Knowledge and Practice of Incremental Dialysis: A Survey of Canadian Nephrologists
Bibliographic record
Abstract
Background: Incremental hemodialysis, a strategy to individualize dialysis prescription at initiation, is being linked to enhanced quality of life and acceptability by patients and decreased health care costs. We aimed to explore knowledge and practice pattern regarding facility-based incremental hemodialysis in Canada. Methods: A web-based survey of nephrologists, elicited current incremental hemodialysis (HD) prescribing practices, clinical and patient factors used to determine suitability for treatment, and potential barriers to implementation. The survey was circulated over a period of six weeks (September 21, 2020 and October 30, 2020). Results: The overall response rates 35% (243/691 nephrologists surveyed). Majority (66/111, 59%) of respondents prescribed incremental HD using an individualized approach at the discretion of the nephrologist. Most centers (200/203, 98%) did not report policy or guidance for implementation. Residual urine output was identified as the most important factor for eligibility (112/172, 65%), electrolyte stability (76/172,44%) and existing patient goals of care (69/117, 40%). The majority of nephrologists agreed that dialysis prescriptions are dynamic and should take residual kidney function into consideration; however, 74% of nephrologists did not think there was strong evidence supporting incremental dialysis. Potential barriers identified were patient safety, logistics of scheduling, limited evidence, and acceptance of dose escalation. Despite these barriers, 82% of participants felt that that facility-based incremental dialysis is feasible with their current resources and 78% agreed that with specific exclusion and inclusion criteria, incremental dialysis is a safe option. Conclusions: Incremental hemodialysis is commonly practiced amongst Canadian nephrologists despite a lack of formal criteria for initiation and treatment escalation. This highlights a need for research to guide policy and practice for incremental hemodialysis in Canada.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".