Peritoneal dialysis catheter insertion in patients with obesity: a cohort study and single centre approach to increasing uptake
Bibliographic record
Abstract
BACKGROUND: The global prevalence of obesity in patients with end-stage kidney disease requiring kidney replacement therapy is rising. While peritoneal dialysis (PD) offers advantages for many patients, its use in those with obesity has been historically limited due to concerns about catheter insertion-related complications, mechanical issues, and infection risk. This study aimed to evaluate PD catheter patency, infection rates, and modality outcomes in obese and non-obese patients to inform best practices and guide programme expansion. METHODS: This single-region observational study analysed outcomes from 157 patients who underwent PD catheter insertion between 2020 and 2023 at the Northern Ireland Regional Nephrology and Transplant Centre. Patients were classified as obese (BMI ≥ 30, n = 44) or non-obese (BMI < 30, n = 113). Laparoscopic and percutaneous catheter insertion techniques were used, and primary outcomes included catheter patency (primary, primary assisted, secondary) and infection rates (exit site infection, tunnel infection, peritonitis) 1-year post-insertion. Kaplan-Meier survival analysis and descriptive statistics were applied to compare outcomes between groups. RESULTS: Patency rates were high in both groups, with no significant differences: primary patency was 88% in non-obese patients and 80% in obese patients (p = 0.13). Similarly, primary assisted patency was 94% versus 89% (p = 0.26), and secondary patency was 96% versus 89% (p = 0.11). Patency and infection rates remained within standards set in ISPD guidelines for both groups, although obese patients showed a non-significant trend toward higher peritonitis rates (0.09). Transfer to haemodialysis occurred more frequently in the obese group (34% vs. 19%, p = 0.06). Mortality rates were comparable (9% non-obese, 6% obese). CONCLUSIONS: This study demonstrates that, with appropriate surgical techniques and periprocedural care, obese patients can achieve PD outcomes comparable to those of non-obese individuals. These findings challenge the traditional reluctance to offer PD to obese patients and advocate for the expansion of PD programs to include this growing demographic. CLINICAL TRIAL NUMBER: Not Applicable.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".