Evidence map›Paper›PMID 37969311›Full record

ReviewJournal of thoracic disease2023

The utility of quantitative computed tomography in cohort studies of chronic obstructive pulmonary disease: a narrative review.

Qi Dai, Xiaoxiao Zhu, Jingfeng Zhang, Zhaoxing Dong, Eugenio Pompeo, Jianjun Zheng, Jingyun Shi

Open access · diamondAbstract readReview
In one paragraph

Review in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.3field-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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Quantitative computed tomography and predictive modelling for COPD exacerbations.European respiratory review : an official journal of the European Respiratory Society · 2025
    Pooled it
  2. Imaging Markers of Chronic Obstructive Pulmonary Disease on Computed Tomography of the Lungs: a Narrative Review.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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 at 3 institutions in 2 countries.

Qi DaiSchool of Medicine, Tongji University, Shanghai, China.
Xiaoxiao ZhuDepartment of Respiratory and Critical Care Medicine, Ningbo No.2 Hospital, Ningbo, China.
Jingfeng ZhangDepartment of Radiology, Ningbo No.2 Hospitall, Ningbo, China.
Zhaoxing DongDepartment of Respiratory and Critical Care Medicine, Ningbo No.2 Hospital, Ningbo, China.
Eugenio PompeoDepartment of Thoracic Surgery, Policlinico Tor Vergata University, Rome, Italy.
Jianjun ZhengDepartment of Radiology, Ningbo No.2 Hospitall, Ningbo, China.
Jingyun ShiSchool of Medicine, Tongji University, Shanghai, China.
Ningbo No.6 Hospital · CNTongji University · CNPoliclinico Tor Vergata · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: Chronic obstructive pulmonary disease (COPD) is a significant contributor to global morbidity and mortality. Quantitative computed tomography (QCT), a non-invasive imaging modality, offers the potential to assess lung structure and function in COPD patients. Amidst the coronavirus disease 2019 (COVID-19) pandemic, chest computed tomography (CT) scans have emerged as a viable alternative for assessing pulmonary function (e.g., spirometry), minimizing the risk of aerosolized virus transmission. However, the clinical application of QCT measurements is not yet widespread enough, necessitating broader validation to determine its usefulness in COPD management. Methods: We conducted a search in the PubMed database in English from January 1, 2013 to April 20, 2023, using keywords and controlled vocabulary related to QCT, COPD, and cohort studies. Key Content and Findings: Existing studies have demonstrated the potential of QCT in providing valuable information on lung volume, airway geometry, airway wall thickness, emphysema, and lung tissue density in COPD patients. Moreover, QCT values have shown robust correlations with pulmonary function tests, and can predict exacerbation risk and mortality in patients with COPD. QCT can even discern COPD subtypes based on phenotypic characteristics such as emphysema predominance, supporting targeted management and interventions. Conclusions: QCT has shown promise in cohort studies related to COPD, since it can provide critical insights into the pathogenesis and progression of the disease. Further research is necessary to determine the clinical significance of QCT measurements for COPD management.

Indexed as

chronic obstructive pulmonary disease (COPD)cohort studyQuantitative computed tomography (QCT)

Identifiers

PMID37969311
PMCPMC10636446
OpenAlexW4388105222

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.