Suboptimal use of risk reduction therapy in peripheral arterial disease patients at a major teaching hospital
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Current evidence suggests that modification of atherosclerosis risk factors plays an important role in reducing adverse cardiovascular outcomes in patients with peripheral arterial disease (PAD). This study was undertaken to determine whether patients in this high-risk group were adequately using risk factor modification therapy. DESIGN AND SETTING: Prospective study of consecutive patients with PAD from a teaching hospital. PATIENTS AND METHODS: The collected data included information about atherosclerotic risk factors and utilization of risk factor modification therapy RESULTS: The 391 patients had a mean (standard deviation of 3 (1) atherosclerotic risk factors. Hypertension was identified in 56.8% of patients (222/391), of whom only 37.4% (83/222) had adequate blood pressure control (BP <140/90 mm Hg). The prevalence of diabetes mellitus (DM) was 35 % (137/391). Among patients with DM, only 49% (67/137) had adequate blood glucose control (glycosylated hemoglobin, HbA1c <7%). Statins were currently prescribed in 61% of patients (238/391), 38.7% (92/238) of whom continued to have low-density lipoprotein (LDL) >2.5 mmol/L, compared to a rate of 76.5% (117/153) among non-statin users (P<.001). The majority of patients of patients ( 72.4%; 283/391) were overweight/obese. Many patients (67.3%; 263/391) were nonsmokers; however, most (73.4%; 193/263) had a history of smoking. Antiplatelets were prescribed for 78.3% of patients (306/391), of whom 70.6% (216/306) were taking aspirin. Angiotensin converting enzyme (ACE) inhibitors were prescribed for 44.8% of patients (175/391). Among rampril users, only 36.8% of patients (53/144) were on an optimal dose. CONCLUSION: Although atherosclerotic risk factors were prevalent in patients with PAD, we found that patients received sub-optimal use of risk reduction treatments. Effective strategies to encourage health professionals to use these adjunctive therapies need to be developed.
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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) | 0.001 | 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) | 0.001 | 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".