Optimization of Dialysis Modality Transitions for Improved Patient Care
Bibliographic record
Abstract
PURPOSE OF REVIEW: Initial and subsequent modality decisions are important, impacting both clinical outcomes and quality of life. Transition from chronic kidney disease to dialysis and between dialysis modalities are periods were patients may be especially vulnerable. Reviewing our current knowledge surrounding these critical periods and identifying areas for future research may allow us to develop dialysis strategies beneficial to patients. SOURCES OF INFORMATION: We searched the electronic database PubMed and queried Google Scholar for English peer-reviewed articles using appropriate keywords (non-exhaustive list): dialysis transitions, peritoneal dialysis, home hemodialysis, integrated care pathway, and health-related quality of life. Primary sources were accessed whenever possible. METHODS: In this narrative review, we aim to expose the controversies surrounding home-dialysis first strategies and examine the evidence underpinning home-dialysis first strategies as well as home-to-home and home-to-in-center transitions. KEY FINDINGS: Diverse factors must be taken into consideration when choosing initial and subsequent dialysis modalities. Given the limitations of available data (and lack of convincing benefit or detriment of one modality over the other), patient-centered considerations may prime over suspected mortality benefits of one modality or another. LIMITATIONS: Available data stem almost exclusively from retrospective and observational studies, often using large national and international databases, susceptible to bias. Furthermore, this is a narrative review which takes into account the views and opinions of the authors, especially as it pertains to optimal dialysis pathways. IMPLICATIONS: Emphasis must be placed on individual patient goals and preferences during modality selection while planning ahead to achieve timely and appropriate transitions limiting discomfort and anxiety for patients. Further research is required to ascertain specific interventions which may be beneficial to 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 | 0.006 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".