Comparing Care Models in Assisted Peritoneal Dialysis: Insights from the Alberta Experience
Bibliographic record
Abstract
Background: Assisted peritoneal dialysis (aPD) provides home-based support by trained healthcare professionals for individuals otherwise ineligible for independent peritoneal dialysis (PD). Alberta Kidney Care South (AKC-S) initiated an aPD program in 2011, initially led by licensed nursing practitioners (LPNs) until transitioning to healthcare aides (HCAs) in July 2018. Our objective was to assess outcomes of participants in the aPD program based on the care delivery model (LPN vs. HCA). Methods: This quantitative study utilized an interrupted time-series model to analyze participants in the AKC-S aPD program from its inception in 2011 until December 31, 2021. Deidentified data was extracted from the Nephrology electronic database. Participants were categorized into two phases based on the implementation of the care delivery model change from LPN to HCA on July 1, 2018. Phase one comprised participants who initiated aPD before this date, while phase two included those who began aPD after. The primary outcome was monthly median exit time from PD between the two care groups. Endpoints were defined as death, transplant, transfer to in-center HD, transfer to independent PD, or exit from the program. Secondary outcomes included reason for program exit and rates of peritonitis compared between the two phases. Results: A total of 135 patients received aPD (mean age= 70.7 ± 11.2 years; 44.4% female). We had 57 individuals in phase one, and 55 in phase two (23 still active participants were excluded), with no difference in sex between groups (p = 0.055). We found no difference in the time spent on PD between the LPN phase (1.89 [1.02, 3.85] years) and the HCA phase (1.41 [0.59, 3.25]), p= 0.41. There was no significant difference in the reason for exit after the change in care model (p= 0.64). The incidence rate of peritonitis in phase one was 0.403 (25 participants) and 0.466 (29 participants) in phase two, which was not statistically significant, p = 0.60. Conclusion: Our study revealed no significant difference in the duration of peritoneal dialysis (PD), reasons for program exit, or incidence of peritonitis between the LPN and HCA care models. The HCA model offers a cost-effective alternative to in-center modalities while offering personalized, in-person services that may greatly enhance the quality of care for those undergoing peritoneal dialysis.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".