Susceptibility-Weighted Magnetic Resonance Imaging (MRI) of Microbleeds in Pediatric Concussion
Bibliographic record
Abstract
OBJECTIVE: The long-term consequences of pediatric concussion on brain structure are poorly understood. This study aimed to evaluate the presence and clinical significance of cerebral microbleeds several years after pediatric concussion. METHODS: Children and adolescents 8-19 years of age with either a history of concussion (n = 35), or orthopedic injury (n = 20) participated. Mean time since injury for the sample was 30.4 months (SD = 19.6). Participants underwent susceptibility-weighted imaging, rated their depression and postconcussion symptoms, and completed cognitive testing. Parents of participants also completed symptom ratings for their child. Hypointensities in susceptibility-weighted images indicative of cerebral microbleeds were calculated as a measure of hypointensity burden. RESULTS: Hypointensity burden did not differ significantly between participants with a history of concussion and those with a history of orthopedic injury. Depression ratings (self and parent report), postconcussion symptom ratings (self and parent report), and cognitive performance did not significantly correlate with hypointensity burden in the concussion group. CONCLUSIONS: These findings suggest that at approximately 2.5 years postinjury, children and adolescents with prior concussion do not have a greater amount of cerebral microbleeds compared to those with orthopedic injury. Future research should use longitudinal study designs and investigate children with persistent postconcussive symptoms to gain better insight into the long-term effects of concussion on cerebral microbleeds.
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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 | 0.002 |
| 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".