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.

Keywords

Cardiac troponin I / Heat stroke / High-temperature / Mortality

Conflict of interest statement

The authors declare no conflict of interest.

Author contributions

Huang R contributed to writing the original draft, software, methodology, formal analysis, data curation, conceptualization, and review and editing. Wu X contributed to writing, review and editing, software, methodology, formal analysis, and data curation. Xiang Y and Jiang J contributed to software, resources, methodology, formal analysis, and data curation. Ai S, Que W, Wu H, and Zhang S contributed to software, methodology, investigation, and data curation. Zhou F contributed to writing, review and editing, visualization, validation, supervision, resources, project administration, data curation, conceptualization, and funding acquisition. Ma Y contributed to writing, review and editing, visualization, validation, supervision, project administration, methodology, and conceptualization.

Funding

This study was supported by an Eagle Talent Project of Chongqing Emergency Medical Center (SYRCCY20230312) and a key project co-organized by the Health Commission and Science & Technology Bureau of Chongqing Province (2024ZDXM024). This study was also supported by the General Project of the Chongqing Province Natural Science Foundation (CSTB2024NSCQ-MSX0873) and Chongqing Key Laboratory of Emergency Medicine (2023-KFKT-03).

Ethical approval of studies and informed consent

The study followed the principles of the Declaration of Helsinki as revised in 2013. This multicenter study was approved, and written informed consent was waived by a steering ethics committee, Ethical Committee of Chongqing Emergency Medical Center (approval number: 2023120701, 2023-11-28), which provided approval for all participating sites.

Acknowledgments

We thank all the patients who participated in this study, as well as all the clinicians and staff involved in data collection and analysis. We thank Editage for the language polishing.

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