The availability of support and peritoneal dialysis survival: A cohort study
Bibliographic record
Abstract
Background:Providing support is important to maintain a patient on peritoneal dialysis (PD), though its impact on outcomes has not been investigated thoroughly. We examined the association between having support and risk of a transfer to hemodialysis.Methods:In this retrospective observational cohort study, we used data captured in the Dialysis Measurement Analysis and Reporting system about patients who started PD in Alberta, Canada, between 1 January 2013 and 30 September 2018. Support was defined as the availability of a support person in the home who was able, willing and available to provide support for PD in the patient’s residence. The outcome of interest was a transfer to hemodialysis for at least 90 days. We estimated the cumulative incidence of a transfer over time accounting for competing risks and hazard ratios to summarise the association between support and a transfer. We split follow-up time as hazard ratios varied over time.Results:Six hundred and eighty-three incident PD patients, median age 58 years (IQR: 47–68) and 35% female, were followed for a median of 15 months. The cumulative incidence of a transfer to hemodialysis at 24 months was 26%. Having support was associated with a reduced risk of a transfer between 3 and 12 months after the start of dialysis (HR3-12mo: 0.44; 95% CI: 0.25–0.78), but not earlier (hazard ratio (HR)<3mo: 0.96; 95% confidence interval (CI): 0.55–1.69) or later (HR>12mo: 1.19; 95% CI: 0.65–2.17).Conclusions:A transfer to hemodialysis is common. Having a support person at home is associated with a short-term protective effect after the initiation of 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".