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Aim This study aimed to experimentally verify the safety and effectiveness of evaporative plus convective cooling used in heat stroke treatment using a doll simulating a patient with heat stroke. Methods Evaporative plus convective cooling was simulated by blowing air through a fan (speed: approximately 1.0 or 2.5 m/s) and using normal (20°C) or slightly warm (40°C) water on a doll whose surface body temperature was set at 40°C. We measured the change in surface body temperature using a surface heater attached to the back of the doll's chest cover and observed aerosol generation (size: ≥5 μm) using a particulate visualization system. Three particle counters were placed to measure the generated particles that were not captured by the particulate visualization system. Results The cooling effect of the 2.5 m/s wind speed was greater than that of the 1.0 m/s wind speed. No particles >0.5 μm were observed, and no aerosol particles were generated. Conclusions Our results thus suggested that wind force has a significant effect, and there was no risk of aerosol‐related viral infection in evaporative plus convective cooling. However, this does not rule out the risk of droplet infection. Heat stroke treatment simulation was conducted using dolls resembling heat stroke patients, and a greater cooling effect was observed with a typical electric fan than with a handheld fan. Because no aerosol was generated from the body surface by evaporation, there was no risk of aerosol‐related viral infection.

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.

Body cooling is recommended for patients with heat stroke and heat exhaustion. However, differences in the outcomes of patients who do or do not receive active cooling therapy have not been determined. The best available evidence supporting active cooling is based on a case series without comparison groups; thus, the effectiveness of this method in improving patient prognoses cannot be appropriately quantified. Therefore, we compared the outcomes of heat stroke patients receiving active cooling with those of patients receiving rehydration-only therapy. This prospective observational multicenter registry-based study of heat stroke and heat exhaustion patients was conducted in Japan from 2010 to 2019. The patients were stratified into the “severe” group or the “mild-to-moderate” group, per clinical findings on admission. After conducting multivariate logistic regression analyses, we compared the prognoses between patients who received “active cooling + rehydration” and patients who received “rehydration only,” with in-hospital death as the endpoint. Sex, age, onset situation (i.e., exertional or non-exertional), core body temperature, liver damage, renal dysfunction, and disseminated intravascular coagulation were considered potential covariates. Among those who received active cooling and rehydration-only therapy, the in-hospital mortality rates were 21.5% and 35.5%, respectively, for severe patients (n = 231) and 3.9% and 5.7%, respectively, for mild-to-moderate patients (n = 578). Rehydration-only therapy was associated with a higher in-hospital mortality in patients with severe heat illness (adjusted odds ratio [aOR], 3.29; 95% confidence interval [CI], 1.21–8.90), whereas the cooling methods were not associated with lower in-hospital mortality in patients with mild-to-moderate heat illness (aOR, 2.22; 95% CI, 0.92–5.84). Active cooling was associated with lower in-hospital mortality only in the severe group. Our results indicated that active cooling should be recommended as an adjunct to rehydration-only therapy for patients with severe heat illness.

Rapid assessment of severity is crucial for timely intervention and improved patient outcomes in heatstroke (HS). However, existing biomarkers are limited in their accuracy and accessibility in ER settings. A prospective pilot study was conducted to assess urinary liver fatty acid-binding protein (L-FABP) levels using a point-of-care testing (POCT) upon HS. Severity was estimated using initial Sequential Organ Failure Assessment (SOFA) scores, and outcomes were measured using modified Rankin Scale (mRS) scores. In 78 severe HS patients, semi-quantitative L-FABP measurements were performed in ER and patients were divided as P-group (positive group, L-FABP ≧ 12.5 ng/mL on POCT) and N-group (negative group: L-FABP < 12.5ng/mL, on POCT). urinary L-FABP concentrations were also measured on admission, with a median concentration of 48.3 ng/mL. The positive correlation was observed between urinary L-FABP concentration and pulse rate ( r  = 0.300, P  < 0.01) and lactate ( r  = 0.259, P  < 0.01). The POCT of L-FABP showed promise in predicting severity, as indicated by higher concentrations in patients with higher initial SOFA scores. Furthermore, the comparison between semi-quantitative POCT measurements and urine concentrations of L-FABP measured by enzyme-linked immunosorbent assay (ELISA) revealed significant differences among three POCT groups (POC Range < 12.5 ng/ml, 12.6–100 ng/ml, and 55 > 100 ng/ml, P  = 0.001). Additionally, patients in the POCT positive group had significantly worse outcomes at discharge compared to the negative group, although this difference diminished over time. The study demonstrates the feasibility and potential utility of POCT for initial L-FABP in estimating severity in HS patients. This rapid and accessible testing method may aid in early field triage and intervention, ultimately improving patient outcomes in the management of HS.

Background The 5A score including five components “Age, Activities of daily living, Arrest, Acidemia and Albumin” was developed as an easy-to-use screening tool for predicting in-hospital mortality among patients with accidental hypothermia. However, the external validity of the 5A score has not yet been evaluated. We aimed to perform an external validation of the 5A score model. Method This secondary analysis of the multicenter, prospective cohort Japanese Association for Acute Medicine-Hypothermia Study (2018–2019), which was conducted at 87 and 89 institutions throughout Japan, collected data from December 2018 to February 2019 and from December 2019 to February 2020. Adult accidental hypothermia patients whose body temperature was 35 °C or less were included in this analysis. The probability of in-hospital mortality was calculated using a logistic regression model of the 5A score. The albumin was not recorded in this database; thus, it was imputed by estimation. Predictions were compared with actual observations to evaluate the calibration of the model. Furthermore, decision-curve analysis was used to evaluate the clinical usefulness. Results Of the 1363 patients registered in the database, data of 1139 accidental hypothermia patients were included for analysis. The median [interquartile range] age was 79 [68–87] years, and there were 625 men (54.9%) in the study cohort. The predicted probability and actual observation by risk groups produced the following results: low 7% (5.4–8.6), mild 19.1% (17.4–20.8), moderate 33.2% (29.9–36.5), and high 61.9% (55.9–67.9) predicted risks, and the low 12.4% (60/483), mild 17.7% (59/334), moderate 32.6% (63/193), and high 69% (89/129) observed mortality. These results indicated that the model was well calibrated. Decision-curve analysis visually indicated the clinical utility of the 5A score model. Conclusion This study indicated that the 5A score model using estimated albumin value has external validity in a completely different dataset from that used for the 5A model development. The 5A score is potentially helpful to predict the mortality risk and may be one of the valuable information for discussing the treatment strategy with patients and their family members.

Heatstroke is a life-threatening event that affects people worldwide. Currently, there are no established tools to predict the outcomes of heatstroke. Although the Sequential Organ Failure Assessment (SOFA) score is a promising tool for judging the severity of critically ill patients. Therefore, in this study, we investigated whether the SOFA score could predict the outcome of patients hospitalized with severe heatstroke, including the classical and exertional types, by using data from a Japanese nationwide multicenter observational registry. We performed retrospective subanalyses of the Japanese Association for Acute Medicine heatstroke registry, 2019. Adults with a SOFA score ≥ 1 hospitalized for heatstroke were analyzed. We analyzed data for 225 patients. Univariate and multivariable analyses showed a significant difference in the SOFA score between non-survivors and survivors in classical and exertional heatstroke cases. The area under the receiver operating characteristic curve were 0.863 (classical) and 0.979 (exertional). The sensitivity and specificity of SOFA scores were 50.0% and 97.5% (classical), 66.7% and 97.5% (exertional), respectively, at a cutoff of 12.5, and 35.0% and 98.8% (classical), 33.3% and 100.0% (exertional), respectively, at a cutoff of 13.5. This study revealed that the SOFA score may predict mortality in patients with heatstroke and might be useful for assessing prognosis.

Aim Heat‐related illness is common, but its epidemiology and pathological mechanism remain unclear. The aim of this study was to report current clinical characteristics, prognostic factors, and outcomes of heat‐related illness in Japan. Methods We undertook a prospective multicenter observational study in Japan. Only hospitalized patients with heat‐related illness were enrolled from 1 July to 30 September 2017 and 1 July to 30 September 2018. Results A total of 763 patients were enrolled in the study. Median age was 68 years (interquartile range, 49–82 years) and median body temperature on admission was 38.2°C (interquartile range, 36.8–39.8°C). Non‐exertional cause was 56.9% and exertional cause was 40.0%. The hospital mortality was 4.6%. The median Japanese Association for Acute Medicine disseminated intravascular coagulation (JAAM DIC), Sequential Organ Failure Assessment (SOFA), and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores on admission were 1 (0–2), 4 (2–6), and 13 (8–22), respectively. To predict hospital mortality, areas under the receiver operating characteristic curves were 0.776 (JAAM DIC score), 0.825 (SOFA), and 0.878 (APACHE II). There were 632 cases defined as heatstroke by JAAM heat‐related illness criteria, 73 cases diagnosed as having DIC. A total of 16.6% patients had poor neurological outcome (modified Rankin Scale ≥ 4) at hospital discharge. In the multivariate analysis, Glasgow Coma Scale and platelets were independent predictors of mortality. Type of heatstroke, Glasgow Coma Scale, and platelets were independent predictors of poor neurological outcome. Body temperature was not associated with mortality or poor neurological outcome. Conclusions In this study, hospital mortality of heat‐related illness was <5%, one‐sixth of the patients had poor neurological outcome. The APACHE II, SOFA, and JAAM DIC scores predicted hospital mortality. Body temperature was not associated with mortality or poor neurological outcome. Receiver operating characteristic curves of the Acute Physiology and Chronic Health Evaluation II, Sequential Organ Failure Assessment, and Japanese Association for Acute Medicine disseminated intravascular coagulation scores for predicting hospital mortality in cases of heat‐related illness in Japan.

In this study, we aimed to develop and validate a machine learning-based mortality prediction model for hospitalized heat-related illness patients. After 2393 hospitalized patients were extracted from a multicentered heat-related illness registry in Japan, subjects were divided into the training set for development (n = 1516, data from 2014, 2017–2019) and the test set (n = 877, data from 2020) for validation. Twenty-four variables including characteristics of patients, vital signs, and laboratory test data at hospital arrival were trained as predictor features for machine learning. The outcome was death during hospital stay. In validation, the developed machine learning models (logistic regression, support vector machine, random forest, XGBoost) demonstrated favorable performance for outcome prediction with significantly increased values of the area under the precision-recall curve (AUPR) of 0.415 [95% confidence interval (CI) 0.336–0.494], 0.395 [CI 0.318–0.472], 0.426 [CI 0.346–0.506], and 0.528 [CI 0.442–0.614], respectively, compared to that of the conventional acute physiology and chronic health evaluation (APACHE)-II score of 0.287 [CI 0.222–0.351] as a reference standard. The area under the receiver operating characteristic curve (AUROC) values were also high over 0.92 in all models, although there were no statistical differences compared to APACHE-II. This is the first demonstration of the potential of machine learning-based mortality prediction models for heat-related illnesses.

Recently, a letter to the editor was published to comment on the 5A score which is the prediction model for accidental hypothermia patients comparing the HOPE score. In this letter, we responded to the comments to clarify the difference between the 5A score and the HOPE score.

Background Heat-related illnesses are a serious public health concern and are exacerbated by global warming. Wet-Bulb Globe Temperature (WBGT) is widely used as a heat stress indicator, but its clinical impact remains unclear. This study aimed to investigate the association between hourly variations in WBGT and the incidence of hospitalizations for heat-related illness in Japan using a nationwide database. By incorporating individual-level clinical data and performing stratified analyses, we sought to provide a more granular understanding of how heat exposure affects the risk of heat-related illness requiring hospitalization. Methods We conducted a time-stratified, case-crossover study using data collected from July to September in 2020 and 2021 in the Heatstroke STUDY registry. The inclusion criteria were patients registered in the Heatstroke STUDY registry, specifically hospitalized patients with heat-related illness who were transported to participating hospitals during the study period. Hourly WBGT values were assigned based on the nearest monitoring station to each hospital. Conditional logistic regression and distributed lag models were used to estimate associations between WBGT and the risk of hospitalization. Results A total of 1,653 heat-related illness hospitalizations were analyzed. The mean patient age was 67.9 years; 67.6% were male. Each 1 °C increase in WBGT at onset (hospital arrival) was associated with a significantly increased risk of hospitalization (OR 1.10, 95% CI: 1.05–1.15). The cumulative effect over the prior six hours was also significant (OR 1.56, 95% CI: 1.50–1.62). Compared with WBGT < 25 °C, adjusted ORs were 3.39 (25–27 °C), 8.81 (28–30 °C), and 22.10 (≥ 31 °C). Stratified analyses suggested stronger associations among several subgroups; however, only patients with mental disorders showed statistically significant effect modification, whereas elevated WBGT posed a risk across all groups. Conclusions Higher WBGT levels were associated with an increased risk of heat-related hospitalization. Although the effect appeared greater in some subgroups, only patients with mental disorders demonstrated statistically significant effect modification, suggesting elevated WBGT confers risk broadly.