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Objective Variability in recovery time following sport-related concussion (SRC) is poorly understood. We explored the utility of brief mood, anxiety, and sleep questionnaires as postinjury predictors of SRC symptom clearance in adolescents. Method At initial visit 0–2 weeks postinjury, concussed athletes aged 12–18 years self-reported injury/medical factors (prior concussion, loss of consciousness, amnesia, and concussion symptom severity) and were administered psychological symptom measures. At 3 months, medical record review determined return-to-play (RTP) date. Subjects were divided into two datasets, with the first utilized for developing cutoff scores and then validated with the second dataset. Results A total of 64% of the 141 participants had early RTP (within 21 days postinjury), and 23% had late RTP (postinjury day 30 or later). The Generalized Anxiety Disorder Screener (GAD-7, M  = 2.1, SD  = 3.1) was the only significant predictor (p  = .001), with a 1.4-fold [95% CI 1.2–1.8] increased risk for every point. No other factors in the full model discriminated recovery groups (p s > .05). Receiver operating characteristic curve analysis derived a GAD-7 cut score ≥3 (sensitivity= 56.7%, specificity = 74.2%, AUCs = 0.63–0.79, p s < .001). Conclusions Postconcussion anxiety symptoms may help identify individuals at increased risk for prolonged recovery. [ABSTRACT FROM AUTHOR]

Objective To establish a cut score for the Montreal Cognitive Assessment (MoCA) that distinguishes mild cognitive impairment (MCI) from normal cognition (NC) in a community-based African American (AA) sample. Methods A total of 135 AA participants, from a larger aging study, diagnosed MCI (n = 90) or NC (n = 45) via consensus diagnosis using clinical history, Clinical Dementia Rating score, and comprehensive neuropsychological testing. Logistic regression models utilized sex, education, age, and MoCA score to predict MCI versus NC. Receiver operating characteristic (ROC) curve analysis determined a cut score to distinguish MCI from NC based on optimal sensitivity, specificity, diagnostic accuracy, and greatest perpendicular distance above the identity line. ROC results were compared with previously published MoCA cut scores. Results The MCI group was slightly older (M MCI = 64.76[5.87], M NC = 62.33[6.76]; p =.033) and less educated (M MCI = 13.07[2.37], M NC = 14.36[2.51]; p =.004) and had lower MoCA scores (M MCI=21.26[3.85], M NC = 25.47[2.13]; p <.001) than the NC group. Demographics were non-significant in regression models. The area under the curve (AUC) was significant (MoCA =.83, p <.01) and an optimal cut score of <24 maximized sensitivity (72%), specificity (84%), and provided 76% diagnostic accuracy. In comparison, the traditional cut score of <26 had higher sensitivity (84%), similar accuracy (76%), but much lower specificity (58%). Conclusions This study provides a MoCA cut score to help differentiate persons with MCI from NC in a community-dwelling AA sample. A cut score of <24 reduces the likelihood of misclassifying normal AA individuals as impaired than the traditional cut score. This study underscores the importance of culturally appropriate norms to optimize the utility of commonly used cognitive screening measures. [ABSTRACT FROM AUTHOR]