{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["9(1)"],"submitter":["Topole E"],"pubmed_abstract":["Rationale
Acquiring high-quality spirometry data in clinical trials is important, particularly when using forced expiratory volume in 1 s or forced vital capacity as primary end-points. In addition to quantitative criteria, the American Thoracic Society (ATS)/European Respiratory Society (ERS) standards include subjective evaluation which introduces inter-rater variability and potential mistakes. We explored the value of artificial intelligence (AI)-based software (ArtiQ.QC) to assess spirometry quality and compared it to traditional over-reading control.Methods
A random sample of 2000 sessions (8258 curves) was selected from Chiesi COPD and asthma trials (n=1000 per disease). Acceptability using the 2005 ATS/ERS standards was determined by over-reader review and by ArtiQ.Q"],"journal":["ERJ open research"],"pagination":["00292-2022"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9907146"],"repository":["biostudies-literature"],"pubmed_title":["Artificial intelligence based software facilitates spirometry quality control in asthma and COPD clinical trials."],"pmcid":["PMC9907146"],"pubmed_authors":["Biondaro S","Stanojevic S","Ray K","Montagna I","Corradi M","Graham B","Das N","Topole E","Corre S","Topalovic M"],"additional_accession":[]},"is_claimable":false,"name":"Artificial intelligence based software facilitates spirometry quality control in asthma and COPD clinical trials.","description":"Rationale
Acquiring high-quality spirometry data in clinical trials is important, particularly when using forced expiratory volume in 1 s or forced vital capacity as primary end-points. In addition to quantitative criteria, the American Thoracic Society (ATS)/European Respiratory Society (ERS) standards include subjective evaluation which introduces inter-rater variability and potential mistakes. We explored the value of artificial intelligence (AI)-based software (ArtiQ.QC) to assess spirometry quality and compared it to traditional over-reading control.Methods
A random sample of 2000 sessions (8258 curves) was selected from Chiesi COPD and asthma trials (n=1000 per disease). Acceptability using the 2005 ATS/ERS standards was determined by over-reader review and by ArtiQ.Q","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Jan","modification":"2025-04-19T20:51:21.995Z","creation":"2025-04-19T20:51:21.995Z"},"accession":"S-EPMC9907146","cross_references":{"pubmed":["36776483"],"doi":["10.1183/23120541.00292-2022"]}}