Conversion of the Seattle Angina Questionnaire into EQ-5D utilities for ischemic heart disease: a systematic review and catalog of the literature
Bibliographic record
Abstract
BACKGROUND: There is a paucity of preference-based (utility) measures of health-related quality of life for patients with ischemic heart disease (IHD); in contrast, the Seattle Angina Questionnaire (SAQ) is a widely used descriptive measure. Our objective was to perform a systematic review of the literature to identify IHD studies reporting SAQ scores in order to apply a mapping algorithm to convert these to preference-based scores for secondary use in economic evaluations. METHODS: Relevant articles were identified in MEDLINE (Ovid), EMBASE (Ovid), Cochrane Library (Wiley), HealthStar (Ovid), and PubMed from inception to 2012. We previously developed and validated a mapping algorithm that converts SAQ descriptive scores to European Quality of Life-5 Dimensions (EQ-5D) utility scores. In the current study, this mapping algorithm was used to estimate EQ-5D utility scores from SAQ scores. RESULTS: Thirty-six studies met the inclusion criteria. The studies were categorized into three groups, ie, general IHD (n=13), acute coronary syndromes (n=4), and revascularization (n=19). EQ-5D scores for patients with general IHD were in the range of 0.605-0.843 at baseline, and increased to 0.649-0.877 post follow-up. EQ-5D scores for studies of patients with recent acute coronary syndromes increased from 0.706-0.796 at baseline to 0.795-0.942 post follow-up. The revascularization studies had EQ-5D scores in the range of 0.616-0.790 at baseline, and increased to 0.653-0.928 after treatment; studies that focused only on coronary artery bypass grafting increased from 0.643-0.788 at baseline to 0.653-0.928 after grafting, and studies that focused only on percutaneous coronary intervention increased in score from 0.616-0.790 at baseline to 0.668-0.897 after treatment. CONCLUSION: In this review, we provide a catalog of estimated health utility scores across a wide range of disease severity and following various interventions in patients with IHD. Our catalog of EQ-5D scores can be used in IHD-related economic evaluations.
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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 | 0.023 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.039 | 0.032 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 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".