Cardiovascular drift in trained paraplegic and able-bodied individuals during prolonged wheelchair exercise: effect of fluid replacement
Bibliographic record
Abstract
The progressive heart rate (HR) increase and stroke volume (SV) decline during prolonged constant-load leg exercise signifies cardiovascular drift (CVdrift); fluid replacement is known to minimize this phenomenon. Like their able-bodied counterparts (AB), paraplegic athletes undergo prolonged exercise during training and competition, which could result in CVdrift. The aim of this study is to address the role of rehydration on preventing CVdrift in spinal cord injured (SCI) paraplegic athletes. Eight SCI athletes with an injury level between C7 and T6 and 9 AB subjects performed 60-min constant-load exercise on a wheelchair ergometer in a thermo-neutral environment. No fluid was taken in 1 trial, whereas 85% of sweat losses were replaced by drinking water in another trial. Cardic output (CO), SV, HR, and oral temperature (Tor) were determined during exercise. Prolonged exercise resulted in similar HR (18 beats·min(-1) for AB and 12 beats·min(-1) for SCI) and Tor (0.63 °C for AB and 0.71 °C for SCI) elevation and SV decline (-8.5 mL·beat(-1) for AB and -5.5 mL·beat(-1) for SCI), whereas CO remained unchanged. Water intake restrained the exercise-induced hyperthermia and resulted in smaller SV decline (-4.0 mL for AB and -3.0 mL for SCI, p < 0.01). In conclusion, CVdrift was similar in SCI and AB subjects during prolonged wheelchair exercise. Likewise, the beneficial effects of hydration in both groups were analogous.
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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) | 0.001 | 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".