Appropriate Reconciliation of Cardiovascular Medications After Elective Surgery and Postdischarge Acute Hospital and Ambulatory Visits
Bibliographic record
Abstract
OBJECTIVE: To describe appropriate discharge reconciliation of cardiovascular medications and assess associations with postdischarge healthcare utilization in surgical patients. DESIGN: Retrospective cohort study from January 2007 to December 2011. SETTING: An academic medical center. PATIENTS: Seven hundred and fifty-two adults undergoing elective noncardiac surgery and taking antiplatelet agents, beta-blockers, renin-angiotensin system inhibitors, or statin lipid-lowering agents before surgery. MEASUREMENTS: Primary predictor: appropriate discharge reconciliation of preoperative cardiovascular medications (continuation without documented contraindications). Primary outcomes: acute hospital visits (emergency department visits or hospitalizations) and unplanned ambulatory visits (primary care or surgical) at 30 days after surgery. RESULTS: Preoperative medications were appropriately reconciled in 436 (58.0%) patients. For individual medications, appropriate discharge reconciliation occurred for 156 of the 327 patients on antiplatelet agents (47.7%), 507 of the 624 patients on beta-blockers (81.3%), 259 of the 361 patients on renin-angiotensin system inhibitors (71.8%), and 302 of the 406 patients on statins (74.4%). In multivariable analyses, appropriate reconciliation of all preoperative medications was not associated with acute hospital (adjusted odds ratio [AOR], 0.94; 95% confidence interval [CI], 0.63-1.41) or unplanned ambulatory visits (AOR, 1.48; 95% CI, 0.94-2.35). Appropriate reconciliation of statin therapy was associated with lower odds of acute hospital visits (AOR, 0.47; 95% CI, 0.26-0.85). There were no other statistically significant associations between appropriate reconciliation of individual medications and either outcome. CONCLUSIONS: Although large gaps in appropriate discharge reconciliation of chronic cardiovascular medications were common in patients undergoing elective surgery, these gaps were not consistently associated with postdischarge acute hospital or ambulatory visits.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".