ESBL<i>Escherichia coli</i>Ventriculitis after Aneurysm Clipping: A Rare and Difficult Therapeutic Challenge
Bibliographic record
Abstract
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.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".