Evidence map›Paper›PMID 31504558›Full record

ArticleThe Journal of antimicrobial chemotherapy2019

Can phenotypic data complement our understanding of antimycobacterial effects for drug combinations?

Frank Kloprogge, Robert Hammond, Andrew Copas, Stephen H Gillespie, Oscar Della Pasqua

Open access · hybridAbstract read
In one paragraph

Article in The Journal of antimicrobial chemotherapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 35% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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

5 authors at 2 institutions in 1 country.

Frank KloproggeInstitute for Global Health, University College London, London, UK.
Robert HammondSchool of Medicine, University of St Andrews, St Andrews, UK.
Andrew CopasInstitute for Global Health, University College London, London, UK.
Stephen H GillespieSchool of Medicine, University of St Andrews, St Andrews, UK.
Oscar Della PasquaClinical Pharmacology and Therapeutics Group, School of Pharmacy, University College London, London, UK.
University College London · GBUniversity of St Andrews · GB

Funding

Medical Research Council MR/P014534/1
6 · The paper itself

Abstract

objectivesTo demonstrate how phenotypic cell viability data can provide insight into antimycobacterial effects for the isoniazid/rifampicin treatment backbone.

methodsData from a Mycobacterium komossense hollow-fibre infection model comprising a growth control group, rifampicin at three different exposures (Cmax = 0.14, 0.4 and 1.47 mg/L with t½ = 1.57 h and τ = 8 h) and rifampicin plus isoniazid (Cmax rifampicin = 0.4 mg/L and Cmax isoniazid = 1.2 mg/L with t½ = 1.57 h and τ = 8 h) were used for this investigation. A non-linear mixed-effects modelling approach was used to fit conventional cfu data, quantified using solid-agar plating. Phenotypic proportions of respiring (alive), respiring but with damaged cell membrane (injured) and 'not respiring' (dead) cells data were quantified using flow cytometry and Sytox Green™ (Sigma-Aldrich, UK) and resazurin sodium salt staining and fitted using a multinomial logistic regression model.

resultsIsoniazid/rifampicin combination therapy displayed a decreasing overall antimicrobial effect with time (θTime1/2 = 438 h) on cfu data, in contrast to rifampicin monotherapy where this trend was absent. In the presence of isoniazid a phenotype associated with cell injury was displayed, whereas with rifampicin monotherapy a pattern of phenotypic cell death was observed. Bacterial killing onset time on cfu data correlated negatively (θTime50 = 28.9 h, θLAGRIF50 = 0.132 mg/L) with rifampicin concentration up to 0.165 mg/L and this coincided with a positive relationship between rifampicin concentration and the probability of phenotypic cell death.

conclusionsCell viability data provide structured information on the pharmacodynamic interaction between isoniazid and rifampicin that complements the understanding of the antibacillary effects of this mycobacterial treatment backbone.

Indexed as

Models, TheoreticalAntitubercular AgentsIsoniazidLogistic ModelsMicrobial ViabilityMycobacteriaceaePhenotypeRifampinTuberculosis, PulmonaryAntitubercular AgentsIsoniazidRifampin

Identifiers

PMID31504558
PMCPMC6857198
OpenAlexW2970763701

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.