Statin Utilization and Recommendations Among HIV- and HCV-infected Veterans: A Cohort Study
Bibliographic record
Abstract
BACKGROUND: Human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections are associated with increased risk of cardiovascular disease (CVD). The potential impact of recently updated cholesterol guidelines on treatment of HIV- and HCV-infected veterans is unknown. METHODS: We performed a retrospective cohort study to assess statin use and recommendations among 13 579 HIV-infected, 169 767 HCV-infected, and 6628 HIV/HCV-coinfected male veterans aged 40-75 years. Prior 2004 Adult Treatment Panel (ATP-III) guidelines were compared with current 2013 American College of Cardiology/American Heart Association (ACC/AHA) cholesterol guidelines and 2014 US Department of Veterans Affairs (VA)/US Department of Defense (DoD) joint clinical practice guidelines using laboratory, medication, and comorbidity data from the VA Clinical Case Registry from 2008 through 2010. RESULTS: Using risk criteria delineated by the ATP-III guidelines, 50.6% of HIV-infected, 45.9% of HCV-infected, and 33.8% of HIV/HCV-coinfected veterans had an indication for statin therapy. However, among those eligible, 22.7%, 30.5%, and 31.5%, respectively, were not receiving ATP-III recommended statin therapy. When current cholesterol guidelines were applied by VA/DoD and ACC/AHA criteria, increases in recommendations for statins were found in all groups (57.3% and 66.1% of HIV-infected, 64.4% and 73.7% of HCV-infected, 49.1% and 58.5% of HIV/HCV-coinfected veterans recommended). CONCLUSIONS: Statins were underutilized among veterans infected with HIV, HCV, and HIV/HCV according to previous ATP-III guidelines. Current VA/DoD and ACC/AHA guidelines substantially expand statin recommendations and widen the gap of statin underutilization in all groups. These gaps in care present an opportunity to improve CVD prevention efforts in these at-risk populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".