Cardiac Performance Evaluation in Patients with Muscular Dystrophy - Top-Institutions - MDSpire

Cardiac Performance Evaluation in Patients with Muscular Dystrophy

  • By

  • Naomi Khanna

  • Joseph Mahgerefteh

  • Noah Elkins

  • Daphne T. Hsu

  • Jacqueline M. Lamour

  • Leslie Delfiner

  • Induja Gajendran

  • Neha Bansal

  • February 20, 2026

  • 0 min

Share

Top Institutions in Cardiology

Brief introduction explaining scope and methodology.

  • #1

    Johns Hopkins University
    Johns Hopkins University

    Baltimore, MD

    Key Differentiators

    • Cardiology
    • Neuromuscular Medicine
    • Pediatric Cardiology

  • #2

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Cardiology
    • Neurology
    • Echocardiography

  • #3

    Cincinnati Children's Hospital Medical Center
    Cincinnati Children's Hospital Medical Center

    Cincinnati, OH

    Key Differentiators

    • Pediatric Cardiology
    • Neuromuscular Medicine

  • #4

    University of California, San Francisco (UCSF)
    University of California, San Francisco (UCSF)

    San Francisco, CA

    Key Differentiators

    • Cardiology
    • Neurology
    • Muscular Dystrophy Research

  • #5

    Nationwide Children's Hospital
    Nationwide Children's Hospital

    Columbus, OH

    Key Differentiators

    • Pediatric Cardiology
    • Neuromuscular Disorders

Original Source(s)

Cardiac Performance Evaluation in Patients with Muscular Dystrophy

  • by Naomi Khanna, Joseph Mahgerefteh, Noah Elkins, Daphne T. Hsu, Jacqueline M. Lamour, Leslie Delfiner, Induja Gajendran, Neha Bansal

  • February 20, 2026

Related Content

Case Report: Persistent fifth aortic arch with coarctation and fourth aortic arch interruption causing infant heart failure – the prenatal and postnatal echocardiographic course

Safety and efficacy of sacubitril/valsartan vs. benazepril administered as initial treatment for STEMI patients with mid-range ejection fraction: a propensity score matching analysis

Heart failure risk prediction based on machine learning and interpretability analysis