IMPORTANCE Recovery after concussion varies, with adolescents taking longer (approximately 30 days) than adults. Many factors have been reported to influence recovery, including preinjury factors, perceptions about recovery, comorbid conditions, and sex. However, 1 factor that may play a role in recovery but has received little attention from researchers is the timeliness of clinical evaluation and care. OBJECTIVE To investigate the association of time since injury with initiation of clinical care on recovery time following concussion. DESIGN, SETTING, AND PARTICIPANTS This retrospective, cross-sectional study was conducted in a sports medicine clinic between August 2016 and March 2018. Eligible participants were aged 12 to 22 years and had a diagnosed, symptomatic concussion; patients were excluded if recovery data were incomplete. Participants were divided into 2 groups: those seen within 7 days of the injury (early) vs between 8 and 20 days of the injury (late). Data were analyzed between June 2019 and August 2019. EXPOSURES Time from injury (concussion) to initiation of clinical care. MAIN OUTCOMES AND MEASURES Recovery time; testing with the Post-Concussion Symptom Scale, Immediate Post-Concussion Assessment and Cognitive Testing, and Vestibular/Ocular Motor Screening instruments; demographic factors, medical history, and injury information. RESULTS A total of 416 individuals were eligible, and 254 (61.1%) were excluded, leaving 162 (38.9%) in analyses. The early group (98 patients) and late group (64 patients) did not differ in age (mean [SD] age, early, 15.3 [1.6] years; late, 15.4 [1.6] years), number of female patients (early, 51 of 98 [52.0%]; late, 40 of 64 [62.5%]), or other demographic, medical history, or injury information. The groups also were similar on symptom severity, cognitive, ocular, and vestibular outcomes at the first clinic visit. Results from a logistical regression supported being in the late group (adjusted odds ratio, 5.8 [95% CI, 1.9-17.6]; P = .001) and visual motion sensitivity symptoms greater than 2 (adjusted odds ratio, 4.5 [95% CI, 1.1-18.0]; P = .04) as factors significantly associated with recovery time.CONCLUSIONS AND RELEVANCE Findings suggest that earlier initiation of clinical care is associated with faster recovery after concussion. Other factors may also influence recovery time. Further research is needed to determine the role of active rehabilitation and treatment strategies, as well as demographic factors, medical history, and injury characteristics on the current findings.

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BACKGROUND Current concussion symptom inventories emphasize total number or symptoms and severity and overlap with other conditions, such as mental health disorders, which may limit their specificity and clinical utility. OBJECTIVE To develop and test the reliability and validity of a new Concussion Clinical Profiles Screening tool (CP Screen) in both healthy controls and concussed. METHODS CP Screen is a 29-item self-report, clinical profile-based symptom inventory that measures the following 5 concussion clinical profiles: 1) anxiety/mood, 2) cognitive/fatigue, 3) migraine, 4) ocular, and 5) vestibular; and the following 2 modifying factors: 1) sleep and 2) neck. Post-Concussion Symptom Scale (PCSS), vestibular/ocular motor screening (VOMS) tool, and Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) were conducted. CP Screen was administered in community a concussion surveillance program and 2 sports medicine concussion clinics. Responses include 248 athletes, 121 concussed, and 127 controls, enrolled between 2018 and 2019. RESULTS Internal consistency of the CP Screen in the control (Cronbach's alpha = .87) and concussed (Cronbach's alpha = .93) samples was high. Moderate to high correlations among the CP Screen factors and PCSS factors and VOMS items, supporting concurrent validity. ROC curve analysis for identifying concussed from controls was significant (P < .001) for all CP Screen factor and modifier scores with excellent AUCs for migraine (.93), ocular (.88), vestibular (.85), and cognitive (.81) factors, demonstrating predictive validity. CONCLUSION The CP Screen demonstrated strong reliability, concurrent validity with commonly used concussion assessment (ie, PCSS, VOMS, and ImPACT), and predictive validity for identifying concussion. The CP Screen extends current symptom inventories by evaluating more specific symptoms that may reflect clinical profiles and inform better clinical care.

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Background: Symptoms, cognition, balance, and other domains are commonly assessed at baseline testing as part of comprehensive preseason evaluations among collegiate student-athletes. Although approximately 27% of college students have at least 1 sleep disorder, researchers have yet to examine the role of a preexisting sleep disorder on preinjury baseline performance. Purpose: To compare athletes with and without a reported history of diagnosed sleep disorders on commonly used baseline concussion assessments. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A total of 666 National Collegiate Athletic Association student-athletes completed baseline measures including the Balance Error Scoring System (BESS), Brief Symptom Inventory–18 (BSI-18), Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT), Post-Concussion Symptom Scale (PCSS), Sport Concussion Assessment Tool–5th Edition (SCAT5), and Standardized Assessment of Concussion (SAC). There were 333 athletes with a history of diagnosed sleep disorders who were matched on age, sex, sport, and concussion history to 333 athletes with no history of diagnosed sleep disorders. Participants in both groups had a mean age of 19.89 ± 1.36 years and included 182 (54.7%) male athletes, and 126 (37.8%) reported a history of ≥1 concussions. Results: A series of 1-way analyses of covariance with Bonferroni corrections revealed significant group differences on the BESS (F1,559 = 8.88; P < .01); BSI-18 somatization (F1,640 = 18.48; P < .01), depression (F1,640 = 18.78; P < .01), anxiety (F1,640 = 19.42; P < .01), and global severity index (F1,640 = 27.18; P < .01); PCSS (F1,424 = 29.42; P < .01); SCAT5 symptom number (F1,634 = 28.79; P < .01) and symptom severity (F1,634 = 31.74; P < .01); and SAC (F1,578 = 4.36; P = .037). Specifically, while the sleep disorder group did perform better on the BESS, they also reported higher symptoms on the BSI-18, PCSS, and SCAT5 and performed worse on the SAC. There were no group differences on ImPACT performance. Conclusion: Collegiate student-athletes with diagnosed sleep disorders reported elevated affective and concussion symptoms at baseline that could affect the interpretation of postinjury impairments and symptoms. Based on the small effect sizes of our findings, however, the magnitude of these differences is of questionable clinical significance. Still, clinicians should consider diagnosed sleep disorders as reported during preparticipation sports physical examinations when interpreting baseline and postinjury concussion assessments.

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