Evidence map›Paper›PMID 40596670›Full record

ArticleCommunications medicine2025

Feasibility of serial measurement of nitrite for pharmacodynamic monitoring and precision prescribing in urinary tract infections.

Ellen V Stadler, Alison Holmes, Danny O'Hare, Mark Sutton, Colin Brown, Timothy M Rawson

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Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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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

1 citing paper in PubMed.

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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

6 authors.

Ellen V StadlerCentre for Antimicrobial Optimisation, Imperial College London, London, UK. ellen.stadler20@imperial.ac.uk.ORCID http://orcid.org/0000-0002-8208-8434
Alison HolmesCentre for Antimicrobial Optimisation, Imperial College London, London, UK.ORCID http://orcid.org/0000-0001-5554-5743
Danny O'HareCentre for Antimicrobial Optimisation, Imperial College London, London, UK.
Mark SuttonAntimicrobial Discovery, Development and Diagnostics (AD3) UK Health Security Agency, Porton Down, Salisbury, Wiltshire, UK.
Colin BrownHealthcare Associated Infections, Fungal, Antimicrobial Resistance, Antimicrobial Use, and Sepsis Division, UK Health Security Agency, London, UK.
Timothy M RawsonCentre for Antimicrobial Optimisation, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-2630-9722

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ability to monitor host- and bacteria-specific biomarkers along with antimicrobial drug concentration at the site of infection offers potential for individualised approaches to antimicrobial therapy. Although urine collection is straightforward and directly linked to the infection site, the assessment of urinary tract infection (UTI) biomarkers during infection has not been extensively explored. The aim of this study is to evaluate the potential of monitoring urinary nitrite levels as a biomarker for antimicrobial pharmacodynamics in UTI treatment.

methodsResistant and susceptible E. coli strains were cultured in oxygen-free artificial urine, with amoxicillin added after 15 h. Colony-forming unit (CFU) counts, nitrite, and creatinine levels were measured at 5 timepoints over 66 h. Urine samples from 25 UTI patients and 25 non-UTI controls were analysed for bacterial growth, nitrite, and creatinine. Spearman rank correlation and Mann-Whitney U-tests were used for statistical analysis.

resultsOur in-vitro model demonstrates that measuring the bacteria-specific urinary biomarker nitrite during E. coli growth in artificial urine can effectively be applied to assess antimicrobial pharmacodynamics over the course of UTI treatment. In an in-vitro UTI model, nitrite concentration can differentiate between resistant and susceptible E. coli strains and correlates with CFU counts. Analysis of 25 clinical UTI samples is consistent with these findings, showing correlations between nitrite levels and CFU counts.

conclusionsHere we show that nitrite generation by E. coli may have clinical relevance as a biomarker for infection progression and antimicrobial treatment outcomes, offering a valuable tool for monitoring the pharmacodynamic responses to antimicrobial therapy in UTIs.

Identifiers

PMID40596670
PMCPMC12217021

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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.