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Updated: Sep 18, 2025
A Preclinical Model of Exertional Heat Stroke in Mice
Published on: July 1, 2021
Predictive Factors and Nomogram for 30-Day Mortality in Heatstroke Patients: A Retrospective Cohort Study
Anxin Li1, Yuchen Zhang2, Xiaoshi Zhang1
1Chongqing University Central Hospital, Chongqing Emergency Medical Centre, School of Medicine, Department of Endocrinology, Chongqing, People's Republic of China.
Objective:
Heatstroke (HS) is a severe condition associated with significant morbidity and mortality. In this study we aimed to identify early risk factors that impacted the 30-day mortality of HS patients and establish a predictive model to assist clinicians in identifying the risk of death.
Methods:
We conducted a retrospective cohort study, analyzing the clinical data of 203 HS patients between May 2016-September 2024. The patients were divided into two groups: those who had died within 30 days of symptom onset; and those who had survived. We analyzed the risk factors affecting 30-day mortality. A nomogram was drawn to visualize the clinical model. We used the receiver operating characteristic (ROC) curve and calibration curve to verify the accuracy of the nomogram. A decision curve analysis was also performed to evaluate the clinical usefulness of the nomogram.
Results:
Within a 30-day period, 57 patients (28.08%) died. The APACHE II score, the ratio of lactate-to-albumin (LAR), and the core temperature at 30 minutes after admission were independent risk factors for death of HS patients at 30 days. The area under the ROC curve (AUC) for predicting mortality based on the APACHE II score was 0.867, with a sensitivity of 96.5% and a specificity of 61.6%. Moreover, the AUC for predicting mortality based on the LAR was 0.874, with a sensitivity of 93.0% and a specificity of 77.4%. The AUC based on the core temperature at 30 minutes after admission was 0.774, with a sensitivity of 70.2% and a specificity of 78.8%. Finally, the AUC for predicting death due to HS using the combination of these three factors was 0.928, with a sensitivity of 82.5% and a specificity of 91.8%. The calibration curve and the decision-curve analysis showed that the new nomogram had better accuracy and potential application value in predicting the prognosis of HS patients.
Conclusion:
A nomogram with these three indicators in combination-APACHE II score, lactate-to-albumin ratio, and core temperature at 30 minutes after admission-can be used to predict 30-day mortality of heatstroke patients.
