Cotard’s syndrome resulting from acyclovir treatment in patients with impaired renal function – literature review
Bibliographic record
Abstract
with particular emphasis on mental disorders, such as the Cotard's syndrome, in patients with renal failure who receive acyclovir.A mechanism of neuropsychiatric effects of antiviral toxicity most likely occurs when 9-carboxymethoxymethylguanine (9-CMMG), which is acyclovir's main metabolite, crosses the blood-brain barrier and inhibits mitochondrial DNA polymerase, which leads to mitochondrial toxicity and ultimately increased uremic toxicity.Due to the rarity of this phenomenon, both the pathomechanism and treatment have not been sufficiently studied.Literature review.The literature review centres around the occurrence of neurological and psychiatric side effects, especially nihilistic disorders, in patients with renal failure taking acyclovir or its prodrug, valacyc lovir.Case reports refer to the patients with no history of serious mental illnesses in the past and indicate that the 9-CMMG metabolite can be used as a marker for neuropsychiatric disorders.Conclusions.Acyclovir is a commonly used drug which in rare cases can be neurotoxic.Neurological side effects include disorientation, confusion, impaired consciousness, dysarthria, agitation, visual and auditory hallucinations, psychosis and delusions of being dead, typical AbstrActObjectives.This article aims to review the literature on neurological and psychiatric complications of acyclovir
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".