Seoul Women's College of Nursing, Seoul, South Korea.
Department of Health Administration, Hanyang Women's University, Seoul, South Korea.
Medicine (Baltimore). 2024 Sep 27;103(39):e39901. doi: 10.1097/MD.0000000000039901.
Chronic obstructive pulmonary disease (COPD) remains a significant global health burden exacerbated by tobacco smoking, occupational exposure, and air pollution. COPD is one of the top 3 causes of death worldwide. In South Korea, the COPD burden is expected to increase due to ongoing exposure to risk factors and the aging population. COPD is extensively underdiagnosed or underestimated, owing to a lack of public awareness. This study aimed to develop and validate a nomogram for COPD by using national data to promote early diagnosis and intervention. This study drew on a dataset from the 7th Korea National Health and Nutrition Examination Survey from 2016 to 2018, including 10,819 subjects aged 40 years or older with spirometry results. Influence of demographic, socioeconomic, and health-related factors on the incidence. Multivariable logistic regression was used to identify the significant predictors of the nomogram. The nomogram was validated using receiver operating characteristic curves, calibration plots, and concordance index (C-index). Internal validation was performed by bootstrapping. In the final analysis, 1059 (14.0%) participants had COPD. Key risk factors associated with increased COPD risk included being male, aged 70 and older, lower educational level, living in a rural area, current smoking status, underweight, and history of tuberculosis and asthma. The area under the curve (AUC) of the model was 0.822 (95% CI: 0.810-0.832), indicating that the nomogram has a high ability to identify COPD. The nomogram demonstrated solid predictive performance, as confirmed by calibration plots with a C-index (of 0.822) for the validation set with 1000 bootstrap samples. In conclusion, we developed a tool for the early detection of COPD with good properties in primary care settings, without spirometry. Appropriate and early diagnosis of COPD can have a crucial impact on public health.
慢性阻塞性肺疾病（COPD）仍然是一个重大的全球健康负担，其恶化原因包括烟草吸烟、职业暴露和空气污染。COPD 是全球前三大死因之一。在韩国，由于持续暴露于危险因素和人口老龄化，COPD 的负担预计将会增加。由于公众意识不足，COPD 广泛被低估或诊断不足。本研究旨在利用国家数据开发和验证 COPD 的列线图，以促进早期诊断和干预。本研究基于 2016 年至 2018 年第七次韩国国家健康和营养检查调查的数据，包括 10819 名年龄在 40 岁或以上、有肺量计结果的受试者。影响发病的人口统计学、社会经济和健康相关因素。多变量逻辑回归用于确定列线图的显著预测因素。使用受试者工作特征曲线、校准图和一致性指数（C 指数）验证列线图。内部验证通过引导程序进行。最终分析中，1059 名（14.0%）参与者患有 COPD。与 COPD 风险增加相关的主要危险因素包括男性、70 岁及以上、教育程度较低、居住在农村地区、当前吸烟状况、体重不足以及结核病和哮喘病史。模型的曲线下面积（AUC）为 0.822（95%CI：0.810-0.832），表明列线图具有较高的识别 COPD 的能力。校准图的 C 指数（验证集中 1000 个 bootstrap 样本为 0.822）表明，该列线图具有可靠的预测性能。总之，我们开发了一种在没有肺量计的情况下用于 COPD 早期检测的工具，在初级保健环境中具有良好的性能。对 COPD 的适当和早期诊断对公共卫生具有至关重要的影响。
