A prehospital risk assessment tool predicts clinical outcomes in hospitalized patients with heat-related illness: a Japanese nationwide prospective observational study

Abstract

We previously developed a risk assessment tool to predict outcomes after heat-related illness (J-ERATO score), which consists of six binary prehospital vital signs. We aimed to evaluate the ability of the score to predict clinical outcomes for hospitalized patients with heat-related illnesses. In a nationwide, prospective, observational study, adult patients hospitalized for heat-related illnesses were registered. A binary logistic regression model and receiver operating characteristic (ROC) curve analysis were used to assess the relationship between the J-ERATO and survival at hospital discharge as a primary outcome. Among eligible patients, 1244 (93.0%) survived to hospital discharge. Multivariable logistic regression analysis revealed that the J-ERATO was an independent predictor for survival to discharge (adjusted odds ratio [OR] 0.47; 95% confidence interval [CI] 0.37-0.59) and occurrence of disseminated intravascular coagulation (DIC) on day 1 (adjusted OR 2.07; 95% CI 1.73-2.49). ROC analyses revealed an optimal J-ERATO cut-off of 5 for prediction of mortality at discharge (area under the curve [AUC] 0.742; 95% CI 0.691-0.787) and DIC development on day 1 (AUC 0.723; 95% CI 0.684-0.758). The J-ERATO obtained before transportation could be helpful in predicting the severity and mortality of hospitalized patients with heat-related illnesses.

Figure 1

Patient flowchart. CA, cardiac arrest.

Figure 2

The area under the receiver operating characteristic curve of the J-ERATO score to predict mortality after heat-related illness. (A, left) The J-ERATO score cut-off of 5 points provided optimal sensitivity and specificity to predict mortality at discharge (AUC [95%CI], 0.742 [0.691–0.787]; sensitivity, 74.2% [64.5–82.0]; specificity, 64.4% [61.7–67.0]; PPV, 13.5% [10.8–16.7]; NPV, 97.1% [95.7–98.0]; positive likelihood ratio, 2.1 [1.8–2.4]; negative likelihood ratio, 0.4 [0.3–0.6]). (A, right) Calibration plot. Left: X-axis: predicted probability, Y-axis: observed probability. AUC, the area under the receiver operating characteristic curve; CI, confidence interval; DIC, disseminated intravascular coagulation; PPV, positive predictive values; NPV, negative predictive values.

Figure 3

The area under the receiver operating characteristic curve of the J-ERATO score to predict the presence of DIC on day 1. The J-ERATO score cut-off of 5 points provided optimal sensitivity and specificity to predict the presence of DIC on day 1 (AUC [95%CI], 0.723 [0.684–0.758]; sensitivity, 70.1% [63.1–76.3]; specificity, 64.0% [60.2–67.6]; PPV, 35.8% [31.1–40.9]; NPV, 88.2% [84.9–90.8]; positive likelihood ratio, 1.9 [1.7–2.2]; negative likelihood ratio,0.5 [0.4–0.6]). AUC, the area under the receiver operating characteristic curve; CI, confidence interval; DIC, disseminated intravascular coagulation; PPV, positive predictive values; NPV, negative predictive values.

Figure 4

Boxplots displaying the association between the J-ERATO and SOFA scores on the first day after hospital admission. In total, 937 patients were included in the analysis. The numbers of patients in the J-ERATO score groups of 0, 1, 2, 3, 4, 5, and 6 were 19, 75, 97, 140, 224, 302, and 80, respectively. A significant linear trend was observed between the J-ERATO and SOFA scores on day 1 (Spearman’s rank correlation coefficient [r_S] = 0.418, P < 0.0001). J-ERATO, early risk assessment tool for detecting clinical outcomes in patients with heat-related illness; SOFA: Sequential Organ Failure Assessment.