How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers?

Diana BetancorJosé María OlaguibelJosé Manuel Rodrigo-MuñozEbymar ArismendiPilar BarrancoBlanca BarrosoIrina BoboleaBlanca CárdabaMaría Jesús CruzElena CurtoVictoria Del PozoFrancisco-Javier Gonzalez-BarcalaCarlos Martínez-RiveraJoaquim MullolXavier MuñozCesar PicadoVicente PlazaSantiago QuirceManuel Jorge RialLorena Soto RetesAntonio ValeroMarcela Valverde-MongeJoaquin Sastre

Published in: Clinical and translational allergy (2022)

In conclusion, our results suggest that grouping the biomarkers proposed by Heany et al. are insufficient to diagnose eosinophilic phenotypes in asthmatic patients. Sputum analysis remains the gold standard to assess airway inflammation.

Keyphrases

ejection fraction
lung function
newly diagnosed
machine learning
cystic fibrosis
chronic obstructive pulmonary disease
deep learning
chronic rhinosinusitis
patient reported outcomes
air pollution
allergic rhinitis