Moorman, Joseph Randall
Professor, Medicine: Cardiovascular Medicine
- Residency, Internal Medicine, Duke University Medical Center
- Fellowship, Cardiology & Cardiac Electrophysiology, University of Virginia
- MD, Medicine, University of Mississippi
Mathematical Analysis of Cardiac Rhythms
<br/><br/>Our goal is to develop predictive monitoring for early diagnosis of subacute, potentially catastrophic illness. To date, our focus has been on premature infants in an intensive care unit.
<br/><br/>The clinical problem that we first addressed is neonatal sepsis, a bacterial infection of the bloodstream in premature newborn infants in the intensive care unit. This illness is common and adds greatly to morbidity and mortality of these fragile patients, and is difficult to diagnose in its early and most treatable stages. We reasoned that continuous monitoring of a sensitive physiological measure like heart rate variability might show changes before obvious signs of a critical illness so advanced that therapy would not help.
<br/><br/>We began by inspecting heart rate records over prolonged periods in infants at risk of sepsis. We found obvious changes in the <em>heart rate characteristics</em> of septic infants even before they were clinically ill, with reduced variability and transient decelerations similar to the findings in fetal distress. Since there were no measures available to detect these findings, we developed new mathematical techniques of sample entropy and sample asymmetry. We did clinical studies to develop predictive multivariate statistical models based on our new measures, and we validated them at a second medical center. We recently completed a multicenter randomized clinical trial of 3000 very low birthweight infants into to test the hypothesis that our monitoring system improves infants outcomes. Indeed it does <em>monitored infants had a more than 20% reduction in mortality</em>.
<br/><br/>The scholarly output of this work has been more than 20 full-length clinical and mathematical papers, 2 Ph.D. degrees (Biomedical Engineering, Biophysics), and 5 Masters in Biomedical Engineering degrees funded by the National Institutes of Health, American Heart Association, Virginias Center for Innovative Technology, the Coulter Foundation and the University of Virginia FEST Program and Childrens Medical Center.
<br/><br/>We have 5 US, 2 European and 1 Canadian patents issued on this work, and more pending. Through the University of Virginia Patent Foundation, this technology was licensed in 1999, and is now in the hands of Medical Prediction Systems Corporation (MPSC), Charlottesville, with whom we have consulting and equity agreements. MPSC was formed as a Virginia C Corporation in 2002, successfully obtained 510(k) FDA clearance, and sells the HeRO (<em>He</em>art <em>R</em>ate <em>O</em>bserver) system with the indication of detecting reduced variability and transient decelerations in newborn infants. HeRO monitors are at work in more than 1000 beds in 17 NICUs.
<br/><br/>The new work is to develop monitoring for neonatal apnea, another major cause of morbidity in the NICU. The current art is limited to clinical observations and to unwieldy bedside monitoring units. We have received an NIH GO grant to develop new mathematical algorithms for continuous quantitative analysis of apnea using sophisticated waveform analysis and statistical techniques.
<br/><br/>We intend to carry these ideas into other clinical settings, especially hospital units in which continuous monitoring is already the standard of practice such as the CCU and SICU.
<br/><br/>Another area of much interest and activity centers on atrial fibrillation, the most common sustained arrhythmia in adults. Here, the focus is on numerical analysis to lead to rapid diagnosis in implanted devices, and on clinical decision analysis using large databases of Holter monitor and comprehensive clinical features.