Parasympathetic baroreflexes and heart rate variability during acute stage of sport concussion recovery
Bibliographic record
Abstract
PRIMARY OBJECTIVE: To assess and compare the parasympathetic state of individuals in healthy vs concussion groups, by measuring cardiovascular metrics under resting and baroreflex conditions using a squat-stand manoeuvre. RESEARCH DESIGN: This was a retrospective mixed-method study, with participants who sustained a medically diagnosed sport concussion (n = 12), being tested within 72-hours post-injury. METHODS AND PROCEDURES: Participant's heart rate (Electrocardiogram, ECG) and blood pressure (finger plethysmography) data was collected during rest and during 10-second squat-stands (10SS, 0.05 Hz). Blood pressure and heart rate standard deviation data was analysed in the 0-5 seconds and 6-10 seconds periods of squatting and standing. Resting and baroreflex ECG data were analysed via Fourier Transformations for %Low Frequency and %High Frequency (%LF and %HF). RESULTS: The control group alleviated more pressure and had a significantly higher standard deviation of heart rate during the 6-10 seconds of squatting (p < 0.05). Overall heart rate standard deviation in the concussion group was significantly lower than healthy controls when standing (p < 0.05). There were no differences in %LF and % HF between groups or between rest and 10SS. CONCLUSION: This study provides preliminary evidence that autonomic function is dysregulated following mTBI within the initial 72 hours of injury.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".