Evidence map›Paper›PMID 28184155›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2017

Risk factors for FEV

Shujing Chen, Changhui Wang, Bing Li, Guochao Shi, Huiping Li, Jing Zhang, Yutong Gu, Jian Zhou, Yuanlin Song, Chunxue Bai

Open access · goldAbstract readComparative StudyMulticenter Study
In one paragraph

Article 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, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
1.2field-weighted citation impact, top 20% 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, 2 syntheses or guidelines pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Review
  5. Design of the SPIROMICS Study of Early COPD Progression: SOURCE Study.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2024
    Article
  6. Article
  7. Article
  8. Investigation of time profile of FEVScientific reports · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Re-Defining High Risk COPD with Parameter Response Mapping Based on Machine Learning Models.International journal of chronic obstructive pulmonary disease · 2022
    Article
  13. Article
  14. Article
  15. Review
  16. [Delayed diagnosis is associated with greater disease severity of chronic obstructive pulmonary disease].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2018
    Article
  17. Article
  18. 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

10 authors at 7 institutions in 2 countries.

Shujing ChenDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University.
Changhui WangDepartment of Pulmonary Medicine, Shanghai Tenth People's Hospital.
Bing LiDepartment of Pulmonary Medicine, Shanghai Changzheng Hospital.
Guochao ShiDepartment of Pulmonary Medicine, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine.
Huiping LiDepartment of Pulmonary Medicine, Shanghai Pulmonary Hospital, Shanghai, People's Republic of China.
Jing ZhangDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University.
Yutong GuDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University.
Jian ZhouDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University.
Yuanlin SongDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University.
Chunxue BaiDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University.
Sun Yat-sen University · CNFudan University · CNShanghai Changzheng Hospital · CNShanghai Jiao Tong University · CNShanghai Pulmonary Hospital · CNShanghai Tenth People's Hospital · CNThe First Affiliated Hospital, Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly diagnosis of COPD is often not achieved due to limited recognition and limited access to the pulmonary function test. Our hypothesis was that lung function decline may be different between populations with mild COPD and those who are at high risk and do not receive treatment. PATIENTS AND

methodsSubjects with mild COPD and those from a high-risk COPD population were recruited from a community-based COPD epidemiological study after obtaining consent. Baseline clinical characteristics, symptom questionnaire, spirometry, low-dose computed tomography (LDCT) chest scan, and blood plasma biomarker data were collected initially and then 1 year later.

resultsA total of 617 participants were recruited, and 438 eventually completed the first-year follow-up visit; 72 participants (46 males) were in the mild COPD group, and 225 participants (165 males) were in the high-risk group. The mean forced expiratory volume in the first second of expiration (FEV

conclusionGroup category was an independent influential factor associated with FEV

Indexed as

Forced Expiratory VolumeAgedAged, 80 and overBiomarkersChinaChi-Square DistributionDisease ProgressionFemaleHumansLogistic ModelsLungMaleMiddle AgedMultivariate AnalysisOdds RatioPrognosisBiomarkersbiomarkerCOPDEmphysema Indexlung function declinespirometry

Identifiers

PMID28184155
PMCPMC5291456
OpenAlexW2581166394

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.