Cutaneous Vascular Responses and Thermoregulation in Individuals with Spinal Cord Injury Following Acute Body-Weight Supported Treadmill Training
Bibliographic record
Abstract
Muscular paralysis secondary to spinal cord injury (SCI) renders regular physical activity more difficult to perform. As a result, the arterial vascular system undergoes detrimental adaptations, leading to reduced lower limb blood flow (BF) and skin temperature (ST). Ultimately, individuals with SCI have reduced skin integrity and potential for wound healing. Body-weight supported treadmill training (BWSTT) allows individuals with impaired independent walking ability to undergo upright treadmill ambulation. PURPOSE: To determine the effect of a single session of BWSTT on lower limb superficial femoral artery BF and ST in individuals with chronic SCI. METHODS: Individuals with chronic SCI (> 1 yr post-injury; ASIA A-C) performed one session of BWSTT (14–40 min) on two separate occasions: 1. Left and right thigh and shank ST were measured using a Thermal Imaging Processor before and immediately following BWSTT in one female and five males (35.8±15.4 yrs). 2. Left and right thigh and shank ST and superficial femoral artery BF were measured in two females and three males (40.0± 12.1 yrs) before and immediately following both passive range-of-motion (PROM) and BWSTT; PROM and BWSTT were separated by a 10-min rest interval. ST and BF were measured using an Infrared Thermographic Scanner and Doppler ultrasound, respectively. RESULTS: Following a single session of BWSTT, there was a significant increase in thigh ST (pre: 27.21±0.47°C; post: 28.19±0.46°C, p<.05) and a strong trend toward increased shank temperature (pre: 27.25±0.44°C; post: 27.87±0.24°C; p=.05), with ST measured using a Thermal Imaging Processor. When using a hand-held Infrared Thermographic Scanner, we were unable to detect changes in ST in 5 participants following either BWSTT or PROM. There was no effect of BWSTT or PROM on BF. CONCLUSION: This preliminary evidence suggests that a single session of BWSTT may be effective in increasing cutaneous ST. These results are encouraging because an increase in lower limb ST may indicate a decreased risk for pressure sores. However, our results do not confirm that an increase in ST following BWSTT is related to increased superficial femoral artery BF. Additional research is necessary to clarify our results and to determine the effects of multiple successive bouts of BWSTT. Supported by NSERC.
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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) | 0.000 | 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".