Novel equations better predict lung age: a retrospective analysis using two cohorts of participants with medical check-up examinations in Japan

新的方程式能更好地预测肺龄:一项基于日本两组接受体检参与者的回顾性分析

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Abstract

BACKGROUND: The lung age equations developed by the Japanese Respiratory Society encounter several problems when being applied in a clinical setting. AIMS: To establish novel spirometry-derived lung age (SDL age) equations using data from a large number of Japanese healthy never-smokers with normal spirometric measurements and normal body mass indices (BMIs). METHODS: The participants had undergone medical check-ups at the Center for Preventive Medicine of St Luke's International Hospital between 2004 and 2012. A total of 15,238 Japanese participants (5,499 males and 9,739 females) were chosen for the discovery cohort. The other independent 2,079 individuals were selected for the validation cohort. The original method of Morris and Temple was applied to the discovery cohort. RESULTS: As a result of the linear regression analysis for forced expiratory volume in 1 s (FEV1), spirometric variables using forced vital capacity (FVC) improved the adjusted R(2) values to greater than 0.8. On the basis of the scatter plots between chronological age and SDL age, the best model included the equations using FEV1 and %FVC in females and males (R(2)=0.66 and 0.55, respectively), which was confirmed by the validation cohort. The following equations were developed: SDL age (females)=0.84×%FVC+50.2-40×FEV1 (l) and SDL age (males)=1.00×%FVC+50.7-33.3×FEV1 (l). CONCLUSIONS: This study produced novel SDL age equations for Japanese adults using data from a large number of healthy never-smokers with both normal spirometric measurements and BMIs.

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