Evidence map›Paper›PMID 33380396›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2020

[Application of a multiple linear regression model of FEV1 in pulmonary function test].

Quanming Dong, Tianran Song, Chenyu Jiang, Qin Yao, Fang Chen

Open access · greenAbstract read
In one paragraph

Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 73% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 1 institution in 1 country.

Quanming DongFirst Clinical College of Zhejiang Chinese Medical University, Hangzhou 310053, China.
Tianran SongFirst Clinical College of Zhejiang Chinese Medical University, Hangzhou 310053, China.
Chenyu JiangFirst Clinical College of Zhejiang Chinese Medical University, Hangzhou 310053, China.
Qin YaoFirst Clinical College of Zhejiang Chinese Medical University, Hangzhou 310053, China.
Fang ChenDepartment of Lung Function Tests, First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou 310053, China.
Zhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo construct a multiple linear regression model of forced expiratory volume in 1 second (FEV1) for estimating FEV1 in special populations unable to receive or uncooperative in pulmonary ventilation function tests.

methodsThe multiple linear regression model of FEV1 was constructed based on the data of 813 individuals undergoing pulmonary function tests in First Affiliated Hospital of Zhejiang Chinese Medical University between September, 2017 and September, 2019, and was validated using the data of another 94 individuals from the same hospital between January and July, 2020. FEV1 of the individuals was measured by pulmonary ventilation function test, and respiratory resistance (Rrs) was measured using forced oscillation technique (FOT). Pearson correlation analysis was used to assess the correlation between the factors, and the model equation was established by multiple stepwise regression analysis. The calculated FEV1 based on the model was compared with the measured FEV1 among both the individuals included for modeling and validation.

resultsFEV1 was not significantly correlated with BMI (

conclusionsThe multiple linear regression model for calculating FEV1 constructed in this study is suitable for clinical application.

Indexed as

LungAdultFemaleForced Expiratory VolumeHumansLinear ModelsMaleRespiratory Function TestsSex FactorsFEV1multiple linear regressionpulmonary function test

Identifiers

PMID33380396
PMCPMC7835695
OpenAlexW3114305357

What OpenQuestion holds

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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.