Evidence map›Paper›PMID 34708120›Full record

ArticleERJ open research2021

Computed tomography total airway count predicts progression to COPD in at-risk smokers.

Miranda Kirby, Benjamin M Smith, Naoya Tanabe, James C Hogg, Harvey O Coxson, Don D Sin, Jean Bourbeau, Wan C Tan

Abstract read
In one paragraph

Article in ERJ open research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Article
  3. Small Airway Disease in Pre-COPD and Early COPD: Insights Into the Pulmonary "Silent Zone".International journal of chronic obstructive pulmonary disease · 2026
    Review
  4. Determinants of airway morphology in asthma: Inflammatory and noninflammatory factors.The journal of allergy and clinical immunology. Global · 2025
    Article
  5. Article
  6. Airway tapering in COPD.The European respiratory journal · 2024
    Article
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Review
  13. Review
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.

Miranda KirbyDept of Physics, Ryerson University, Toronto, ON, Canada.
Benjamin M SmithDept of Medicine, McGill University, Montreal, QC, Canada.
Naoya TanabeUBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada.ORCID https://orcid.org/0000-0002-7481-0212
James C HoggUBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada.
Harvey O CoxsonUBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada.
Don D SinUBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada.
Jean BourbeauMontreal Chest Institute of the Royal Victoria Hospital, McGill University Health Centre, Montreal, QC, Canada.ORCID https://orcid.org/0000-0002-7649-038X
Wan C TanUBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is limited understanding of how to identify people at high risk of developing COPD. Our objective was to investigate the association between computed tomography (CT) total airway count (TAC) and incident COPD over 3 years among ever-smokers from the population-based Canadian Cohort Obstructive Lung Disease (CanCOLD) study. CT and spirometry were acquired in ever-smokers at baseline; spirometry was repeated at 3-year follow-up. CT TAC was generated by summing all airway segments in the segmented airway tree (VIDA Diagnostics, Inc.). CT airway wall area, wall thickness for a theoretical airway with 10 mm perimeter (Pi10), and low attenuation areas below -856 HU (LAA

Identifiers

PMID34708120
PMCPMC8542990

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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.