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Abstract
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OBJECTIVES: Different individuals may make different return to play (RTP) decisions due to different risk assessments or risk tolerances. Our objectives were to determine the feasibility of eliciting reinjury risk assessments with Bayesian methods, and risk tolerance with questionnaires, from clinicians and athletes in a real-world RTP setting.
DESIGN: Feasibility study with a descriptive prospective case-series.
METHODS: We recruited the athlete, sport physician and physiotherapist caring for an athlete ("triplet") within on-going groin and hamstring injury studies. We applied Bayesian methods to elicit estimates for reinjury risk over the next 2 months, based on the available clinical knowledge, and projected activity level. We used a standardized questionnaire to elicit factors affecting risk tolerance.
RESULTS: Although our methods appeared feasible in general, there were important challenges that included language, time availability of practicing clinicians, and general work-flow issues related to embedding our study within an on-going larger study. We did obtain valuable data from more than one person on 10 of the 15 eligible athletes recruited. Despite the limited number of cases, there were clinically meaningful differences in risk estimates in some cases. In one triplet, participants estimated the reinjury risk between 1-10%, 20-50% and 30-40% for the same athlete. The most common factors modifying risk tolerance were "timing and season", "pressure from athlete", and "external pressure".
CONCLUSIONS: Bayesian methods for risk elicitation in clinical sport medicine are feasible, and large differences in both risk estimation and risk tolerance sometimes occur.
Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Language: en |