A Change to Radiological Peritoneal Dialysis Catheter Insertion: Three-Month Outcomes
Bibliographic record
Abstract
BACKGROUND: Best practices for peritoneal dialysis (PD) catheter insertion call for timely placement of catheters to reduce complications and increase the likelihood of a successful initiation of PD. The purpose of our study was to assess if a change in approach to PD catheter insertion, including a switch to radiological insertion of PD catheters and introduction of a dialysis access nurse to coordinate all patient care, was associated with more outpatient procedures and achievement of guideline-based outcomes, including timelier PD starts. ♢ METHODS: We conducted a single-center retrospective chart review of all patients that had their first PD catheter inserted at our center over a 7-year period ending in 2007. ♢ RESULTS: PD catheters were placed in 88 patients by interventional radiology and in 125 patients by surgical insertion during an earlier period. Insertion of PD catheters by interventional radiology was significantly associated with a higher rate of outpatient procedures (70% vs 32%, p < 0.0001) than surgical placement. At PD start, 82% of patients that underwent radiological insertions had an estimated glomerular filtration rate of over 8 mL/minute/1.73 m(2) and their mean serum albumin level was 38.2 g/L. ♢ CONCLUSIONS: The new procedure of radiological insertion of PD catheters, coordinated by a dedicated dialysis access nurse, was associated with more outpatient procedures than the earlier surgical method and allowed patients to receive a PD catheter with timing consistent with clinical practice recommendations.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".