Appropriateness of Ticagrelor Use at Initiation: A Population-Based Cohort Study
Bibliographic record
Abstract
PURPOSE: Ticagrelor is recommended following an acute coronary syndrome if used appropriately. Its use has not yet been well described in the context of ambulatory clinical practice. The objective of this study was to assess the proportion of ticagrelor new users who initiated this medication appropriately and explore associated factors. METHODS: A retrospective population-based inception cohort study was conducted using Quebec administrative databases. The study population included all Quebec residents aged ≥18 years who had a first ticagrelor prescription claim between 1 January, 2012, and 31 March, 2015, and had been continuously eligible in the Quebec public drug plan during the 365 days preceding the first ticagrelor claim. The initial ticagrelor prescription was considered appropriate if:1) it met the indication for use criterion, 2) the prescribed daily dose was 90 mg twice a day, and 3) there was a concomitant use of acetylsalicylic acid (ASA) 80-81 mg daily. Factors potentially associated with the ticagrelor appropriateness of use were included in a logistic log-binomial regression model. RESULTS: A total of 7,073 patients were included in the study, 6,013 (85.0%) had an appropriate indication, 6,895 (97.5%) were prescribed ticagrelor 90 mg twice a day, and 6,385 (90.3%) had a concomitant prescription of ASA. A total of 5,371 (75.9%) patients were prescribed ticagrelor in accordance with all criteria. Twelve factors were associated with prescription appropriateness. CONCLUSIONS: A large majority of patients initiated ticagrelor appropriately. Further improvement in appropriateness may come at targeting indication for use.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".