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Record W2078123507 · doi:10.1155/2015/694807

ESBL<i>Escherichia coli</i>Ventriculitis after Aneurysm Clipping: A Rare and Difficult Therapeutic Challenge

2015· article· en· W2078123507 on OpenAlexaff
Frederick A. Zeiler, J. Silvaggio

Bibliographic record

VenueCase Reports in Neurological Medicine · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsVentriculitisMedicineMeningitisVentriculostomyMeropenemSubarachnoid hemorrhageIntraventricular hemorrhageSurgeryHydrocephalusAntibioticsMicrobiologyAntibiotic resistance

Abstract

fetched live from OpenAlex

Background. Extended spectrum beta-lactamase (ESBL) produced Escherichia coli (E. coli) ventriculitis is a rare infection of the central nervous system, with increasing rarity in the adult population. The therapeutic strategy to achieve cure may need to involve a combination of intraventricular and intravenous (IV) therapy. Objective. To describe a case of ESBL E. coli meningitis/ventriculitis in an adult and outline the antimicrobial therapy that leads to cure. Methods. We retrospectively reviewed the records of a patient admitted to the neurosurgical department for aneurysmal subarachnoid hemorrhage, who developed ESBL E. coli ventriculitis. Results. A 55-year-old female, admitted for a Fisher grade 3, World Federation of Neurological Surgeons grade 1, subarachnoid hemorrhage, developed ESBL E. coli ventriculitis requiring a combination of intraventricular gentamicin and high dose intravenous meropenem for clearance. Cerebrospinal fluid clearance occurred at 7 days after initiation of combined therapy. The patient remained shunt dependent. Conclusions. Meningitis and ventriculitis caused by ESBL E. coli species are rare and pose significant challenges to the treating physician. Early consideration for combined intraventricular and IV therapy should be made.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.266
Teacher spread0.241 · 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 designObservational
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

Citations3
Published2015
Admission routes1
Has abstractyes

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