Comment on “Independent Predictors of Heat-Related Illness-Induced Acute Respiratory Failure”

We read with great interest the recent article by Kuo et al., titled "Independent Predictors of Heat-Related Illness-Induced acute respiratory failure: A Multicenter Cross-sectional Study," published in the journal of Archives of Academic Emergency Medicine (2025; 13(1): e64. The authors addressed a significant complication of heat-related illness by identifying readily available clinical predictors for acute respiratory failure (ARF), providing crucial insights for emergency physicians in the early stratification of high-risk patients—a topic highly relevant specially considering the ongoing global warming. We propose considerations that may add depth and practical relevance to forthcoming manuscripts addressing heat-related illness–induced ARF. Statistical Considerations The study does not clearly distinguish whether factors such as tachypnea and hyperthermia function as independent or dependent variables. A more precise statistical evaluation examining the association between hypertension history and increased risk of HRI-induced ARF would be valuable. Prospective validation of these predictors across diverse geographical and climatic settings represents a logical next step to confirm generalizability. While the overall sample size (820 patients) is appreciated, the limited number of ARF events (n=29, 3.5%) may constrain statistical power, particularly for analyzing less prevalent variables. Study Period and Data Consistency The extended data collection period (January 2010 to October 2021) and potential confounding factors require consideration. The authors should clarify whether significant changes in HRI care policies occurred at participating centers during this timeframe and how temporal variance was addressed to ensure data consistency. The relatively small number of ARF cases (29 cases, 3.5%) over this extended period underscores the rarity of this complication and merits further explanation. Demographic Considerations The predominantly male study population (80%) raises questions about generalizability. Commentary on whether this gender distribution reflects local HRI exposure patterns and how it might affect model applicability to female patients would be valuable. The exclusion of individuals under 20 years (mean age 50.0 ± 18.4 years) warrants explanation, as this omission might exclude a vulnerable population susceptible to HRI. Diagnostic Criteria The absence of Arterial Blood Gas (ABG) analysis in the diagnostic discussion is notable, as ABG remains essential for confirming ARF and characterizing associated acid-base disorders in severe HRI. Clarification regarding whether ABG was part of routine diagnostic protocols and whether parameters such as pH or bicarbonate were considered as predictors would strengthen the model's pathophysiological foundation and clinical relevance. The biological plausibility of identified predictors—particularly hyperthermia and tachypnea as core physiological responses to severe HRI—suggests their potential transcendence of geographical boundaries. Information regarding plans for external validation studies across different settings would help assess the model's universal applicability .