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Incremental value of machine learning for risk prediction in tetralogy of Fallot.
Ishikita, Ayako; McIntosh, Chris; Roche, S Lucy; Barron, David J; Oechslin, Erwin; Benson, Lee; Nair, Krishnakumar; Lee, Myunghyun M; Gritti, Michael N; Hanneman, Kate; Karur, Gauri Rani; Wald, Rachel M.
Afiliación
  • Ishikita A; Division of Cardiology, Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, ON, Canada.
  • McIntosh C; Division of Cardiology, Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, ON, Canada.
  • Roche SL; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
  • Barron DJ; Joint Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada.
  • Oechslin E; Division of Cardiology, Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, ON, Canada.
  • Benson L; Department of Cardiovascular Surgery, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.
  • Nair K; Division of Cardiology, Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, ON, Canada.
  • Lee MM; Division of Cardiology, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.
  • Gritti MN; Division of Cardiology, Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, ON, Canada.
  • Hanneman K; Department of Cardiovascular Surgery, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.
  • Karur GR; Division of Cardiology, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.
  • Wald RM; Joint Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada.
Heart ; 110(8): 560-568, 2024 Mar 22.
Article en En | MEDLINE | ID: mdl-38040450
OBJECTIVE: Machine learning (ML) can facilitate prediction of major adverse cardiovascular events (MACEs) in repaired tetralogy of Fallot (rTOF). We sought to determine the incremental value of ML above expert clinical judgement for risk prediction in rTOF. METHODS: Adult congenital heart disease (ACHD) clinicians (≥10 years of experience) participated (one cardiac surgeon and four cardiologists (two paediatric and two adult cardiology trained) with expertise in heart failure (HF), electrophysiology, imaging and intervention). Clinicians identified 10 high-yield variables for 5-year MACE prediction (defined as a composite of mortality, resuscitated sudden death, sustained ventricular tachycardia and HF). Risk for MACE (low, moderate or high) was assigned by clinicians blinded to outcome for adults with rTOF identified from an institutional database (n=25 patient reviews conducted by five independent observers). A validated ML model identified 10 variables for risk prediction in the same population. RESULTS: Prediction by ML was similar to the aggregate score of all experts (area under the curve (AUC) 0.85 (95% CI 0.58 to 0.96) vs 0.92 (0.72 to 0.98), p=0.315). Experts with ≥20 years of experience had superior discriminative capacity compared with <20 years (AUC 0.98 (95% CI 0.86 to 0.99) vs 0.80 (0.56 to 0.93), p=0.027). In those with <20 years of experience, ML provided incremental value such that the combined (clinical+ML) AUC approached ≥20 years (AUC 0.85 (95% CI 0.61 to 0.95), p=0.055). CONCLUSIONS: Robust prediction of 5-year MACE in rTOF was achieved using either ML or a multidisciplinary team of ACHD experts. Risk prediction of some clinicians was enhanced by incorporation of ML suggesting that there may be incremental value for ML in select circumstances.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tetralogía de Fallot / Taquicardia Ventricular / Cardiopatías Congénitas Límite: Adult / Child / Humans Idioma: En Revista: Heart Asunto de la revista: CARDIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tetralogía de Fallot / Taquicardia Ventricular / Cardiopatías Congénitas Límite: Adult / Child / Humans Idioma: En Revista: Heart Asunto de la revista: CARDIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Reino Unido