Heatstroke Over the Past Decade: Risk Factors, Long-Term Health Consequences, and Preventive Measures
摘要
Heatstroke (HS) encompasses acute multi-organ dysfunction and increases susceptibility to subsequent heat-related conditions, making timely diagnosis and intervention critical.
ObjectiveThis systematic review aimed to identify risk factors and long-term health consequences, evaluate cooling methods for field interventions, and assess the accuracy of predictive technologies.
MethodsA comprehensive search of five major databases (MEDLINE/PubMed, Embase, Web of Science, Scopus, and CINAHL) was conducted in May 2024 for peer-reviewed English studies published between January 2014 and May 2024. Eligibility criteria included populations diagnosed with classic or exertional heatstroke (EHS) and reports on clinical outcomes. Methodological quality was assessed using the JBI critical appraisal tools, and the certainty of the evidence was determined using the GRADE system. Results were synthesized narratively due to study heterogeneity.
ResultsOut of 1346 identified records, 39 studies were included. Risk of Bias (RoB) assessment categorized 66.7% of studies as low RoB, 20.5% as moderate, and 12.8% as low/moderate. High-precision data confirm a bimodal age risk distribution: runners younger than 30 have a 5.5-fold higher incidence of EHS, while classic heatstroke peaks at ≥ 65; at ≥ 80 years, it is 4.45 per 100,000 (moderate certainty). Among comorbidities, neuropsychiatric disorders carried the highest independent risk (aOR 7.69; 95% CI 4.06–14.54; P < 0.01) (high certainty). Survivors face significant chronic risks, with strong associations found for acute myocardial infarction (aHR 7.43) and chronic kidney disease (aHR 4.35) (low certainty due to serious inconsistency/imprecision). Cold-water immersion (CWI) is the definitive gold standard (0.14–0.22 °C/min), achieving cooling rates that are mathematically five times faster than cold IV saline (0.039 °C/min; P < 0.01) (moderate certainty). Emerging machine learning models utilizing wearable sensors achieved a predictive AUC of 0.99, though clinical certainty is low due to small event samples and suspected publication bias.
ConclusionsCWI is the gold standard treatment for rapidly reducing core temperature to prevent permanent organ damage. “Cool first, transport second” should be prioritized, with prevention targeted at young athletes and elderly populations with neuropsychiatric conditions. Future research is needed on predictive models in large clinical cohorts to translate laboratory validation into real-time prevention.