Delays in Filling Clopidogrel Prescription After Hospital Discharge and Adverse Outcomes After Drug-Eluting Stent Implantation
Bibliographic record
Abstract
BACKGROUND: Adjuvant clopidogrel therapy is essential after drug-eluting stent (DES) implantation. The frequency with which patients delay filling a clopidogrel prescription after DES implantation and the association of this delay with adverse outcomes is unknown. METHODS AND RESULTS: This was a retrospective cohort study of patients discharged after DES implantation from 3 large integrated health care systems. Filling a clopidogrel prescription was based on pharmacy dispensing data. The primary end point was all-cause mortality or myocardial infarction (MI). Of 7402 patients discharged after DES implantation, 16% (n=1210) did not fill a clopidogrel prescription on day of discharge and the median time delay was 3 days (interquartile range, 1 to 23 days). Compared with patients filling clopidogrel on day of discharge, patients with any delay in filling clopidogrel had higher death/MI rates during follow-up (14.2% versus 7.9%; P<0.001). In multivariable analysis, patients with any delay had increased risk of death/MI (hazard ratio, 1.53; 95% confidence interval, 1.25 to 1.87). Patients with any delay remained at increased risk of adverse outcomes when the delay cutoff was changed to >1, >3, or >5 days after discharge. Factors associated with delay included older age, prior MI, diabetes, renal failure, prior revascularization, cardiogenic shock, in-hospital bleeding, and clopidogrel use within 24 hours of admission. CONCLUSIONS: One in 6 patients delay filling their index clopidogrel prescription after hospital discharge after DES implantation. This delay was associated with increased risk of adverse outcomes and highlights the importance of the transition period from hospital discharge to outpatient setting as a potential opportunity to improve care delivery and patient outcomes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".