Evidence map›Paper›PMID 28243075›Full record

Observational studyInternational journal of chronic obstructive pulmonary disease2017

Longitudinal changes in structural abnormalities using MDCT in COPD: do the CT measurements of airway wall thickness and small pulmonary vessels change in parallel with emphysematous progression?

Shin Takayanagi, Naoko Kawata, Yuji Tada, Jun Ikari, Yukiko Matsuura, Shin Matsuoka, Shoichiro Matsushita, Noriyuki Yanagawa, Yasunori Kasahara, Koichiro Tatsumi

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in International journal of chronic obstructive pulmonary disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 11% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Guideline
  2. Article
  3. Article
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  5. Review
  6. Article
  7. Article
  8. Contributions of Emphysema and Functional Small Airway Disease on Intrapulmonary Vascular Volume in COPD.International journal of chronic obstructive pulmonary disease · 2022
    Article
  9. Article
  10. Re-Defining High Risk COPD with Parameter Response Mapping Based on Machine Learning Models.International journal of chronic obstructive pulmonary disease · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Observational
  16. Article
  17. Review
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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

10 authors at 2 institutions in 1 country.

Shin TakayanagiDepartment of Respirology, Graduate School of Medicine, Chiba University, Inohana, Chuo-ku, Chiba-shi, Chiba.
Naoko KawataDepartment of Respirology, Graduate School of Medicine, Chiba University, Inohana, Chuo-ku, Chiba-shi, Chiba.
Yuji TadaDepartment of Respirology, Graduate School of Medicine, Chiba University, Inohana, Chuo-ku, Chiba-shi, Chiba.
Jun IkariDepartment of Respirology, Graduate School of Medicine, Chiba University, Inohana, Chuo-ku, Chiba-shi, Chiba.
Yukiko MatsuuraDepartment of Respirology, Graduate School of Medicine, Chiba University, Inohana, Chuo-ku, Chiba-shi, Chiba.
Shin MatsuokaDepartment of Radiology, St Marianna University School of Medicine, Sugao, Miyamae-ku, Kawasaki-shi, Kanagawa, Japan.
Shoichiro MatsushitaDepartment of Radiology, St Marianna University School of Medicine, Sugao, Miyamae-ku, Kawasaki-shi, Kanagawa, Japan.
Noriyuki YanagawaDepartment of Respirology, Graduate School of Medicine, Chiba University, Inohana, Chuo-ku, Chiba-shi, Chiba.
Yasunori KasaharaDepartment of Respirology, Graduate School of Medicine, Chiba University, Inohana, Chuo-ku, Chiba-shi, Chiba.
Koichiro TatsumiDepartment of Respirology, Graduate School of Medicine, Chiba University, Inohana, Chuo-ku, Chiba-shi, Chiba.
Chiba University · JPSt. Marianna University School of Medicine · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent advances in multidetector computed tomography (MDCT) facilitate acquiring important clinical information for managing patients with COPD. MDCT can detect the loss of lung tissue associated with emphysema as a low-attenuation area (LAA) and the thickness of airways as the wall area percentage (WA%). The percentage of small pulmonary vessels <5 mm

methodsWe performed pulmonary function tests (PFTs), an MDCT, and a COPD assessment test (CAT) in 58 patients with COPD at the time of their enrollment at the hospital and 2 years later. We analyzed the change in clinical parameters including CT indices and examined the effect of exacerbations and smoking cessation on the structural changes.

resultsThe CAT score and forced expiratory volume in 1 second (FEV

conclusionThe WA% at the distal bronchi and the %CSA <5 did not change in parallel with parameters of LAA over the same period. We propose that airway disease and vascular remodeling may be reversible to some extent by smoking cessation and appropriate treatment. Optimal management may have a greater effect on pulmonary vascularity and airway disease than parenchymal deconstruction in the early stage of COPD.

Indexed as

Multidetector Computed TomographyVascular RemodelingAgedComputed Tomography AngiographyDisease ProgressionFemaleForced Expiratory VolumeHumansLongitudinal StudiesLungMaleMiddle AgedPhlebographyPredictive Value of TestsProspective StudiesPulmonary Arteryemphysemathe number of low-attenuation clusters (LAN)the percentage of small pulmonary vessels <5 mm2 (%CSA <5)wall area percentage (WA%)

Identifiers

PMID28243075
PMCPMC5315203
OpenAlexW2588116588

What OpenQuestion holds

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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.