Patient Perspectives on Incremental Peritoneal Dialysis: A National Survey
Bibliographic record
Abstract
Background: Incremental peritoneal dialysis (PD) may improve quality of life, reduce therapy burden and ease transition to PD. Incremental approaches for automated PD (APD) include: less than 7 days a week, carrying no daytime dwell, reduced dwell volumes or less time on the cycler. For CAPD, decreasing the exchange frequency or reducing dwell volumes are also strategies. We sought to understand patient preferences for various strategies via the dissemination of a national survey to individuals on PD. Methods: A pilot tested, anonymous, voluntary survey was administered in Aug-Sep 2023. The American Kidney Fund (AKF) distributed the survey via an online link to those receiving charitable assistance from AKF, social media platform, and AKF’s monthly newsletter. The survey was for those over 18 years, on PD now or in the past year, and the goal was “to learn about ways that PD can help patients have a good quality of life”. Descriptive results were analyzed. Results: Of the 564 respondents, 9.6% were aged 18- 39 years, 75.9% between 40-69 years and 23.8% over 70 years with 59.1% females, 62.5% Caucasian, and 15.5% identifying as black. PD was initiated <1 year in 35.1% of patients. Within 6 months of PD-start, 70.6% of patients reported performing PD treatment 7 days a week. Patients ranked various initial preferred PD prescriptions between 1-4, with 1 as most important as shown in figure 1. Less days of PD treatment per week consistently emerged with the highest priority rankings (ranging from 48- 61.2%) among those receiving APD versus reducing to a single daily dwell for CAPD (42.7%). Conclusion: Patients value less days of PD treatment per week or a single daily exchange over other approaches to incremental PD. Days off from PD as a strategy is currently underutilized in most patients at time of PD initiation. Further research should evaluate the safety and feasibility of providing these prescription variations in select incident individuals.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".