The Impact of Treatment Modality on Infection-Related Hospitalization Rates in Peritoneal Dialysis and Hemodialysis Patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Infection is a major cause of morbidity and mortality in the dialysis population. This study compares the rates of infection-related hospitalization (IRH) in incident chronic dialysis patients initiating outpatient peritoneal dialysis (PD) and hemodialysis (HD). METHODS AND PATIENTS: This was a retrospective cohort study at the dialysis program of a tertiary-care center in Toronto, Canada. Incident chronic dialysis patients that were eligible for both PD and HD and started outpatient dialysis between 1 January 2004 and 31 August 2008 were included. Dialysis modality was assigned at the start of outpatient dialysis treatment. All hospital admissions were reviewed and incidence of IRH was compared between PD and HD using Poisson regression. RESULTS: Of 264 incident chronic dialysis patients, 168 (64%) were eligible for both treatment modalities: 71 (42%) started outpatient PD and 97 (58%) started outpatient HD. The unadjusted and adjusted incidence rate ratios (IRR) of IRH did not differ significantly between PD and HD: 1.23 [95% confidence interval (CI) 0.65-2.32, p=0.37] and 1.14 (95% CI 0.58-2.23, p=0.71) respectively. There was no difference between PD and HD in the risk of access loss (28% vs 35%, p=0.73), modality change (22% vs 0%, p=0.10), or death (17% vs 6%, p=0.60) following hospitalization for infection. Patients starting outpatient treatment on PD versus HD were more likely to be hospitalized for peritonitis (IRR 3.20, 95% CI 1.16-9.09; p=0.029) and there was a trend for fewer hospitalizations for bacteremia (IRR 0.19, 95% CI 0.028-1.30; p=0.091). The risk of IRH did not differ between PD and HD in the subgroup of patients that received adequate predialysis care (IRR 1.16, 95% CI 0.59-2.27; p=0.67) or when patients starting outpatient HD with a central venous catheter were excluded (IRR 1.52, 95% CI 0.53-4.37; p=0.44). CONCLUSIONS: Patients that initiate outpatient peritoneal dialysis do not have a significantly increased risk of infection-related hospitalization compared to those that initiate outpatient hemodialysis.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".