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International Olympic Committee Consensus Statement: Methods for Recording and Reporting of Epidemiological Data on Injury and Illness in Sports 2020 (Including the STROBE Extension for Sports Injury and Illness Surveillance (STROBE-SIIS))International Olympic Committee Injury and Illness Epidemiology Consensus Group et al. Orthop J Sports Med. 2020.
. 2020 Feb 18;8(2):2325967120902908. doi: 10.1177/2325967120902908. eCollection 2020 Feb. Authors International Olympic Committee Injury and Illness Epidemiology Consensus Group; Roald Bahr, Ben Clarsen, Wayne Derman, Jiri Dvorak, Carolyn A Emery, Caroline F Finch, Martin Hägglund, Astrid Junge, Simon Kemp, Karim M Khan, Stephen W Marshall, Willem Meeuwisse, Margo Mountjoy, John W Orchard, Babette Pluim, Kenneth L Quarrie, Bruce Reider, Martin Schwellnus, Torbjørn Soligard, Keith A Stokes, Toomas Timpka, Evert Verhagen, Abhinav Bindra, Richard Budgett, Lars Engebretsen, Uğur Erdener, Karim ChamariItem in Clipboard
AbstractBackground: Injury and illness surveillance, and epidemiological studies, are fundamental elements of concerted efforts to protect the health of the athlete. To encourage consistency in the definitions and methodology used, and to enable data across studies to be compared, research groups have published 11 sport- or setting-specific consensus statements on sports injury (and, eventually, illnesses) epidemiology to date.
Objective: To further strengthen consistency in data collection, injury definitions, and research reporting through an updated set of recommendations for sports injury and illness studies, including a new Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist extension.
Study design: Consensus statement of the International Olympic Committee (IOC).
Methods: The IOC invited a working group of international experts to review relevant literature and provide recommendations. The procedure included an open online survey, several stages of text drafting and consultation by working groups, and a 3-day consensus meeting in October 2019.
Results: This statement includes recommendations for data collection and research reporting covering key components: defining and classifying health problems, severity of health problems, capturing and reporting athlete exposure, expressing risk, burden of health problems, study population characteristics, and data collection methods. Based on these, we also developed a new reporting guideline as a STROBE extension-the STROBE Sports Injury and Illness Surveillance (STROBE-SIIS).
Conclusion: The IOC encourages ongoing in- and out-of-competition surveillance programs and studies to describe injury and illness trends and patterns, understand their causes, and develop measures to protect the health of the athlete. The implementation of the methods outlined in this statement will advance consistency in data collection and research reporting.
Keywords: STROBE; epidemiologic methods; illness; injuries; surveillance.
© The Author(s) 2020.
Conflict of interest statementOne or more of the authors has declared the following potential conflict of interest or source of funding: B.R. receives payment for duties as Editor-in-Chief of The Orthopaedic Journal of Sports Medicine. AOSSM checks author disclosures against the Open Payments Database (OPD). AOSSM has not conducted an independent investigation on the OPD and disclaims any liability or responsibility relating thereto.
FiguresFigure 1.
Distribution of health problems by…
Figure 1.
Distribution of health problems by consequences (not to scale). Adapted from Clarsen and…
Figure 1.Distribution of health problems by consequences (not to scale). Adapted from Clarsen and Bahr.
Figure 2.
Examples of hypothetical prospectively collected…
Figure 2.
Examples of hypothetical prospectively collected injury/illness data (adapted from Finch and Marshall). “X”…
Figure 2.Examples of hypothetical prospectively collected injury/illness data (adapted from Finch and Marshall). “X” indicates when a period of surveillance is ended because the athlete left, unrelated to health problems, before the end of the study period; this is called censoring.
Figure 3.
Classification tree for subsequent health…
Figure 3.
Classification tree for subsequent health problems (adapted from Hamilton et al). Definitions: (1)…
Figure 3.Classification tree for subsequent health problems (adapted from Hamilton et al). Definitions: (1) index injury (illness) is the first recorded injury (illness), and (2) subsequent injury (illness) is any injury (illness) occurring after the index injury (illness): (a) subsequent injury to a different location than the index injury (subsequent illness involving a different system than the index illness), (b) subsequent injury to the same location but of a different tissue type than the index injury (subsequent illness involving the same system but of a different type/other diagnosis), or (c) subsequent recurrent injury (illness) is a subsequent injury to the same site and of the same type as the index injury (subsequent illness involving the same system and type as the index illness). Third, fourth, or more health problems should be assessed relative to the initial index health problem and all other previous ones (eg, second and third health problems).
Figure 4.
Example of severity scores being…
Figure 4.
Example of severity scores being used to track the severity of 3 “typical”…
Figure 4.Example of severity scores being used to track the severity of 3 “typical” health problems. Each black dot represents the weekly severity score. The area in orange represents a gradual-onset injury (cumulative severity score [sum of weekly scores, as the area under the curve] = 1820), the black area represents a short-duration illness (score = 100), and the dark red area represents an acute medial collateral ligament injury (score = 362).
Figure 5.
Risk matrix based on the…
Figure 5.
Risk matrix based on the duration of time loss illustrating the burden of…
Figure 5.Risk matrix based on the duration of time loss illustrating the burden of match injuries among professional rugby teams in New Zealand between 2005 and 2018 (unpublished data). The darker the yellow, the greater the burden. The curved gray lines represent points with equal burden. The vertical and horizontal error bars represent 95% CIs. See also Table 6, illustrating the same dataset in more detail.
Figure 6.
Risk matrix based on Oslo…
Figure 6.
Risk matrix based on Oslo Sports Trauma Research Center Questionnaire on Health Problems…
Figure 6.Risk matrix based on Oslo Sports Trauma Research Center Questionnaire on Health Problems severity scores illustrating the burden of injuries and illnesses affecting elite Norwegian endurance athletes (unpublished data). Error bars represent 95% CIs.
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