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Feasibility evaluation of non-invasive cardiac function technology during echocardiography-based cardiac stress testing

  • Davinder RamsinghEmail author
  • Michael Ma
  • Jin Kyung Kim
  • Margaret Knoll
  • John W. PattonIII
  • Maxime Cannesson
Original Research
  • 14 Downloads

Abstract

Evaluation of cardiac function during periods of stress is of key importance for the perioperative setting. Non-invasive hemodynamic monitors provide markers of cardiac function. This pilot study sought to evaluate the ability of a non-invasive hemodynamic monitor to detect cardiac stress during formal stress echocardiography testing. The primary goal was to compare the change in hemodynamic values during the pre/during/post phases of stress echocardiography testing in patients who had results negative versus positive for myocardial ischemia. Adult patients scheduled for outpatient cardiac stress testing were screened. Only patients scheduled for stress-echocardiography testing were consented. Patients with history of arrhythmias were excluded. During the testing, patients wore a cuff-based hemodynamic sensor (Nexfin system, Edwards Lifesciences). Data from the hemodynamic sensor were compared to the findings of the stress study. A total of 37 patients were enrolled, with 31 patients included for analysis. Five patients had stress studies positive for coronary ischemia. Comparison of the hemodynamic variables between patients who had a positive stress study versus negative showed a significant reduction in the percentage change in dP/dt and stroke volume from baseline (p < 0.05). This pilot study indicates that patients who have abnormal stress echocardiograms also have significantly reduced values from a noninvasive hemodynamic monitor. Further evaluation of the clinical utility of this technology, to assist in the care of patients at risk for cardiac ischemia, should be carried out.

Keywords

Cardiac stress testing Non-invasive hemodynamic monitoring Preoperative cardiac function evaluation Preoperative testing Preoperative risk-stratification 

Notes

Acknowledgements

Briahnna Austin, BS: Department of Anesthesiology & Perioperative Care, Loma Linda University Medical Center. Roll: Biostatistician.

Funding

This project was departmentally supported.

Compliance with ethical standards

Conflict of interest

Davinder Ramsingh, MD—Consultant and Funded Research from Edwards Lifesciences, Consultant for Fujifilm Sonosite, Funded research from General Electric on Point of Care Ultrasound and Anesthesia Delivery Systems, Funded research from Merck Pharmaceuticals, Funded research from Pacira Pharmaceuticals, Funded research from Masimo Corporation. Maxime Cannesson, MD, PhD—Ownership interest in Sironis, a company developing closed-loop systems, Consultant and Funded Research from Edwards Lifesciences, Consultant for Masimo Corp, Funded Research from National Institutes of Health: Grant Nos. R01 GM117622 (“Machine Learning of Physiological Variables to Predict Diagnose and Treat Cardiorespiratory Instability”) and R01 NR013912 (“Predicting Patient Instability Noninvasively for Nursing Care-Two [PPINNC-2]”).

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Anesthesiology & Perioperative CareLoma Linda University Medical CenterLoma LindaUSA
  2. 2.Department of AnesthesiologyUniversity of California Irvine Medical CenterOrangeUSA
  3. 3.Division of Cardiology, Department of MedicineUniversity of California Irvine Medical CenterOrangeUSA
  4. 4.Department of AnesthesiologyStanford University School of MedicineStanfordUSA
  5. 5.Department of AnesthesiologyRonald Reagan University of California-Los Angeles Medical CenterLos AngelesUSA

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