An Updated Subsequent Injury Categorisation Model (SIC-2.0): Data-Driven Categorisation of Subsequent Injuries in Sport
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Accounting for subsequent injuries is critical for sports injury epidemiology. The subsequent injury categorisation (SIC-1.0) model was developed to create a framework for accurate categorisation of subsequent injuries but its operationalisation has been challenging.
The objective of this study was to update the subsequent injury categorisation (SIC-1.0 to SIC-2.0) model to improve its utility and application to sports injury datasets, and to test its applicability to a sports injury dataset.
The SIC-1.0 model was expanded to include two levels of categorisation describing how previous injuries relate to subsequent events. A data-driven classification level was established containing eight discrete injury categories identifiable without clinical input. A sequential classification level that sub-categorised the data-driven categories according to their level of clinical relatedness has 16 distinct subsequent injury types. Manual and automated SIC-2.0 model categorisation were applied to a prospective injury dataset collected for elite rugby sevens players over a 2-year period. Absolute agreement between the two coding methods was assessed.
An automated script for automatic data-driven categorisation and a flowchart for manual coding were developed for the SIC-2.0 model. The SIC-2.0 model was applied to 246 injuries sustained by 55 players (median four injuries, range 1–12), 46 (83.6%) of whom experienced more than one injury. The majority of subsequent injuries (78.7%) were sustained to a different site and were of a different nature. Absolute agreement between the manual coding and automated statistical script category allocation was 100%.
The updated SIC-2.0 model provides a simple flowchart and automated electronic script to allow both an accurate and efficient method of categorising subsequent injury data in sport.
The authors would like to thank Simon Harries, Dr. Angus Bathgate and Katie Ryan for collection of the injury records.
All authors contributed to the original concept. LAT, LVF and MKD designed the SIC-2.0 flowchart and wrote the automated script. LAT performed the manual coding of the injury dataset. All authors contributed to the drafting and final approval of the manuscript. This work was undertaken by LAT as a component of his PhD under the supervision of authors JLC, CFF, MKD and LVF.
Compliance with Ethical Standards
Conflict of interest
Liam Toohey, Michael Drew, Lauren Fortington, Caroline Finch and Jill Cook declare that they have no conflict of interest.
The research was supported by a Grant from the Australian Institute of Sport High Performance Research Fund awarded to Fortington, Drew, Harries and Finch. The funding body had no input to the conduct or reporting of the research project. This work was supported by an Australian Government Research Training Program Scholarship awarded to Liam Toohey for support during his PhD. Prof. Cook is supported by a NHMRC (National Health and Medical Research Council) practitioner fellowship (No. 1058493). The Australian Centre for Research into Injury in Sport and its Prevention (ACRISP) is one of the International Research Centres for Prevention of Injury and Protection of Athlete Health supported by the International Olympic Committee (IOC).
All procedures performed in studies involving human participants were in accordance with the ethical standards of the Human Research Ethics Committee of Federation University Australia (C15-014) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
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