Abstract 3685: Reduced Systemic Arterial Compliance is an Independent Predictor of Mortality in Patients with Diabetes
Bibliographic record
Abstract
Background: Diabetes is associated with accelerated vascular calcification and stiffening of the arteries. Reduced systemic arterial compliance (SAC) is regarded as a major factor in the development of hypertension, contributing to increased left ventricular afterload and myocardial oxygen demand and reduced coronary flow reserve. We thus hypothesized that reduced SAC is an independent predictor of mortality in patients with diabetes. Methods: We retrospectively analyzed data of 528 consecutive patients with type 2 diabetes who had a Doppler-echocardiographic exam in our institution. Blood pressure was measured in all patients at the time of echocardiography. SAC was calculated as the ratio of stroke volume index to arterial pulse pressure. Results: Follow up was completed in 97% of patients and mean follow-up time was 2.9±1.2 years. Mean age was 66±11 years with 68% males and 68% with coronary artery disease (CAD). Fifty percent of the patients had markedly reduced SAC on the basis of the cut-off value (SAC <0.6 ml/m 2 /mmHg) previously reported to be associated with adverse outcome in patients with hypertension. Patients with reduced SAC were significantly older (68±11 vs. 65±10, p=0.002) and had a higher prevalence of hypertension (78 vs. 22%, p<0.0001) and lower LV ejection fraction (51±15 vs. 57±13%, p=0.001). The prevalence of male gender, CAD, and obesity assessed with body mass index (BMI) was similar in patients with reduced SAC compared to those with higher SAC values. Five-year survival was significantly lower in patients with reduced SAC (68±5 vs. 87±4%, p<0.005). After adjusting for age, gender, LV ejection fraction, CAD, BMI, and blood pressure, reduced SAC remained a powerful and independent predictor of total mortality (Hazard ratio: 1.70 95% Confidence interval: 1.14 –2.58; p=0.008). Conclusion : Reduced SAC is encountered frequently in patients with type 2 diabetes and is a major risk factor for total mortality in this population. The SAC, which is easily measurable in the context of routine echocardiographic exam, should be taken into consideration when evaluating these patients with regards to prognosis and treatment. Funded by: Québec Heart Institute Foundation
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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 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".