Persisting Effects of Concussion on Heart Rate Variability during Physical Exertion
Bibliographic record
Abstract
The purpose of this study was to evaluate cardiac autonomic modulation in university athletes during the post-acute to late phase (mean, 95 days ±63) of injury at rest and during physical exertion. We also sought to evaluate the effect of time since injury and number of injuries on heart rate variability (HRV). We hypothesized that physical exertion would reveal persisting modifications in HRV following a concussion. We included, in a cross-sectional design, athletes who sustained a concussion and matched controls. Concussions were identified by a medical doctor using established criteria. Twelve male concussed and 12 control athletes took part in the study. Control participants were teammates who were chosen to match the concussed athletes with regard to their height, weight, education, and age. The beat-to-beat electrocardiogram intervals of the participants were measured at rest and during physical exertion (isometric hand grip contraction; IHGC), which was sustained for 3 minutes at 30% of the participants' maximum. Linear and nonlinear parameters of HRV were calculated. The ratio between low and high frequency (LF/HF) bands was calculated to assess the sympathovagal balance. During the IHGC, but not at rest, concussed athletes presented significantly lower power in HF bands, leading to a significantly higher LF/HF ratio (p ≤ 0.05). Thus, asymptomatic athletes still may exhibit modifications in cardiac autonomic modulation weeks to months following injury. These modifications may only become apparent during physical exertion. Monitoring HRV may aid diagnosis and provide insight about safe return to play.
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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 | 0.002 |
| 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".