Neuropsychological And Neurophysiological Deficits Following A Sport-related Concussion In Children And Adults
Bibliographic record
Abstract
A concussion is the most common type of head injury in athletes younger than 20 years of age. Although the majority of concussions resolve rapidly in adults (7-10 days), recovery could be different in children and adolescents. Several neurophysiological studies using event-related potentials show that adult athletes have cerebral anomalies in the absence of clinical symptoms. However, the consequences of a sport-related concussion on the developing brain are less known. PURPOSE: To determine whether age differences exist with respect to cognitive functioning following a sport-related concussion. METHODS: This retrospective study assessed cognitive functioning using standardized neuropsychological tests as well as event-related potentials elicited by a visual 3-stimulus oddball paradigm in concussed and non-concussed athletes divided into three distinct age groups [9-12 yrs (n = 32), 13-16 yrs (n =34), and adults (n = 30)]. Electroencephalographic (EEG) activity was recorded using a high density montage (128 electrodes). In order to maintain sample homogeneity, time elapsed since the last concussion was less than one year. Group comparisons were investigated with a series of ANOVAs. RESULTS: No group differences were found for any of the neuropsychological tests used (all ps > 0.05). Concussed athletes displayed a significantly lower amplitude for the P3b component of their ERP compared to their non injured teammates (F 1,88 = 8.72; p < 0.01). No age-related differences were found among the concussed groups, (p > 0.05). CONCLUSIONS: These data suggested persistent neurophysiological deficits that are present up to one year following a concussion. The reduction in P3b amplitude for the concussed athletes reflects a deficit in the capacity to allocate attentional resources efficiently. Supported by CIHR and FRSQ to DE and ML
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".