Evidence map›Paper›PMID 38505045›Full record

ArticleJournal of thoracic disease2024

Feasibility and performance of the chronic obstructive pulmonary disease population screener and chronic obstructive pulmonary disease screening questionnaire in a Chinese physical examination center.

Xiaoqing Huang, Hanguang Yu, Enmin Huang, Shuqian Wang, Jiali Chen, Jinweng Weng, Peter S P Cho, Mi Hyoung Moon, Mei Song, Xueying Fang

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2024. 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. Trial
  2. Trial
  3. COPD-Lung Cancer Comorbidity: Mechanistic Insights and Precision Oncology Implications.International journal of chronic obstructive pulmonary disease · 2026
    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

10 authors.

Xiaoqing HuangDepartment of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
Hanguang YuDepartment of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
Enmin HuangGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Department of Gastroenterological Surgery and Hernia Center, Sun Yat-sen University Sixth Affiliated Hospital, Guangzhou, China.
Shuqian WangDepartment of Respiratory and Critical Care Medicine, Mianyang Third People's Hospital, Mianyang, China.
Jiali ChenDepartment of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
Jinweng WengDepartment of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
Peter S P ChoDepartment of Respiratory Medicine, King's College Hospital, London, UK.
Mi Hyoung MoonDepartment of Thoracic and Cardiovascular Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Mei SongDepartment of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
Xueying FangDepartment of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Shantou University Medical College, Shantou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic obstructive pulmonary disease (COPD) affects up to 13% of the Chinese population, though it is under diagnosed throughout China. Screening among asymptomatic individual as part of routine health checks in China can facilitate early diagnosis and intervention to prevent disease progress. The COPD Population Screener (COPD-PS) or COPD Screening Questionnaire (COPD-SQ) has yet to be applied in Chinese physical examination centers (PECs) for COPD screening, and their feasibility and effectiveness should be clarified before full-scale implementation. This study is the first to apply the COPD-PS and COPD-SQ in a public hospital PEC in China to assess their feasibility and effectiveness and to identify their optimal cutoff values. Methods: People aged ≥40 years who attended the Second Affiliated Hospital of Shantou University PECs from September 2021 to December 2022 were asked to complete the COPD-PS and COPD-SQ and to undergo spirometry. The optimal cutoff values of the two questionnaires at the maximal Youden index were found, and the sensitivity and specificity were calculated. Results: Data from 198 participants were analyzed; mean [standard deviation (SD)] age of patients was 63.52 (10.94) years. Twenty-five participants (12.63%) were diagnosed with COPD. The number of COPD patients classified as Global Initiative for Chronic Obstructive Lung Disease (GOLD) grades 1 to 4 were 8, 12, 4, and 1, respectively. The area under the curves (AUCs) of the COPD-PS and COPD-SQ were 0.730 and 0.738, respectively. The optimal COPD-PS cutoff value of 4 points corresponded to a sensitivity of 72.00% and a specificity of 60.10%. The COPD-SQ optimal cutoff value of 15 points corresponded to a sensitivity of 76.00% and a specificity of 63.60%. Conclusions: Applying the COPD-PS and COPD-SQ in Chinese PECs is feasible, cost-effective and effective. COPD-PS and COPD-SQ can facilitate the early diagnosis of COPD, and whether they can improve the participants' quality of life would benefit a further study. It is recommended that the COPD-PS or COPD-SQ questionnaires be added to the screening of the physical examination program in PECs as part of health checks for people over 40 years old.

Indexed as

Chronic obstructive pulmonary disease (COPD)health checksphysical examination center (PEC)questionnairessensitivity and specificity

Identifiers

PMID38505045
PMCPMC10944747

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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.