Unusual and complicated peritonitis: Your questions answered
Bibliographic record
Abstract
Effective treatment of infections is a growing challenge owing to antimicrobial resistance. Peritoneal dialysis (PD) patients experience more frequent hospitalisations than the general population and have greater exposure to antibiotics, making them particularly vulnerable to this threat. Over the last decade, we have noted a surge in cases of complicated peritoneal dialysis–associated peritonitis (PD peritonitis) caused by antimicrobial-resistant organisms, including extended-spectrum beta-lactamase (ESBL), AmpC beta-lactamase-producing Enterobacterales, Pseudomonas aeruginosa and fungi. Practitioners must be alert to these organisms, seek early recognition of these resistance patterns and make timely adjustments in order to avoid delay in treatment that may increase risk of PD catheter removal and technique failure. We present a case of successful treatment of ESBL peritonitis, highlight its challenges, while providing guidance on management of other unusual and complicated PD peritonitis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".