What tests and measures accurately diagnose persisting post-concussive symptoms in children, adolescents and adults following sport-related concussion? A systematic review
Bibliographic record
Abstract
OBJECTIVE: To determine what tests and measures accurately diagnose persisting post-concussive symptoms (PPCS) in children, adolescents and adults following sport-related concussion (SRC). DESIGN: A systematic literature review. DATA SOURCES: MEDLINE, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, CINAHL and SPORTDiscus through March 2022. ELIGIBILITY CRITERIA: Original, empirical, peer-reviewed findings (cohort studies, case-control studies, cross-sectional studies and case series) published in English and focused on SRC. Studies needed to compare individuals with PPCS to a comparison group or their own baseline prior to concussion, on tests or measures potentially affected by concussion or associated with PPCS. RESULTS: Of 3298 records screened, 26 articles were included in the qualitative synthesis, including 1016 participants with concussion and 531 in comparison groups; 7 studies involved adults, 8 involved children and adolescents and 11 spanned both age groups. No studies focused on diagnostic accuracy. Studies were heterogeneous in participant characteristics, definitions of concussion and PPCS, timing of assessment and the tests and measures examined. Some studies found differences between individuals with PPCS and comparison groups or their own pre-injury assessments, but definitive conclusions were not possible because most studies had small convenience samples, cross-sectional designs and were rated high risk of bias. CONCLUSION: The diagnosis of PPCS continues to rely on symptom report, preferably using standardised symptom rating scales. The existing research does not indicate that any other specific tool or measure has satisfactory accuracy for clinical diagnosis. Future research drawing on prospective, longitudinal cohort studies could help inform clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".