MétaCan
Menu
Back to cohort
Record W3126655518 · doi:10.1177/0897190021989931

Ceftazidime-Induced Neurotoxicity in an 80-Year-Old Female With Renal Dysfunction: A Case Report

2021· article· en· W3126655518 on OpenAlexaff
Laetissia Amirouche, Alexandra Cerulli-Kanellopoulos, Sébastien Landry, Véronique Leblanc, Ghislain Léger

Bibliographic record

VenueJournal of Pharmacy Practice · 2021
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsDr. Georges-L.-Dumont University Hospital CentreUniversité de Montréal
Fundersnot available
KeywordsMedicineCeftazidimeDiscontinuationNeurotoxicityContext (archaeology)Adverse effectIntensive care unitIntensive care medicineEncephalopathyCephalosporinPediatricsInternal medicineAntibioticsToxicityPseudomonas aeruginosa

Abstract

fetched live from OpenAlex

Neurological toxicity is a relatively rare adverse reaction reported in elderly patients treated with cephalosporins. We present a case of ceftazidime-induced encephalopathy in the context of acute kidney injury in an 80-year-old female treated for a Pseudomonas aeruginosa prosthetic joint infection. During the course of treatment, the patient developed sudden confusion and disorientation. The patient’s mental state progressively worsened, eventually leading to intubation and admission to the intensive care unit. As imaging and laboratory analyses revealed no alternative causes explaining the patient’s symptoms, ceftazidime was stopped under the suspicion of drug-induced neurotoxicity. Shortly after ceftazidime discontinuation, the patient’s condition drastically improved and returned to baseline within 5 days. This case reveals the potential severity of cephalosporin-induced neurotoxicity in elderly patients and highlights the importance of quickly detecting such adverse events in order to prevent dire outcomes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.060
GPT teacher head0.390
Teacher spread0.330 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacy PracticeSame topicAntibiotics Pharmacokinetics and EfficacyFrench-language works237,207