Association of eGFR at Peritoneal Dialysis (PD) Catheter Insertion with PD-Related Complications
Bibliographic record
Abstract
Background: Guidelines now reflect a shift towards an intent to defer dialysis strategy, irrespective of modality. In peritoneal dialysis (PD), this may increase the risk of early complications. The objective of this study was to determine if early PD-related complications were associated with eGFR prior to PD catheter insertion. Methods: We conducted a retrospective study using the North American PD catheter registry across 23 sites. Patients undergoing PD catheter insertions were initially grouped by pre-dialysis eGFR < 9 ml/min and >10 ml/min. The eGFR was then analyzed as a continuous variable. The primary outcome was the occurrence of PD related complications within 90 days of insertion. Adjusted risk between eGFR and outcomes was calculated using cause-specific Cox models. Results: Of 1,537 patients with first PD catheter insertions, 1033 (67%) had a pre-dialysis eGFR < 9 versus 504 (33%) with ≥ 10. Patients with eGFR < 9 were more likely to be younger (median age 60 vs.63), female (44 vs 32%) and have fewer comorbidities. There was no significant difference in PD related complications between the eGFR < 9 and eGFR ≥ 10 groups (aHR 1.12 [0.86, 1.45]). However, in the lower GFR group, which represented two-thirds of the population, there was an increased risk for every 1ml/min eGFR decline below 9ml/min (aHR 1.18 [1.09, 1.28]) (Figure 1). The most common PD-related complications included; flow restriction (7%), leak (3%) and pain (3%). Conclusion: PD-related complications were similar when comparing an insertion eGFR of <9 to >10 ml/min. However, when assessing eGFR as a continuum, there was an increased risk of complications by 18% for each 1ml/min drop in GFR below 9ml/min suggesting intent to defer start targets should account for modality.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".