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Caroline F Finch - One of the best experts on this subject based on the ideXlab platform.

  • international olympic committee consensus statement methods for recording and reporting of epidemiological data on Injury and illness in sport 2020 including strobe extension for sport Injury and illness surveillance strobe siis
    British Journal of Sports Medicine, 2020
    Co-Authors: Roald Bahr, Caroline F Finch, Benjamin Clarsen, Astrid Junge, Martin Hagglund, Wayne Derman, Carolyn A Emery, Jiri Dvorak, Simon Kemp, Karim M Khan
    Abstract:

    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-specific or setting-specific consensus statements on Sports Injury (and, eventually, illness) epidemiology to date. Our objective was 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. 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. 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). The IOC encourages ongoing in- and out-of-competition surveillance programmes and studies to describe Injury and illness trends and patterns, understand their causes and develop measures to protect the health of the athlete. Implementation of the methods outlined in this statement will advance consistency in data collection and research reporting.

  • time to event analysis for Sports Injury research part 1 time varying exposures
    British Journal of Sports Medicine, 2019
    Co-Authors: Rasmus Nielsen, Caroline F Finch, Merete Moller, Adam Hulme, Michael Lejbach Bertelsen, Daniel Ramskov, Daniel Theisen, Lauren V Fortington, Mohammad Ali Mansournia
    Abstract:

    Background ‘How much change in training load is too much before Injury is sustained, among different athletes?’ is a key question in Sports medicine and Sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous Injury, biomechanics, sleep/stress) when studying Sports Injury aetiology. Aim To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and Injury-related outcomes. Content Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport Injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport Injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills. Conclusion To increase knowledge about the association between changes in training load and Injury, we encourage Sports Injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective Sports Injury data. This will ensure appropriate interpretation of time-to-event data.

  • time to event analysis for Sports Injury research part 2 time varying outcomes
    British Journal of Sports Medicine, 2019
    Co-Authors: Rasmus Nielsen, Caroline F Finch, Merete Moller, Adam Hulme, Michael Lejbach Bertelsen, Daniel Ramskov, Daniel Theisen, Lauren V Fortington, Mohammad Ali Mansournia
    Abstract:

    Background Time-to-event modelling is underutilised in Sports Injury research. Still, Sports Injury researchers have been encouraged to consider time-to-event analyses as a powerful alternative to other statistical methods. Therefore, it is important to shed light on statistical approaches suitable for analysing training load related key-questions within the Sports Injury domain. Content In the present article, we illuminate: (i) the possibilities of including time-varying outcomes in time-to-event analyses, (ii) how to deal with a situation where different types of Sports injuries are included in the analyses (ie, competing risks), and (iii) how to deal with the situation where multiple subsequent injuries occur in the same athlete. Conclusion Time-to-event analyses can handle time-varying outcomes, competing risk and multiple subsequent injuries. Although powerful, time-to-event has important requirements: researchers are encouraged to carefully consider prior to any data collection that five injuries per exposure state or transition is needed to avoid conducting statistical analyses on time-to-event data leading to biased results. This requirement becomes particularly difficult to accommodate when a stratified analysis is required as the number of variables increases exponentially for each additional strata included. In future Sports Injury research, we need stratified analyses if the target of our research is to respond to the question: ‘how much change in training load is too much before Injury is sustained, among athletes with different characteristics?’ Responding to this question using multiple time-varying exposures (and outcomes) requires millions of injuries. This should not be a barrier for future research, but collaborations across borders to collecting the amount of data needed seems to be an important step forward.

  • Sports biostatistician a critical member of all Sports science and medicine teams for Injury prevention
    British Journal of Sports Medicine, 2018
    Co-Authors: Marti Casals, Caroline F Finch
    Abstract:

    Sports science and medicine need specialists to solve the challenges that arise with Injury data. In the Sports Injury field, it is important to be able to optimise Injury data to quantify Injury occurrences, understand their aetiology and most importantly, prevent them. One of these specialty professions is that of Sports Biostatistician. The aim of this paper is to describe the emergent field of Sports Biostatistics and its relevance to Injury prevention. A number of important issues regarding this profession and the science of Sports Injury prevention are highlighted. There is a clear need for more multidisciplinary teams that incorporate biostatistics, epidemiology and public health in the Sports Injury area.

  • Sports Injury surveillance systems a review of methods and data quality
    Sports Medicine, 2016
    Co-Authors: Christina L Ekegren, Belinda J Gabbe, Caroline F Finch
    Abstract:

    Background and Aims Data from Sports Injury surveillance systems are a prerequisite to the development and evaluation of Injury prevention strategies. This review aimed to identify ongoing Sports Injury surveillance systems and determine whether there are gaps in our understanding of injuries in certain sport settings. A secondary aim was to determine which of the included surveillance systems have evaluated the quality of their data, a key factor in determining their usefulness.

Dawn R Comstock - One of the best experts on this subject based on the ideXlab platform.

John Orchard - One of the best experts on this subject based on the ideXlab platform.

  • sport medicine diagnostic coding system smdcs and the orchard Sports Injury and illness classification system osiics revised 2020 consensus versions
    British Journal of Sports Medicine, 2020
    Co-Authors: John Orchard, Martin Hagglund, Willem H Meeuwisse, Wayne Derman, Torbjorn Soligard, Martin P Schwellnus, Roald Bahr
    Abstract:

    Coding in Sports medicine generally uses Sports-specific coding systems rather than the International Classification of Diseases (ICD), because of superior applicability to the profile of Injury and illness presentations in sport. New categories for coding were agreed on in the ‘International Olympic Committee (IOC) consensus statement: Methods for recording and reporting of epidemiological data on Injury and illness in Sports 2020.’ We explain the process for determining the new categories and update both the Sport Medicine Diagnostic Coding System (SMDCS) and the Orchard Sports Injury and Illness Classification System (OSIICS) with new versions that operationalise the new consensus categories. The author group included members from an expert group attending the IOC consensus conference. The primary authors of the SMDCS (WM) and OSIICS (JO) produced new versions that were then agreed on by the remaining authors using expert consensus methodology. The SMDCS and OSIICS systems have been adjusted and confirmed through a consensus process to align with the IOC consensus statement to facilitate translation between the two systems. Problematic areas for defining body part categories included the groin and ankle regions. For illness codes, in contrast to the ICD, we elected to have a taxonomy of ‘organ system/region’ (eg, cardiovascular and respiratory), followed by an ‘aetiology/pathology’ (eg, environmental, infectious disease and allergy). Companion data files have been produced that provide translations between the coding systems. The similar structure of coding underpinning the OSIICS and SMDCS systems aligns the new versions of these systems with the IOC consensus statement and also facilitates easier translation between the two systems. These coding systems are freely available to the sport and exercise research community.

  • revision uptake and coding issues related to the open access orchard Sports Injury classification system osics versions 8 9 and 10 1
    Open access journal of sports medicine, 2010
    Co-Authors: John Orchard, Katherine Rae, John Brooks, Martin Hagglund, Lluis Til, David Wales, Tim Wood
    Abstract:

    The Orchard Sports Injury Classification System (OSICS) is one of the world’s most commonly used systems for coding Injury diagnoses in Sports Injury surveillance systems. Its major strengths are that it has wide usage, has codes specific to Sports medicine and that it is free to use. Literature searches and stakeholder consultations were made to assess the uptake of OSICS and to develop new versions. OSICS was commonly used in the Sports of football (soccer), Australian football, rugby union, cricket and tennis. It is referenced in international papers in three Sports and used in four commercially available computerised Injury management systems. Suggested Injury categories for the major Sports are presented. New versions OSICS 9 (three digit codes) and OSICS 10.1 (four digit codes) are presented. OSICS is a potentially helpful component of a comprehensive Sports Injury surveillance system, but many other components are required. Choices made in developing these components should ideally be agreed upon by groups of researchers in consensus statements.

  • the orchard Sports Injury classification system osics version 10
    Clinical Journal of Sport Medicine, 2007
    Co-Authors: Katherine Rae, John Orchard
    Abstract:

    Injury classification systems are generally used in Sports medicine (1) to accurately classify diagnoses for summary studies, permitting easy grouping into parent categories for tabulation and (2) to create a database from which cases can be extracted for research on specific injuries. Clarity is most important for the first purpose, whereas diagnostic detail is particularly important for the second. An ideal classification system is versatile and appropriate for all Sports and all data collection scenarios. The Orchard Sports Injury Classification System (OSICS) was developed in 1992 primarily for the first purpose, a specific study examining the incidence of Injury at the elite level of football in Australia. As usage of the OSICS expanded into different Sports, limitations were noted and therefore many revisions have been made. A recent study found the OSICS-8, whilst superior to the International Classification of Diseases Australian Modification (ICD-10-AM) in both speed of use and 3-coder agreement, still achieved a lower level of agreement than expected. The study also revealed weaknesses in the OSICS-8 that needed to be addressed. A recent major revision resulted in the development of the new 4-character OSICS-10. This revision attempts to improve interuser agreement, partly by including more diagnoses encountered in a Sports medicine setting. The OSICS-10 should provide far greater depth in classifications for the benefit of those looking to maintain diagnostic information. It is also structured to easily collapse down into parent classifications for those wanting to preserve basic information only. For those researchers wanting information collected under broader Injury headings, particularly those not using fully computerized systems, the simplicity of the OSICS-8 system may still suffice. Language: en

  • classifying Sports medicine diagnoses a comparison of the international classification of diseases 10 australian modification icd 10 am and the orchard Sports Injury classification system osics 8
    British Journal of Sports Medicine, 2005
    Co-Authors: Katherine Rae, Helena Britt, John Orchard, Caroline F Finch
    Abstract:

    Background: The International classification of diseases 10-Australian modification (ICD-10-AM) and the Orchard Sports Injury classification system (OSICS-8) are two classifications currently being used in Sports Injury research. Objectives: To compare these two systems to determine which was the more reliable and easier to apply in the classification of Injury diagnoses of patients who presented to Sports physicians in private Sports medicine practice. Methods: Ten Sports physicians/Sports physician registrars each coded one of 10 different lists of 30 Sports medicine diagnoses according to both ICD-10-AM and OSICS-8 in random order. The coders noted the time taken to apply each classification system, and allocated an ease of fit score for individual diagnoses into the systems. The 300 diagnoses were each coded twice more by “expert” coders from each system, and these results compared with those of the 10 volunteers. Results: Overall, there was a higher level of agreement between the different coders for OSICS-8 than for ICD-10-AM. On average, it was 23.5 minutes quicker to complete the task with OSICS-8 than with ICD-10-AM. Furthermore, there was also higher concordance between the three coders with OSICS-8. Subjective analysis of the codes assigned indicated reasons for disagreement and showed that, in some instances, even the “expert” coders had difficulties in assigning the most appropriate codes. Conclusions: Based on the results of this study, OSICS-8 appears to be the preferred system for use by inexperienced coders in Sports medicine research. The agreement between coders was, however, lower than expected. It is recommended that changes be made to both OSICS-8 and ICD-10-AM to improve their reliability for use in Sports medicine research.

Thomas P Dompier - One of the best experts on this subject based on the ideXlab platform.

Sarah B. Knowles - One of the best experts on this subject based on the ideXlab platform.