Background. Aortic stenosis (AS) is the most common heart valve disease in developed countries. The advent of transcatheter aortic valve implantation (TAVI) significantly improved patients' outcome but made clinical management more complex. The aim of the present study was to describe TAVIApp, a mobile app we developed to guide the management of AS, and test its efficacy. Methods and Results. Clinical cases comprising 42 patients with AS were blindly evaluated by (A) an interventional cardiologist, assisted by the Heart Team (EXPERT), (B) young residents in cardiology, and (C) a young resident supported by TAVIApp. There was poor concordance between Group A and Group B with low performance by young residents (k=0.52; p<0.001). However, concordance increased to an optimal value when young residents were supported by TAVIApp (k=1.0; p<0.001) for the diagnosis of severe AS and eligibility assessment. Furthermore, regarding the selection of the most appropriate prosthesis size, concordance to Group A was poor without TAVIApp support (Group B) (k=0.78; p=0.430), but excellent with TAVIApp (k=1.0; p<0.001). Conclusions. This study is the first describing and validating a new mobile application to support the management of AS. TAVIApp supports cardiologists in the evaluation of stenosis severity, eligibility for TAVI or AVR, and selection of the most appropriate prosthesis size in individual patients.

Description and validation of TAVIApp: A novel mobile application for support of physicians in the management of aortic stenosis - Management of aortic stenosis with TAVIApp

Indolfi C.;Sabatino J.;De Rosa S.;Ricci P.;
2017-01-01

Abstract

Background. Aortic stenosis (AS) is the most common heart valve disease in developed countries. The advent of transcatheter aortic valve implantation (TAVI) significantly improved patients' outcome but made clinical management more complex. The aim of the present study was to describe TAVIApp, a mobile app we developed to guide the management of AS, and test its efficacy. Methods and Results. Clinical cases comprising 42 patients with AS were blindly evaluated by (A) an interventional cardiologist, assisted by the Heart Team (EXPERT), (B) young residents in cardiology, and (C) a young resident supported by TAVIApp. There was poor concordance between Group A and Group B with low performance by young residents (k=0.52; p<0.001). However, concordance increased to an optimal value when young residents were supported by TAVIApp (k=1.0; p<0.001) for the diagnosis of severe AS and eligibility assessment. Furthermore, regarding the selection of the most appropriate prosthesis size, concordance to Group A was poor without TAVIApp support (Group B) (k=0.78; p=0.430), but excellent with TAVIApp (k=1.0; p<0.001). Conclusions. This study is the first describing and validating a new mobile application to support the management of AS. TAVIApp supports cardiologists in the evaluation of stenosis severity, eligibility for TAVI or AVR, and selection of the most appropriate prosthesis size in individual patients.
2017
Aged
Aortic Valve
Aortic Valve Stenosis
Cardiologists
Female
Humans
Internship and Residency
Male
Risk Assessment
Risk Factors
Severity of Illness Index
Treatment Outcome
Workforce
Disease Management
Mobile Applications
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12317/68545
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