Do the Y‐set and double‐bag systems reduce the incidence of CAPD peritonitis?
Bibliographic record
Abstract
BACKGROUND: Peritonitis is the most frequent serious complication of continuous ambulatory peritoneal dialysis (CAPD). It has a major influence on the number of patients switching from CAPD to haemodialysis and has probably restricted the wider acceptance and uptake of CAPD as an alternative mode of dialysis. This systematic review sought to determine if modifications of the transfer set (Y-set or double-bag systems) used in CAPD exchanges are associated with a reduction in peritonitis and an improvement in other relevant outcomes. METHODS: Based on a comprehensive search strategy, we undertook a systematic review of randomized or quasi-randomized controlled trials comparing double-bag and/or Y-set CAPD exchange systems with standard systems, or comparing double-bag with Y-set systems, in patients with end-stage renal disease (ESRD) treated with CAPD. Only published data were used. Data were abstracted by a single investigator onto a standard form and subsequently entered into Review Manager 4.0.4. Its statistical package, Metaview 3.1, calculated an odds ratio (OR) for dichotomous data and a (weighted) mean difference for continuous data with 95% confidence intervals. RESULTS: Twelve eligible trials with a total of 991 randomized patients were identified. In trials comparing either the Y-set or double-bag systems with the standard systems, significantly fewer patients (133/363 vs 158/263; OR 0.33, 95% CI 0.24-0.46) experienced peritonitis and the number of patient-months on CAPD per episode of peritonitis was consistently greater. When the double-bag systems were compared with the Y-set systems significantly fewer patients experienced peritonitis (44/154 vs 66/138; OR 0.44, 95% CI 0.27-0.71) and the number of patient-months on CAPD per episode of peritonitis was also greater. CONCLUSIONS: Double-bag systems should be the preferred exchange systems in CAPD.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".