Evidence map›Paper›PMID 27405818›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2016

Steady-state volume of distribution of two-compartment models with simultaneous linear and saturated elimination.

Xiaotian Wu, Fahima Nekka, Jun Li

Abstract read
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In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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.

Xiaotian WuDepartment of Mathematics, Shanghai Maritime University, Shanghai, 201306, People's Republic of China.
Fahima NekkaFaculté de pharmacie, Université de Montréal, Montréal, QC, H3C 3J7, Canada. fahima.nekka@umontreal.ca.
Jun LiFaculté de pharmacie, Université de Montréal, Montréal, QC, H3C 3J7, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The model-independent estimation of physiological steady-state volume of distribution ([Formula: see text]), often referred to non-compartmental analysis (NCA), is historically based on the linear compartment model structure with central elimination. However the NCA-based steady-state volume of distribution ([Formula: see text]) cannot be generalized to more complex models. In the current paper, two-compartment models with simultaneous first-order and Michaelis-Menten elimination are considered. In particular, two indistinguishable models [Formula: see text] and [Formula: see text], both having central Michaelis-Menten elimination, while first-order elimination exclusively either from central or peripheral compartment, are studied. The model-based expressions of the steady-state volumes of distribution [Formula: see text] and their relationships to NCA-based [Formula: see text] are derived. The impact of non-linearity and peripheral elimination is explicitly delineated in the formulas. Being concerned with model identifiability and indistinguishability issues, an interval estimate of [Formula: see text] is suggested.

Indexed as

Models, BiologicalPharmaceutical PreparationsPharmacokineticsAnimalsArea Under CurveDose-Response Relationship, DrugErythropoietinHumansLinear ModelsRatsRecombinant ProteinsErythropoietinPharmaceutical PreparationsRecombinant ProteinsCompartment analysisIndistinguishabilityNon-compartmental analysisSimultaneous first-order and Michaelis–Menten eliminationSteady-state volume of distribution

Identifiers

PMID27405818

What OpenQuestion holds

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Registered trials

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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.