Is cardiorespiratory fitness a determinant of cardiomyopathy in the setting of type 2 diabetes?
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine whether high fitness attenuates the defects in left ventricular (LV) structure, function and triglyceride (TG) content in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: Patients (n = 74) with T2DM and ≥1 additional cardiac risk factor were recruited to participate in this cross-sectional study. Outcome measures of interest were LV structure and function by magnetic resonance imaging (MRI) and myocardial TG content by (1)H-magnetic resonance spectroscopy (MRS). The primary exposure variable was cardiorespiratory fitness defined by peak oxygen consumption scaled to fat-free mass (FFM; VO2peak-FFM). RESULTS: Mean age was 53.5 years; 42.9% were women and mean glycosylated haemoglobin (HbA1c) was 8.0% with the mean duration of T2DM 8.2 years. VO2peak-FFM was crudely associated with both LV end systolic (r = 0.35, p = 0.002) and diastolic volumes (r = 0.32, p = 0.004), but not with ejection fraction (r = -0.15, p = 0.206), myocardial TG (r = -0.04, p = 0.734) or early diastolic peak filling rate (PFR; r = -0.01, p = 0.887). In multiple linear regression analyses, among measures of LV structure/function, VO2peak-FFM was independently associated only with LV end-diastolic volume (EDV) (β = 1.037, p = 0.038). CONCLUSION: In individuals with T2DM at increased cardiovascular (CV) risk, cardiorespiratory fitness is not associated with LV morphology, function or myocardial TG content.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".