Ertapenem-Induced Encephalopathy: A Case Report Highlighting Carbapenem-associated Neurotoxicity
Bibliographic record
Abstract
Background: Ertapenem is a once-daily carbapenem antibiotic commonly used in the treatment of complicated infections. Although traditionally associated with a lower risk of central nervous system (CNS) toxicity compared to imipenem, emerging reports highlight the potential for ertapenem-induced neurotoxicity, especially in patients with renal impairment and hypoalbuminemia. Early recognition is crucial, as symptoms are often reversible with drug discontinuation Case Presentations: We report a case of a 46-year-old woman with type 2 diabetes, advanced chronic kidney disease, developmental delay, and hypoalbuminemia who developed acute encephalopathy with visual hallucinations approximately three weeks into outpatient ertapenem therapy for suspected diabetic foot osteomyelitis. Despite stable vitals and supportive care for acute kidney injury, she exhibited a sudden decline in mental status. Extensive investigations excluded metabolic, structural, and infectious causes. Ertapenem was discontinued, and the patient was treated with intravenous albumin and supportive measures, resulting in rapid and complete neurologic recovery within 48 hours. A Naranjo score of 7 supported a probable adverse drug reaction. Conclusions: This case highlights ertapenem-induced encephalopathy as a reversible yet under recognized complication in vulnerable populations. Risk factors such as renal dysfunction and hypoalbuminemia should prompt close monitoring and dose adjustment. Albumin infusion may represent a promising adjunctive therapy in select cases.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| 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".