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October 9, 2025Circulation Research

Abstract Wed136: Integration of Mechanistic Fontan Circulatory Models with Interpretable Machine Learning Classifiers

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Authors

NSNoah A. SchenkAEAlexander EgbeBCBrian E. Carlson

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Overview

Integration of clinical metrics and hemodynamic modeling improves risk stratification in Fontan circulation, suggesting better patient outcomes.

Key Points

  • Model-derived parameters significantly outperform clinical variables in predicting patient outcomes.
  • Integration of hemodynamic modeling increased AUROC from 0.67 to 0.78 for patient outcome prediction.
  • The study utilizes a lumped-parameter mechanistic model calibrated with data from 51 patients aged 25±8 years.
  • Findings support earlier referral for advanced therapies and precision management of complex congenital circulations.

Cite This Study

Schenk et al. (2025) studied this question.

synapsesocial.com/papers/68e77f09d1c187e1c108fb89https://doi.org/10.1161/res.137.suppl_1.wed136
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