What is the physiological time to recovery after concussion? A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM OR OBJECTIVE: The aim of this study is to consolidate studies of physiological measures following sport-related concussion (SRC) to determine if a time course of postinjury altered neurobiology can be outlined. This biological time course was considered with respect to clinically relevant outcomes such as vulnerability to repeat injury and safe timing of return to physical contact risk. DESIGN: Systematic review. DATA SOURCES: PubMed, CINAHL, Cochrane Central, PsychINFO. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Studies were included if they reported original research on physiological or neurobiological changes after SRC. Excluded were cases series <5 subjects, reviews, meta-analyses, editorials, animal research and research not pertaining to SRC. RESULTS: A total of 5834 articles were identified, of which 80 were included for full-text data extraction and review. Relatively few longitudinal studies exist that follow both physiological dysfunction and clinical measures to recovery. SUMMARY/CONCLUSIONS: Modalities of measuring physiological change after SRC were categorised into the following: functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy, cerebral blood flow, electrophysiology, heart rate, exercise, fluid biomarkers and transcranial magnetic stimulation. Due to differences in modalities, time course, study design and outcomes, it is not possible to define a single 'physiological time window' for SRC recovery. Multiple studies suggest physiological dysfunction may outlast current clinical measures of recovery, supporting a buffer zone of gradually increasing activity before full contact risk. Future studies need to use generalisable populations, longitudinal designs following to physiological and clinical recovery and careful correlation of neurobiological modalities with clinical measures.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it