AB022. SOH23ABS_065. Barriers to the prescription of ACE inhibitors in patients with peripheral arterial disease or related cardiovascular disease
Bibliographic record
Abstract
Background: Guidelines recommend that patients with peripheral arterial disease (PVD) should be medically treated to reduce the occurrence of serious cardiovascular events. Angiotensin-converting enzyme inhibitors (ACE-Is) and angiotensin receptor blockers (ARBs) are recommended in this cohort but the rate of prescription of ACE-Is is low. We identified factors associated with the prescription of ACE-Is in patients with symptomatic PAD. Methods: Using the vascular quality initiative (SVS-VQI) database, we evaluated the medical management of 1,239 patients that had undergone procedures for PVD 2017–2021. We collected baseline data, number of patients prescribed ACE-Is or (ARBs), number of patients who were not and any medical reason indicated. Results: At time of procedure, average patient age was 67.2 years and included 829 males and 410 females. Comorbidities included 1,062 (86%) patients with diabetes, 151 (12%) on dialysis, 1,039 (84%) with hypertension, 351 (28%) with coronary artery disease, and 966 (78%) with history of smoking; 876 (70.1%) patients were on aspirin, and 1,024 (83%) were on a statin drug; 556/1,239 (45%) patients were not prescribed ACE-Is/ARBs, 89 (0.07%) patients had a medical reason and 467 (38%) patients had no medical reason for not being prescribed ACE-Is/ARBs. Conclusions: About 40% of the patients with peripheral arterial disease were not optimally managed with ACE-Is/ARBs. We still need to better understand the barriers and facilitators to the application of the guidelines.
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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".