Contributions to forearm desaturation during transient ischemia in healthy adult males and females across the lifespan
Bibliographic record
Abstract
This study investigated skeletal muscle tissue oxygenation (StO2) desaturation in males and females across the adult lifespan. One hundred-two individuals (51 females) of 41 young, 34 midlife, and 27 older adults completed a vascular occlusion test with near-infrared spectroscopy (NIRS + VOT). This included five minutes of arterial occlusion, inducing transient ischemia in the forearm flexor muscle group while recording StO2. The magnitude of desaturation (StO2mag) was quantified as the difference between baseline StO2 and the minimum StO2 value observed during ischemia. The rate of desaturation was also examined. Forearm adipose tissue thickness (ATT), forearm lean mass, and handgrip muscular strength were measured. A p ≤ 0.05 was considered significant. Two-way between factor Analysis of variance (ANOVAs) indicated that males exhibited significantly ( p < 0.001) less ATT than females (collapsed across age) and that forearm lean mass ( p < 0.001) and muscular strength ( p < 0.001) decreased across the lifespan independent of sex. Bivariate analyses revealed significant ( p < 0.05) associations for sex, age, ATT, forearm lean mass, and muscular strength with the desaturation metrics. The ATT values demonstrated the strongest relations with StO2mag and desaturation rate ( r = −0.620 and 0.618). Using a model comparison approach, ATT plus age offered the best predictive power for StO2mag and desaturation rate ( R2 = 0.456 and 0.438) such that the inclusion of sex did not improve the models. These findings suggested differences in desaturation were primarily explained by variations in ATT and, to a lesser extent, age, but biological sex had no meaningful effect. Future studies must determine what other factors influence desaturation during ischemia.
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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".