Bibliographic record
Abstract
1.2.5 Conclusions. HNHD is a cost-effective dialysis modality, expected to be dominant when compared to IHD under usual conditions. The strength of our conclusions is limited by the non-randomized design. 1.2.1 Introduction. This thesis compares the relative cost-effectiveness of two forms of hemodialysis, conventional in-centre hemodialysis (IHD), where treatments take place in the hospital three times a week for four hours, and home nocturnal hemodialysis (HNHD), where treatments take place overnight in the home for six to eight hours. 1.2.3 Methods. We performed a one-year prospective costing study, during which 19 IHD and 24 HNHD patients underwent interviews to assess their utility score for current health by the standard gamble method. We used decision analysis techniques to examine the relative cost-effectiveness of HNHD and IHD over a lifetime with end stage renal disease using a Markov state-transition model comparing two strategies: only IHD or starting on IHD and subsequently transferring to HNHD. In addition, we examined methodological issues that arose during these studies. 1.2.4 Results. The total cost for health care delivery was 20% less for HNHD with projected mean annual costs more than $10,000 lower ($56,394 vs. $68,935). HNHD was associated with a higher utility score (0.77 +/- 0.23 vs. 0.53 +/- 0.35, p=.03), and was the dominant strategy with an incremental cost-effectiveness ratio (ICER) of $45,932 saved per quality-adjusted life years (QALY) gained. In the decision analysis, HNHD was associated with a quality-adjusted survival estimate of 5.79 QALYs, with lifetime costs of $538,094. The values for IHD were 5.31 QALYs and $543,602 respectively, yielding an ICER of $11,475 saved per QALY gained. Important determinants of cost-effectiveness were transplantation time and whether benefits declined over time. Methodological issues were identified in modeling two time periods, interpreting cost-effectiveness acceptability curves, and eliciting preferences by different techniques. 1.2.2 Population. We compared all patients from the HNHD program at the Humber River Regional Hospital (n=33), and patients from the IHD program at St. Michael's Hospital in Toronto (n=23), selected if they were felt to be suitable for and interested in home hemodialysis. The groups were demographically similar.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".