The impact of concussion on cardiac autonomic function: A systematic review
Bibliographic record
Abstract
PRIMARY OBJECTIVE: To evaluate the evidence regarding the effect of concussion on cardiac autonomic function (CAF). INCLUSION CRITERIA: Original research; available in English; included participants with concussion or mild traumatic brain injury (mTBI) and a comparison group; included measures of heart rate (HR) and/or heart rate variability (HRV) as outcomes. Studies of humans (greater than 6 years old) and animals were included. Critical appraisal tools: The Downs and Black (DB) criteria and Structured Effectiveness Quality Evaluation Scale (SEQES). RESULTS: Nine full-length articles and four abstracts were identified. There is conflicting evidence regarding CAF at rest following concussion. There is evidence of elevated HR and reduced HRV with low-intensity, steady-state exercise up to 10 days following concussion. There was no significant difference in HRV during isometric handgrip testing or HR while performing cognitive tasks following concussion. The validity of current literature is limited by small sample sizes, lack of female or paediatric participants, methodological heterogeneity and lack of follow-up. CONCLUSIONS: While there is some evidence to suggest CAF is altered during physical activity following concussion, methodological limitations highlight the need for further research. Understanding the effect of concussion on CAF will contribute to the development of more comprehensive concussion management strategies.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".