Normalization of Diastolic Dysfunction in Type 2 Diabetics after Exercise Training
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate the impact of aerobic exercise training on left ventricular diastolic dysfunction (LVDD) and exercise capacity in subjects with type 2 diabetes. METHODS: Twenty-three sedentary subjects with well-controlled type 2 diabetes, free of coronary disease and having different degrees of LVDD, participated in the study. Subjects were treated with oral hypoglycemic agents and/or diet. Eleven subjects (EX) (age: 58 +/- 5 yr; mean +/- SD) underwent a 3-month aerobic exercise training program using a cycle ergometer, whereas a control group (CONT) of 12 subjects (57 +/- 6 yr) maintained their activities of daily living. Exercise capacity and LVDD, using echocardiography, were evaluated before and after the 3-month exercise program. RESULTS: At baseline, anthropometric data were similar between the groups, except for body mass index (BMI), which was higher in CONT (31 +/- 3 vs 28+/- 3 kg x m(-2); P < 0.05). There were no significant differences in glycemic control (HbA1c: 6.4 +/- 1.2 vs 5.8 +/- 1.3%; P = 0.2) or maximal oxygen uptake (26.7 +/- 5.9 vs 28.6 +/- 3.9 mL x kg(-1) x min(-1); P = 0.4) between groups. Normalization of LVDD was observed in 5 of 11 EX subjects, (P < 0.0001) of whom four had grade 1 LVDD before exercise training. No change in diastolic function was observed in the CONT group. After exercise training, maximal oxygen uptake increased in the EX group (28.6 +/- 3.9 vs 32.7 +/- 5.7 mL x kg(-1) x min(-1); P < 0.05), whereas there was no change in the CONT group (26.7 +/- 5.9 vs 27.3 +/- 6.2 mL x kg(-1) x min(-1); P = 0.58). In both groups, there was no significant change in BMI. CONCLUSIONS: Along with an improvement in exercise capacity, aerobic exercise training has the potential to reverse LVDD in patients with well-controlled, uncomplicated type 2 diabetes.
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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".