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评价南亚人群及居住在其他国家的南亚人群肺功能测试中肺活量测定法的参考值方程。

Reference equations for evaluation of spirometry function tests in South Asia, and among South Asians living in other countries.

机构信息

Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.

Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.

出版信息

Eur Respir J. 2022 Dec 1;60(6). doi: 10.1183/13993003.02962-2021. Print 2022 Dec.

DOI:10.1183/13993003.02962-2021
PMID:35896203
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9712850/
Abstract

BACKGROUND

There are few data to support accurate interpretation of spirometry data in South Asia, a major global region with a high reported burden of chronic respiratory disease.

METHOD

We measured lung function in 7453 healthy men and women aged ≥18 years, from Bangladesh, North India, South India, Pakistan and Sri Lanka, as part of the South Asia Biobank study. First, we assessed the accuracy of existing equations for predicting normal forced vital capacity (FVC), forced expiratory volume in 1 s (FEV) and FEV/FVC ratio. Then, we used our data to derive (n=5589) and internally validate (n=1864) new prediction equations among South Asians, with further external validation among 339 healthy South Asians living in Singapore.

RESULTS

The Global Lung Initiative (GLI) and National Health and Nutrition Examination Survey consistently overestimated expiratory volumes (best fit GLI-African American, mean±sd z-score: FEV -0.94±1.05, FVC -0.91±1.10; n=7453). Age, height and weight were strong predictors of lung function in our participants (p<0.001), and sex-specific reference equations using these three variables were highly accurate in both internal validation (z-scores: FEV 0.03±0.99, FVC 0.04±0.97, FEV/FVC -0.03±0.99) and external validation (z-scores: FEV 0.31±0.99, FVC 0.24±0.97, FEV/FVC 0.16±0.91). Further adjustment for study regions improves the model fit, with highest accuracy for estimation of region-specific lung function in South Asia.

CONCLUSION

We present improved equations for predicting lung function in South Asians. These offer the opportunity to enhance diagnosis and management of acute and chronic lung diseases in this major global population.

摘要

背景

亚洲南部是一个拥有大量慢性呼吸道疾病报告负担的主要地区,但目前用于准确解读该地区肺功能检测数据的资料十分有限。

方法

我们在南亚生物库研究中对来自孟加拉国、北印度、南印度、巴基斯坦和斯里兰卡的 7453 名年龄≥18 岁的健康男性和女性进行了肺功能检测。首先,我们评估了现有的预测正常用力肺活量(FVC)、1 秒用力呼气量(FEV)和 FEV/FVC 比值的方程的准确性。然后,我们使用来自南亚人群的数据(n=5589)推导出(n=1864)并在内部验证(n=5589)了新的预测方程,进一步在居住在新加坡的 339 名健康南亚人群中进行了外部验证。

结果

全球肺功能倡议(GLI)和美国国家健康和营养调查数据一致高估了呼气量(最佳拟合 GLI-非洲裔美国人,平均±标准差 z 分数:FEV-0.94±1.05,FVC-0.91±1.10;n=7453)。在我们的研究参与者中,年龄、身高和体重是肺功能的强有力预测因素(p<0.001),使用这三个变量的性别特异性参考方程在内部验证中高度准确(z 分数:FEV0.03±0.99,FVC0.04±0.97,FEV/FVC-0.03±0.99)和外部验证(z 分数:FEV0.31±0.99,FVC0.24±0.97,FEV/FVC0.16±0.91)。进一步调整研究区域可改善模型拟合度,从而可提高对南亚特定区域肺功能的估计准确性。

结论

我们提出了用于预测南亚人群肺功能的改良方程。这为在这个主要的全球人群中加强对急性和慢性肺部疾病的诊断和管理提供了机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/270cf3bbdc15/ERJ-02962-2021.07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/8e620551d00f/ERJ-02962-2021.01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/9a28dd5387b2/ERJ-02962-2021.02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/b56d059161d3/ERJ-02962-2021.03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/5b95e5850e40/ERJ-02962-2021.04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/d68cbea90ae9/ERJ-02962-2021.05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/701c895eab50/ERJ-02962-2021.06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/270cf3bbdc15/ERJ-02962-2021.07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/8e620551d00f/ERJ-02962-2021.01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/9a28dd5387b2/ERJ-02962-2021.02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/b56d059161d3/ERJ-02962-2021.03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/5b95e5850e40/ERJ-02962-2021.04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/d68cbea90ae9/ERJ-02962-2021.05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/701c895eab50/ERJ-02962-2021.06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6119/9712850/270cf3bbdc15/ERJ-02962-2021.07.jpg

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