Abstract 195: Statin Use and Its Facility Level Variation in Patients With Ischemic Cerebrovascular Disease: Insights From the Department of Veterans Affairs
Bibliographic record
Abstract
Background: The 2013 ACC/AHA cholesterol guideline recommends high-intensity statin therapy in patients 75 or younger and moderate-intensity statins in patients > 75 years with atherosclerotic cardiovascular disease including those with ischemic cerebrovascular disease (ICVD). Statin prescribing patterns and their facility-level variation in patients with ICVD are unknown. Methods: We examined the frequency and facility-level variation in the use of any and correct intensity statins in patients with ICVD (ischemic stroke or carotid arterial disease) who received primary care in 130 facilities across the Veterans Affairs (VA) health care system with or without concomitant ischemic heart disease (IHD) or peripheral artery disease (PAD). We then calculated median rate ratios (MRR) adjusted for patient demographic factors to assess the magnitude of facility-level variation in statin prescribing patterns for comparable patients. Results: Among 339,771 ICVD patients, 182,231 (53.6%) had ICVD without IHD (with or without PAD) and 163,730 (48.2%) had ICVD without IHD or PAD. Rates of statin use in the entire ICVD group, patients with ICVD without IHD, and ICVD alone were 78.1%, 70.9% and 69.9%, respectively. Median facility-level rates of any statin use were 78.1% (IQR 75.5-80.7), 70.7% (67.9-73.8) and 69.9% (66.9-73.1), respectively. Correct intensity statins were prescribed among 40.2% of the entire ICVD group, 30.5% with ICVD without IHD, and 29.6% with ICVD alone. Median facility-level rate of correct statin use in all ICVD patients was 39.1% (35.8-43.9), 29.9% (26.0-34.6) for patients with ICVD without IHD and 29.0% (25.4-33.7) in those with ICVD alone.Calculated MRRs reflect approximately 22% variation among two facilities treating two identical ICVD patients with statin therapy and a 27-28% variation in identical ICVD patients for correct statin intensity (Table). Conclusions: The use of statin and especially guideline-recommended statin intensity is suboptimal in ICVD patients, especially patients without concomitant IHD or PAD. There is significant facility-level variation in receipt of guideline directed statin therapy in ICVD patients. Interventions are needed to improve guideline directed moderate to high-intensity statin use and reduce variation in care in this high risk group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".