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

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.

Re-evaluation of the diagnostic value of fractional exhaled nitric oxide & its impact in patients with asthma.

BACKGROUND & OBJECTIVES: The diagnostic value of fractional exhaled nitric oxide (FeNO) in patients with asthma remains controversial. This study was aimed to re-evaluate the diagnostic value of FeNO in specific groups with asthma and identify potential factors associated with FeNO. METHODS: FeNO measurement and bronchial provocation test (BPT) or bronchodilator test (BDT) were performed in patients with suggestive symptoms for asthma. Correlation analysis was performed, and receiver-operating characteristic (ROC) curves and area under the curve (AUC) were calculated to evaluate the accuracy of FeNO in diagnosis. RESULTS: A total of 265 (66.3%) patients with asthma were identified in 400 individuals suspected to have asthma from October 2014 to June 2015. Positive correlations of gender (r=0.138, P=0.005), atopy (r=0.598, P <0.001) and rhinitis (r=0.485, P <0.001) but negative correlations of age (r=-0.220, P <0.001) and the cumulative methacholine dosage with a 20 per cent decrease in forced expiratory volume in one second (r=-0.197, P <0.001) with FeNO were found. AUC of FeNO in whole population and patients with atopy and rhinitis was 0.728 [95% confidence interval (CI) 0.675-0.781, P <0.001] and 0.752 (95% CI 0.640-0.865, P <0.001), while the cut-offs were 23.5 and 44.5 parts per billion (ppb), respectively, rendering sensitivities, specificities, positive predictive value and negative predictive value of 79.9, 54.7, 77.9, 58.1 and 78.7, 67.9, 89.2 and 48.7 per cent, respectively. The cut-off of FeNO with specificity of 90 per cent (FeNO90) for all patients and a sub-group of patients with atopy and rhinitis was 59.5 and 90.5 ppb, respectively, while FeNO90decreased by 12 ppb with every 10 years. INTERPRETATION & CONCLUSIONS: : Our findings show that the diagnostic value of FeNO varies in different groups of patients with asthma, thus, the cut-off point should be adjusted in different asthmatic sub-populations. A cut-off point of FeNO with a specificity >90 per cent could decrease the false-positive rate.