Objective To retrospectively analyze the clinical characteristics of heat stroke (HS) and HS-acute kidney injury (AKI), analyze the risk factors leading to death in patients, and provide new ideas for the prevention and treatment of HS. Methods Patients with HS who visited 13 hospitals in Sichuan subtropical monsoon climate and HS high-incidence areas between July 2019 and September 2023 were retrospectively selected. According to whether in-hospital death or AKI occurred, the patients were divided into survival group and death group, AKI group and non-AKI group. According to serum creatinine level, patients in the AKI group were divided into AKI stage 1 group, AKI stage 2 group and AKI stage 3 group. The main clinical manifestations and important clinical data of the patients were analyzed, and the risk factors affecting the death of patients were analyzed by multivariate logistic regression. Results A total of 195 patients with HS and 115 patients with HS-AKI were included. The results of multivariate logistic regression analysis showed that AKI, abnormal coagulation function, nervous system injury, neutrophil/lymphocyte ratio, and D-dimer were independent risk factors for death (P＜0.05). The results of clinical characteristics analysis of HS-AKI showed that the mortality rate of patients with AKI stage 2 and AKI stage 3 was higher (P＜0.05). Conclusions AKI, abnormal coagulation function, nervous system injury, neutrophil/lymphocyte ratio, and D-dimer are independent risk factors for death in HS. Therefore, active treatment of patients with HS combined with AKI, abnormal coagulation function, and nervous system injury in the future will help reduce the risk of death in patients.
Objective To explore the value of quick Sequential Organ Failure Assessment (qSOFA) score and blood markers in differentiating and predicting emergency heat stroke from sepsis, and to construct a rapid differentiation model. Methods A retrospective cohort study was conducted, including heat stroke patients and sepsis patients admitted to the Chongqing Emergency Medical Center between January 2021 and December 2024. The qSOFA score and blood marker indicators at admission were collected, with the “final diagnosis (sepsis or heat stroke) within 48 hours after admission” as the study endpoint. The logistic regression analysis method was selected to screen for independent predictive factors, construct a joint prediction model, and evaluate the discriminant efficacy using the area under the curve (AUC) of the receiver operating characteristic. Results A total of 133 sepsis patients and 66 heat stroke patients were included. The qSOFA score showed differentiation ability in univariate analysis (P=0.002), but had no independent predictive value after adjusting for diabetes, age, and gender (P=0.565). The results of multiple logistic regression analysis showed that procalcitonin (PCT), C-reactive protein (CRP), and monocyte count (MONO) were independent predictive factors (P<0.05). The combined prediction model of PCT, CRP, and MONO (AUC=0.984) showed higher discriminatory efficacy than PCT (AUC=0.809), CRP (AUC=0.886), and MONO (AUC=0.671). Conclusions The prediction model constructed by combining PCT, CRP, and MONO has good efficiency in differentiating sepsis from heat stroke, providing a reliable clinical decision-making tool for early accurate differentiation in the emergency department.