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Background Increased sports participation, including marathons, necessitates robust medical support due to inherent health risks like cardiac arrest. Effective safety systems for mass-gathering events require early risk prediction, timely medical intervention, and pre-identified transport routes to medical facilities for emergencies. Objective This descriptive epidemiological study aimed to analyze medical incidents at the Yokohama Citizen's Marathon since the introduction of its full marathon in 2015. It also sought to describe trends in the evolving medical support system and their associated outcomes. Methods A retrospective review of medical records from 2015 to 2024 was conducted. The study specifically focused on the incidence of cardiac arrest, heat stroke, muscle cramps, and other related conditions encountered by runners, alongside an examination of the concurrent changes in the marathon's medical support framework over the study period. Results Across 134,946 full marathon participants (147,861 total runners), 4669 medical staff (3.1% ± 0.4% of runners) were deployed. A total of 136 emergency transports (an average annual rate of 0.1% of runners, ranging from 0.05% to 0.2%) occurred, with 27 hospitalizations (an average annual rate of 0.02% of runners, ranging from 0.01% to 0.03%) and three cases of cardiac arrest (an average annual rate of 0.002% of runners, ranging from 0% to 0.004%). The patient presentation ratio (PPR) was 14.76 per 1000 runners annually (ranging from 11.1 to 17.7), while the transport-to-hospital ratio (TTHR) was 0.96 per 100 patient presentations annually (ranging from 0.4 to 2.1). Discussion Annual analysis and subsequent updates to medical protocols were found to be associated with a lower patient presentation ratio and a stable transport-to-hospital ratio when compared to data from previous reports. These findings suggest that systematic improvements in both the planning and response phases of the medical support system contributed to observed reductions in emergency incidents during marathon events. Conclusion The continuous evaluation and iterative adjustment of medical data are crucial for enhancing safety in large-scale marathon events. While a majority of medical incidents involved minor illnesses, the occurrence of life-threatening emergencies, such as cardiac arrest, profoundly underscores the indispensable need for meticulous planning, robust interdisciplinary collaboration among medical teams, and effective communication strategies. Ongoing, data-driven adjustments to medical protocols and response mechanisms, adapted to varying conditions of mass-gathering events, are essential to ensure the continued safety and well-being of participants in citizen marathons.
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http://dx.doi.org/10.7759/cureus.87424 | DOI Listing |
Nutr Clin Pract
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Department of Clinical Nutrition, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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September 2025
Department of Gastroenterology, Austin Health, Heidelberg, Victoria, Australia.
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View Article and Find Full Text PDFBiom J
October 2025
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Accelerated failure time (AFT) models offer an attractive alternative to Cox proportional hazards models. AFT models are collapsible and, unlike hazard ratios in proportional hazards models, the acceleration factor-a key effect measure in AFT models-is collapsible, meaning its value remains unchanged when adjusting for additional covariates. In addition, AFT models provide an intuitive interpretation directly on the survival time scale.
View Article and Find Full Text PDFWounds
August 2025
Department of Nursing, Federal University of Ceará, Ceará, Brazil.
Background: Diabetic foot ulcers (DFUs) are a major clinical challenge, particularly among patients with refractory ulcers, that often lead to severe complications such as infection, amputation, and high mortality. Innovations supported by strong clinical evidence have the potential to improve healing outcomes, enhance quality of life, and reduce the economic burden on individuals and health care systems.
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Knee Surg Relat Res
September 2025
Florida Orthopaedic Institute, Gainesville, FL, 32607, USA.
Background: A clear understanding of minimal clinically important difference (MCID) and substantial clinical benefit (SCB) is essential for effectively implementing patient-reported outcome measurements (PROMs) as a performance measure for total knee arthroplasty (TKA). Since not achieving MCID and SCB may reflect suboptimal surgical benefit, the primary aim of this study was to use machine learning to predict patients who may not achieve the threshold-based outcomes (i.e.
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