Cardiovascular Function After Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND: Autonomic dysfunction after spinal cord injury (SCI) is an under-researched area when compared with motor and sensory dysfunction. Cardiovascular autonomic dysfunction is a particular concern, leading to impaired control of blood pressure and heart rate. OBJECTIVES: (1) To determine the prevalence of hypotension in individuals with SCI during and after rehabilitation; (2) To investigate changes in cardiovascular variables during and after rehabilitation; (3) To evaluate the influence of personal and lesion characteristics on cardiovascular variables. METHODS: Cardiovascular variables (resting systolic [SAP] and diastolic [DAP] arterial pressures and resting [HRrest] and peak heart rates [HRpeak]) were measured on 5 test occasions: start of inpatient rehabilitation, 3 months later, at discharge, and at 1 and 5 years after discharge. The time course and effects of personal and lesion characteristics on cardiovascular variables were studied using multilevel regression analyses. RESULTS: The prevalence of hypotension was unchanged during rehabilitation and for 5 years after discharge. Odds for hypotension were highest in those with cervical and high thoracic lesions, younger individuals, and men. DAP increased during the 5 years after discharge. HRrest decreased during and after rehabilitation. SAP, DAP, HRrest, and HRpeak were lowest in those with cervical and high thoracic lesions. SAP and DAP increased with age; HRpeak decreased with age. CONCLUSIONS: These longitudinal data provide normative values for blood pressure and heart rate changes with time after injury according to lesion and personal characteristics. These results can be used to guide clinical practice and place changes in cardiovascular function caused by interventions in perspective.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".