Development and evaluation of a predictive nomogram for survival in heat stroke patients: a retrospective cohort study

Shao, Fang; Shi, Xian; Huo, Shuhua; Liu, Qingyu; Shi, Ji-xue; Kang, Jian; Gong, Peng; Shi, Yan; Wang, Guo-xing; Qin, Lijie; Wang, Fei; Feng, Kai; Chen, Fengying; Yin, Yongjie; Ma, Tao; Li, Yan; Wu, Yang Chang; Chen, Hao; Yu, Chang-xiao; Yang, Song; Gan, Weiqun; Wang, Qianqian; Du, Liu-ye-zi; Zhao, Mingchen; Tang, Zi-ren

doi:10.5847/wjem.j.1920-8642.2022.092

Cited by 7 publications

(9 citation statements)

References 19 publications

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“…Our multicenter study design and externally validated nomogram shared some similarities with the previously published HS nomogram and may offer some advantages. [23] Predictors such as HR and GCS are presented in our nomogram, which is consistent with the validated nomogram of Shao et al [23]. However, incorporating more variables, such as social factors, treatment, and outcome data, may result in higher AUC values for our model.…”

Section: Discussionsupporting

confidence: 87%

Development and validation of a prognostic model of survival for classic heatstroke patients: A multicenter study

Wang

et al. 2023

Preprint

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Background Classic heatstroke (CHS) is a life-threatening illness characterized by extreme hyperthermia, dysfunction of the central nervous system and multiorgan failure. Accurate predictive models are useful in the treatment decision-making process and risk stratification.This study was to develop and externally validate a prediction model of survival for hospitalized patients with CHS. Methods In this retrospective study, we enrolled patients with CHS who were hospitalized from June 2022 to September 2022 at 3 hospitals in Southwest Sichuan (training cohort) and 1 hospital in Central Sichuan (external validation cohort). Prognostic factors were identified utilizing least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis in the training cohort. A predictive model was developed based on identified prognostic factors, and a nomogram was built for visualization. The areas under the receiver operator characteristic (ROC) curves (AUCs) and the calibration curve were utilized to assess the prognostic performance of the model in both the training and external validation cohorts. The Kaplan‒Meier method was used to calculate survival rates. Result A total of 189 patients (median age, 75 [68–81] years) were included. Social isolation, self-care ability, comorbidities, body temperature, heart rate, Glasgow Coma Scale (GCS), procalcitonin (PCT), aspartate aminotransferase (AST) and diarrhea were found to have a significant or near-significant association with worse prognosis among hospitalized CHS patients. The AUCs of the model in the training and validation cohorts were 0.994 (95% [CI], 0.975–0.999) and 0.815 (95% [CI], 0.596–0.956), respectively. The model's prediction and actual observation demonstrated strong concordance on the calibration curve regarding 7-day survival probability. According to K‒M survival plots, there were significant differences in survival between the low-risk and high-risk groups in the training cohort and borderline significant differences in the external validation cohort. Conclusion We designed and externally validated a prognostic prediction nomogram for CHS. This model has promising predictive performance and could be applied in clinical practice for managing patients with CHS.

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Section: Discussionsupporting

confidence: 87%

Development and validation of a prognostic model of survival for classic heatstroke patients: A multicenter study

Wang

et al. 2023

Preprint

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“…Our study was not the rst try to use a nomogram in predicting the mortality of HS patients as a matter of fact .As mentioned earlier, there have been some researches on the independent risk factors and predictive model for death from HS [7][8][9][10]. Zhong L et al [7] indicated that the duration of cooling, heart rate at admission, and SOFA score are independent risk factors for death.…”

Section: Discussionmentioning

confidence: 96%

“…The main subjects of the study were predominantly male (95.2%), which also existed the possibility of selective bias. Shao F et al [9] and Wei D et al [10] constructed an impressive nomogram for predicting survival in patients with HS. Shao F's nomogram was based on white blood cell count, creatine, alanine aminotransferase (ALT), maximum heart rate, invasive ventilation, initial mean arterial pressure and GCS score.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, early identi cation of patients with HS at high risk of death based on early indicators is crucial for clinicians. Currently, there have been some researches on the independent risk factors and predictive model for prognosis of HS [7][8][9][10]. Zhong L et al [7] and Wu X et al [8] were focused on the risk factors ant prediction of mortality from HS, however, their studies only concentrated on male patients.…”

Section: Introduction Page 4/19mentioning

confidence: 99%

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Predictive Factors and Nomogram for 30-Day Mortality in Heat Stroke Patients: A Retrospective Case-Control Study

Li,

Zhang,

Zhang

et al. 2024

Preprint

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Objective This study aimed to identify early risk factors that impacted the 30-day mortality of heat stroke patients and establish a predictive model to assist clinicians in identifying the risk of death. Methods A retrospective case-control study was conducted, analyzing the clinical data of 72 patients with heat stroke admitted to Chongqing Emergency Medical Center between May 2016 and October 2023. The patients were divided into two groups to implement a control study: one comprising individuals who had died within 30 days of symptom onset, and the other consisting of those who had survived. The study analyzed the risk factors affecting 30-day mortality, plotted receiver operating characteristic (ROC) curves to evaluate patient’s mortality, and developed a model to predict the risk of death in heat stroke patients. The calibration curve and decision curve were used to evaluate the accuracy and clinical prediction efficiency of the nomogram. Results Within a 30-day period, 21 patients (29.167%) died. The APACHE II score, the ratio of lactate to albumin (Lac/Alb ratio), the core temperature at 30 minutes after admission were the independent risk factors for 30-day death in heat stroke patients. The area under the ROC curve for predicting mortality based on the APACHE II score was 0.820 (95% CI 0.716–0.924, P < 0.001). The best cut-off value was 29, with a sensitivity of 57.1% and a specificity of 92.2%. Moreover, the area under the ROC curve for predicting mortality based on the Lac/Alb ratio was 0.902 (95% CI 0.830–0.975, P < 0.001). The optimal cut-off value was 0.160, with a sensitivity of 90.5% and a specificity of 88.2%. The area under the ROC curve based on the core temperature at 30 minutes after admission was 0.700 (95% CI 0.544–0.855, P = 0.008). The optimal cut-off value was determined to be 39.5℃, with a sensitivity of 61.9% and a specificity of 80.4%. Finally, the area under the ROC curve for predicting death due to heat stroke using the combination of these three factors was 0.917 (95% CI 0.851–0.983, P < 0.001), with a sensitivity of 76.2% and a specificity of 92.2%. Conclusion The nomogram developed using these three indicators can be used in combination to predict 30-day mortality in heat stroke patients.

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“…[1] Heatstroke (HS) is characterized by elevated core body temperature (over 40.0 °C) and neurological disorders. [2] Therefore, a rapid diagnosis and accurate treatment are key components for a good prognosis.…”

Section: Introductionmentioning

confidence: 99%

Glutamine supplementation attenuates intestinal apoptosis by inducing heat shock protein 70 in heatstroke rats

Du¹,

Xu²,

Xun³

et al. 2023

World Journal of Emergency Medicine

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BACKGROUND: Heatstroke is the most hazardous heat-related illness and has a high fatality rate. We investigated whether glutamine supplementation could have a protective eff ect on heatstroke rats. METHODS:Twenty-five 12-week-old male Wistar rats (weight 305±16 g) were randomly divided into a control group (n=5), heatstroke (HS) group (n=10), and heatstroke+glutamine (HSG) group (n=10). Seven days before heat exposure, glutamine (0.4 g/[kg•d]) was administered to the rats in the HSG group by gavage every day. Three hours after heat exposure, serum samples were collected to detect white blood cells, coagulation indicators, blood biochemical indicators, and inflammatory cytokines in the rats. The small intestine tissue was stained to analyze pathological structural changes and apoptosis. Finally, immunohistochemistry and Western blotting were used to analyze the expression levels of heat shock protein 70 (HSP70). Multiple comparisons were analyzed by using one-way analysis of variance, and the Bonferroni test was conducted for the post hoc comparisons. RESULTS:After heat exposure, the core temperature of the HS group (40.65±0.31 °C) was higher than the criterion of heatstroke, whereas the core temperature of the HSG group (39.45±0.14 °C) was lower than the criterion. Glutamine supplementation restored the increased white blood cells, coagulation indicators, blood biochemical indicators, and inflammatory cytokines that were induced by heatstroke to normal levels. The intestinal mucosa was injured, and the structure of tight junctions was damaged in the HS group; however, the structure of intestinal mucosal epithelial cells was stable in the HSG group. Glutamine supplementation alleviated intestinal apoptosis and up-regulated HSP70 expression.CONCLUSION: Glutamine supplementation may alleviate intestinal apoptosis by inducing the expression of HSP70 and have a protective eff ect on heatstroke rats.

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Development and evaluation of a predictive nomogram for survival in heat stroke patients: a retrospective cohort study

Cited by 7 publications

References 19 publications

Development and validation of a prognostic model of survival for classic heatstroke patients: A multicenter study

Development and validation of a prognostic model of survival for classic heatstroke patients: A multicenter study

Predictive Factors and Nomogram for 30-Day Mortality in Heat Stroke Patients: A Retrospective Case-Control Study

Glutamine supplementation attenuates intestinal apoptosis by inducing heat shock protein 70 in heatstroke rats

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