Abstract 17580: Angina Pectoris in Diabetic Patients: Insights From the Duke Databank for Cardiovascular Disease
Bibliographic record
Abstract
Background: Angina pectoris (AP) has different prognostic implications in various populations. Patients with diabetes mellitus (DM) may experience neuropathy such that AP may not be perceived in the setting of coronary artery disease (CAD). The association between the presence or absence of AP in DM patients with CAD is unknown. Methods: We analyzed DM patients with obstructive CAD who underwent coronary angiography at Duke University Medical Center from 2002 to 2011 and compared patients without AP to those with AP. DM and AP were defined based on physician-obtained past medical history at catheterization. Patients were categorized as no AP, atypical AP or typical AP within the 6 weeks prior. We assessed the association with subsequent cardiovascular (CV) death/CV hospitalization and all-cause mortality in patients with no or atypical AP relative to typical AP using multivariable Cox proportional hazards analysis. Results: In the Duke Databank, 5550 patients met criteria for inclusion and 1732 (31%) had no AP, 1075 (19%) had atypical AP and 2743 (50%) had typical AP. Those without AP more often had a prior MI and lower ejection fraction, but had similar HbA1c values compared to those with atypical AP or typical AP. Over a median follow-up of 5.4 years (IQR: 2.9-8.8), the lack of recent AP was associated with increased risk for outcomes (Table). Following adjustment, the lack of recent AP was independently associated with increased mortality compared to typical AP. Conclusions: In DM patients with CAD, the lack of AP was associated with increased mortality, but similar risk for CV events compared to patients with typical AP. Future studies are needed to assess whether these findings are related to increased severity of disease in those without AP or whether AP leads to differential management that improves survival.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".