Cost‐effectiveness of clopidogrel in acute coronary syndromes in Sweden: a long‐term model based on the cure trial
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to evaluate the long-term cost-effectiveness of clopidogrel on top of standard therapy (including ASA) in patients with acute coronary syndromes without ST-segment elevation in Sweden. METHODS AND RESULTS: Incremental cost-effectiveness ratios (ICER) were assessed using a Markov model with transition probabilities estimated from the Swedish hospital discharge and cause of death registers. Patients were assumed to be treated for 1 year, with treatment effects (RR = 0.8) and costs taken from the Clopidogrel in Unstable Angina to prevent Recurrent ischaemic Events Trial. Two scenarios were analysed: with patients similar to those in the trial and with patients similar to those from the register. In the first scenario, the predicted net direct cost was 160 euro and the net total cost -54 euro, which with an incremental survival of 0.12 years give the ICER of 1365 euro per life-year gained from the health care payer perspective (including direct costs) and cost savings from the societal perspective (also including indirect costs). The net costs in the second scenario were 149 euro, giving an ICER of 1009 euro for both perspectives. CONCLUSIONS: Adding clopidogrel to standard therapy including ASA is cost-effective in the studied setting and compares favourably with other cardiovascular treatment and prevention strategies.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".