Abstract 12428: Efficacy of a Risk Reduction Program to Improve Cardiovascular Outcomes in Patients With Peripheral Arterial Disease: A Propensity Score-Matched Study
Bibliographic record
Abstract
Introduction: Patients with peripheral arterial disease (PAD) are often undertreated for cardiovascular (CV) risk factors, and they are at high risk for CV events. Hypothesis: A program that focuses on guideline-based risk factor management reduces adverse CV and limb events in PAD patients. Methods: A propensity-score matched observational cohort study with up to 7 years of follow-up was conducted using administrative databases in Ontario, Canada. Symptomatic PAD patients that were enrolled in the Systematic Assessment of Vascular Risk (SAVR) program between July 2004 and April 2007 were matched with up to 2 (control) patients with PAD from other Ontario tertiary vascular centers not enrolled in the program. The primary outcome was a composite of death, stroke or myocardial infarction (MI). Secondary outcomes included lower limb amputation and revascularization procedures. Cox proportional hazards regression analysis was used to compare outcomes between the groups. Results: A total of 791 patients were studied. During follow-up, the SAVR group (n=290) experienced the primary outcome at a significantly lower rate than the control group (adjusted HR, 0.64 [95% CI, 0.52 to 0.78]; P<0.001) (Figure). SAVR patients were also less likely to undergo major amputation (adjusted HR, 0.47 [95% CI, 0.29 to 0.77]; P=0.002), minor amputation (adjusted HR, 0.26 [95% CI, 0.13 to 0.54]; P<0.001), arterial bypass surgery (adjusted HR, 0.47 [95% CI, 0.30 to 0.73]; P<0.001), and less likely to have a hospitalization due to heart failure (adjusted HR, 0.73 [95% CI, 0.53 to 0.998]; P=0.048). The rate of peripheral angioplasty was higher among the SAVR group (adjusted HR, 3.0 [95% CI, 2.2 to 4.1]; P<0.001). Conclusions: A multifactor risk reduction program targeted to patients with PAD is associated with fewer adverse CV and limb events over the long-term. Greater focus is needed on developing structured programs for risk factor control in these high-risk patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".