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Predicting Heart Failure Outcomes Using Patient-Reported Health Status: Real-World Validation of the KCCQ-12 | JACC

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Manage episode 487785931 series 3609188
Content provided by American College of Cardiology. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by American College of Cardiology or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode, Dr. Valentin Fuster discusses groundbreaking research validating the Kansas City Cardiomyopathy Questionnaire (KCCQ-12) as a powerful real-world predictor of heart failure outcomes using advanced machine learning on outpatient data. Emphasizing the critical importance of patient-reported health status, he highlights that listening to patients remains essential even in an era dominated by AI-driven medicine.

  continue reading

730 episodes

Artwork
iconShare
 
Manage episode 487785931 series 3609188
Content provided by American College of Cardiology. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by American College of Cardiology or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode, Dr. Valentin Fuster discusses groundbreaking research validating the Kansas City Cardiomyopathy Questionnaire (KCCQ-12) as a powerful real-world predictor of heart failure outcomes using advanced machine learning on outpatient data. Emphasizing the critical importance of patient-reported health status, he highlights that listening to patients remains essential even in an era dominated by AI-driven medicine.

  continue reading

730 episodes

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