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Record W4415548601 · doi:10.1177/08968608251389773

Culture-negative peritonitis secondary to splenic infarcts in peritoneal dialysis: Case report and literature review

2025· article· en· W4415548601 on OpenAlexaff
Raphael Ronald Harrisson

Bibliographic record

VenuePeritoneal Dialysis International · 2025
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsHôpital Charles-Le Moyne
Fundersnot available
KeywordsPeritoneal dialysisPeritonitisThrombosisAbdominal painDialysis catheterSplenic infarctionCatheterAnticoagulant

Abstract

fetched live from OpenAlex

This case report describes a 66-year-old male on continuous cycling peritoneal dialysis (PD) with polycythemia vera and type 2 diabetes. He presented with culture-negative PD-associated peritonitis secondary to splenic infarcts and further accompanied by a splenic vein thrombosis and posterior brain circulation infarcts. His abdominal pain was atypical for peritonitis, being mild and localized to the left side, with an unremitting course despite several treatment attempts with appropriate antimicrobial coverage. An extensive workup for thromboembolic causes was unremarkable. Initially, the patient was started on aspirin and later treated with hydroxyurea and long-term warfarin. His PD catheter was removed due to concerns about an underlying biofilm, and a new one was inserted one month later, while on temporary hemodialysis, without recurrence. This case highlights that non-infectious, culture-negative PD peritonitis related to splenic infarction should be considered in patients with left-sided abdominal pain, poor clinical response to appropriate antibiotics and significant risk factors for thromboembolic events, such as hematologic disorders like polycythemia vera and splenomegaly. Maintaining a high clinical suspicion can prevent unnecessary antibiotic use and reduce repeated exposure to intravenous contrast for imaging studies. Early initiation of long-term anticoagulation might also prevent futile PD catheter removal if subsequent clinical improvement is obtained.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.303
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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