Jennifer M Medina McKeon1, Heather M Bush2, Ashley Reed3, Angela Whittington4, Timothy L Uhl5, Patrick O McKeon5. 1. Department of Rehabilitation Sciences, University of Kentucky, Lexington, KY, USA. Electronic address: jennifer.medina@uky.edu. 2. Department of Biostatistics, University of Kentucky, Lexington, KY, USA. 3. Department of Rehabilitation Sciences, University of Kentucky, Lexington, KY, USA; School of Health Sciences, Kent State University, Kent, OH, USA. 4. Department of Rehabilitation Sciences, University of Kentucky, Lexington, KY, USA; Wando High School, Mount Pleasant, SC, USA. 5. Department of Rehabilitation Sciences, University of Kentucky, Lexington, KY, USA.
Abstract
OBJECTIVES: Although ankle sprains have the highest recurrence rate of any musculoskeletal injury, objective estimates of when an athlete is likely to return-to-play (RTP) are unknown. The purpose was to compare time to return-to-play probability timelines for new and recurrent ankle sprains in interscholastic athletes. DESIGN: Observational. METHODS: Ankle sprain data were collected at seven high schools during the 2007-2008 and 2008-2009 academic years. Ankle sprains were categorized by time lost from participation (same day return, next-day return, 3-day return, 7-day return, 10-day return, >22-day return, no return [censored data]). Time-to-event analyses were used to determine the influence of ankle injury history on return-to-play after an ankle sprain. RESULTS: 204 ankle sprains occurred during 479,668 athlete-exposures, 163 were new (4 censored) and 35 recurrent (1 censored). There was no significant difference (p=0.89) between the time-to-event curves for new and recurrent ankle sprains. The median (inter-quartile rage) time to return-to-play for new sprains (inter-quartile range)=3 days (same day to 7 day return); recurrent sprains=next day return (next day to 7 day return). Noteworthy probabilities [95% CIs] include: same day return (new=25.2[18.7, 31.9], recurrent=17.1[6.6, 30.3]); next-day return (new=43.6[35.3, 52.7], recurrent=51.4[32.5, 67.5]); and 7-day return (new=85.9[73.8, 94.4], recurrent=94.3[47.8, 99.5]). CONCLUSIONS: Previous injury history did not affect time until return-to-play probabilities for ankle sprains. Time until return-to-play analyses that describe the likelihood of return-to-play are useful to clinicians by providing prognostic guidelines and can be used for educating athletes, coaches, and parents about the likely timeframe of being withheld from play.
OBJECTIVES: Although ankle sprains have the highest recurrence rate of any musculoskeletal injury, objective estimates of when an athlete is likely to return-to-play (RTP) are unknown. The purpose was to compare time to return-to-play probability timelines for new and recurrent ankle sprains in interscholastic athletes. DESIGN: Observational. METHODS: Ankle sprain data were collected at seven high schools during the 2007-2008 and 2008-2009 academic years. Ankle sprains were categorized by time lost from participation (same day return, next-day return, 3-day return, 7-day return, 10-day return, >22-day return, no return [censored data]). Time-to-event analyses were used to determine the influence of ankle injury history on return-to-play after an ankle sprain. RESULTS: 204 ankle sprains occurred during 479,668 athlete-exposures, 163 were new (4 censored) and 35 recurrent (1 censored). There was no significant difference (p=0.89) between the time-to-event curves for new and recurrent ankle sprains. The median (inter-quartile rage) time to return-to-play for new sprains (inter-quartile range)=3 days (same day to 7 day return); recurrent sprains=next day return (next day to 7 day return). Noteworthy probabilities [95% CIs] include: same day return (new=25.2[18.7, 31.9], recurrent=17.1[6.6, 30.3]); next-day return (new=43.6[35.3, 52.7], recurrent=51.4[32.5, 67.5]); and 7-day return (new=85.9[73.8, 94.4], recurrent=94.3[47.8, 99.5]). CONCLUSIONS: Previous injury history did not affect time until return-to-play probabilities for ankle sprains. Time until return-to-play analyses that describe the likelihood of return-to-play are useful to clinicians by providing prognostic guidelines and can be used for educating athletes, coaches, and parents about the likely timeframe of being withheld from play.
Authors: Lindsey K Lepley; Patrick O McKeon; Shane G Fitzpatrick; Catherine L Beckemeyer; Timothy L Uhl; Timothy A Butterfield Journal: J Athl Train Date: 2016-11-10 Impact factor: 2.860
Authors: Janet E Simon; Erik A Wikstrom; Dustin R Grooms; Carrie L Docherty; Thomas P Dompier; Zachary Y Kerr Journal: J Athl Train Date: 2018-01-26 Impact factor: 2.860