Dong Quanming, Song Tianran, Jiang Chenyu, Yao Qin, Chen Fang
First Clinical College of Zhejiang Chinese Medical University, Hangzhou 310053, China.
Department of Lung Function Tests, First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou 310053, China.
Nan Fang Yi Ke Da Xue Xue Bao. 2020 Dec 30;40(12):1799-1803. doi: 10.12122/j.issn.1673-4254.2020.12.15.
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.
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.
FEV1 was not significantly correlated with BMI (=-0.026, =0.457), poorly correlated with body mass (=0.382, =0.000), positively correlated with height (=0.723, =0.000), and negatively correlated with Rrs (=-0.503, =0.000) with an obvious gender differences (=18.517, =0.000). FEV1 was positively correlated with age among individuals below 25 years of age (=0.578, =0.000) and was negatively correlated with age among those beyond or at the age of 25 (=-0.589, =0.000). For individuals beyond or at the age of 25 years, the variables of height, gender, age and Rrs were included in the model, and the calculated FEV1 did not differ significantly from the measured values in either the modeling sample (=751; =1.293, =0.196) or the verification sample (=83;=-1.736, =0.086), and the two values were well correlated in the verification sample (=0.891, =0.000). For individuals below 25 years, only height was included in the model, and the calculated FEV1 and the measured values showed no significant difference in the modeling sample (=62; =-0.009, =0.993) or the verification sample (=11; =-0.635, =0.540) with a good correlation in the verification sample (=0.795, =0.003).
The multiple linear regression model for calculating FEV1 constructed in this study is suitable for clinical application.
构建1秒用力呼气容积（FEV1）的多元线性回归模型，用于估计无法接受或不配合肺通气功能检查的特殊人群的FEV1。
基于2017年9月至2019年9月在浙江中医药大学附属第一医院接受肺功能检查的813例个体的数据构建FEV1的多元线性回归模型，并使用同一医院2020年1月至7月的另外94例个体的数据进行验证。通过肺通气功能检查测量个体的FEV1，采用强迫振荡技术（FOT）测量呼吸阻力（Rrs）。采用Pearson相关分析评估各因素之间的相关性，通过多元逐步回归分析建立模型方程。将基于模型计算得到的FEV1与建模和验证所纳入个体的实测FEV1进行比较。
FEV1与BMI无显著相关性（r = -0.026，P = 0.457），与体重相关性较差（r = 0.382，P = 0.000），与身高呈正相关（r = 0.723，P = 0.000），与Rrs呈负相关（r = -0.503，P = 0.000），且存在明显的性别差异（F = 18.517，P = 0.000）。25岁以下个体的FEV1与年龄呈正相关（r = 0.578，P = 0.000），25岁及以上个体的FEV1与年龄呈负相关（r = -0.589，P = 0.000）。对于25岁及以上个体，模型纳入了身高、性别、年龄和Rrs变量，在建模样本（n = 751；t = 1.293，P = 0.196）或验证样本（n = 83；t = -1.736，P = 0.086）中，基于模型计算得到的FEV1与实测值差异均无统计学意义，且在验证样本中两者相关性良好（r = 0.891，P = 0.000）。对于25岁以下个体，模型仅纳入了身高，在建模样本（n = 62；t = -0.009，P = 0.993）或验证样本（n = 11；t = -0.635，P = 0.540）中，计算得到的FEV1与实测值差异均无统计学意义，且在验证样本中两者相关性良好（r = 0.795，P = 0.003）。
本研究构建的计算FEV1的多元线性回归模型适用于临床应用。
