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Record W4406572197 · doi:10.1016/j.xkme.2025.100968

A Case Report of Herpes Simplex Virus Associated Peritoneal Dialysis Peritonitis With Novel Use of Intraperitoneal Acyclovir

2025· article· en· W4406572197 on OpenAlexaff
Arti Dhoot, Bourne L. Auguste, Jenny Ng, Helen Genis, Nisha Andany, Gemini Tanna

Bibliographic record

VenueKidney Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicinePeritonitisSimplexVirologyMathematicsInternal medicine

Abstract

fetched live from OpenAlex

Viral etiologies, such as herpes simplex virus (HSV), for peritonitis can be misclassified as culture negative peritonitis because of poor accessibility of viral testing in the effluent fluid. Inaccurate diagnosis and subsequent ineffective treatment can lead to unnecessary catheter removal for presumed refractory peritonitis. Here, we report a 73-year-old woman with a history of genital HSV-2 on continuous cyclic peritoneal dialysis who presented with HSV-2 related peritonitis. She initially presented with hypotension, suprapubic pain, and cloudy effluent with an elevated white blood cell count preceded by a 1-week history of genital lesions. Elevated cell counts were primarily lymphocyte and monocyte predominant. Bacterial and fungal cultures were negative, and she had minimal improvement in cell counts after 1 week of empiric antibiotics. Effluent was positive for HSV-2. Acyclovir was reconstituted in a 2.5% Dianeal bag and administered via the intraperitoneal route for local effects and avoidance of neurotoxicity. Her cell counts normalized within a week of starting intraperitoneal antiviral therapy and repeat effluent was negative for HSV at 2 weeks. There is one case report describing HSV-2 related peritonitis; however, to our knowledge, this is the first case of viral peritonitis treated with IP acyclovir successfully.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.311
Teacher spread0.278 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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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