Predictive Analytic Tool for Diagnosis of Coronary Allograft Vasculopathy

In 2016, Eric Vu, MD, had just completed a pediatric cardiac anesthesia fellowship at Texas Children’s Hospital and was interested in pursuing an additional fellowship in pediatric anesthesia research at Baylor College of Medicine. Fortunately, he received an IARS Mentored Research Award that year for his research on “Predictive Analytic Tool for Diagnosis of Coronary Allograft Vasculopathy” that provided the support to make this opportunity possible. His initial IMRA-funded investigation set out to use signal processing of ECG signals to develop computational tools to predict cardiac arrest in single ventricle patients. These algorithms were expanded to pediatric patients after heart transplant, and eventually incorporated into a multivariate model for interstage patients undergoing testing as a multicenter study. Today, Dr. Vu’s work in this area has expanded and he and his team are now working on a real-time monitor of cerebral autoregulation for neonatal and pediatric cardiopulmonary bypass cases.

With the help of the IMRA, Dr. Vu was able to secure dedicated research time and pursue a Masters in Clinical Investigation to obtain additional skills in clinical design, biostatistics, and biomedical informatics, which helped him to advance in his career. Today, Dr. Vu is an Associate Professor of Anesthesiology (Pediatric Anesthesiology) at Northwestern University, Feinberg School of Medicine, and the Medical Director of Cardiac Anesthesia, and Chair of the Transfusion Medicine Committee at the Ann & Robert H. Lurie Children’s Hospital. He remains resolute in his determination to discover more intelligent monitors that clinicians can use as tools to provide better care for their patients, translating to improved patient outcomes. Below, Dr. Vu recalls his research journey, his work leveraging technology to provide better patient care and his hopes for the future of anesthesia research.

1. What is your current position? How long have you been in this position? What was your role when you were first funded by IARS?

My current position is associate professor at Northwestern University, Feinberg School of Medicine. I am the Medical Director of Cardiac Anesthesia at Ann & Robert H. Lurie Children’s Hospital and the Chair of the Transfusion Medicine Committee. In addition, I am the Associate Program Director of the Pediatric Anesthesia Fellowship and Program Director of the Pediatric Cardiovascular Anesthesia Fellowship. I have been in this position for about 5 years.

When I was first funded by IARS, I had just completed a pediatric cardiac anesthesia fellowship at Texas Children’s Hospital and was using the IARS funding to support an additional fellowship in pediatric anesthesia research.

2. What was the goal of your initial research project? Was it met?

The goal of the initial research project was to use signal processing of ECG signals to develop computational tools to predict cardiac arrest in single ventricle patients. The algorithms were expanded to pediatric patients after heart transplant. This algorithm was incorporated into a multivariate model for interstage patients undergoing testing as a multicenter study. This work has expanded, and we are now working on a real-time monitor of cerebral autoregulation for neonatal and pediatric cardiopulmonary bypass cases.

3. How did your findings impact patient care?

The algorithm is able to detect clinical deterioration versus health in single ventricle patients after stage 1 palliation surgery 2 hours prior to any intervention requiring chest compressions or unplanned intubation with a receiver operating characteristic curve (ROC) area of 0.81. When combined with a multivariate logistic regression model incorporating heart rate, pulse oximetry, respiration rate variability, and heart rate variability, the ROC area improves to 0.91. A monitor which displays the real time risk of patient arrest has been developed and undergoing clinical testing and validation. For cerebral autoregulation monitoring, we are now conducting a randomized trial to assess the effectiveness and utility of monitoring.

4. How did your research impact the field of anesthesiology?

It is too soon to tell! But the hope is that with more intelligent monitors, clinicians can have tools at their disposal to better take care of patients, which should ideally translate to improved patient outcomes.

5. How did the award affect your research/professional trajectory?

Looking back, the award was instrumental in a very crucial part in my career. The transition from fellow to faculty is such an important few years (often times unrecognized!) that ultimately shapes the path and subsequently, bulk of one’s future career. With the award, I was able to have dedicated research time and pursue a Masters in Clinical Investigation to obtain additional skills in clinical design, biostatistics, and biomedical informatics.

6. How do you feel about having received the IARS Mentored Research Award?

I feel honored and grateful for the IARS Mentored Research Award. It supports the very important work and career development of so many individuals who are working to advance our specialty.

7. What is something that someone would be surprised to learn about you?

I’m incredibly forgetful but love to leverage technology to help me. I’ll also never say no to a great coffeeshop or restaurant.

8. What drew you to academic anesthesiology and to your particular area of research?

Academic anesthesiology is such a fantastic intersection of research, teaching, and clinical work that is immensely rewarding. My background in biomedical engineering lends itself to research in data science and medical informatics. I love thinking about how we are shaping the future of our dynamic specialty and what we can one day build to help us take care of patients.

9. What is your vision for the future of anesthesia research?

I think it goes without saying that in anesthesia research, the balance between clinical and academic productivity is always the challenge. I take an optimistic stance on this and think that if people can follow their passion, the work or immense hill that is required begins to level or melt away. Nonetheless, success requires a team which includes mentorship, departmental support, and grants / awards. With that said, I think the future is exciting! With the increased interest in machine learning, we are applying new tools to medicine every day. I can’t wait to see what the future holds.