RT Journal Article
SR Electronic
T1 170 Risk factors for post-concussion subsequent musculoskeletal injuries
JF British Journal of Sports Medicine
JO Br J Sports Med
FD BMJ Publishing Group Ltd and British Association of Sport and Exercise Medicine
SP A66
OP A67
DO 10.1136/bjsports-2021-IOC.156
VO 55
IS Suppl 1
A1 Buckley, Thomas
A1 Oldham, Jessie
A1 Howard, Caroline
A1 Lynall, Robert
A1 Swanik, Buz
A1 Getchell, Nancy
YR 2021
UL http://bjsm.bmj.com/content/55/Suppl_1/A66.3.abstract
AB Background Elevated rates (1.5 to 3.0 times) of musculoskeletal (MSK) injuries in the first year post-concussion have been recently identified in diverse athletic populations; however, clinically feasible risk factors have received limited attention.Objective To identify clinical predictors of post-concussion subsequent musculoskeletal (MSK) injuries.Design Prospective longitudinal.Setting U.S. Intercollegiate Athletics .Patients (or Participants) We enrolled 66 student-athletes (53.0% Female, Age: 20.0 ± 1.1 years old, Height: 1.75 ± 0.11m, Weight: 78.7 ± 20.9kg) from 16 sports who were diagnosed with sports-related concussions.Interventions (or Assessment of Risk Factors) Electronic medical records were tracked for a year following the concussion for diagnosed lower extremity MSK injuries.Main Outcome Measurements All participants completed a multifaceted concussion baseline consisting of 1) 22-item 0–6 self-reported symptom checklist with outcomes including, 1) number of symptoms endorsed, 2) total symptom score, 3) Standard Assessment of Concussion, 4) Balance Error Scoring System, 5) Immediate Post-Concussion Assessment and Cognitive Testing composite scores, 6) clinical reaction time, and 7) the King-Devick test. The concussion participants completed the same exam acutely post-concussion (<48 hours) and binary logistic regression was used to identify predictors of subsequent MSK from the change scores (Acute minus Baseline).Results The participant demographics and injury characteristics (p=0.318,. Exp(B)=1.020) and concussion clinical outcomes (p=0.461, Exp(B)=1.200) did not predict subsequent MSK. Exploratory analysis failed to identify any individual predictive variable from the clinical measures inclduing total symptoms (Δ=9.3, p=0.738), symptoms severity (Δ=21.1, p=0.738), BESS (Δ=-0.6 errors, p=0.474), SAC (Δ=-0.7, p=0.938), Verbal Memory (Δ=1.6, p=0.064), Visual Memory (Δ=5.1, p=0.724), Motor Speed (Δ=0.6, p=0.297), Reaction Time (Δ=0.04 s, p=0.642), CRT (Δ=15.8 ms, p=0.446), King-Devick (Δ=6.9 s, p=0.792).Conclusions None of the standard concussion assessments significantly predicted MSK injury in the year following concussion. Thus, clinicians are not able to utilize common neurological measures or participant demographics to identify those at risk for subsequent LE MSK suggesting injury prevention programs should be implemented for all post-concussion athletes