Relative Contribution of Residual Renal Function and Peritoneal Clearance to Adequacy of Dialysis
Bibliographic record
Abstract
Studies of the adequacy of peritoneal dialysis and recommendations have assumed that renal and peritoneal clearances are comparable and therefore additive. The CANUSA data were reanalyzed in an effort to address this assumption. Among the 680 patients in the original CANUSA study, 601 had all of the variables of interest for this report. Adequacy of dialysis was estimated from GFR (mean of renal urea and creatinine clearance) and from peritoneal creatinine clearance. The Cox proportional-hazards model was used to evaluate the time-dependent association of these independent variables with patient survival. For each 5 L/wk per 1.73 m(2) increment in GFR, there was a 12% decrease in the relative risk (RR) of death (RR, 0.88; 95% confidence interval [CI], 0.83 to 0.94) but no association with peritoneal creatinine clearance (RR, 1.00; 95% CI, 0.90 to 1.10). Estimates of fluid removal (24-h urine volume, net peritoneal ultrafiltration, and total fluid removal) then were added to the Cox model. For a 250-ml increment in urine volume, there was a 36% decrease in the RR of death (RR, 0.64; 95% CI, 0.51 to 0.80). The association of patient survival with GFR disappeared (RR, 0.99; 95% CI, 0.94 to 1.04). However, neither net peritoneal ultrafiltration nor total fluid removal was associated with patient survival. Although these results may be explained partly, statistically, by less variability in peritoneal clearance than in GFR, the latter seems to be physiologically more important than the former. The assumption of equivalence of peritoneal and renal clearances is not supported by these data. Recommendations for adequate peritoneal dialysis need to be reevaluated in light of these observations.
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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 | 0.012 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".