Editor's Note: From September 22nd to 24th, 2024, the 20th International Society for Diseases of the Esophagus (ISDE) conference was grandly held in Edinburgh, Scotland. A study by Dr. Andrew Seely from the University of Ottawa's Faculty of Medicine on predictive vital sign monitoring during the perioperative period for esophageal cancer was selected for abstract presentation at the conference (Abstract No.: S19.05). Oncology Frontier conducted an exclusive interview with Prof. Seely at the conference venue to discuss his research.

Oncology Frontier: What are the current technologies used for predictive vital sign monitoring peri-esophagectomy, and how effective are they in improving patient outcomes? Can you provide some examples that have demonstrated significant benefits?

Andrew Seely: There is currently no proven technologies that use predictive monitoring to improve care. It’s an area of burgeoning interest and exciting research, development and commercialization. We are at the early stages of applying predictive monitoring tools based on machine learning, where we integrate the information of multiple vital signs measured continuously over time. So, for example, there is a tool called the Visensia Safety Index, which integrates all of the vital signs to provide a prediction of subsequent deterioration, which can then be tracked in real time over time. And we are evaluating that at the University of Ottawa in surgical patients at this time. But there have been no proven clinical trials demonstrating benefit to predictive monitoring. In addition, novel technology for the future includes where we analyze patterns of variation of heart rate and respiratory rate, and then do machine learning on that information to create predictive clinical decision support tools to improve care in the emergency room, the ICU, or even on ward patients. That is an innovative use of heart rate variability and respiratory rate variability analysis in order to derive a better understanding of the patient status, their trajectory and their risk of deterioration. A challenge in this technology is getting access to high quality continuous waveform or continuous vital sign data with which to be to perform predictive monitoring. However, there’s been new improvements in wearable monitors, new improvements in being able to access waveform data, data from patients in hospitals, and that is allowing us to develop and apply this technology further. So it’s an exciting domain of research, development and commercialization that is going to evolve further in the coming years.

Oncology Frontier: What are the main challenges associated with predictive vital sign monitoring in the perioperative setting? How do you address these challenges?

Andrew Seely: Well, a principal challenge is access to continuously monitored vital sign data and or waveform data, such as electrocardiogram or capnography data. So you have to have that data in order to perform predictive analyses on continuously monitored data. So that is one challenge, but as I mentioned, things are improving in that respect. A second challenge is that when everyone talks about predictive information, you are providing that predictive clinical decision support to clinicians such that they can improve a decision that they are making. For example, when to take a patient off a breathing machine in an ICU, we have a tool called extubation advisor that can optimize a clinician’s ability to determine the timing and safety of taking a patient off a breathing machine, off a ventilator. But a challenge is that clinical decision support requires a physician to utilize that information and factor it into their decision making. And we are just starting to understand how doctors, in fact, utilize a predictive clinical decision support, how they trust it when they do, when they don’t, and so that is a challenge as well.

Oncology Frontier: Looking ahead, what advancements or innovations do you foresee in predictive vital sign monitoring for peri-esophagectomy? How might emerging technologies or approaches further enhance patient care and surgical outcomes in the future?

Andrew Seely: So I would highlight two principal areas where predictive monitoring can be useful in the management of esophageal resections or any patient undergoing complex surgery. First, I think that we can utilize better preoperative assessments to identify risks of postoperative adverse events to create targeted pathways that are individualized to help prevent certain post operative adverse events. For example, if instead of having one enhanced recovery pathway for all patients, the concept is that to have a modular approach where patients who are at increased risk for pulmonary complications postoperatively get targeted interventions like high flow, heated humidity, oxygen, or inspiratory muscle training preoperatively, and those things would help prevent postoperative pulmonary complications. So it’s a modular, individualized, targeted approach to risk mitigation postoperatively. So that is one. A second, I think, is to use continuous predictive monitoring in the post operative period to provide early warning for adverse events and improved management and prevention, ideally of deterioration secondary to those adverse events. So earlier detection of anastomotic leak ,or pulmonary infection, or atrial risk for atrial arrhythmias, all those things, I think, could help prevent the development of those adverse events or the consequences of those adverse events.