Four-hour acetaminophen concentration estimation after ingested dose based on pharmacokinetic models
Bibliographic record
Abstract
INTRODUCTION: The United Kingdom has recently changed the indications for N-acetylcysteine treatment for acetaminophen intoxication. Any ingestion over 75 mg/kg is now referred to the hospital. A model based on pharmacokinetic parameters was developed to predict 4-h acetaminophen concentration for this and other ingested doses. METHODOLOGY: EMBASE and Medline were searched to obtain values for volume of distribution, absorption, and elimination constants and bioavailability for acetaminophen. Four-hour concentrations were calculated for ingestion doses currently recommended for hospital referral in different countries. Calculated plasma concentrations at 4 h for several doses were plotted against the Rumack-Matthew and the United Kingdom treatment lines. RESULTS: Six articles were used for the calculations (4 adult and 2 pediatric). In order to achieve a 4-h acetaminophen concentration of 100 mg/L, doses (mg/kg ± 99.9CI) of 180.5 ± 43.2 for adults and 396.1 ± 115.5 for children were calculated. DISCUSSION: A dose of 75 mg/kg would likely yield a 4-h acetaminophen concentrations well below 100 mg/L. Medical toxicologists and poison information specialists are left without evidence-based guidance for which patients or which ingestion history would now warrant referral to hospital for acetaminophen concentration measurement. Larger toxicokinetic studies in acetaminophen overdose are needed to define ingestion dose for referral to hospital.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".