A retrospective review of empiric acyclovir prescribing practices for suspected viral central nervous system infections: A single-centre study
Bibliographic record
Abstract
Background: Acyclovir has an important role in the treatment of viral central nervous system (CNS) infection, especially herpes simplex virus (HSV)-1 encephalitis. It is therefore used broadly as empiric therapy for many patients who present to the hospital with symptoms of a possible neurologic infection. We sought to review our practices in acyclovir prescribing, deprescribing, and associated investigations for the clinical syndromes it treats. Methods: Through a retrospective chart review, we identified patients prescribed acyclovir for a possible CNS infection upon admission to Vancouver General Hospital between January 1, 2019, and December 31, 2019. Patient demographics, signs, symptoms, and comorbidities were taken from admission consultation notes or discharge summaries; their investigations, including laboratory tests and imaging, were also recorded. The primary purpose was to describe the appropriateness of empiric acyclovir use in suspected meningoencephalitis cases. Results: Among the 108 patients treated with acyclovir, 94 patients had an indication for starting empiric treatment for encephalitis or meningitis. There was suspicion and workup for encephalitis alone in 76 patients. Among discharge diagnoses, the most common was delirium of a different identified source (18 cases), followed by unknown/other (15 cases). There were seven patients whose CSF viral PCR test was positive for HSV or varicella-zoster virus (VZV); three of them had HSV-1 encephalitis. There were two total adverse events recorded attributed to acyclovir; both cases were of mild acute kidney injury. Conclusion: We found that in many patients, acyclovir was not necessary or could have been stopped earlier, avoiding toxicity and drug costs.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".