initial HIC, peak HIC, PO2/FIO2, and medical interventions like CRRT and vasopressors were selected for univariate logistic regression analysis.\u003c/p\u003e \u003cp\u003eThe statistical analysis revealed that CRRT, PO2/FIO2, vasopressors, initial HIC score, peak HIC score, peak PT, initial AST, peak AST, initial ALT, peak ALT, peak PT, and peak creatinine levels were significantly elevated in the death group than in the improvementgroup (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These indicators may have significant clinical implications in predicting the prognosis of EHS.\u003c/p\u003e \u003cp\u003eHowever, no significant differences were observed between the two group in other indicators such as D-dimer, myocardial enzymes, and admission creatinine levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNivariate Logistic regression analysis for risk factors of death in CHS patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS.E.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWaid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRRT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8.902\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePO2/FIO2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.0021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNE\u003c/p\u003e \u003cp\u003e(\u0026micro;g/(kg.min))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIC\u003c/p\u003e \u003cp\u003e(Intial, Score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIC\u003c/p\u003e \u003cp\u003e(Peak, Score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.851\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer\u003c/p\u003e \u003cp\u003e(Initial, mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer\u003c/p\u003e \u003cp\u003e(Peak, mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePT\u003c/p\u003e \u003cp\u003e(Initial ,S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePT\u003c/p\u003e \u003cp\u003e(Peak,S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003cp\u003e(Initial,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003cp\u003e(Peak,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003cp\u003e(Initial ,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003cp\u003e(Peak,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScr\u003c/p\u003e \u003cp\u003e(Intial, \u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScr\u003c/p\u003e \u003cp\u003e(Peak, \u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMYO\u003c/p\u003e \u003cp\u003e(Initial, \u0026micro;g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMYO\u003c/p\u003e \u003cp\u003e(Peak, \u0026micro;g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCRRT: continuous renal replacement therapy; NE: noradrenaline; HIC: heat stroke coagulopathy score; PT: prothrombin time; AST: aspartate aminotransferase; ALT: alanine transaminase; Scr: serum reatinine; MYO: myohemoglobin.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Multivariate Logistic Regression Analysis of Risk Factors for Mortality\u003c/h2\u003e \u003cp\u003eTo further identify independent risk factors for mortality in elderly heat stroke patients, variables with statistical significance from the univariate logistic regression analysis were included in the multivariate logistic regression analysis. A backward stepwise regression method was used, with an entry criterion of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and a removal criterion of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.10. The final model included the initial HIC score, initial AST value, and peak serum creatinine (Scr) level. The results indicated that the initial HIC score, initial AST value, and peak Scr level are independent risk factors for mortality in elderly heat stroke patients. The ROC curve analysis showed that the initial HIC score, initial AST value, and peak Scr level have better predictive value for mortality (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate Logistic regression analysis for risk factors of death in CHS patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS.E.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWaid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIC\u003c/p\u003e \u003cp\u003e(Intial, Score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e170.433\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIC\u003c/p\u003e \u003cp\u003e(Peak, Score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003cp\u003e(Initial,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScr\u003c/p\u003e \u003cp\u003e(Peak,U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHIC: heat stroke coagulopathy score; AST: aspartate aminotransferase; Scr: serum reatinine.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHeat stroke represents the most severe form of heat-related illness, characterized by extreme hyperthermia and central nervous system dysfunction, with a high risk of mortality and disability [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. It has a very high mortality and morbidity rate and is significantly influenced by seasonal and regional factors, particularly in \"oven-like\" Chinese cities such as Chongqing, Wuhan, and Nanjing [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Elderly individuals are especially vulnerable to heat stroke, with reported mortality rates exceeding 50%, largely due to age-related neuroendocrine dysregulation, impaired thermoregulation, and progressive decline in multi-organ functional reserve [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This is especially common in elderly individuals with poor health or those with chronic conditions such as cardiovascular disease, diabetes, and hypertension [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Consistent with our findings, the mortality rate in elderly heat stroke patients was 30.9%. Although there was no significant age difference between the two groups, the death group had a higher average age. Additionally, the number of comorbidities in the death group was significantly higher than in the improvement group, suggesting that elderly patients with underlying diseases are at higher risk for poor prognosis. Due to reduced multi-system reserve and chronic disease accumulation, elderly patients are more likely to develop multi-organ dysfunction syndrome under heat stress.\u003c/p\u003e \u003cp\u003eThe definition of heat stroke proposed in 2002 highlighted that the mechanism leading to multi-organ failure is multifactorial, involving a combination of cytotoxic effects from hyperthermia, coagulopathy, and systemic inflammatory response syndrome [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Organs such as the lungs, kidneys, liver, and coagulation system are particularly vulnerable. In heat stroke patients, the balance between heat production and dissipation is disrupted, leading to an excess of heat. This is further exacerbated by the increase in skin blood flow to promote heat dissipation, resulting in excessive blood storage and redistribution, which reduces gastrointestinal blood flow. This can damage intestinal tight junctions, allowing endotoxins to enter the bloodstream through the intestinal mucosa [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Due to the anatomical features of the portal venous system, these endotoxins first affect the liver, making it a key organ in heat stroke pathophysiology [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Additionally, the coagulopathy mechanism in heat stroke may involve fibrinolysis, manifesting as prolonged prothrombin time (PT), activated partial thromboplastin time (aPTT), increased D-dimer levels, reduced platelet count, and multi-organ dysfunction, reflected by elevated creatinine, creatine kinase, lactate dehydrogenase, and transaminases [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Furthermore, rhabdomyolysis, a hallmark of heat stroke, further exacerbates kidney injury [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In our study, the death group exhibited significantly higher levels of liver, kidney, coagulation, and muscle injury markers on admission and during hospitalization, especially AST, ALT, creatinine, PT, D-dimer, and myoglobin levels. Inflammation plays a key role in the development of MODS in heat stroke. Hyperthermia can disrupt immune system function, triggering systemic inflammation that directly or indirectly damages various cells and further induces systemic coagulopathy, bleeding, and tissue necrosis, with endothelial cells being the primary target of injury [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Our study also found that norepinephrine (NE) doses were significantly higher in the death group, indicating greater instability in circulatory function, which required higher doses of vasopressors for stabilization, a finding that suggests the severity of the systemic inflammatory response and endothelial damage.\u003c/p\u003e \u003cp\u003eMoreover, acute respiratory distress syndrome (ARDS) is a common manifestation in heat stroke patients, caused by inflammatory alveolar-capillary leakage, surfactant dysfunction, and neutrophil infiltration [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In our study, the death group had a significantly higher rate of mechanical ventilation and CRRT use, along with poorer oxygenation, highlighting the critical role of respiratory support in the comprehensive treatment of elderly heat stroke patients. However, we found no significant differences in ICU and total hospital length of stay between the two groups, possibly due to the rapid progression and early death in the death group. Notably, we introduced the heat stroke coagulopathy (HIC) score and found it to be significantly associated with patient mortality. The death group had significantly higher HIC scores on admission and during hospitalization compared to the improvement group, suggesting that coagulopathy is not only a consequence of heat stroke but may also be a key factor in its pathogenesis. Heat stroke coagulopathy is a key diagnostic criterion for heat stroke and a major complication leading to heat stroke-related mortality [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The HIC score, as a tool integrating coagulation indicators, could serve as a useful clinical marker for early risk assessment and prognosis stratification [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Through multivariate logistic regression analysis, we further confirmed that the initial HIC score, initial AST value, and peak serum creatinine (Scr) level are independent risk factors for mortality in elderly heat stroke patients. For example, patients with an HIC score\u0026thinsp;\u0026ge;\u0026thinsp;4, significantly elevated AST levels, or rapid increases in creatinine should be considered high-risk and treated with early multi-organ support.\u003c/p\u003e \u003cp\u003eThis study focuses on the elderly, a high-risk group for heat stroke, and systematically explores their clinical features and prognostic factors within the regional climate context (Chongqing). It innovatively applies the HIC score to the prognosis evaluation of elderly heat stroke and clearly establishes its independent association with mortality risk. Additionally, clinical biomarkers such as initial AST values and peak Scr levels, which are easily accessible, were identified as risk factors with high clinical translation potential.\u003c/p\u003e \u003cp\u003eHowever, this study has several limitations. First, the sample size is relatively small. Second, the retrospective design might involve inherent biases. Third, the data were collected from a single geographic region (Chongqing), which may limit the generalizability of the findings. Additionally, the limited data on elderly or very elderly patients may have further biased the results. To address these issues, future large-scale, multi-center, prospective studies are needed to validate these risk factors and explore their associations with treatment response and long-term prognosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the Ethics Committee of Jiulongpo District People\u0026apos;s Hospital (Approval No. 202501) and registered with the Chinese Clinical Trial Registry (ChiCTR305494). Due to the retrospective nature of the study, the requirement for informed consent was waived by the ethics committee.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIBA T, CONNORS J M, LEVI M, et al. Heatstroke-induced coagulopathy: Biomarkers, mechanistic insights, and patient management [J]. EClinicalMedicine. 2022;44:101276.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eROBERTS W O, ARMSTRONG L E, SAWKA M N, et al. ACSM Expert Consensus Statement on Exertional Heat Illness: Recognition, Management, and Return to Activity [J]. Curr Sports Med Rep. 2021;20(9):470\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRomanello M, Napoli CD, Green C, Kennard H, et al. The 2023 report of the Lancet Countdown on health and climate change: the imperative for a health-centred response in a world facing irreversible harms. Lancet. 2023;402(10419):2346\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMCGEEHIN MA. The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States [J]. Environ Health Perspect. 2001;109(Suppl 2):185.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Aring;STR\u0026ouml;M DO. Heat wave impact on morbidity and mortality in the elderly population: a review of recent studies [J]. Maturitas. 2011;69(2):99\u0026ndash;105.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eROBERTS W O, ARMSTRONG L E, SAWKA M N, et al. ACSM expert consensus statement on exertional heat illness: recognition, management, and return to activity [J]. Curr Sports Med Rep. 2021;20(9):470\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eROMANELLO M, NAPOLI C D, GREEN C, et al. The 2023 report of the Lancet Countdown on health and climate change: the imperative for a health-centred response in a world facing irreversible harms [J]. Lancet (London England). 2023;402(10419):2346\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO\u0026rsquo;CONNOR FG. Heat-Related Illnesses [J]. Annals of internal medicine; 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEPSTEIN Y. Heatstroke [J]. N Engl J Med. 2019;380(25):2449\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAL MAHRI S. BOUCHAMA A. Heatstroke [J]. Handbook of clinical neurology, 2018, 157: 531\u0026thinsp;\u0026ndash;\u0026thinsp;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e!!!. INVALID CITATION !!! [8, 13\u0026ndash;15].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBOUCHAMA A, DEHBI M, MOHAMED G, et al. Prognostic factors in heat wave\u0026ndash;related deaths: a meta-analysis [J]. Arch Intern Med. 2007;167(20):2170\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHIJMANS R J, CAMERON S E, PARRA JL, et al. Very high resolution interpolated climate surfaces for global land areas [J]. Int J Climatology: J Royal Meteorological Soc. 2005;25(15):1965\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMISSET B, DE JONGHE B, BASTUJI-GARIN S, et al. Mortality of patients with heatstroke admitted to intensive care units during the 2003 heat wave in France: a national multiple-center risk-factor study [J]. Crit Care Med. 2006;34(4):1087\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHELED Y, RAV-ACHA M, SHANI Y, et al. The golden hour for heatstroke treatment [J]. Mil Med. 2004;169(3):184\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLEON L R BOUCHAMAA. Heat stroke [J]. Compr Physiol. 2015;5(2):611\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBELVAL L N, CASA D J, ADAMS W M, et al. Consensus Statement- Prehospital Care of Exertional Heat Stroke [J]. Prehospital Emerg care. 2018;22(3):392\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCOMP G, PUGSLEY P. Heat Stroke Management Updates: A Description of the Development of a Novel In-Emergency Department Cold-Water Immersion Protocol and Guide for Implementation [J]. Ann Emerg Med. 2025;85(1):43\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCRAMER M N, GAGNON D, LAITANO O, et al. Human temperature regulation under heat stress in health, disease, and injury [J]. Physiol Rev. 2022;102(4):1907\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBRENNAN M, O\u0026rsquo;KEEFFE S T, MULKERRIN E C. Dehydration and renal failure in older persons during heatwaves-predictable, hard to identify but preventable? [J]. Age Ageing. 2019;48(5):615\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSMITH C J, ALEXANDER L M, KENNEY WL. Nonuniform, age-related decrements in regional sweating and skin blood flow [J]. Am J Physiol Regul Integr Comp Physiol. 2013;305(8):R877\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLEON L R, HELWIG BG. Heat stroke: role of the systemic inflammatory response [J]. Journal of applied physiology (Bethesda, Md: 1985), 2010, 109(6): 1980-8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBOUCHAMA A, KNOCHEL JP. Heat stroke [J]. N Engl J Med. 2002;346(25):1978\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZHANG Z, WU X. Heat stroke: pathogenesis, diagnosis, and current treatment [J]. Ageing Res Rev. 2024;100:102409.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBOUCHAMA A, ABUYASSIN B, LEHE C, et al. Classic and exertional heatstroke [J]. Nat Reviews Disease Primers. 2022;8(1):8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXIANG C, GAO L, LIU X, et al. Advances in the comprehensive mechanisms, diagnosis, and treatment of heatstroke-induced coagulopathy [J]. Front Cell Dev Biology. 2025;13:1596039.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTSUCHIDA T. TSUCHIDA T. Rapidly Progressive Disseminated Intravascular Coagulation (DIC) in Severe Fatal Heatstroke: A Diagnostic Challenge Despite Normal Initial Coagulation Tests [J]. Cureus, 2025, 17(3).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIBA T, HELMS J, NAGAOKA I, et al. Sepsis and heatstroke: overlapping and distinct mechanisms of systemic inflammation [J]. Inflamm research: official J Eur Histamine Res Soc [et al]. 2025;74(1):173.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLIU J, LI Q, ZOU Z, et al. The pathogenesis and management of heatstroke and heatstroke-induced lung injury [J]. Volume 13. Burns \u0026amp; Trauma; 2025. p. tkae048.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMUSTAFA K Y, OMER O. Blood coagulation and fibrinolysis in heat stroke [J]. Br J Haematol. 1985;61(3):517\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eENDO Y, INOKUCHI R, YAMAMOTO M, et al. Platelet dysfunction in heatstroke-induced coagulopathy: a retrospective observational study [J]. J Crit Care. 2025;85:154982.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAL-MASHHADANI S A, GADER A G, AL HARTHI S, S, et al. The coagulopathy of heat stroke: alterations in coagulation and fibrinolysis in heat stroke patients during the pilgrimage (Haj) to Makkah [J]. Blood coagulation fibrinolysis: Int J haemostasis Thromb. 1994;5(5):731\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Elderly heat stroke, Clinical characteristics, Chongqing, Multi-organ dysfunction, HIC score","lastPublishedDoi":"10.21203/rs.3.rs-8939854/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8939854/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjective\u003c/p\u003e\n\u003cp\u003eTo retrospectively analyze the clinical characteristics and risk factors of elderly heat stroke (EHS) in the Chongqing area, with the goal of providing evidence for early identification and timely clinical intervention of this condition.\u003c/p\u003e\n\u003cp\u003eMethods\u003c/p\u003e\n\u003cp\u003eIn this multicenter retrospective study, a total of 55 elderly patients with heat stroke from four hospitals in Chongqing, including Jiulongpo District People’s Hospital, Chongqing Emergency Medical Center, Chongqing Liangjiang New Area People’s Hospital, and the University Town Hospital affiliated to Chongqing Medical University were included from January 2022 to December 2024 and randomized to either improvement group or death group based on 28-day clinical outcomes, with clinical characteristics, organ dysfunction, and therapeutic interventions compared between the two groups. Normally distributed continuous variables were expressed as mean ± standard deviation and compared using the independent-samples \u003cem\u003et\u003c/em\u003e-test, whereas non-normally distributed variables were expressed as median (Q1, Q3) and compared using the Wilcoxon rank-sum test. Univariate and multivariate logistic regression analyses were performed to identify risk factors for mortality. Receiver operating characteristic (ROC) curves were used to evaluate sensitivity and specificity. All statistical analyses were two-sided, with \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 considered statistically significant.\u003c/p\u003e\n\u003cp\u003eResults\u003c/p\u003e\n\u003cp\u003eAmong the 55 patients enrolled, 17 (30.9%) died within 28 days and 38 (69.1%) showed clinical improvement. There were no significant differences in age or sex between the two groups. Compared with the improvement group, the patients in the death group exhibited more severe multi-organ dysfunction on admission and significantly higher (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) initial and peak levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), serum creatinine (Scr), prothrombin time (PT), D-dimer, and myoglobin. The median dose of norepinephrine required was also markedly higher in the death group than in the improvement group (0.9 vs. 0.2 μg/kg/min, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). The proportions of mechanical ventilation (100% vs. 47.4%) and continuous renal replacement therapy (CRRT) were significantly higher in the death group than in the improvement group (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Severe hypoxemia (PaO₂/FiO₂ ≤ 200) was more common in the death group than in the improvement group (47.1% vs. 21.1%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003cbr\u003e\nHeat stroke–induced coagulopathy (HIC) scores both at admission (median 4 vs. 3) and at peak were significantly higher in the death group than in the improvement group (median 5 vs. 4, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Univariate logistic regression showed that CRRT, low PaO₂/FiO₂, high vasopressor dose, elevated HIC scores, and increased AST, ALT, PT, and Scr levels were significantly associated with mortality. Multivariate logistic regression identified three independent risk factors for death: high HIC score at admission, elevated initial AST, and high peak Scr. ROC curve analysis demonstrated that the combined predictive value of these three indicators yielded an area under the curve (AUC) of 0.906.\u003c/p\u003e\n\u003cp\u003eConclusions\u003c/p\u003e\n\u003cp\u003eMortality in elderly heat stroke patients is closely associated with early multi-organ dysfunction. A high HIC score at admission, elevated initial AST levels, and increased peak serum creatinine are independent predictors of poor prognosis and may serve as valuable indicators for early risk stratification and clinical intervention.\u003c/p\u003e","manuscriptTitle":"Clinical characteristics and Prognostic Factors of Elderly Heat Stroke in Chongqing: A Multicenter Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 07:03:28","doi":"10.21203/rs.3.rs-8939854/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-21T15:12:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-30T09:37:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-26T07:45:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-26T07:38:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2026-02-22T14:35:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b6724539-e931-40af-b76f-e2702f10a021","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T07:03:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 07:03:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8939854","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8939854","identity":"rs-8939854","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}