Evidence map›Paper›PMID 33293804›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2020

Clinical Features and C-Reactive Protein as Predictors of Bacterial Exacerbations of COPD.

Nick A Francis, David Gillespie, Mandy Wootton, Patrick White, Janine Bates, Jennifer Richards, Hasse Melbye, Kerenza Hood, Christopher C Butler

Open access · goldAbstract read
In one paragraph

Article in International journal of chronic obstructive pulmonary disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Review
  6. Article
  7. Phenotypes, Etiotypes, and Endotypes of Exacerbations of Chronic Obstructive Pulmonary Disease.American journal of respiratory and critical care medicine · 2023
    Review
  8. 11β-HSD1 determines the extent of muscle atrophy in a model of acute exacerbation of COPD.American journal of physiology. Lung cellular and molecular physiology · 2023
    Article
  9. Article
  10. Observational
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

9 authors at 6 institutions in 2 countries.

Nick A FrancisPrimary Care, Population Sciences and Medical Education, University of Southampton, Southampton, England, UK.ORCID 0000-0001-8939-7312
David GillespieCentre for Trials Research, Cardiff University, Cardiff, Wales, UK.ORCID 0000-0002-6934-2928
Mandy WoottonSpecialist Antimicrobial Chemotherapy Unit, Microbiology Cardiff, Public Health Wales, Cardiff, Wales, UK.
Patrick WhiteSchool of Population Health and Environmental Sciences, King's College London, London, England, UK.ORCID 0000-0002-2047-8787
Janine BatesCentre for Trials Research, Cardiff University, Cardiff, Wales, UK.
Jennifer RichardsSpecialist Antimicrobial Chemotherapy Unit, Microbiology Cardiff, Public Health Wales, Cardiff, Wales, UK.
Hasse MelbyeDepartment of Community Medicine, UIT the Arctic University of Norway, Tromsø, Norway.ORCID 0000-0002-9773-3141
Kerenza HoodCentre for Trials Research, Cardiff University, Cardiff, Wales, UK.ORCID 0000-0002-5268-8631
Christopher C ButlerNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, England, UK.ORCID 0000-0002-0102-3453
Cardiff University · GBPublic Health Wales · GBKing's College London · GBUiT The Arctic University of Norway · NOUniversity of Oxford · GBUniversity of Southampton · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Identifying predictors of bacterial and viral pathogens in sputum from patients with acute exacerbations of chronic obstructive pulmonary disease (COPD) may help direct management. Methods: We used data from a trial evaluating a C-reactive protein (CRP) point of care guided approach to managing COPD exacerbations in primary care. We used regression analyses to identify baseline clinical features, including CRP value in those randomized to testing, associated with bacterial, viral or mixed infections, defined by the presence of bacterial and viral pathogens in sputum, detected by culture or polymerase chain reaction (PCR), respectively. Results: Of 386 participants with baseline sputum samples, 79 (20.5%), 123 (31.9%), and 91 (23.6%) had bacterial, viral/atypical, and mixed bacterial/viral/atypical pathogens identified, respectively. Increasing sputum purulence assessed by color chart was associated with increased odds of finding bacterial and mixed (bacterial and viral/atypical) pathogens in sputum (area under the ROC curve (AUROC) for bacterial pathogens =0.739 (95% CI: 0.670, 0.808)). Elevated CRP was associated with increased odds of finding bacterial pathogens and mixed pathogens but did not significantly increase the AUROC for predicting bacterial pathogens over sputum color alone (AUROC for combination of sputum color and CRP = 0.776 (95% CI: 0.708, 0.843), p for comparison of models = 0.053). We found no association between the presence of sputum pathogens and other clinical or demographic features. Conclusion: Sputum purulence was the best predictor of sputum bacterial pathogens and mixed bacterial viral/atypical pathogens in patients with COPD exacerbations in our study. Elevated CRP was associated with bacterial pathogens but did not add to the predictive value of sputum purulence.

Indexed as

C-Reactive ProteinPulmonary Disease, Chronic ObstructiveBacteriaBiomarkersHumansSputumBiomarkersC-Reactive ProteinbacteriaCOPDexacerbationinfectionprimary caresputum

Identifiers

PMID33293804
PMCPMC7718867
OpenAlexW3110633008

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.