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Influence of extreme temperatures on out-of-hospital cardiac arrest cases in Hungary: a national time-series analysis

Nagy, Bettina ORCID: https://orcid.org/0000-0002-8334-2385, Pál-Jakab, Ádám ORCID: https://orcid.org/0000-0002-8625-4815, Kiss, Boldizsár ORCID: https://orcid.org/0000-0003-2059-5462, Morvai, Anna, Sipos, Bence, Pápai, György, Csató, Gábor, Orbán, Gábor ORCID: https://orcid.org/0000-0002-5850-9892, Boussoussou, Nora ORCID: https://orcid.org/0000-0003-3819-4982, Merkely, Béla Péter ORCID: https://orcid.org/0000-0001-6514-0723, Sótonyi, Péter ORCID: https://orcid.org/0000-0002-2216-4298, Gelencsér, András ORCID: https://orcid.org/0000-0003-4563-0295, Szilágyi, Brigitta and Zima, Endre István ORCID: https://orcid.org/0000-0001-5132-6009 (2025) Influence of extreme temperatures on out-of-hospital cardiac arrest cases in Hungary: a national time-series analysis. Resuscitation Plus, 2025 . DOI 10.1016/j.resplu.2025.101194

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Official URL: https://doi.org/10.1016/j.resplu.2025.101194


Abstract

Introduction: Out-of-hospital cardiac arrest (OHCA) represents a critical public health challenge, with poor survival. Our objective was to evaluate the association between extreme temperature events and OHCA incidence in Hungary, and to assess the potential influence of additional meteorological factors, including humidity and solar radiation. Methods: We conducted a national time-series analysis of 116,579 adult OHCA cases from November 1, 2018, to December 31, 2023. Using negative binomial regression with clusterrobust standard errors, we estimated associations between daily OHCA counts and extreme temperature events, controlling for day-of-week, seasonality, and long-term trends. "Addedeffect" models isolated risk attributable to sustained events while controlling for underlying non-linear temperature-health relationships through natural cubic splines. Distributed lag nonlinear models (DLNM) characterized exposure-lag-response patterns over 21 days. Results: The temperature-OHCA relationship exhibited a characteristic U-shape with minimum risk at 19.0°C. Sustained cold spells (≥2 days with daily minimum temperature ≤9.2°C, 2nd percentile) were associated with the highest risk increase (IRR 1.189; 95% CI: 1.089-1.299; p<0.001). Sustained heatwaves (≥3 days with daily average temperature ≥27.1°C, 95th percentile) also significantly increased risk (IRR 1.110; 95% CI: 1.032-1.195; p=0.005). Single severe cold days (minimum temperature <-10°C) carried an IRR of 1.143 (95% CI: 1.012-1.291; p=0.031). DLNM analysis revealed distinct temporal patterns: heat effects were acute and transient (peak at days 2-4, resolved by day 7), while cold effects were delayed and persistent (emerging at day 3, sustained beyond 14 days). Conclusion: Prolonged extreme temperatures represent independent cardiovascular hazards beyond isolated daily exposures. The immediate impact of heat and the delayed, persistent effect of cold carry important implications for public health preparedness, emergency service planning, and the timing of clinical advisories.

Item Type:Article
Uncontrolled Keywords:Out-of-hospital cardiac arrest (OHCA), cardiac arrest (CA), cardiopulmonary resuscitation (CPR), temperature, extreme heat, extreme cold, meteorological factors, sudden cardiac arrest (SCA)
Divisions:Institute of Data Analytics and Information Systems
Subjects:Social welfare, insurance, health care
Funders:National Research, Development and Innovation Fund of Hungary, PhD Excellence Program of Semmelweis University, Hungarian Climate Change National Laboratory, National Cardiovascular Laboratory Artificial Intelligence Core Lab
Projects:TKP2021-EGA-02, EFOP3.6.3-VEKOP-16-2017-00009 ("Semmelweis 250+ Excellence Scholarship"), RRF-2.3.1-21-2022-00014, RRF-2.3.1-21-2022-00003, EKÖP-2024-138
DOI:10.1016/j.resplu.2025.101194
ID Code:12417
Deposited By: MTMT SWORD
Deposited On:14 Jan 2026 10:16
Last Modified:14 Jan 2026 10:16

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