Comparison of mortality in patients with coronary or peripheral artery disease following the first vascular intervention
Bibliographic record
Abstract
OBJECTIVES: Patients with peripheral artery disease (PAD) less frequently achieve secondary prevention goals compared with patients with coronary artery disease (CAD). We aimed to compare mortality rates in patients with PAD and CAD following first vascular intervention. PATIENTS AND METHODS: Patients 18 years of age or older without a history of cardiovascular disease, who underwent first coronary or lower limb vascular intervention between 2002 and 2010, were included in this study. The primary endpoint was all-cause mortality. RESULTS: Of the 9950 participants, 8242 (82.8%) underwent first coronary revascularization and 1708 (17.2%) received first peripheral vascular intervention. During a mean follow-up period of 5.6±2.3 years, 1283 (12.9%) participants died. Compared with CAD patients, patients with PAD had significantly worse long-term prognosis with an increased risk for all-cause mortality (hazard ratio=2.95, 95% confidence interval 2.6-3.3, P<0.0001). This association remained statistically significant following a multivariable analysis (hazard ratio=1.86, 95% confidence interval 1.6-2.1, P<0.0001). Furthermore, PAD patients were less frequently treated with cardioprotective medications including statins, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, aspirin, and clopidogrel (P<0.001). CONCLUSION: Patients with PAD have worse outcome compared with patients with CAD, even in the specific group of patients following first vascular intervention. These findings demand more effort to improve secondary prevention guidelines in all patients with cardiovascular diseases, but especially in PAD patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".