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Acute Fatal Acetaminophen Overdose Without Liver Necrosis

2007· article· en· W2065234725 on OpenAlexaff
Peter P. Singer, Graham Jones, B Bannach, Lloyd N. Denmark

Bibliographic record

VenueJournal of Forensic Sciences · 2007
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsOffice of the Chief Medical Examiner
Fundersnot available
KeywordsAcetaminophenacetaminophen overdoseMedicineNecrosisLiver injuryCentrilobular necrosisDrug overdoseAntipyreticAnalgesicAnesthesiaPharmacologyInternal medicinePoison controlChemistryMedical emergencyAntioxidantBiochemistry

Abstract

fetched live from OpenAlex

Two unusual cases of suicidal overdose of acetaminophen (paracetamol) without the usual extensive centrilobular necrosis of the liver are reported. Both cases were subjected to comprehensive drug screening by immunoassay, and a combination of gas chromatography with mass spectrometry, nitrogen detection, and electron capture detection. Acetaminophen was detected in both cases. No other drugs were detected in case #1, and only a small amount of olanzapine (<0.1 mg/L) was detected in case #2. No anatomical cause of death was identified in either case. If untreated, the normal outcome of a large acetaminophen overdose would be massive hepatic necrosis with delayed death and low blood and tissue acetaminophen concentrations. In contrast, particularly high postmortem acetaminophen concentrations were measured in both our cases with little hepatic tissue damage. For case #1, femoral blood acetaminophen 1280 mg/L, vitreous 878 mg/L, and liver 729 mg/kg; in case #2, cardiac blood 1220 mg/L, vitreous 779 mg/L, liver 3260 mg/kg, and gastric 11,500 mg/500 g. Acetaminophen was measured using high performance liquid chromatography with UV detection (254 nm) using 3-hydroxyacetanilide as the internal standard. The very high concentrations of acetaminophen is these cases but relatively little hepatic damage suggests an alternative, possibly cardiac, mechanism of death.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.146
GPT teacher head0.439
Teacher spread0.294 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations13
Published2007
Admission routes1
Has abstractyes

Explore more

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