Whole-course management of chronic obstructive pulmonary disease in primary healthcare: an internet of things-enabled prospective cohort study in China

Abstract

Background 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). Methods 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. Results 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 (χ2=37 239.9, p<0.001). Female patients are more common exposed to household biofuels (χ2=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%). Conclusion 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. No data are available. Researchers interested in collaboration and further information are invited to contact the corresponding author XZhang.