Department of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
Department of Respiratory and Critical Care Medicine, Henan Provincial People's Hospital, Zhengzhou, Henan, China.
BMJ Open Respir Res. 2024 Apr 5;11(1):e001954. doi: 10.1136/bmjresp-2023-001954.
Despite substantial progress in reducing the global burden of chronic obstructive pulmonary disease (COPD), traditional methods to promote understanding and management of COPD are insufficient. We developed an innovative model based on the internet of things (IoT) for screening and management of COPD in primary healthcare (PHC).
Electronic questionnaire and IoT-based spirometer were used to screen residents. We defined individuals with a questionnaire score of 16 or higher as high-risk population, COPD was diagnosed according to 2021 Global Initiative for COPD (Global Initiative for Chronic Obstructive Lung Disease) criteria. High-risk individuals and COPD identified through the screening were included in the COPD PHC cohort study, which is a prospective, longitudinal observational study. We provide an overall description of the study's design framework and baseline data of participants.
Between November 2021 and March 2023, 162 263 individuals aged over 18 from 18 cities in China were screened, of those 43 279 high-risk individuals and 6902 patients with COPD were enrolled in the cohort study. In the high-risk population, the proportion of smokers was higher than that in the screened population (57.6% vs 31.4%), the proportion of males was higher than females (71.1% vs 28.9%) and in people underweight than normal weight (57.1% vs 32.0%). The number of high-risk individuals increased with age, particularly after 50 years old (χ=37 239.9, p<0.001). Female patients are more common exposed to household biofuels (χ=72.684, p<0.05). The majority of patients have severe respiratory symptoms, indicated by a CAT score of ≥10 (85.8%) or an Modified Medical Research Council Dyspnoea Scale score of ≥2 (65.5%).
Strategy based on IoT model help improve the detection rate of COPD in PHC. This cohort study has established a large clinical database that encompasses a wide range of demographic and relevant data of COPD and will provide invaluable resources for future research.
尽管在降低慢性阻塞性肺疾病（COPD）全球负担方面取得了重大进展，但传统的提高对 COPD 认识和管理的方法仍不够充分。我们开发了一种基于物联网（IoT）的创新模型，用于初级医疗保健（PHC）中的 COPD 筛查和管理。
使用电子问卷和基于 IoT 的肺活量计对居民进行筛查。我们将问卷得分达到 16 分或以上的个体定义为高危人群，根据 2021 年全球慢性阻塞性肺疾病倡议（Global Initiative for Chronic Obstructive Lung Disease，GOLD）标准诊断 COPD。通过筛查确定的高危人群和 COPD 患者被纳入 COPD PHC 队列研究，这是一项前瞻性、纵向观察性研究。我们提供了研究设计框架的总体描述和参与者的基线数据。
2021 年 11 月至 2023 年 3 月，中国 18 个城市的 18 岁以上人群中共有 162263 人接受了筛查，其中 43279 人为高危人群，6902 人为 COPD 患者被纳入队列研究。在高危人群中，吸烟者的比例高于筛查人群（57.6% vs. 31.4%），男性比例高于女性（71.1% vs. 28.9%），体重不足的比例高于正常体重（57.1% vs. 32.0%）。高危人群的数量随年龄增长而增加，特别是 50 岁以后（χ²=37239.9，p<0.001）。女性患者更常见接触家用生物燃料（χ²=72.684，p<0.05）。大多数患者呼吸症状严重，CAT 评分≥10 分（85.8%）或改良医学研究委员会呼吸困难量表评分≥2 分（65.5%）。
基于 IoT 模型的策略有助于提高 PHC 中 COPD 的检出率。该队列研究建立了一个包含 COPD 广泛人口统计学和相关数据的大型临床数据库，将为未来的研究提供宝贵的资源。
