Incremental peritoneal dialysis is a safe and feasible prescription in incident patients with preserved residual kidney function
Bibliographic record
Abstract
BACKGROUND: Incremental peritoneal dialysis (PD) is recommended as a component of high-quality care by the international society for PD; however, its feasibility and clinical outcomes have not been widely reported. The aim of this study is to describe our experience with incremental PD. METHODS: This was a retrospective cohort study of incident PD patients at Eastern Health between 2015 and 2019. Patients who stopped PD within 30 days were excluded. Incremental PD was defined in CAPD as using <8 L/day of exchange volume and in automated PD as dialysing without a last fill. Dialysis modality accorded with patient and physician preferences. RESULTS: The 96 patients were included in this study; 54 with incremental PD. Compared to full-dose PD, incremental PD patients were more likely to be female, had less comorbid diabetes (28% vs. 52%) and higher residual kidney function (RKF) (Kt/V 2.0 ± 0.7 vs. 1.4 ± 0.7). Age, BMI and starting eGFR did not differ between groups. Incremental PD exposed patients to lower exchange volumes (4.4 ± 2.1 vs. 8.5 ± 1.1 L/day), glucose load (46 ± 41 g/day vs. 119 ± 46) and was associated with a longer peritonitis-free survival. PD technique survival, rates of peritonitis or hospitalization were comparable between groups. Predictors for longer incremental PD use included older age and higher starting eGFR. CONCLUSIONS: Incremental PD is a feasible, goal-directed initial prescription in patients with RKF with comparable peritonitis rates and technique survival. Validation of this prescription in prospective studies is warranted.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".