Predictive value of quick Sequential Organ Failure Assessment score and blood markers for differentiating and predicting emergency heat stroke and sepsis_West China Medical Journal

Authors：

HU Hongling ¹ , ZHOU Fating ¹ , WANG Shu ² , XIA Meng ¹ , LUO Jie ¹ ,  AI Shanmu ¹

1. Department of Emergency, Chongqing Emergency Medical Center, Chongqing University Affiliated Central Hospital, Chongqing 400014, P. R. China;
2. Department of Critical Care Medicine, Chongqing Emergency Medical Center, Chongqing University Affiliated Central Hospital, Chongqing 400014, P. R. China;

Corresponding?author：

AI Shanmu, Email: aishanmu@126.com

Keywords：

Heat stroke; sepsis; procalcitonin; c-reactive protein; monocyte count

DOI：

10.7507/1002-0179.202510030

Video：

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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.

Citation： HU Hongling, ZHOU Fating, WANG Shu, XIA Meng, LUO Jie, AI Shanmu. Predictive value of quick Sequential Organ Failure Assessment score and blood markers for differentiating and predicting emergency heat stroke and sepsis. West China Medical Journal, 2025, 40(11): 1761-1765. doi: 10.7507/1002-0179.202510030 Copy

1.	Khan A, Mubeen M. Heat stroke in the era of global warming: a call for urgent action. Ann Glob Health, 2025, 91(1): 1.
2.	Vicedo-Cabrera AM, Scovronick N, Sera F, et al. The burden of heat-related mortality attributable to recent human-induced climate change. Nat Clim Chang, 2021, 11(6): 492-500.
3.	Deng X, Zhao L, Xiao C, et al. Heatstroke characteristics and meteorological conditions in Hefei, China: thresholds and driving factors. BMC Public Health, 2025, 25(1): 352.
4.	McGeehin MA, Mirabelli M. The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States. Environ Health Perspect, 2001, 109(Suppl 2): 185-189.
5.	Liu SY, Song JC, Mao HD, et al. Expert consensus on the diagnosis and treatment of heat stroke in China. Mil Med Res, 2020, 7(1): 1.
6.	全軍熱射病防治與研究中心, 全軍熱射病防治專家組, 全軍重癥醫學專業委員會. 中國熱射病診斷與治療指南 (2025 版). 解放軍醫學雜志, 2025, 50(4): 367-386.
7.	Lu B, Li S, Zhang L, et al. Heatstroke induces lethal coagulopathy via Z-DNA binding protein 1-mediated pyroptosis. Science, 2022, 376(6599): 1111-1117.
8.	Iba T, Helms J, Levi M, et al. The role of platelets in heat-related illness and heat-induced coagulopathy. Thromb Res, 2023, 231: 152-158.
9.	Singer M, Deutschman CS, Seymour CW, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA, 2016, 315(8): 801-810.
10.	Huang M, Cai S, Su J. The pathogenesis of sepsis and potential therapeutic targets. Int J Mol Sci, 2019, 20(21): 5376.
11.	Ackerman MH, Ahrens T, Kelly J, et al. Sepsis. Crit Care Nurs Clin North Am, 2021, 33(4): 407-418.
12.	徐嘯天, 盧中秋. 熱射病患者血清 CRP、TNF-α、IL-6 指標的檢測及臨床意義分析. 數理醫藥學雜志, 2021, 34(8): 1145-1147.
13.	Bruchim Y, Ginsburg I, Segev G, et al. Serum histones as biomarkers of the severity of heatstroke in dogs. Cell Stress Chaperones, 2017, 22(6): 903-910.
14.	尹小雪, 葉鋼. 勞力性熱射病患者體內炎癥介質表達與臨床預后的相關研究. 中國急救醫學, 2020, 40(8): 759-762.
15.	劉福菁, 顧體軍, 周鑫疊, 等. 中性粒細胞與淋巴細胞比值對重癥中暑患者預后的預測價值. 中華急診醫學雜志, 2023, 32(1): 82-88.
16.	Pierrakos C, Velissaris D, Bisdorff M, et al. Biomarkers of sepsis: time for a reappraisal. Crit Care, 2020, 24(1): 287.
17.	張健峰, 顧曉蕾, 李斌, 等. 血乳酸聯合 qSOFA 評分對早期篩選診斷膿毒癥患者的價值. 臨床急診雜志, 2021, 22(5): 344-347.
18.	汪穎, 王迪芬, 付江泉, 等. SOFA、qSOFA 評分和傳統指標對膿毒癥預后的判斷價值. 中華危重病急救醫學, 2017, 29(8): 700-704.
19.	戴佳文, 吳健, 顧彬, 等. TCC 清單與 qSOFA 評分對嚴重創傷合并膿毒癥的早期診治價值. 中華急診醫學雜志, 2019, 28(2): 185-189.
20.	胡紅玲, 周法庭, 羅杰, 等. 早期 qSOFA 評分聯合血清學指標預測膿毒癥感染源的臨床研究. 臨床急診雜志, 2025, 26(1): 61-65.
21.	Evans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Crit Care Med, 2021, 49(11): e1063-e1143.
22.	Chung H, Lee JH, Jo YH, et al. Circulating monocyte counts and its impact on outcomes in patients with severe sepsis including septic shock. Shock, 2019, 51(4): 423-429.
23.	全軍熱射病防治專家組, 全軍重癥醫學專業委員會, 中國醫藥教育協會血栓與止血危重病專業委員會, 等. 熱射病性凝血病診療中國專家共識. 解放軍醫學雜志, 2023, 48(11): 1237-1247.
24.	Vallés PG, Gil Lorenzo AF, Garcia RD, et al. Toll-like receptor 4 in acute kidney injury. Int J Mol Sci, 2023, 24(2): 1415.

1. Khan A, Mubeen M. Heat stroke in the era of global warming: a call for urgent action. Ann Glob Health, 2025, 91(1): 1.
2. Vicedo-Cabrera AM, Scovronick N, Sera F, et al. The burden of heat-related mortality attributable to recent human-induced climate change. Nat Clim Chang, 2021, 11(6): 492-500.
3. Deng X, Zhao L, Xiao C, et al. Heatstroke characteristics and meteorological conditions in Hefei, China: thresholds and driving factors. BMC Public Health, 2025, 25(1): 352.
4. McGeehin MA, Mirabelli M. The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States. Environ Health Perspect, 2001, 109(Suppl 2): 185-189.
5. Liu SY, Song JC, Mao HD, et al. Expert consensus on the diagnosis and treatment of heat stroke in China. Mil Med Res, 2020, 7(1): 1.
6. 全軍熱射病防治與研究中心, 全軍熱射病防治專家組, 全軍重癥醫學專業委員會. 中國熱射病診斷與治療指南 (2025 版). 解放軍醫學雜志, 2025, 50(4): 367-386.
7. Lu B, Li S, Zhang L, et al. Heatstroke induces lethal coagulopathy via Z-DNA binding protein 1-mediated pyroptosis. Science, 2022, 376(6599): 1111-1117.
8. Iba T, Helms J, Levi M, et al. The role of platelets in heat-related illness and heat-induced coagulopathy. Thromb Res, 2023, 231: 152-158.
9. Singer M, Deutschman CS, Seymour CW, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA, 2016, 315(8): 801-810.
10. Huang M, Cai S, Su J. The pathogenesis of sepsis and potential therapeutic targets. Int J Mol Sci, 2019, 20(21): 5376.
11. Ackerman MH, Ahrens T, Kelly J, et al. Sepsis. Crit Care Nurs Clin North Am, 2021, 33(4): 407-418.
12. 徐嘯天, 盧中秋. 熱射病患者血清 CRP、TNF-α、IL-6 指標的檢測及臨床意義分析. 數理醫藥學雜志, 2021, 34(8): 1145-1147.
13. Bruchim Y, Ginsburg I, Segev G, et al. Serum histones as biomarkers of the severity of heatstroke in dogs. Cell Stress Chaperones, 2017, 22(6): 903-910.
14. 尹小雪, 葉鋼. 勞力性熱射病患者體內炎癥介質表達與臨床預后的相關研究. 中國急救醫學, 2020, 40(8): 759-762.
15. 劉福菁, 顧體軍, 周鑫疊, 等. 中性粒細胞與淋巴細胞比值對重癥中暑患者預后的預測價值. 中華急診醫學雜志, 2023, 32(1): 82-88.
16. Pierrakos C, Velissaris D, Bisdorff M, et al. Biomarkers of sepsis: time for a reappraisal. Crit Care, 2020, 24(1): 287.
17. 張健峰, 顧曉蕾, 李斌, 等. 血乳酸聯合 qSOFA 評分對早期篩選診斷膿毒癥患者的價值. 臨床急診雜志, 2021, 22(5): 344-347.
18. 汪穎, 王迪芬, 付江泉, 等. SOFA、qSOFA 評分和傳統指標對膿毒癥預后的判斷價值. 中華危重病急救醫學, 2017, 29(8): 700-704.
19. 戴佳文, 吳健, 顧彬, 等. TCC 清單與 qSOFA 評分對嚴重創傷合并膿毒癥的早期診治價值. 中華急診醫學雜志, 2019, 28(2): 185-189.
20. 胡紅玲, 周法庭, 羅杰, 等. 早期 qSOFA 評分聯合血清學指標預測膿毒癥感染源的臨床研究. 臨床急診雜志, 2025, 26(1): 61-65.
21. Evans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Crit Care Med, 2021, 49(11): e1063-e1143.
22. Chung H, Lee JH, Jo YH, et al. Circulating monocyte counts and its impact on outcomes in patients with severe sepsis including septic shock. Shock, 2019, 51(4): 423-429.
23. 全軍熱射病防治專家組, 全軍重癥醫學專業委員會, 中國醫藥教育協會血栓與止血危重病專業委員會, 等. 熱射病性凝血病診療中國專家共識. 解放軍醫學雜志, 2023, 48(11): 1237-1247.
24. Vallés PG, Gil Lorenzo AF, Garcia RD, et al. Toll-like receptor 4 in acute kidney injury. Int J Mol Sci, 2023, 24(2): 1415.

West China Medical Journal

Predictive value of quick Sequential Organ Failure Assessment score and blood markers for differentiating and predicting emergency heat stroke and sepsis

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