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Development and Application of a System Based on Artificial Intelligence for Transcatheter Aortic Prosthesis Selection.
Rösler, Álvaro M; Fraportti, Jonathan; Nectoux, Pedro; Constantin, Gabriel; Cazella, Sílvio; Nunes, Mauro Ricardo Pontes; Lucchese, Fernando A.
Affiliation
  • Rösler ÁM; Hospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
  • Fraportti J; Universidade Federal de Ciências da Saúde de Porto Alegre - UFCSPA, Porto Alegre, RS, Brazil.
  • Nectoux P; Hospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
  • Constantin G; Hospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
  • Cazella S; Hospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
  • Nunes MRP; Universidade Federal de Ciências da Saúde de Porto Alegre - UFCSPA, Porto Alegre, RS, Brazil.
  • Lucchese FA; Hospital São Francisco - Santa Casa de Misericórdia de Porto Alegre, Porto Alegre, RS, Brazil.
Braz J Cardiovasc Surg ; 33(4): 391-397, 2018.
Article in En | MEDLINE | ID: mdl-30184037
INTRODUCTION: The interest in Expert systems has increased in the medical area. Some of them are employed even for diagnosis. With the variability of transcatheter prostheses, the most appropriate choice can be complex. This scenario reveals an enabling environment for the use of an Expert system. The goal of the study was to develop an Expert system based on artificial intelligence for supporting the transcatheter aortic prosthesis selection. METHODS: The system was developed on Expert SINTA. The rules were created according to anatomical parameters indicated by the manufacturing company. Annular aortic diameter, aortic area, aortic perimeter, ascending aorta diameter and Valsalva sinus diameter were considered. After performing system accuracy tests, it was applied in a retrospective cohort of 22 patients with submitted to the CoreValve prosthesis implantation. Then, the system indications were compared to the real heart team decisions. RESULTS: For 10 (45.4%) of the 22 patients there was no concordance between the Expert system and the heart team. In all cases with discordance, the software was right in the indication. Then, the patients were stratified in two groups (same indication vs. divergent indication). The baseline characteristics did not show any significant difference. Mortality, stroke, acute myocardial infarction, atrial fibrillation, atrioventricular block, aortic regurgitation and prosthesis leak did not present differences. Therefore, the maximum aortic gradient in the post-procedure period was higher in the Divergent Indication group (23.9 mmHg vs. 11.9 mmHg, P=0.03), and the mean aortic gradient showed a similar trend. CONCLUSION: The utilization of the Expert system was accurate, showing good potential in the support of medical decision. Patients with divergent indication presented high post-procedure aortic gradients and, even without clinical repercussion, these parameters, when elevated, can lead to early prosthesis dysfunction and the necessity of reoperation.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Heart Valve Prosthesis / Artificial Intelligence / Transcatheter Aortic Valve Replacement Type of study: Observational_studies / Prognostic_studies Limits: Aged / Aged80 / Female / Humans / Male Language: En Journal: Braz J Cardiovasc Surg Journal subject: ANGIOLOGIA / CARDIOLOGIA Year: 2018 Document type: Article Affiliation country: Brazil Country of publication: Brazil

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Heart Valve Prosthesis / Artificial Intelligence / Transcatheter Aortic Valve Replacement Type of study: Observational_studies / Prognostic_studies Limits: Aged / Aged80 / Female / Humans / Male Language: En Journal: Braz J Cardiovasc Surg Journal subject: ANGIOLOGIA / CARDIOLOGIA Year: 2018 Document type: Article Affiliation country: Brazil Country of publication: Brazil