{"id":1730941,"date":"2025-06-17T11:16:59","date_gmt":"2025-06-17T15:16:59","guid":{"rendered":"https:\/\/med.virginia.edu\/faculty\/faculty-listing\/rm3h\/"},"modified":"2025-06-25T15:19:33","modified_gmt":"2025-06-25T19:19:33","slug":"rm3h","status":"publish","type":"faculty-listing","link":"https:\/\/med.virginia.edu\/faculty\/faculty-listing\/rm3h\/","title":{"rendered":"Moorman, Joseph Randall"},"content":{"rendered":"<p>Our  goal is to develop predictive monitoring for early diagnosis of subacute,  potentially catastrophic illness.&nbsp; To date, our focus has been on  premature infants in an intensive care unit.<\/p>\n<p>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.&nbsp; 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.&nbsp; 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.<\/p>\n<p>We  began by inspecting heart rate records over prolonged periods in infants at  risk of sepsis.&nbsp; 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.&nbsp; Since there were no measures available to detect these  findings, we developed new mathematical techniques of sample entropy and sample  asymmetry.&nbsp; We did clinical studies to develop predictive multivariate  statistical models based on our new measures, and we validated them at a second  medical center.&nbsp; 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\u2019 outcomes.&nbsp; Indeed it does \u2013 <em>monitored  infants had a more than 20% reduction in mortality<\/em>.&nbsp; <\/p>\n<p>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, Virginia\u2019s Center for Innovative  Technology, the Coulter Foundation and the University of Virginia FEST Program  and Children\u2019s Medical Center.<\/p>\n<p>We  have 5 US, 2 European and 1 Canadian patents issued on this work, and more  pending.&nbsp; 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.&nbsp; 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.&nbsp; HeRO monitors are at work  in more than 1000 beds in 17 NICUs.<\/p>\n<p>The  new work is to develop monitoring for neonatal apnea, another major cause of  morbidity in the NICU.&nbsp; The current art is limited to clinical  observations and to unwieldy bedside monitoring units.&nbsp; 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.<\/p>\n<p>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.<\/p>\n<p>Another  area of much interest and activity centers on atrial fibrillation, the most  common sustained arrhythmia in adults.&nbsp; 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.<\/p>\n","protected":false},"featured_media":1734524,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"_links_to":"","_links_to_target":""},"otheraff":[2387,2392,2396],"phd-degree":[],"primary":[2347],"research-discipline":[],"research-opportunity":[],"training-grant":[],"class_list":["post-1730941","faculty-listing","type-faculty-listing","status-publish","has-post-thumbnail","hentry","otheraff-biomedical-engineering","otheraff-cardiovascular-research-center","otheraff-molecular-physiology-and-biological-physics","primary-medicine-cardiovascular-medicine"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.1.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Moorman, Joseph Randall - Research Faculty Directory<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/med.virginia.edu\/faculty\/faculty-listing\/rm3h\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Moorman, Joseph Randall - Research Faculty Directory\" \/>\n<meta property=\"og:description\" content=\"Our goal is to develop predictive monitoring for early diagnosis of subacute, potentially catastrophic illness.&nbsp; 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