Effects of light-emitting diode therapy (LEDT) on cardiopulmonary and hemodynamic adjustments during aerobic exercise and glucose levels in patients with diabetes mellitus: A randomized, crossover, double-blind and placebo-controlled clinical trial
Bibliographic record
Abstract
The aim of this study was to evaluate the acute effects of light-emitting diode therapy (LEDT) on cardiopulmonary adjustments and muscle oxygenation dynamics during transition to moderate exercise, as well as in glucose and lactate levels in patients with type 2 diabetes mellitus (T2DM). Sixteen individuals with T2DM (age 55.1±5.4 years) performed four separate tests receiving LEDT or placebo in random order, at intervals of at least 14 days. A light-emitting diode array (50GaAIAs LEDs, 850nm, 75mW per diode) was used to perform LEDT bilaterally on the quadriceps femoris and triceps surae muscles for 40s at each site. After, a moderate cycling exercise was performed and oxygen uptake, muscular deoxyhemoglobin, heart rate and cardiac output were measured. Lactate and glucose levels were measured before LEDT/placebo and after the exercise. The LEDT decreased the glucose levels after the exercise compared with values before LEDT (173.7±61.0 to 143.5±53.5 mg/dl, P=0.02) and it did not affect the cardiopulmonary and hemodynamic adjustments in exercise, as well as lactate levels in both groups. In conclusion, the LEDT in combination with moderate exercise acutely decreased the glucose levels in men with T2DM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".