Cost-Effectiveness Analysis of High-Efficiency Hemodiafiltration Versus Low-Flux Hemodialysis Based on the Canadian Arm of the CONTRAST Study
Bibliographic record
Abstract
AIM: The aim of this study was to assess the cost effectiveness of high-efficiency on-line hemodiafiltration (OL-HDF) compared with low-flux hemodialysis (LF-HD) for patients with end-stage renal disease (ESRD) based on the Canadian (Centre Hospitalier de l'Université de Montréal) arm of a parallel-group randomized controlled trial (RCT), the CONvective TRAnsport STudy. METHODS: An economic evaluation was conducted for the period of the RCT (74 months). In addition, a Markov state transition model was constructed to simulate costs and health benefits over lifetime. The primary outcome was costs per quality-adjusted life-year (QALY) gained. The analysis had the perspective of the Quebec public healthcare system. RESULTS: A total of 130 patients were randomly allocated to OL-HDF (n = 67) and LF-HD (n = 63). The cost-utility ratio of OL-HDF versus LF-HD was Can$53,270 per QALY gained over lifetime. This ratio was fairly robust in the sensitivity analysis. The cost-utility ratio was lower than that of LF-HD compared with no treatment (immediate death), which was Can$93,008 per QALY gained. CONCLUSIONS: High-efficiency OL-HDF can be considered a cost-effective treatment for ESRD in a Canadian setting. Further research is needed to assess cost effectiveness in other settings and healthcare systems.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".