Mortality risk stratification in heat stroke using cardiac troponin I and bedside parameters: a retrospective study
Abstract
Background: This study aimed to characterize fatal heat stroke (HS) and develop a risk-prediction model for early identification of high-risk patients. Methods: Patients with HS were divided into survival and nonsurvival groups based on discharge outcomes. Baseline demographics and laboratory parameters were compared. After univariate logistic regression identified candidate variables ( P < 0.05), stepwise multivariate logistic regression was performed to select independent predictors of mortality for the final model. A combined predictive model was constructed and evaluated using the Hosmer–Lemeshow test and area under the receiver operating characteristic curve (AUC). Differences in AUCs between models were compared using DeLong test. The optimal cutoff value was determined using the Youden index. Internal validation of the final model was performed using the bootstrap method with 1000 resamples. Results: A total of 209 patients with HS were analyzed, including 165 survivors (78.9%). Nonsurvivors were significantly older, had a higher proportion of females, and exhibited elevated respiratory rate, international normalized ratio, hydroxybutyrate dehydrogenase, cardiac troponin I (cTnI), neutrophil-to-lymphocyte ratio, systemic immune-inflammation index (SII), quick Sequential (Sepsis-related) Organ Failure Assessment (qSOFA), and Acute Physiology and Chronic Health Evaluation II scores, along with lower lymphocyte percentage (all P < 0.05). Multivariate logistic regression identified age, cTnI, qSOFA, and SII as independent risk factors for mortality. The combined model demonstrated excellent discriminatory power (AUC = 0.955 vs. age = 0.897; qSOFA = 0.789; cTnI = 0.847; SII = 0.596; DeLong P < 0.05), outperforming all individual predictors. Conclusion: Older age, elevated cTnI, higher qSOFA, and SII scores independently predict mortality in HS patients. The combination of these factors offers superior predictive value. Trial Registration: Chinese Clinical Trial Registry; www.chictr.org.cn; ChiCTR2400079671.
Fields of Study & Subjects
Thermoregulation and physiological responses
Climate Change and Health Impacts
Exercise and Physiological Responses
Publication details
- Journal / source
- Emergency and Critical Care Medicine
- Publisher
- Ovid Technologies (Wolters Kluwer Health)
- Volume
- 6
- Issue
- 2
- Pages
- 110–116
- Publication date
- 21 April 2026
- Language
- EN