Systematic review of the cost-effectiveness of interventions for heart valve replacement
Bibliographic record
Abstract
Background Heart valve replacement (HVR) is necessary when patients with valvular heart disease (VHD) reach a certain degree of severity; otherwise there is a high mortality within the next few years. The systematic review answers the question about the hight of the reported cost-effectiveness in studies investigating different options for HVR using a decision analytical model (DAM). Methods We performed a systematic review in the databases PubMed, Web of Science, NHS EED, HTA and EconBiz without any time restrictions. As completeness check for our review we searched DARE and Cochrane Library additionally for reviews and performed a cross-check in the reference lists of the included studies. We included only original studies and HTAs, which investigated both costs and benefits in a comparative DAM approach to compute the ICER. For analysis we used the CHEERS-Checklist. Preliminary Results Initially we identified 2.313 references. After screening we included 20 papers. Studies were primarily performed in the UK, Canada and the USA. Frequently studies used a Markov model (n = 11) with mostly yearly cycles (n = 10) to estimate the cost-effectiveness. The Markov model often starts with a hypothetical cohort of high-risk or inoperable patients aged either 60, 70 or mostly 80 years with degenerative VHD (aortic stenosis n = 14 or mitral insufficiency n = 6). The incremental cost-effectiveness ratio varied notably between studies (range: €7,908 - €750,000 per quality-adjusted life-year gained). This range may be explained by different frameworks of the DAM. The majority of the studies took the perspective of the third party payer (n = 15) and used a lifetime horizon (n = 9). Conclusions (a) Initiating more research concerning other patient populations with VHD (e.g. children, adolescents, young adults) and patients living in countries outside of Europe and the USA (b) Strengthening standardization of DAM for economic evaluations to improve comparability between studies Key messages: Economic evaluations using DAM are common in cardiovascular research. However there is a lack of standardization in such studies and of certain patient populations like children.
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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 | 0.017 | 0.089 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".