Abstract 11123: Outcomes After Percutaneous Coronary Intervention for Patients With Stable Coronary Disease and Left Ventricular Systolic Dysfunction
Bibliographic record
Abstract
Background: Clinical trial data suggest a modest improvement in outcomes when coronary bypass surgery (CABG) is added to medical therapy for patients with stable coronary artery disease (CAD) and left ventricular systolic dysfunction (LVSD). However, limited data are available to understand the impact of percutaneous coronary interventions (PCI) on mortality for patients with stable CAD and LVSD. Methods: We studied 901 patients in the Duke Databank for Cardiovascular Diseases. All patients underwent a coronary angiogram at Duke University for suspected CAD between 1995 and 2012. Patients included in the analysis all had CAD amenable to PCI (>50% stenosis) in at least 1 vessel, reduced LVEF (< 35%), and stable CAD. Patients with CCS class III or IV angina or CABG within 30 days were excluded. Of 901 patients, 259 were treated with PCI and 642 were treated with medical therapy. Propensity scores for PCI, created from 24 different variables (including age, LVEF, comorbid conditions, and medications), were used to assemble a matched cohort of 444 patients (222 pairs) receiving PCI or medical therapy alone. A survival curve was derived using the Kaplan-Meier method and the hazard ratio (HR) for mortality was estimated using Cox regression modeling. Results: In the matched cohort, the mean age was 63 years with 321 (72%) males. Three-vessel disease was present in 70 patients (16%). The mean EF was 27% and 153 (35%) reported NYHA Class III/IV symptoms; 392 (88%) were treated with beta-blockers and 378 (85%) with ACE-inhibitors or ARBs. Over 12 years of follow-up, patients in both groups had similar mortality (Figure), HR 0.87 (95% confidence interval 0.68-1.10). Conclusion: In this well-profiled, propensity-matched cohort, there was no significant difference in long-term mortality between patients treated with medical therapy alone or with medical therapy plus PCI. More studies are needed to understand the impact of PCI on other outcomes including symptoms and functional status.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".