<i>Pasteurella</i> Species Peritoneal Dialysis‐Associated Peritonitis: Household Pets as a Risk Factor
Bibliographic record
Abstract
BACKGROUND: Pasteurella species are Gram-negative coccobacilli that are a part of the normal oropharyngeal flora of numerous domestic animals. They have been recognized as a rare but significant cause of peritonitis in patients undergoing peritoneal dialysis (PD). A consensus about management strategies for PD-associated peritonitis caused by Pasteurella species currently does not exist. METHODS: The microbiological database serving the Manitoba Renal Program was searched from 1997 to 2013 for cases of Pasteurella species PD-associated peritonitis, and charts were reviewed. PubMed was searched for case reports and data were abstracted. RESULTS: Seven new local cases and 30 previously reported cases were analyzed. This infection is clinically similar to other forms of PD peritonitis, with household pet exposure appearing to be the strongest risk factor. Cats are the most commonly implicated pet. Direct contact between the pet and the equipment was commonly reported (25 of 37 patients) but was not necessary for infection to develop. The mean duration of treatment was 15 days. Complication rates were low, with only 11% of patients requiring PD catheter removal. There was no mortality reported. CONCLUSION: Pasteurella species are a rare cause of PD-associated peritonitis that can be successfully treated with a two-week course of intraperitoneal antibiotics with a high likelihood of catheter salvage.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".