Recent advances in peritoneal dialysis catheter placement: the association between method of insertion, operator, and prior abdominal surgery and outcomes
Bibliographic record
Abstract
PURPOSE OF REVIEW: Peritoneal dialysis (PD) is associated with comparable outcomes to hemodialysis and is much less expensive to provide in most parts of the world. A well functioning PD catheter is required, but complications are frequent, and while there are guidelines for the placement and care of a PD access, they are based on low-quality evidence. RECENT FINDINGS: Data reporting the outcomes of percutaneous, as compared to surgical pathways for placement of catheters and the role of operator type in determining outcomes are examined. The impact of prior abdominal procedures on patient selection and the prognostic importance of the presence of adhesions at the time of catheter insertion are reviewed. SUMMARY: There are conflicting data about the relative merits of percutaneous as compared to surgical placement of catheters that may relate to differences in patient selection, operator experience, or operator volume. Prior abdominal procedures are not associated with worse PD catheter outcomes and likely should not influence patient selection, except in exceptional circumstances. Finally, the presence of adhesions is associated with a higher risk of complications. However, even in the presence of adhesions, the termination of PD therapy and need for re-intervention occurs in <20% of patients.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".