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

backgroundThis study aimed to establish an effective nomogram to predict the survival of heat stroke (HS) based on risk factors.

methodsThis was a retrospective, observational multicenter cohort study. We analyzed patients diagnosed with HS, who were treated between May 1 and September 30, 2018 at 15 tertiary hospitals from 11 cities in Northern China.

resultsAmong the 175 patients, 32 patients (18.29%) died before hospital discharge. After the univariate analysis, mechanical ventilation, initial mean arterial pressure <70 mmHg, maximum heart rate, lab results on day 1 (white blood cell count, alanine aminotransferase, creatinine), and Glasgow admission prediction score were included in multivariate analysis. Multivariate Cox regression showed that invasive ventilation, initial mean arterial pressure <70 mmHg (1 mmHg=0.133 kPa), and Glasgow admission prediction score were independent risk factors for HS. The nomogram was established for predicting 7-d and 14-d survival in the training cohort. The nomogram exhibited a concordance index (C-index) of 0.880 (95% confidence interval [95% CI] 0.831-0.930) by bootstrapping validation (B=1,000). Furthermore, the nomogram performed better when predicting 14-d survival, compared to 7-d survival. The prognostic index cut-off value was set at 2.085, according to the operating characteristic curve for overall survival prediction. The model showed good calibration ability in the internal and external validation datasets.

conclusionA novel nomogram, integrated with prognostic factors, was proposed; it was highly predictive of the survival in HS patients.