Application of a multiple linear regression model of FEV1 in pulmonary function test.
10.12122/j.issn.1673-4254.2020.12.15
- Author:
Quanming DONG
1
;
Tianran SONG
1
;
Chenyu JIANG
1
;
Qin YAO
1
;
Fang CHEN
2
Author Information
1. First Clinical College of Zhejiang Chinese Medical University, Hangzhou 310053, China.
2. Department of Lung Function Tests, First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou 310053, China.
- Publication Type:Journal Article
- Keywords:
FEV1;
multiple linear regression;
pulmonary function test
- MeSH:
Adult;
Forced Expiratory Volume;
Humans;
Linear Models;
Lung;
Respiratory Function Tests;
Sex Factors
- From:
Journal of Southern Medical University
2020;40(12):1799-1803
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To 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.
METHODS:The 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.
RESULTS:FEV1 was not significantly correlated with BMI (
CONCLUSIONS:The multiple linear regression model for calculating FEV1 constructed in this study is suitable for clinical application.
