Evidence map›Paper›PMID 31747890›Full record

ArticleBMC infectious diseases2019

Prediction model for pneumonia in primary care patients with an acute respiratory tract infection: role of symptoms, signs, and biomarkers.

G H Groeneveld, J W van 't Wout, N J Aarts, C J van Rooden, T J M Verheij, C M Cobbaert, E J Kuijper, J J C de Vries, J T van Dissel

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 24 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

G H GroeneveldDepartment of Internal Medicine and Infectious Diseases, Leiden University Medical Center, P.O. box 9600, 2300 RC, Leiden, the Netherlands. g.h.groeneveld@lumc.nl.
J W van 't WoutDepartment of Internal Medicine and Infectious Diseases, Leiden University Medical Center, P.O. box 9600, 2300 RC, Leiden, the Netherlands.
N J AartsDepartment of Radiology, HMC Bronovo, P.O. box 432, 2501 CK, The Hague, the Netherlands.
C J van RoodenDepartment of Radiology, HAGA hospital, P.O. box 40551, 2504 LN, The Hague, the Netherlands.
T J M VerheijJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, PO Box 85500, 3508 GA, Utrecht, the Netherlands.
C M CobbaertDepartment of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Center, P.O. box 9600, 2300 RC, Leiden, the Netherlands.
E J KuijperDepartment of Medical Microbiology, Leiden University Medical Center, Leiden, P.O. box 9600, 2300 RC, Leiden, the Netherlands.
J J C de VriesDepartment of Medical Microbiology, Leiden University Medical Center, Leiden, P.O. box 9600, 2300 RC, Leiden, the Netherlands.
J T van DisselCentre for Infectious Disease Control, National Institute for Public Health and the Environment (Rijksinstituut voor Volksgezondheid en Milieu, RIVM), Bilthoven, the Netherlands.
Leiden University Medical Center · NLBronovo Hospital · NLHaga Hospital · NLUniversity Medical Center Utrecht · NL

Funding

Netherlands Genomics Initiative (NGI) 050-060-452Virgo consortium, funded by the Dutch government FES0908ZonMw 204000001
6 · The paper itself

Abstract

backgroundDiagnosing pneumonia can be challenging in general practice but is essential to distinguish from other respiratory tract infections because of treatment choice and outcome prediction. We determined predictive signs, symptoms and biomarkers for the presence of pneumonia in patients with acute respiratory tract infection in primary care.

methodsFrom March 2012 until May 2016 we did a prospective observational cohort study in three radiology departments in the Leiden-The Hague area, The Netherlands. From adult patients we collected clinical characteristics and biomarkers, chest X ray results and outcome. To assess the predictive value of C-reactive protein (CRP), procalcitonin and midregional pro-adrenomedullin for pneumonia, univariate and multivariate binary logistic regression were used to determine risk factors and to develop a prediction model.

resultsTwo hundred forty-nine patients were included of whom 30 (12%) displayed a consolidation on chest X ray. Absence of runny nose and whether or not a patient felt ill were independent predictors for pneumonia. CRP predicts pneumonia better than the other biomarkers but adding CRP to the clinical model did not improve classification (- 4%); however, CRP helped guidance of the decision which patients should be given antibiotics.

conclusionsAdding CRP measurements to a clinical model in selected patients with an acute respiratory infection does not improve prediction of pneumonia, but does help in giving guidance on which patients to treat with antibiotics. Our findings put the use of biomarkers and chest X ray in diagnosing pneumonia and for treatment decisions into some perspective for general practitioners.

Indexed as

AdultAgedAnti-Bacterial AgentsBiomarkersCalcitoninC-Reactive ProteinFemaleHumansMaleMiddle AgedMultivariate AnalysisNetherlandsPneumoniaPrimary Health CarePrognosisProspective StudiesAnti-Bacterial AgentsBiomarkersCalcitoninC-Reactive ProteinAntibioticBiomarkersChest X rayCRPPneumoniaPrediction modelPrimary careRespiratory tract infection

Identifiers

PMID31747890
PMCPMC6865035
OpenAlexW2990633870

What OpenQuestion holds

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LicenceCC BY
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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.