2 Works

Heart Rate Variability: A Possible Machine Learning Biomarker for Mechanical Circulatory Device Complications and Heart Recovery

Theodore Lin, Zain Khalpey & Shravan Aras
Cardiovascular disease continues to be the number one cause of death in the United States, with heart failure patients expected to increase to >8 million by 2030. Mechanical circulatory support (MCS) devices are now better able to manage acute and chronic heart failure refractory to medical therapy, both as bridge to transplant or as bridge to destination. Despite significant advances in MCS device design and surgical implantation technique, it remains difficult to predict response to...

Pulsatility is a Predictive Marker of Improved Cardiac Function in Patients with Liquid Matrixtreated Left Ventricular Assist Devices

Philemon Mikail, Rinku S. Skaria, Marvin J. Slepian, Janny Garcia, Richard G. Smith & Zain I. Khalpey
Objective: Left ventricular assist devices (LVADs) are utilized as a bridge to transplant or as destination therapy for patients with end-stage heart failure. Although cardiac offloading from these devices rarely leads to complete remodeling and functional recovery, the use of mesenchymal cells to modulate heart failure has been explored in recent years due to its intrinsic regenerative properties. Current methods of evaluating cardiac function have too much variability, difficulty of access, or require too frequent...

Registration Year

  • 2022
  • 2021

Resource Types

  • Data Paper


  • University of Arizona
  • Medtronic (United States)
  • Northwest Hospital and Medical Center
  • HonorHealth