The STARRT trial: a cost comparison of optimal vs sub-optimal initiation of dialysis in Canada
Bibliographic record
Abstract
BACKGROUND: Sub-optimal transitioning of patients from chronic kidney disease (CKD) to end stage renal disease (ESRD) may result in poor clinical outcomes and increased healthcare costs. The objectives of this study were to estimate the average total cost per patient who requires initiation of renal replacement therapy (RRT) stratified by status at initiation; optimal (RRT initiation as an outpatient with an arterio-venous [AV] Fistula, Graft or Peritoneal Dialysis [PD] catheter), and sub-optimal (RRT initiation as an inpatient and/or via central venous catheter [CVC]). METHODS: Data from the Study To Assess Renal Replacement Therapy (STARRT), a Canadian, multi-centre, 6 month retrolective study (n = 339), were used for this analysis. Unit costs for resources were obtained from participating hospitals, the literature, and/or standard costing sources. The analysis was performed from the perspective of healthcare payors and reported in 2011 Canadian Dollars (CAD). A propensity score technique was applied to control for potential confounders between the two groups. RESULTS: Two hundred of the eligible patients for analysis (61.9%) were sub-optimally and 123 (38.1%) were optimally prepared. For this analysis, 106 "matched" pairs were used. The average total cost per patient was estimated to be $63,225 (with a 95% CI ranging from $58,663-$67,958) for the sub-optimally initiated patients, and $39,260 (with a 95% CI ranging from $35,683-$43,007) for the optimally initiated patients (p < 0.001). LIMITATIONS: Costs were calculated utilizing a conservative approach, using the cheapest available prices for medications and other resources. Assumptions had to be made for the costing of dialyses. CONCLUSION: The results of this study indicate, after adjusting for potential confounders, that optimally initiated patients for RRT have significantly lower healthcare-associated costs compared to sub-optimally initiated patients.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".