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Can participants predict where ambulance-requiring cases occur at a half marathon?

Journal article
Authors Finn Nilson
Fredrik Lindberg
Gunnar Palm
Linnea Lundgren
David Rayner
Mats Börjesson
Sofia Thorsson
Amir Khorram-Manesh
Eric Carlström
Published in Scandinavian journal of medicine & science in sports
Volume 28
Issue 12
Pages 2760-2766
ISSN 1600-0838
Publication year 2018
Published at Institute of Clinical Sciences, Department of Surgery
Department of Earth Sciences
Institute of Neuroscience and Physiology
Institute of Health and Care Sciences
Department of Food and Nutrition, and Sport Science
Pages 2760-2766
Language en
Keywords Ambulances, Fatigue, diagnosis, Female, Forecasting, Geography, Humans, Male, Risk Factors, Running
Subject categories Health Sciences


Despite endurance races leading to a substantial number of ambulance-requiring cases (ARC), little is known regarding where they occur, meaning that knowing where to place medical teams, ambulance pick-up points, etc, is difficult. This article investigates whether the location of ARCs can be identified by race participants.Using the world's largest half marathon (Gothenburg half marathon) as a case, 237 runners were asked, post-race, to mark on a map which geographical point of the race was most exhausting. Using the level of agreement tests, these geographical points were then compared with the GPS positions of ARCs.According to the level of agreement tests, the most exhausting positions (MEP), as identified by participants, seem to be highly correlated to the location of ARCs. This study can also show that ambulance-requiring cases seem to be more prevalent towards the end of the race and in uphill sections.By asking participants where they found the race most exhausting it seems possible to identify high-risk places for an ARC. From a practical perspective, using this method could considerably increase the safety of competitors as well as improving the cost-effectiveness of safety interventions at endurance races. Further studies are needed to understand the specific risk factors of the high-risk areas as well as characteristics of collapsed runners.

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