Evidence map›Paper›PMID 26441245›Full record

ArticleBritish journal of clinical pharmacology2016

A novel approach for estimating ingested dose associated with paracetamol overdose.

Todd J Zurlinden, Kennon Heard, Brad Reisfeld

Abstract read
In one paragraph

Article in British journal of clinical pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. A systems pharmacology model for paracetamol overdose and treatment.Journal of pharmacokinetics and pharmacodynamics · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Todd J ZurlindenDepartment of Chemical and Biological Engineering, Colorado State University, Fort Collins, Colorado, 80523-1370.
Kennon HeardDepartment of Emergency Medicine, University of Colorado School of Medicine, 12401 E. 17th Avenue Campus Box B-215, Aurora, CO, 80045.
Brad ReisfeldDepartment of Chemical and Biological Engineering, Colorado State University, Fort Collins, Colorado, 80523-1370.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimIn cases of paracetamol (acetaminophen, APAP) overdose, an accurate estimate of tissue-specific paracetamol pharmacokinetics (PK) and ingested dose can offer health care providers important information for the individualized treatment and follow-up of affected patients. Here a novel methodology is presented to make such estimates using a standard serum paracetamol measurement and a computational framework.

methodsThe core component of the computational framework was a physiologically-based pharmacokinetic (PBPK) model developed and evaluated using an extensive set of human PK data. Bayesian inference was used for parameter and dose estimation, allowing the incorporation of inter-study variability, and facilitating the calculation of uncertainty in model outputs.

resultsSimulations of paracetamol time course concentrations in the blood were in close agreement with experimental data under a wide range of dosing conditions. Also, predictions of administered dose showed good agreement with a large collection of clinical and emergency setting PK data over a broad dose range. In addition to dose estimation, the platform was applied for the determination of optimal blood sampling times for dose reconstruction and quantitation of the potential role of paracetamol conjugate measurement on dose estimation.

conclusionsCurrent therapies for paracetamol overdose rely on a generic methodology involving the use of a clinical nomogram. By using the computational framework developed in this study, serum sample data, and the individual patient's anthropometric and physiological information, personalized serum and liver pharmacokinetic profiles and dose estimate could be generated to help inform an individualized overdose treatment and follow-up plan.

Indexed as

Models, BiologicalAcetaminophenComputer SimulationDose-Response Relationship, DrugDrug OverdoseHumansPredictive Value of TestsTime FactorsTissue DistributionAcetaminophenacetaminophenBayesianoverdoseparacetamolPBPKpharmacokinetic

Identifiers

PMID26441245
PMCPMC4799923

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.