Effects of neuromuscular electrical stimulation on energy expenditure and postprandial metabolism in healthy men
Bibliographic record
Abstract
It is unclear whether neuromuscular electrical stimulation (NMES) has meaningful metabolic effects when users have the opportunity to self-select the intensity to one that can be comfortably tolerated. Nine healthy men aged 28 ± 9 y (mean ± SD) with a body mass index 22.3 ± 2.3 kg/m 2 completed 3 trials involving a 2-h oral glucose tolerance test whilst, in a randomised counterbalanced order, (1) sitting motionless (SIT), (2) standing motionless (STAND); and (3) sitting motionless with NMES of quadriceps and calves at a self-selected tolerable intensity. The mean (95% confidence interval [CI]) total energy expenditure was greater in the NMES trial (221 [180–262] kcal/2 h) and STAND trial (178 [164–191] kcal/2 h) than during SIT (159 [150–167] kcal/2 h) (both, p < 0.05). This was primarily driven by an increase in carbohydrate oxidation in the NMES and STAND trials compared with the SIT trial (p < 0.05). Postprandial insulin iAUC was lower in both NMES and STAND compared with SIT (16.4 [7.7–25.1], 17 [7–27] and 22.6 [10.8–34.4] nmol·120 min/L, respectively; both, p < 0.05). Compared with sitting, both NMES and STAND increased energy expenditure and whole-body carbohydrate oxidation and reduced postprandial insulin concentrations in healthy men, with more pronounced effects seen with NMES. Self-selected NMES is a potential strategy for improving metabolic health. This trial is registered at ClinicalTrials.gov (ID: NCT04389736). Novelty: NMES at a comfortable intensity enhances energy expenditure and carbohydrate oxidation, and reduces postprandial insulinemia. Thus, self-selected NMES represents a potential strategy to improve metabolic health.
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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) | 0.001 | 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".