Moving beyond the cost per quality-adjusted life year: modelling the budgetary impact and clinical outcomes associated with the use of sirolimus-eluting stents.
Bibliographic record
Abstract
Restenosis is a major limitation to the long-term success of percutaneous coronary intervention. Drug-eluting stents are the most recent technological advance in restenosis prevention. While they are effective, their use is associated with a significant incremental cost, and a recent economic evaluation performed by the authors suggested that their use is associated with a cost per quality-adjusted life year of $58,721. How should decision-makers react to this value, particularly given that the use of sirolimus-eluting stents appears more attractive in certain patient subgroups, such as those with complex coronary lesions? In the present paper, the authors explore an alternative method of presenting the results of their economic evaluation, rather than the usual cost per quality-adjusted life year rubric, in an attempt to assist decision-makers in deciding whether, and for whom, to fund sirolimus-eluting stents. Several issues that decision-makers and providers may wish to consider when making such funding decisions are discussed.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".