The implications of the ADEMEX study for the peritoneal dialysis prescription: the role of small solute clearance versus salt and water removal
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review examines the results of the ADEMEX (Adequacy of Peritoneal Dialysis in Mexico) study in the context of other recent advances in peritoneal dialysis, and assesses the implication of this new knowledge for the optimal peritoneal dialysis prescription. RECENT FINDINGS: The prospective randomized controlled ADEMEX study demonstrated no survival advantage of an increased dose of peritoneal small molecule clearance delivered by chronic ambulatory peritoneal dialysis. Coincident with this finding, there has been increasing awareness that many peritoneal dialysis patients are volume expanded, and that there are adverse cardiovascular consequences to this chronic overhydration. As a result there has been a shift away from interest in peritoneal small solute clearance with renewed interest in peritoneal removal of salt and water. There is also increasing evidence of the importance of residual renal function in maintaining euvolemia and as a prognostic indicator for survival. SUMMARY: The ADEMEX study and subsequent investigations have changed the way we perceive the optimal peritoneal dialysis prescription. This has resulted in de-emphasis of peritoneal small molecule clearance and increased emphasis on clinical assessment of dialysis adequacy, preservation of residual renal function, and optimization of salt and water removal.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".