Diastolic Dysfunction in Normotensive Men with Well-Controlled Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Because a pseudonormal pattern of ventricular filling has never been considered in studies that reported a prevalence of left ventricular diastolic dysfunction (LVDD) between 20 and 40%, our aim was to more completely evaluate the prevalence of LVDD in subjects with diabetes. RESEARCH DESIGN AND METHODS: We studied 46 men with type 2 diabetes who were aged 38-67 years; without evidence of diabetic complications, hypertension, coronary artery disease, congestive heart failure, or thyroid or overt renal disease; and with a maximal treadmill exercise test showing no ischemia. LVDD was evaluated by Doppler echocardiography, which included the use of the Valsalva maneuver and pulmonary venous recordings to unmask a pseudonormal pattern of left ventricular filling. RESULTS: LVDD was found in 28 subjects (60%), of whom 13 (28%) had a pseudonormal pattern of ventricular filling and 15 (32%) had impaired relaxation. Systolic function was normal in all subjects, and there was no correlation between LVDD and indexes of metabolic control. CONCLUSIONS: LVDD is much more common than previously reported in subjects with well-controlled type 2 diabetes who are free of clinically detectable heart disease. The high prevalence of this phenomenon in this high-risk population suggests that screening for LVDD in type 2 diabetes should include procedures such as the Valsalva maneuver and pulmonary venous recordings to unmask a pseudonormal pattern of ventricular filling.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".