Are brand-name and generic warfarin interchangeable?: a pharmacological and behavioural investigation
Bibliographic record
Abstract
Background. With Canada's approval in 2000 of two generic warfarin products, the need exists to address whether these brands can be safely interchanged with Coumadin and to determine physician and patient acceptance of generic warfarin. Methods. Multiple-crossover, N-of-1 trials switched patients between generic warfarin and Coumadin, with regular INR testing. Questionnaires on generic warfarin were developed; patient questionnaires were distributed at a Hamilton Anticoagulation Clinic, and physician questionnaires were mailed to 375 random Ontario physicians. Results. After five crossovers each, the three study patients did not have a significant difference in mean INR, dosage adjustments or INR variability between warfarin brands. Patient and physician questionnaires indicated neutral opinions overall, though statistically significant differences occurred based on responder demographic factors. Conclusions. Patients can safely and effectively switch between generic warfarin and Coumadin. While patients and physicians do not have extreme views on generic warfarin overall, a minority do have clear concerns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".