A-180 Clinical Outcome Following Concussion Among Children and Adolescents with a History of Prior Concussion: A Systematic Review
Bibliographic record
Abstract
Abstract Purpose: This systematic review examined the association between prior concussion history and clinical outcomes following concussion among children and adolescents. Data Selection: This review was registered with PROSPERO database for systematic reviews (protocol ID: CRD42016041479 & CRD42019128300) and adhered to PRISMA guidelines. Three searches of nine online databases were conducted: (a) database inception to June of 2016; (b) January 1, 2016 to February 1, 2019; and (c) February 1, 2019 to May 15, 2021. We screened 5,118 abstracts and 51 studies were reviewed. We utilized a likelihood heuristic to assess evidence for an association between concussion history and clinical outcomes. Risk of bias was assessed using the Newcastle-Ottawa scale and level of evidence was appraised using the Oxford Classification for Evidence-Based Medicine. Data Synthesis: Concussion recovery or outcome was reported for 26,643 youth. A median of 36% had a prior history of concussion. Across all studies and outcomes, the majority (k=37, 72.5%) did not find a statistically significant association between lifetime history of concussion and outcome from a subsequent concussion. Important methodological limitations in the literature were identified (e.g., many studies were underpowered and/or coded prior concussion history as a binary variable as opposed to the number of prior concussions). Conclusions: Available studies do not provide compelling evidence that children and adolescents with a history of concussions are at increased risk for worse clinical outcome following a subsequent concussion. Clinicians are cautioned against routinely treating children and adolescents with one or more prior injuries more conservatively. Doing so, in some cases, might be counterproductive.
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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 | 0.013 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".