Use of Perioperative Cardiac Medical Therapy Among Patients Undergoing Coronary Artery Bypass Graft Surgery
Bibliographic record
Abstract
BACKGROUND: Previous studies have demonstrated that cardiac medical therapy is associated with improved clinical outcomes in noncardiac surgery. However, the use of these agents among patients undergoing coronary artery bypass graft (CABG) remains poorly understood. METHODS: We described the in-hospital medication use among 2,389 consecutive patients who underwent CABG at three North American hospitals. Demographic, clinical, and medication use information was extracted from resource and cost accounting systems at each hospital. We examined use of aspirin, angiotensin-converting-enzyme (ACE) inhibitors, beta blockers, and statins during the following seven in-hospital periods: admission, presurgery, the day before surgery, the day of surgery, the day after surgery, postsurgery, and discharge. RESULTS: Medication use throughout hospitalization was low among patients undergoing CABG. Use of ACE inhibitors and statins on the day of surgery was <10%, while aspirin and beta blocker use on the day of surgery was 43.0% and 42.9%, respectively. The use of cardiac medical therapy at hospital discharge was also low (ACE inhibitors: 23.0%; aspirin: 74.9%; beta blockers: 58.9%; and statins: 28.2%). The use of cardiac medical therapy at discharge appeared to increase over time. CONCLUSION: In-hospital cardiac medical therapies are underused among patients undergoing CABG. This is particularly true at discharge, where the benefits of these agents for secondary prevention are well established.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".