Peritoneal Dialysis: A Scoping Review of Strategies to Maximize pd Utilization
Bibliographic record
Abstract
The percentage of end-stage renal disease (ESRD) patients treated with peritoneal dialysis (PD) has declined in many countries since the mid-1990s. Barriers to PD have been reviewed extensively in the literature, but evidence about strategies to address these barriers and maximize the safe and effective use of PD is lacking. We therefore decided to conduct a scoping review identifying strategies to maximize PD use in adults with ESRD. Our search strategy included the following online databases: MEDLINE (OVID), EMBASE, PubMed, Cochrane Controlled Trials Register, Current Controlled Trials, and Cochrane Database of Systematic Reviews for articles published from 1974 to November 2013. Experts in the field were contacted for information about other ongoing or unpublished studies. A complementary search was conducted in the gray literature. Websites of national, provincial or regional agencies were searched for documents regarding policies surrounding the use of PD. Individual dialysis centers need to identify barriers to increasing PD in their program and direct targeted strategies to maximize PD utilization. Our review highlights some effective strategies that may be used. Our review also highlights the need for further research into strategies to maximize PD utilization.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".