Clinical correlates of frequency analyses of cardiovascular control after spinal cord injury
Bibliographic record
Abstract
Spinal cord injury (SCI) has profound effects on cardiovascular autonomic function due to injury to descending autonomic pathways, and cardiovascular diseases are the leading causes of morbidity and mortality after SCI. Evaluation of cardiovascular autonomic dysfunction after SCI and appraisal of simple noninvasive autonomic assessments that are clinically meaningful would be useful to SCI clinicians and researchers. We aimed to assess supine and upright cardiovascular autonomic function from frequency analyses of heart rate and blood pressure variability (HRV and BPV) after SCI. We studied 26 subjects with chronic cervical or thoracic SCI and 17 able-bodied controls. We continuously recorded R-R interval (RRI, by ECG) and beat-to-beat blood pressure (by Finometer) in supine and seated positions. Cardiovascular control was assessed from spectral analysis of RRI and blood pressure time series. Cardiac baroreflex control was assessed from cross-spectral analyses of low-frequency spectra. Supine and upright low-frequency HRV and BPV were reduced in cervical SCI subjects, as were total BPV and HRV. Supine high-frequency HRV was reduced in thoracic SCI subjects. Cardiac baroreflex delay was increased in cervical SCI subjects. Supine frequency domain indexes were correlated with sympathetic skin responses, orthostatic cardiovascular responses, and plasma catecholamine levels. SCI results in reduced sympathetic drive to the heart and vasculature and increased baroreflex delay in cervical SCI subjects and reduced cardiac vagal tone in thoracic SCI subjects. Frequency analyses of autonomic function are related to clinical measures of autonomic control after SCI and provide useful noninvasive clinical tools with which to assess autonomic completeness of injury following SCI.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".