Evidence map›Paper›PMID 40764898›Full record

ArticleBMC infectious diseases2025

Interplay between C-reactive protein responses and antibiotic prescribing in people with suspected infection.

Qingze Gu, Kevin Yuan, Jia Wei, Chang Ho Yoon, Anders Skyrud Danielsen, Augustine Luk, David W Eyre, A Sarah Walker

Abstract read
In one paragraph

Article in BMC infectious diseases, 2025. 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
–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

3 citing papers 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

8 authors.

Qingze GuNuffield Department of Medicine, University of Oxford, Oxford, UK. qingze.gu@ndorms.ox.ac.uk.
Kevin YuanNuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK.
Jia WeiNuffield Department of Medicine, University of Oxford, Oxford, UK.
Chang Ho YoonNuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK.
Anders Skyrud DanielsenDepartment of Microbiology, Oslo University Hospital, Oslo, Norway.
Augustine LukNuffield Department of Medicine, University of Oxford, Oxford, UK.
David W Eyre *Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK.
A Sarah Walker *Nuffield Department of Medicine, University of Oxford, Oxford, UK.

Funding

National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance NIHR200915
6 · The paper itself

Abstract

backgroundSerial measurements of C-reactive protein (CRP) are often taken in hospitals to assess recovery from infection, but their utility remains debated. Previous studies, including our development of CRP centile reference charts for suspected bloodstream infections (BSI), suggest variability in CRP responses across infection types. Here we investigated the association between serial CRP percentile changes, antibiotic prescribing patterns, and patient outcomes in a large cohort with suspected infection, acknowledging that CRP is one of multiple factors in clinical decision-making.

methodsWe analysed 51,544 suspected infection episodes (defined by blood culture collection) from 36,578 patients in Oxfordshire, UK (2016-2021). Episodes were categorised by blood culture results: Gram-positive, Gram-negative, polymicrobial, contaminants, or culture-negative (having previously shown that 51% culture-negatives have CRP responses indistinguishable from culture-positives). The spectrum of antibiotic prescriptions and their changes over time were tracked. Multinomial logistic regression, adjusted for clinical covariates, assessed the association between CRP percentile changes and subsequent prescribing decisions. Linear mixed models evaluated CRP trajectories post-prescribing, and logistic regression associations between early CRP changes (days 1-4) and 5-30-day mortality.

resultsBroad-spectrum antibiotics were predominantly used within the first three days after blood culture collection, followed by a notable shift to narrow-spectrum antibiotics for Gram-positive infections, but with slower de-escalation for Gram-negative and polymicrobial infections. CRP percentile changes were modestly associated with subsequent antibiotic adjustments; in particular, suboptimal recovery, indicated by an increase in CRP centiles, was associated with a higher rate of antibiotic escalation (16.5% vs. 10.7% in expected recovery) and, conversely, faster than expected recovery in CRP was associated with de-escalation (23.6% vs. 17.2%). However, 61.8% of decisions were unchanged despite CRP trends. The relationship between various prescribing decisions and subsequent CRP percentile changes was complex and challenging to estimate, likely due to testing bias. CRP percentile changes during the 4 days post blood culture collection were strongly associated with 5-30-day mortality, highlighting their potential utility as a prognostic indicator.

conclusionsWhile CRP monitoring can inform antibiotic stewardship, its association with prescribing decisions is probably only modest, underscoring the need to integrate a range of clinical factors to optimise infection management.

Indexed as

Anti-Bacterial AgentsBacteremiaC-Reactive ProteinAdultAgedAged, 80 and overDrug PrescriptionsFemaleHumansMaleMiddle AgedPractice Patterns, Physicians'United KingdomAnti-Bacterial AgentsC-Reactive ProteinAntibiotic prescribingAntibiotic stewardshipAntimicrobial resistanceBloodstream infectionCentile reference chartsC-reactive protein

Identifiers

PMID40764898
PMCPMC12326749

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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.