Abstract P250: Emergency Room Consultations and Hospitalizations Following Generic Clopidogrel Commercialization in Quebec, Canada
Bibliographic record
Abstract
Background: Clopidogrel is widely used to prevent atherothrombotic events. Federal standards regulate bioequivalence of generic and brand-name drugs through comparative bioavailability studies but does not regulate clinical equivalence nor tolerability in “real-life” settings. We evaluated the impact of the generic clopidogrel commercialization on some adverse events: emergency room consultations (ER) or hospitalizations. Methods: This is an interrupted time series analysis using the Quebec Integrated Chronic Disease Surveillance System. Rates of adverse events for clopidogrel users (n=75,130) aged ≥ 66 years were calculated monthly, 12 months before and 12 months after generics commercialization. Periods before and after generics commercialization were compared by negative binomial segmented regression models for all users with a specific variable for generic and brand-name users after generics commercialization. Results: Generic clopidogrel analogs (n=6) were commercialized in 2012. There was an approximated monthly mean rate of 157 adverse events per 1000 brand-name and generic users-month. After generics commercialization, there was an immediate increase in rates of adverse events for generic vs. brand-name users (22 vs. 2%, p < 0.0001, Figure 1). This was explained by increased rates of ER (+22%) and hospitalizations (+20%) the month of generic clopidogrel commercialization. Hospitalization trend up to 1 year after generics commercialization was stable for generic users but reduced for brand-name users (-0.9 vs. -2.9%, p = 0.01), while ER trends were comparable (-1.1 vs. -1.8%, p = 0.2443). Conclusion: Among generic clopidogrel users, increased rates of ER and hospitalizations were observed soon after generics commercialization. The trend of hospitalizations was also affected following generic clopidogrel commercialization. Risk and survival analysis studies controlling for potential confounding are required to better characterize generic substitution.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".