State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Diseases, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, China;
J Thorac Dis. 2012 Dec;4(6):594-600. doi: 10.3978/j.issn.2072-1439.2012.11.06.
COPD is often underdiagnosed in a primary care setting where the spirometry is unavailable. This study was aimed to develop a simple, economical and applicable model for COPD screening in those settings.
First we established a discriminant function model based on Bayes' Rule by stepwise discriminant analysis, using the data from 243 COPD patients and 112 non-COPD subjects from our COPD survey in urban and rural communities and local primary care settings in Guangdong Province, China. We then used this model to discriminate COPD in additional 150 subjects (50 non-COPD and 100 COPD ones) who had been recruited by the same methods as used to have established the model. All participants completed pre- and post-bronchodilator spirometry and questionnaires. COPD was diagnosed according to the Global Initiative for Chronic Obstructive Lung Disease criteria. The sensitivity and specificity of the discriminant function model was assessed.
THE ESTABLISHED DISCRIMINANT FUNCTION MODEL INCLUDED NINE VARIABLES: age, gender, smoking index, body mass index, occupational exposure, living environment, wheezing, cough and dyspnoea. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, accuracy and error rate of the function model to discriminate COPD were 89.00%, 82.00%, 4.94, 0.13, 86.66% and 13.34%, respectively. The accuracy and Kappa value of the function model to predict COPD stages were 70% and 0.61 (95% CI, 0.50 to 0.71).
This discriminant function model may be used for COPD screening in primary care settings in China as an alternative option instead of spirometry.
在无法进行肺量测定的基层医疗环境中，慢性阻塞性肺疾病（COPD）常被漏诊。本研究旨在建立一种简单、经济且适用的模型，用于在这些环境中对 COPD 进行筛查。
首先，我们通过逐步判别分析，基于贝叶斯规则，利用中国广东省城乡社区和当地基层医疗机构 COPD 调查中 243 例 COPD 患者和 112 例非 COPD 患者的数据，建立判别函数模型。然后，我们使用该模型对通过相同方法招募的另外 150 名受试者（50 名非 COPD 和 100 名 COPD）进行 COPD 判别。所有参与者均完成了支气管扩张剂预后肺量测定和问卷调查。根据全球慢性阻塞性肺疾病倡议标准诊断 COPD。评估判别函数模型的敏感性和特异性。
建立的判别函数模型包括 9 个变量：年龄、性别、吸烟指数、体重指数、职业暴露、生活环境、喘息、咳嗽和呼吸困难。该功能模型对 COPD 的判别敏感性、特异性、阳性似然比、阴性似然比、准确性和误差率分别为 89.00%、82.00%、4.94、0.13、86.66%和 13.34%。该功能模型预测 COPD 分期的准确性和 Kappa 值分别为 70%和 0.61（95%置信区间，0.50 至 0.71）。
该判别函数模型可作为肺量测定的替代方法，用于中国基层医疗机构的 COPD 筛查。
