Cost-effectiveness of a single-layer high compression bandage versus Unna's boot for venous leg ulcer treatment: the VENOS trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the incremental cost-effectiveness and cost-utility ratios (ICER; ICUR) of a single-layer high compression bandage (SLHCB) compared with Unna's boot (UB) from the perspective of the Brazilian healthcare system, with a time horizon of 26 weeks. METHOD: A health economic evaluation of data from a prospective, randomised, open blinded endpoint study was conducted in 22 primary healthcare services in Porto Alegre city, Brazil, with patients with venous leg ulcers (VLUs) who were randomly allocated to receive SLHCB or UB. Participants were followed until VLU healing or up to 26 weeks. Nurses performed dressings weekly and blinded examiners measured the VLU size by planimetry at baseline and every two weeks. The Short Form-6 Dimensions questionnaire was applied at baseline and on the last day of follow-up to measure quality-adjusted life years (QALYs). The ICER and ICUR were estimated, and probabilistic sensitivity analyses performed. RESULTS: A total of 61 participants were enrolled in the trial, corresponding to 110 VLUs. SLHCB incurred an average expenditure of R$1118.74 (I$442.19) per VLU, while UB incurred R$1078.74 (I$426.38) per VLU. SLHCB exhibited a mean VLU reduction of 64.82% compared with 27.56% for UB. The mean QALY for SLHCB was 0.187 and 0.164 for UB. The ICER was 1.07 (0.42) per percentage point of VLUs healed and the ICUR was 1739.13 (687.40) per QALY gained. CONCLUSION: In this study, SLHCB was cost-effective when compared with UB. These findings may prompt decision-makers to weigh the prospect of allocating an additional R$1.07 (I$0.42) for each percentage point reduction in VLU area or R$1739.13 (I$687.40) per QALY gained. This financial consideration holds significant implications for guiding resource allocation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".