Spectral Analyses of Cardiovascular Control in Rodents with Spinal Cord Injury
Bibliographic record
Abstract
The severity of injury to cardiovascular autonomic pathways following clinical spinal cord injury (SCI) can be evaluated with spectral analyses. Whether this technique provides a translatable assessment of cardiovascular autonomic function in rodent SCI is unknown. Beat-to-beat blood pressure and pulse interval were measured in male rats 1 month after complete T3 or T10 SCI, and in uninjured control animals. Univariate autoregressive spectral analyses were performed and the power of the low frequency (LF), high frequency (HF), and very low frequency (VLF) peaks identified. Frequency domain variables were correlated with the severity of orthostatic hypotension (OH) and the severity of hypertension during autonomic dysreflexia (AD). Total heart rate variability (HRV) and blood pressure variability (BPV) were reduced in animals with T3, but not T10, SCI. VLF and LF HRV were reduced and HF HRV was increased in animals with T3 SCI compared to controls; there were no changes in animals with T10 SCI. BPV in the VLF and LF range was reduced in animals with T3 SCI, but not T10 SCI. In all animals with SCI, severity of OH was positively correlated with LF BPV, and negatively correlated with HF BPV. Severity of AD was positively correlated with HF BPV and HF HRV, and negatively correlated with VLF HRV. Spectral analyses can detect alterations in cardiovascular autonomic function in animals with SCI at rest. These parameters underscore the distinct cardiovascular ramifications of high- versus low-thoracic SCI, and correlate with the severity of AD and OH, clinically-relevant measures of abnormal blood pressure control.
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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 | 0.000 |
| 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".