Analyzing Dual-Task Paradigms to Improve Postconcussion Assessment and Management.

CONTEXT: Dual-task (simultaneous cognitive-motor activities) assessments have been adapted into reliable and valid clinical concussion measures. However, abundant motor and cognitive variations leave researchers and clinicians uncertain about which combinations elicit the intended dual-task effect. Our objective was to examine differences between commonly employed dual-task motor and cognitive combinations among healthy, college-aged individuals. DESIGN: Cross-sectional laboratory study. METHODS: Twenty participants (age: 21.3 [2.4] y; height: 176.0 [9.1] cm; mass: 76.0 [16.4] kg; 20% with concussion history) completed 4 motor tasks (gait, tandem gait, single-leg balance, and tandem balance) under 5 cognitive conditions (single task, subtraction, month reversal, spelling backward, and visual Stroop) in a research laboratory. The motor performance outcomes were spatiotemporal variables for gait and tandem gait and center of pressure path length (in centimeters) for single-leg and tandem balance. Cognitive outcomes were response rate (responses/second) and cognitive accuracy. We used separate repeated-measures analyses of variance for each motor and cognitive outcome with post hoc Tukey t tests. RESULTS: Gait velocity, gait stride length, and tandem gait velocity demonstrated significant cognitive-motor interactions (P's < .001) such that all dual-task conditions resulted in varyingly slower or shorter movement than single task. Conversely, single-leg balance (P = .627) and tandem balance (P = .434) center of pressure path length did not significantly differ among the dual-task cognitive conditions or relative to single task. Statistically significant cognitive-motor interactions were observed only for spelling backward accuracy (P = .004) and response rates for spelling backward, month reversal, and visual Stroop (P's < .001) such that worse accuracy, but faster response rates, occurred during motor tasks. CONCLUSIONS: Gait and tandem gait motor tasks accompanied with spelling backward or subtraction cognitive tasks demonstrated consistently strong dual-task effects and, therefore, may be the best suited for clinical and research use following concussion.

The Interval Between Concussions Does Not Influence Time to Asymptomatic or Return to Play: A CARE Consortium Study.

INTRODUCTION: The purpose of this study was to determine if the time interval between two concussive events influences the number of days to asymptomatic status, days to return to play, or performance on common post-concussion assessments following the second concussion. METHODS: Data from 448 collegiate athletes and service academy cadets with two concussions (time between concussions: median 295.0 days [interquartile range: 125.0-438.2]), 40.0% female) were analyzed from Concussion Assessment Research and Education (CARE) Consortium institutions between 2014 and 2020. Days between concussions was the primary predictor variable. Primary outcome measures included time to asymptomatic and time to return to play following the second concussion. Secondary outcome measures included total number of symptoms, total symptom severity, Balance Error Scoring System total score, and Standardized Assessment of Concussion total score within 48 h of their second concussion. RESULTS: Time between concussions did not significantly contribute to the multivariate time to asymptomatic (p = 0.390), time to return to play (p = 0.859), or the secondary outcomes (p-range = 0.165-0.477) models. Time to asymptomatic (p = 0.619) or return to play (p = 0.524) did not differ between same-season and different-season concussions. Sex significantly contributed to the return to play (p = 0.005) multivariate model. Delayed symptom onset and immediate removal from play/competition significantly contributed to the total number of symptoms (p = 0.001, p = 0.014) and symptom severity (p = 0.011, p = 0.022) multivariate models. CONCLUSION: These results suggest that in a population with a large period between injuries, the time between concussions may not be relevant to clinical recovery.

Optimizing Concussion Care Seeking: Connecting Care-Seeking Behaviors and Neurophysiological States Through Blood Biomarkers.

BACKGROUND: Timely and appropriate medical care after concussion presents a difficult public health problem. Concussion identification and treatment rely heavily on self-report, but more than half of concussions go unreported or are reported after a delay. If incomplete self-report increases exposure to harm, blood biomarkers may objectively indicate this neurobiological dysfunction. PURPOSE/HYPOTHESIS: The purpose of this study was to compare postconcussion biomarker levels between individuals with different previous concussion diagnosis statuses and care-seeking statuses. It was hypothesized that individuals with undiagnosed concussions and poorer care seeking would show altered biomarker profiles. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Blood samples were collected from 287 military academy cadets and collegiate athletes diagnosed with concussion in the Advanced Research Core of the Concussion Assessment, Research and Education Consortium. The authors extracted each participant's self-reported previous concussion diagnosis status (no history, all diagnosed, ≥1 undiagnosed) and whether they had delayed or immediate symptom onset, symptom reporting, and removal from activity after the incident concussion. The authors compared the following blood biomarkers associated with neural injury between previous concussion diagnosis status groups and care-seeking groups: glial fibrillary acidic protein, ubiquitin c-terminal hydrolase-L1 (UCH-L1), neurofilament light chain (NF-L), and tau protein, captured at baseline, 24 to 48 hours, asymptomatic, and 7 days after unrestricted return to activity using tests of parallel profiles. RESULTS: The undiagnosed previous concussion group (n = 21) had higher levels of NF-L at 24- to 48-hour and asymptomatic time points relative to all diagnosed (n = 72) or no previous concussion (n = 194) groups. For those with delayed removal from activity (n = 127), UCH-L1 was lower at 7 days after return to activity than that for athletes immediately removed from activity (n = 131). No other biomarker differences were observed. CONCLUSION: Individuals with previous undiagnosed concussions or delayed removal from activity showed some different biomarker levels after concussion and after clinical recovery, despite a lack of baseline differences. This may indicate that poorer care seeking can create neurobiological differences in the concussed brain.

Optimizing Concussion Care Seeking: Using Machine Learning to Predict Delayed Concussion Reporting.

BACKGROUND: Early medical attention after concussion may minimize symptom duration and burden; however, many concussions are undiagnosed or have a delay in diagnosis after injury. Many concussion symptoms (eg, headache, dizziness) are not visible, meaning that early identification is often contingent on individuals reporting their injury to medical staff. A fundamental understanding of the types and levels of factors that explain when concussions are reported can help identify promising directions for intervention. PURPOSE: To identify individual and institutional factors that predict immediate (vs delayed) injury reporting. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: This study was a secondary analysis of data from the Concussion Assessment, Research and Education (CARE) Consortium study. The sample included 3213 collegiate athletes and military service academy cadets who were diagnosed with a concussion during the study period. Participants were from 27 civilian institutions and 3 military institutions in the United States. Machine learning techniques were used to build models predicting who would report an injury immediately after a concussive event (measured by an athletic trainer denoting the injury as being reported "immediately" or "at a delay"), including both individual athlete/cadet and institutional characteristics. RESULTS: In the sample as a whole, combining individual factors enabled prediction of reporting immediacy, with mean accuracies between 55.8% and 62.6%, depending on classifier type and sample subset; adding institutional factors improved reporting prediction accuracies by 1 to 6 percentage points. At the individual level, injury-related altered mental status and loss of consciousness were most predictive of immediate reporting, which may be the result of observable signs leading to the injury report being externally mediated. At the institutional level, important attributes included athletic department annual revenue and ratio of athletes to athletic trainers. CONCLUSION: Further study is needed on the pathways through which institutional decisions about resource allocation, including decisions about sports medicine staffing, may contribute to reporting immediacy. More broadly, the relatively low accuracy of the machine learning models tested suggests the importance of continued expansion in how reporting is understood and facilitated.