Impact of routine in-hospital assessment of low-density lipoprotein levels and standardized orders on statin therapy in patients undergoing percutaneous coronary interventions.
Bibliographic record
Abstract
BACKGROUND: Previous studies have shown that a significant proportion of patients undergoing percutaneous coronary intervention (PCI) are not receiving guideline-recommended statin therapy upon hospital discharge. We evaluated the impact of the implementation of routine cholesterol profile measurements and standardized orders post-PCI on the number of patients receiving statin therapy. METHODS: We conducted a prospective, observational study on all patients undergoing PCI in an urban teaching hospital from February 2002 to March 2003. Patient baseline characteristics, statin therapy pre- and post-PCI, and fasting lipid profiles were recorded as part of an ongoing PCI database. A similar cohort of patients undergoing PCI in the one-year time period immediately before the intervention was used as a comparison group. RESULTS: A total of 1,748 patients underwent PCI during the study period. Statin therapy was prescribed in 78% of patients pre-PCI and increased to 92% at hospital discharge. In the year before implementation of the standardized post-PCI orders, there was only a 5% absolute increase in statin use after PCI compared to a 14% absolute increase in the study time period (p = < 0.0001). Low-density lipoprotein (LDL) levels were available in 1,268 patients. The median LDL level was 2.08 mmol/L for patients on statin therapy versus 2.40 mmol/L for those not on statins. CONCLUSIONS: Routine assessment of LDL levels and lipid-lowering therapy at the time of PCI resulted in a further increase in statin use. However, approximately one-third of patients still had an LDL level above recommended guidelines for secondary prevention.
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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 | 0.002 | 0.016 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".