Cost-utility of enoxaparin compared with unfractionated heparin in unstable coronary artery disease
Bibliographic record
Abstract
Low molecular weight heparins hold several advantages over unfractionated heparin including convenience of administration. Enoxaparin is one such heparin licensed in the UK for use in unstable coronary artery disease (unstable stable angina and non-Q wave myocardial infarction). In these patients, two large randomised controlled trials and their meta-analysis showed small benefits for enoxaparin over unfractionated heparin at 30–43 days and potentially at one year.<br/><br/>We found no relevant published full economic evaluations, only cost studies, one of which was conducted in the UK. The other studies, from the US, Canada and France, are difficult to interpret since their resource use and costs may not reflect UK practice.<br/><br/>Methods<br/>We aimed to compare the benefits and costs of short-term treatment (two to eight days) with enoxaparin and unfractionated heparin in unstable coronary artery disease. We used published data sources to estimate the incremental cost per quality adjusted life year (QALY), adopting a NHS perspective and using 1998 prices.<br/><br/>Results<br/>The base case was a 0.013 QALY gain and net cost saving of £317 per person treated with enoxaparin instead of unfractionated heparin. All but one sensitivity analysis showed net savings and QALY gains, the exception (the worst case) being a cost per QALY of £3,305. Best cases were a £495 saving and 0.013 QALY gain, or a £317 saving and 0.014 QALY gain per person.<br/><br/>Conclusions<br/>Enoxaparin appears cost saving compared with unfractionated heparin in patients with unstable coronary artery disease. However, cost implications depend on local revascularisation practice.<br/>
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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".