Evidence map›Paper›PMID 36267898›Full record

ArticleERJ open research2022

Clinical application of oscillometry in respiratory diseases: an impulse oscillometry registry.

Xiaolin Liang, Jinping Zheng, Yi Gao, Zhe Zhang, Wen Han, Jing Du, Yong Lu, Li Chen, Tao Wang, Jinming Liu and 7 more

Open access · goldAbstract read
In one paragraph

Article in ERJ open research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
4.2field-weighted citation impact, top 4% 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

29 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
  2. Article
  3. Small airways dysfunction: associated factors, clinical aspects and new perspectives.European respiratory review : an official journal of the European Respiratory Society · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Article
  20. Impulse oscillometry-derived equation for prediction of abnormal FEVThe Lancet regional health. Western Pacific · 2025
    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

17 authors at 14 institutions in 2 countries.

Xiaolin LiangNational Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Jinping ZhengNational Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0002-7511-661X
Yi GaoNational Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0003-1086-6564
Zhe ZhangNational Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Wen HanDept of Respiratory and Critical Care Medicine, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China.
Jing DuDept of Respiratory and Critical Care, West China Hospital, Sichuan University, Chengdu, China.
Yong LuDept of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Li ChenDept of Respiratory Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Tao WangDept of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jinming LiuDept of Pulmonary Circulation, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Gang HuangKey Laboratory of Respiratory Disease of Zhejiang Province, Dept of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Bingrong ZhaoDept of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha, China.
Guihua ZhaoDept of Cardiopulmonary function, Henan Provincial People's Hospital, Zhengzhou, China.
Xuhua ZhangDept of Pulmonary Function Test, Ningxia Medical University General Hospital, Yinchuan, China.
Yi PengDept of Respiratory Medicine, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xin ChenDept of Respiratory and Critical Care Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China.
Ning ZhouDept of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
First Affiliated Hospital of Guangzhou Medical University · CNCapital Medical University · CNCentral South University · CNFujian Medical University · CNHenan Provincial People's Hospital · CNNingxia Medical University · CNSecond Affiliated Hospital of Zhejiang University · CNShanxi Medical University · CNSichuan University · CNTianjin Medical University General Hospital · CNTongji Hospital · CNTongji University · CNUnion Hospital · CNZhujiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Respiratory oscillometry is a promising complement to the traditional pulmonary function tests for its simplicity. The usefulness of oscillometry in adult clinical practice has not been clarified. This study aimed to analyse the characteristics and diagnostic performance of oscillometry in respiratory diseases, and explore the cut-offs of oscillometric parameters for severity grading. Methods: In this multicentre registry of impulse oscillometry (IOS), IOS and spirometric data of healthy individuals and patients with respiratory diseases were collected and analysed. Linear mixed model analysis was performed to explore the effects of disease and forced expiratory volume in 1 s (FEV Results: The study included 567 healthy subjects, 781 asthmatic patients, 688 patients with chronic obstructive pulmonary disease (COPD), 109 patients with bronchiectasis, 40 patients with upper airway obstruction (UAO) and 274 patients with interstitial lung disease (ILD) in the analysis. Compared at the same FEV Conclusion: Respiratory oscillometry is more appropriate to be a tool of evaluating, rather than of diagnosing, respiratory diseases. A severity grading system of oscillometric parameters was developed to help the interpretation of oscillometry in clinical practice.

Identifiers

PMID36267898
PMCPMC9574560
OpenAlexW4229076475

What OpenQuestion holds

Textmetadata
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.