Cardiovascular control, autonomic function, and elite endurance performance in spinal cord injury
Bibliographic record
Abstract
We aimed to determine the relationship between level of injury, completeness of injury, resting as well as exercise hemodynamics, and endurance performance in athletes with spinal cord injury (SCI). Twenty-three elite male paracycling athletes (C3-T8) were assessed for neurological level/completeness of injury, autonomic completeness of injury, resting cardiovascular function, and time to complete a 17.3-km World Championship time-trial test. A subset were also fitted with heart rate (HR) monitors and their cycles were fitted with a global positioning systems device (n = 15). Thoracic SCI exhibited higher seated systolic blood pressure along with superior time-trial performance compared with cervical SCI (all P < 0.01). When further stratified by autonomic completeness of injury, the four athletes with cervical autonomic incomplete SCI exhibited a faster time-trial time and a higher average speed compared with cervical autonomic complete SCI (all P < 0.042). Maximum and average HR also tended to be higher in cervical autonomic incomplete vs autonomic complete. There were no differences in time-trial time, HR, or speed between thoracic autonomic complete vs incomplete SCI. In conclusion, autonomic completeness of injury and the consequent ability of the cardiovascular system to respond to exercise appear to be a critical determinant of endurance performance in elite athletes with cervical SCI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".