Contrast Baths, Intramuscular Hemodynamics, and Oxygenation as Monitored by Near-Infrared Spectroscopy
Bibliographic record
Abstract
Context: Contrast baths (CB) is a thermal treatment modality used in sports medicine, athletic training, and rehabilitation settings. Proposed physiological effects of CB include increasing tissue blood flow and oxygenation and decreasing tissue swelling and edema to promote better healing, improved limb function, and quicker recovery. Objective: To investigate the physiological effects of CB on the intramuscular hemodynamics and oxygenation of the lower leg muscles using near-infrared spectroscopy (NIRS), an optical method for monitoring changes in tissue oxygenated (O2Hb), deoxygenated (HHb), and total hemoglobin (tHb) as well as tissue oxygen saturation index (TSI%). Design: Descriptive laboratory study. Patients or Other Participants: Ten healthy men and women with a mean age of 29 (range = 17 ± 42) years, mean body mass index of 24.6 ± 3.2, and mean adipose tissue thickness of 6.4 ± 2.2 mm. Intervention(s): Conventional CB (10-minute baseline, 4 : 1-minute hot : cold ratio) was applied to the left lower leg. Main Outcome Measure(s): Changes in chromophore concentrations of O2Hb, HHb, tHb, and TSI% of the gastrocnemius muscle were monitored during 10 minutes of baseline measurement, a 30-minute CB protocol, and 10 minutes of recovery using a spatially resolved NIRS. Results: After a 30-minute CB protocol, increases (P < .05) in tissue O2Hb (7.4 ± 4 μM), tHb (7.6 ± 6.1 μM), and TSI% (3.1% ± 2.3%) were observed as compared with baseline measures. Conclusions: Application of CB induced a transient change in the hemodynamics and oxygenation of the gastrocnemius muscle in healthy individuals. The effect of CB application in improving tissue hemodynamics and oxygenation may, therefore, support the therapeutic benefits of CB in the treatment of muscle injuries.
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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 | 0.000 | 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) | 0.002 | 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".