Selection of peritoneal dialysis among older eligible patients with end-stage renal disease
Bibliographic record
Abstract
Background: Older patients with end-stage renal disease (ESRD) are less likely to choose peritoneal dialysis (PD) over hemodialysis (HD). The reasons behind their choice of dialysis modality are not clear. This study seeks to determine the patient-perceived factors that influence ESRD patients' choice of dialysis modality among older ESRD patients who are deemed eligible for both PD and HD. Methods: All patients had completed a multidisciplinary modality assessment, were deemed eligible for both PD and HD, and had received modality education. Semi-structured interviews were conducted and transcripts were read repeatedly to derive potential codes using line-by-line textual analysis. The Capability, Opportunity, Motivation – Behaviour (COM-B) and Theoretical Domain Framework (TDF), validated tools that were developed for designing behavioral change interventions, were used to help guide the coding framework. Results: Among older ESRD patients who are deemed eligible for both PD and HD, factors relevant to their modality decision-making were identified with respect to physical strength/dexterity and having a sound mind (capability), external forces and constraints (opportunity), and values and beliefs (motivation). Often a combination of factors led to an individual's choice of a particular dialysis modality. However, preferences for PD were primarily based around convenience and maintaining a normal life, while a heightened sense of security was the primary reason for those who selected HD. Conclusions: We have identified patient-perceived factors that influence choice of dialysis modality in older individuals with ESRD who are eligible for PD and HD. These factors should be considered and/or addressed within PD programs seeking to promote PD.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".