Effect of PPARγ agonist on aerobic exercise capacity in relation to body fat distribution in men with type 2 diabetes mellitus and coronary artery disease: a 1-yr randomized study
Bibliographic record
Abstract
Targeting metabolic determinants of exercise performance with pharmacological agents that would mimic/potentiate the effects of exercise represents an attractive clinical alternative to counterbalance the poor exercise capacity in patients with type 2 diabetes mellitus (T2DM). We examined the effect of 1-yr treatment with the insulin sensitizer peroxisome proliferator-activated receptor (PPAR)γ agonist rosiglitazone on aerobic exercise capacity and body fat composition/distribution in men with T2DM and stable coronary artery disease (CAD). One-hundred four men (age: 64 ± 7 yr; body mass index: 30.0 ± 4.4 kg/m2) with T2DM and CAD were randomized to receive rosiglitazone or placebo for 1 yr. Aerobic exercise capacity (exercise duration) was assessed with a maximal treadmill test, and body composition/distribution were assessed by dual-energy X-ray absorptiometry/computed tomography scans. At 1 yr, patients with T2DM under PPARγ agonist treatment showed a reduction in aerobic exercise capacity compared with the control group (exercise duration change, −31 ± 8 versus 7 ± 11 s, P = 0.009). Significant increases in body fat mass (3.1 ± 0.4 kg, 12%), abdominal and mid-thigh subcutaneous adipose tissue (AT) levels, and mid-thigh skeletal muscle fat were found (all P < 0.01), whereas no effect on visceral AT levels was observed ( P > 0.05) under treatment. Subcutaneous fat mass gained under PPARγ agonist was the strongest predictor of the worsening in aerobic exercise capacity ( P > 0.0001); no association was found with skeletal muscle fat infiltration nor visceral AT. Treatment with the insulin sensitizer PPARγ agonist rosiglitazone in patients with T2DM and CAD is associated with a worsening in aerobic exercise capacity, which seems to be mainly attributable to weight gain and subcutaneous fat mass expansion.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".