Potentially Unintended Discontinuation of Long-term Medication Use After Elective Surgical Procedures
Bibliographic record
Abstract
BACKGROUND: Transitions between health care settings represent vulnerable periods for medical error. Discontinuation of long-term medication use may occur during discharge from the hospital to the community. METHODS: We performed a population-based, cohort study using administrative records from Ontario, Canada, between April 1, 1997, and September 30, 2002. We studied all residents 66 years and older with continuous use of warfarin, 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors (statins), or beta-blocker ophthalmic drops for 1 or more years. Those who had an overnight hospitalization for selected elective surgical procedures were compared with 2 control groups: one that had an ambulatory procedure and one that had no procedures. All groups were assessed for the outcome of failure to renew the prescription within 6 months. RESULTS: Rates of drug treatment discontinuation after overnight hospitalizations, after ambulatory procedures, and after no procedures were 11.4%, 7.5%, and 4.8%, respectively, in the warfarin group; 4.0%, 3.9%, and 3.9%, respectively, in the statin group; and 8.4%, 8.9%, and 7.9%, respectively, in the ophthalmic drops group. The adjusted odds ratio (OR) was 2.6 (95% confidence interval [CI], 2.0-3.4) for discontinuation of warfarin therapy after overnight hospitalizations and 1.6 (95% CI, 1.4-1.7) after ambulatory procedures. In contrast, there was no increased risk of discontinuing treatment with either statins (OR for overnight hospitalization, 1.0 [95% CI, 0.9-1.2]; OR for ambulatory procedure, 1.0 [95% CI 1.0-1.1]) or ophthalmic drops (OR for overnight hospitalization, 1.0 [95% CI, 0.8-1.5]; OR for ambulatory procedure, 1.1 [95% CI, 1.0-1.2]). CONCLUSIONS: Patients prescribed long-term therapy with warfarin were at risk for potentially unintended medication discontinuation after elective procedures. Patients prescribed statins or beta-blocker ophthalmic drops were not at increased risk.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".