Risk factors of peritoneal dialysis–related peritonitis in the Japan Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS)
Bibliographic record
Abstract
Background: Peritoneal dialysis (PD)-related peritonitis is a major complication of PD. Wide variations in peritonitis prevention, treatment strategies and consequences are seen between countries. These between-country differences may result from modifiable risk factors and clinical practices. Methods: A total of 1225 Japanese PD patients were included and prospectively followed in the Peritoneal Dialysis Outcomes and Practice Patterns Study phase 1 (2014-2018) and phase 2 (2018-2022). Associations between PD-related peritonitis and various risk factors were assessed by Cox proportional hazards survival models. Results: During follow-up (median 1.52 years), 539 peritonitis episodes were experienced by 364 patients. The country crude peritonitis rate was 0.27 episodes/patient-year. In the fully adjusted model, noticeable patient-level factors associated with experiencing any peritonitis included age {hazard ratio [HR] 1.07 per 5-year increase [95% confidence interval (CI) 1.01-1.14]}, serum albumin level [HR 0.63 per 1 g/dl higher (95% CI 0.48-0.82)] and continuous ambulatory peritoneal dialysis (PD) [HR 1.31 versus automated PD (95% CI 1.05-1.63)]. The adoption of antibiotic prophylaxis practice at the time of PD catheter insertion [HR 0.63 (95% CI 0.51-0.78)] or when having complicated dental procedures [HR 0.74 (95% CI 0.57-0.95)] or lower endoscopy [HR 0.69 (95% CI 0.54-0.89)] were associated with lower hazards of any peritonitis, while a routine facility practice of having more frequent regular medical visits was associated with a higher hazard. Conclusion: Identification of risk factors in Japan may be useful for developing future versions of guidelines and improving clinical practices in Japan. Investigation of country-level risk factors for PD-related peritonitis is useful for developing and implementing local peritonitis prevention and treatment strategies.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".