Cun Jiali, Zhong Li, Ji Jingjing, Liu Yan, Liu Zhifeng, Wu Ming
Department of Medical Critical Care Medicine, General Hospital of Southern Theatre Command of PLA, Guangzhou, China.
Department of Traditional Chinese Medicine, The First Affiliated Hospital, Guizhou University of Chinese Medicine, Guiyang, China.
Ren Fail. 2025 Dec;47(1):2525462. doi: 10.1080/0886022X.2025.2525462. Epub 2025 Jul 7.
Despite rising incidence, exertional heatstroke (EHS) lacks validated prognostic scoring tools. This study aimed to developed and validated a 90-day prognostic model for EHS patients.
We conducted a retrospective cohort study of patients with EHS. Logistic regression analysis was utilized to identify the risk predictors associated with 90-day mortality. Using the mathematical transformation principle, the regression coefficients of each risk predictor were reassigned to develop a practical predictive scoring system. In this study, the predictive capability of the scoring model was validated ROC curve analysis (AUC-based risk stratification), with model calibration further confirmed by the Hosmer-Lemeshow test.
Among 273 EHS patients in this cohort, 24 (8.8%) experienced 90-day mortality. Logistic regression analysis revealed acute kidney injury (AKI), prolonged activated partial thromboplastin time (APTT), and low fibrinogen as independent risk predictors. A scoring system (0-5 points) was developed by reassigning each predictor according to the logistic regression coefficient: AKI 3 points, prolonged APTT (≥47 s) 1 point, and fibrinogen (<2 g/L) 1 point. Internal validation using 1000 bootstrapping samples demonstrated that the scoring system had a relatively high discriminative ability, with a C-index of 0.90 (95% CI: 0.90-0.93). Using receiver operating characteristic curve analysis, the composite index incorporating these three risk predictors demonstrated a sensitivity of 78.3% and specificity of 89.9% in predicting 90-day mortality (area under the curve: 0.90; 95% confidence interval (CI): 0.81-0.98; < 0.001).
A predictive scoring system based on AKI, APTT, and fibrinogen can help predict the risk of 90-day mortality in patients with EHS.
尽管劳力性热射病（EHS）的发病率不断上升，但缺乏经过验证的预后评分工具。本研究旨在开发并验证一种针对EHS患者的90天预后模型。
我们对EHS患者进行了一项回顾性队列研究。采用逻辑回归分析来确定与90天死亡率相关的风险预测因素。利用数学变换原理，重新分配每个风险预测因素的回归系数，以开发一个实用的预测评分系统。在本研究中，通过ROC曲线分析（基于AUC的风险分层）验证了评分模型的预测能力，并通过Hosmer-Lemeshow检验进一步确认了模型校准。
在该队列的273例EHS患者中，24例（8.8%）经历了90天死亡。逻辑回归分析显示急性肾损伤（AKI）、活化部分凝血活酶时间（APTT）延长和纤维蛋白原水平低是独立的风险预测因素。根据逻辑回归系数重新分配每个预测因素，开发了一个评分系统（0 - 5分）：AKI为3分，APTT延长（≥47秒）为1分，纤维蛋白原（<2 g/L）为1分。使用1000个自抽样样本进行内部验证表明，该评分系统具有相对较高的判别能力，C指数为0.90（95% CI：0.90 - 0.93）。通过受试者工作特征曲线分析，纳入这三个风险预测因素的综合指数在预测90天死亡率方面表现出78.3%的敏感性和89.9%的特异性（曲线下面积：0.90；95%置信区间（CI）：0.81 - 0.98；P < 0.001）。
基于AKI、APTT和纤维蛋白原的预测评分系统有助于预测EHS患者90天死亡风险。
