SP503INTERNATIONAL VARIATION IN PERITONEAL DIALYSIS (PD) CATHETER PRACTICES: PRELIMINARY RESULTS FROM THE PERITONEAL DIALYSIS OUTCOMES AND PRACTICE PATTERNS STUDY (PDOPPS)
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Variation in clinical and organisational practices associated with PD catheter insertion are very likely to impact on outcomes, with mechanical causes accounting for 12% of technique failure. We sought to describe selected catheter insertion practice pattern differences across facilities participating in PDOPPS. METHODS: The PDOPPS is a prospective cohort study enrolling national stratified-random samples of PD facilities from 6 countries, in collaboration with the International Society of Peritoneal Dialysis. Data on PD catheter insertion practices was collated from the Unit Practice Survey (UPS), distributed in 2016. Early findings and patterns by country are described. SP503 Figure CONCLUSIONS: Japan is least likely to have access to urgent start PD, but has the greatest experience with embedded catheters; Canada has the greatest experience with pre-sternal catheters; laparoscopic insertion is commonly available in all countries except Japan; percutaneous insertion techniques are available in a minority of centres in A/NZ, Canada, and UK and almost no centres in Japan and the US. Wide international variations in PD catheter management provide the opportunity to explore the impact of these practices on patient outcomes. This will be the subject of future enquiry within the PDOPPS.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".