Spinal Cord Injury Impairs Cardiovascular Capacity in Elite Wheelchair Rugby Athletes
Bibliographic record
Abstract
OBJECTIVE: To examine differences in heart rate (HR) responses during international wheelchair rugby competition between athletes with and without a cervical spinal cord injury (SCI) and across standardized sport classifications. DESIGN: Observational study. SETTING: The 2015 Parapan American Games wheelchair rugby competition. PARTICIPANTS: Forty-three male athletes (31 ± 8 years) with a cervical SCI (n = 32) or tetraequivalent impairment (non-SCI, n = 11). MAIN OUTCOME MEASURES: Average and peak HR (HRavg and HRpeak, respectively). To characterize HR responses in accordance with an athletes' International Wheelchair Rugby Federation (IWRF) classification, we separated athletes into 3 groups: group I (IWRF classification 0.5-1.5, n = 15); group II (IWRF classification 2.0, n = 15); and group III (IWRF classification 2.5-3.5, n = 13). RESULTS: Athletes with SCI had lower HRavg (111 ± 14 bpm vs 155 ± 13 bpm) and HRpeak (133 ± 12 bpm vs 178 ± 13 bpm) compared with non-SCI (both P < 0.001). Average HR was higher in group III than in I (136 ± 25 bpm vs 115 ± 20 bpm, P = 0.045); however, SCI athletes showed no difference in HRavg or HRpeak between groups. Within group III, SCI athletes had lower HRavg (115 ± 6 bpm vs 160 ± 8 bpm) and HRpeak (135 ± 11 bpm vs 183 ± 11 bpm) than non-SCI athletes (both P < 0.001). CONCLUSIONS: This study is the first to demonstrate attenuated HR responses during competition in SCI compared with non-SCI athletes, likely due to injury to spinal autonomic pathways. Among athletes with SCI, IWRF classification was not related to differences in HR. Specific assessment of autonomic function after SCI may be able to predict HR during competition and consideration of autonomic impairments may improve the classification process.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".