Evidence map›Paper›PMID 31072364›Full record

ArticleBMC pulmonary medicine2019

Annual decline in forced expiratory volume and airway inflammatory cells and mediators in a general population-based sample.

Natalia Kononova, Liv Ingunn Bjoner Sikkeland, Faiza Mahmood, Maria Vistnes, Johny Kongerud, Gunnar Einvik, Vidar Søyseth

Abstract read
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In one paragraph

Article in BMC pulmonary medicine, 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
–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.

  1. Antioxidants (Basel, Switzerland) · 2023
    Article
  2. Article
  3. Article
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

7 authors.

Natalia KononovaFaculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway. natalia.kononova@medisin.uio.no.
Liv Ingunn Bjoner SikkelandFaculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Faiza MahmoodUnit of Medical Biochemistry, Division of Diagnostics and Technology, Akershus University Hospital, Lørenskog, Norway.
Maria VistnesDepartment of Internal Medicine, Diakonhjemmet Hospital, Oslo, Norway.
Johny KongerudFaculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Gunnar EinvikDepartment of Pulmonology, Division of Medicine, Akershus University Hospital, Lørenskog, Norway.
Vidar SøysethFaculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew studies have examined the relationships between sputum inflammatory markers and subsequent annual decline in forced expiratory volume in 1 s (dFEV

methodsThe study, conducted from 2003 to 2005, included 120 healthy Norwegian subjects aged 40 to 70 years old. At baseline, the participants completed a self-administered respiratory questionnaire and underwent a clinical examination that included spirometry, venous blood sampling, and induced sputum examination. From 2015 to 2016, 62 (52%) participants agreed to a follow-up examination that did not include induced sputum examination. Those with a FEV

resultsThe mean dFEV

conclusionsIn this cohort of presumably healthy subjects, we found no associations between sputum inflammatory cells or mediators and dFEV

Indexed as

Forced Expiratory VolumeVital CapacityAdultAgedCytokinesFemaleHealthy VolunteersHumansInflammation MediatorsLungMaleMiddle AgedMultivariate AnalysisNorwayRegression AnalysisSpirometryCytokinesInflammation MediatorsAirway inflammationAnnual decline in forced expiratory volumeHealthy individualsInduced sputumSputum cellsSputum cytokines and chemokines

Identifiers

PMID31072364
PMCPMC6509765

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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.