Peritoneal dialysis catheter implantation by nephrologists is associated with higher rates of peritoneal dialysis utilization: a population-based study
Bibliographic record
Abstract
BACKGROUND: The likelihood of peritoneal dialysis (PD) utilization following a PD catheter insertion attempt is poorly described. We explored the risk factors for PD nonuse, focusing on the method of PD catheter implantation. METHODS: This population-based retrospective cohort study employed Ontario administrative health data to identify 3886 predialysis adults who had an incident PD catheter implantation between 2002 and 2010. The impact of the method of catheter implantation including open-surgical (open, n = 1884), surgical-laparoscopic (laparoscopic, n = 1154), nephrology-percutaneous (nephrology, n = 498) and radiology-percutaneous (radiology, n = 350) on rates of PD utilization (defined as four consecutive weeks of PD) was examined. RESULTS: Eighty-three percent of study patients received PD. After adjustment, relative to patients with openly inserted catheters, PD utilization was greater for those with nephrology-inserted catheters [adjusted hazard ratio (aHR) 1.59, 95% confidence interval (CI) 1.29-1.95] and similar for radiology-inserted catheters [aHR 1.16, 95% CI 0.94-1.43] or laparoscopic-inserted catheters [aHR 0.97 (95% CI 0.86-1.09)]. Among PD nonusers, death occurred in 10% of the open group, 6% of the laparoscopic group, 27% of the radiology group and in fewer than 3% of the nephrology group. Sixty-nine percent received hemodialysis in the open group, 63% in the laparoscopic group, 61% in the radiology group and 88% in the nephrology group. Those remaining predialysis comprised 12% of the open group, 22% of the laparoscopic group, 11% of the radiology group and <3% of the nephrology group. CONCLUSIONS: Nephrology insertion resulted in lower overall rates of PD nonuse, particularly due to death or remaining predialysis. Greater use may be related to insertion timing, technique or greater commitment on the part of nephrologists to the success of PD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".