Left Ventricular Diastolic Dysfunction and Its Predictive Factors Among Saudi Patients With Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: Diabetes mellitus places a significant burden on society in terms of healthcare expenditures and poor health outcomes and complications. Heart failure is one of its complications which increases morbidity and mortality for patients with diabetes. The purpose of this study was to assess the prevalence of left ventricular diastolic dysfunction (LVDD) and its predictors among Saudi patients with type 2 diabetes mellitus (T2DM). Methods: This retrospective cross-sectional study was conducted between May 2021 and May 2022 at King Saud University Medical City in Riyadh, Saudi Arabia. Medical records of adult patients with T2DM without prior cardiovascular disease who underwent echocardiographic examination were reviewed, and data were extracted. Echocardiographic findings were reviewed for the diagnosis of LVDD. Results: A total of 251 participants were included in the study. LVDD was diagnosed in 66.9% of the participants. The majority (89.9%) had grade I. The mean age was 59 ± 9.1 years and the mean diabetes duration was 20 ± 8.5 years. Of the patients, 76.9% had hypertension and 81.2% had dyslipidemia. The mean body mass index was 32.9 ± 6.6 kg/m2 and the mean glycated hemoglobin level was 7.7±2.3%. LVDD correlated with older age, longer duration of diabetes, obesity, poor glycemic control, higher systolic blood pressure, the presence of hypertension, and the usage of antihypertensive and lipid-lowering medications. In logistic regression analysis, older age and higher body mass index were the only independent risk factors of LVDD. Conclusion: The prevalence of LVDD among Saudi patients with T2DM was high. It was associated significantly with age and obesity. These findings highlight the need for early monitoring, and treatment to prevent its progression and reduce morbidity and mortality.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".