Evidence map›Paper›PMID 36175436›Full record

ArticleNPJ primary care respiratory medicine2022

Estimation of lung age via a spline method and its application in chronic respiratory diseases.

Xiaolin Liang, Yanqing Xie, Yi Gao, Yumin Zhou, Wenhua Jian, Mei Jiang, Hongyu Wang, Jinping Zheng

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ primary care respiratory medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 1 institution in 3 countries.

Xiaolin Liang *National 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, Guangdong, China.ORCID 0000-0002-1579-6617
Yanqing Xie *National 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, Guangdong, China.
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, Guangdong, China.
Yumin ZhouNational 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, Guangdong, China.
Wenhua JianNational 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, Guangdong, China.
Mei JiangNational 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, Guangdong, China.
Hongyu WangNational 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, Guangdong, China.ORCID 0000-0002-4341-8410
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, Guangdong, China. jpzhenggy@163.com.ORCID 0000-0002-7511-661X
First Affiliated Hospital of Guangzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung age is a simplified concept that makes spirometry data easier to understand, but it is not widely used due to limitations in estimation methods. The aim of this study was to develop new equations to estimate lung age and to explore the application value of lung age in chronic respiratory diseases. Retrospective spirometric data of 18- to 80-year-old healthy subjects were used to develop the lung age estimation equations. Models were respectively built by multiple linear regression, piecewise linear regression, and the natural cubic spline method. Patients with chronic obstructive pulmonary disease (COPD) and asthma were subdivided into stages I-IV according to the severity of airflow limitation under the recommendation of the Global Initiative for Chronic Obstructive Lung Disease. Propensity score matching was performed to balance age, height and sex between healthy subjects and patients. The difference between lung age and chronological age (∆ lung age) of patients with COPD and asthma was analyzed. A total of 3409 healthy subjects, 280 patients with COPD and 285 patients with asthma data were included in the analysis. The lung age estimation equation with the best goodness of fit was built by the spline method and composed of FEV

Indexed as

AsthmaPulmonary Disease, Chronic ObstructiveAdolescentAdultAgedAged, 80 and overHumansLungMiddle AgedRetrospective StudiesSpirometryYoung Adult

Identifiers

PMID36175436
PMCPMC9522795
OpenAlexW4298005015

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.