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COMPAIR: a comparison of directly supervised clinic versus virtually supervised home spirometry
Ashish Pradhan1, Jacqui Pollington2, Dinesh Saralaya3
1The Nottingham Asthma Centre, Nottingham City Hospital NHS Foundation Trust, Nottingham, UK.
Virtually supervised at-home spirometry (VSHS) provides reliable lung function measures comparable to in-clinic tests for asthma and COPD patients. Artificial intelligence over-reading enhances accuracy and patient convenience in VSHS.
Area of Science:
- Pulmonary Medicine
- Digital Health
- Artificial Intelligence in Healthcare
Background:
- Spirometry is crucial for diagnosing and monitoring respiratory conditions like asthma and COPD.
- Traditional in-clinic spirometry can be inconvenient for patients.
- Exploring remote monitoring solutions is essential for improving patient access and adherence.
Purpose of the Study:
- To compare directly supervised in-clinic spirometry (DSCS) with virtually supervised at-home spirometry (VSHS).
- To assess the utility of artificial intelligence (AI) over-reading in VSHS.
- To evaluate patient satisfaction with VSHS.
Main Methods:
- A multicentre, prospective study involving adult asthma/COPD patients.
- Spirometry (FEV1, FVC) performed using NuvoAir Air Next device in-clinic and remotely.
- AI (ArtiQ.QC) and manual over-reading compared with healthcare provider assessments.
Main Results:
- Excellent concordance (ICC >0.95) between DSCS and VSHS for FEV1 and FVC.
- AI over-reading by ArtiQ.QC showed slightly higher concordance than manual over-reading.
- Good agreement observed via Bland-Altman plots, with better agreement using AI.
- Over 95% of patients found the VSHS system easy to use and expressed willingness for future use.
Conclusions:
- VSHS with AI over-reading provides reliable and consistent lung function measures for asthma/COPD patients.
- VSHS enables convenient remote spirometry without compromising data quality.
- This approach holds potential for both research and clinical applications in respiratory care.
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