Early and Established Peritoneal Dialysis Prescriptions in the US Peritoneal Dialysis Outcomes and Practice Patterns Study
Bibliographic record
Abstract
Background: PD prescriptions evolve within and between patients due to residual kidney function loss, peritoneal membrane changes, & accrual of comorbidities/complications. Limited contemporary data exist on these changes. We explored PD prescription differences between early (<4 months on PD [PD-early]) & established (≥4 months on PD [PD-late]) patients in the US-PDOPPS cohort. Methods: At study entry, we identified 8139 PD early & 5941 PD late adult PDOPPS participants from U.S. facilities (2014-2022). Automated peritoneal dialysis (APD) & continuous ambulatory peritoneal dialysis (CAPD) prescriptions were analyzed separately. Results: CAPD was used in 14% of PD-early & 11% of PD-late patients. Among CAPD patients, mean daily volume was 7.58L (SD = 2.04) in PD-Early vs. 8.24L (SD = 2.64) in PD-Late with similar exchange distribution (≥4 exchanges: 70% PD-early, 68% PD-late). Median urine volume was lower in PD-late patients (0.95L vs 1.05L PD-early) with greater anuria (20% vs 9%). In APD patients, prescriptions with ≥5 cycles were more common in PD-late vs. PD early patients (41% vs 27%). Cycler volume > 8 L was slightly higher in PD-late vs. PD-early patients (63% vs. 57%). 24-hour urine volume was lower in PD-late vs. PD-early patients (0.80L vs 0.90L), & anuria higher (21% vs 13%). Conclusion: PD prescription intensification differs by modality, with the major changes being to: (1) increase dwell volumes vs number of exchanges in CAPD, in contrast to (2) increase number of cycles in APD and to a lesser extent total volume. Further research should explore drivers of these changes (i.e. increasing solute clearances) and their impact on clinical outcomes including burden of therapy. Funding: Other NIH Support - ADS is partially supported by Institutional Development Award Number U54GM115677 from the National Institute of General Medical Sciences of the National Institutes of Health, which funds Advance Clinical and Translational Research (Advance-CTR)., Commercial Support - Vantive,
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".