Vascular events In noncardiac Surgery patIents cOhort evaluatioN study-2 (VISION-2)
Principal Investigators: McGillion M, Devereaux PJ, Scott T, Peter E, Doyle T.
Co-Investigators: Alvarado K, Andrews G, Bessissow A, Bhavnani S, Biccard B, Buckley N, Busse J, Carroll S, Cheng D, Choiniere M, Conen D, Cortes OL, Cowan D, Downey B, Duceppe E, Dvirnik N, Fergusson D, Garg A, Gilron I, Graham M, Guyatt G, Johnson A, Karanicolas P, Kavsak P, Kessler BF, Lalu M, Lamy A, Lavis J, MacDermid J, Marcucci M, Martin J, Mazer D, McAlister F, McManus B, Metcalfe K, Mrkobrada M, Ouellette C, Pare G, Parlow J, Parry M, Patel A, Paul J, Petch J, Roshanov P, Samavi R, Schunemann H, Sessler D, Srinathan S, Tandon V, Tarride JE, Vanstone M, Watt-Watson J, Whitlock R, Xie F, Yang S, Bianco D (Lived Experience Representative)
Funding: Canadian Institutes of Health Research (CIHR) -European Commission team grant competition: Horizon 2020 Team Grant – Canada-EU Smart Living Environments – Transitions in Care. SMILE: Providing digitalised prevention and prediction support for ageing people in smart living environments. Canadian (2021 – 2024)
Methods: The Vitaliti™ device continuously captures patients’ pulse oximetry, respiration rate, heart rate, core body temperature, NIBP, and high-fidelity biometric signals (i.e., 5-lead ECG and PPG), 24 hours a day, both on the surgical ward and into the home setting for a total of 30 postoperative days. There are 3 phases to this project:
In Phase 1, 1,000 patients undergoing noncardiac surgery will be recruited from 5 sites in Canada: two in Ontario, one each in Manitoba and Quebec, and one in Ohio. Continuous biometric data will be collected using the Vitaliti™ device.The Vitaliti™ device will continuously capture patients’ pulse oximetry, respiration rate, heart rate, core body temperature, NIBP, and high-fidelity biometric signals (i.e., 5-lead ECG and PPG), 24 hours a day, both on the surgical ward and into the home setting for a total of 30 postoperative days.
Phase 2 will consist of an exploratory analysis to summarize the available data and identify potential features to be used within the event classification models. Unsupervised techniques, without associated labels and including data clustering and generative modelling approaches will help to investigate and refine the feasible window of detection for clinically annotated adverse events.
Phase 3 will consist of deep learning prediction models. Deep learning is an exciting and recent specialization of machine learning, which utilizes representation learning to organize and automatically extract progressive layers of features directly from raw data. This allows classification models to be developed without traditionally extensive feature engineering cycles. These deep learning methodologies will be employed in hybrid structures to build classification models to detect postoperative major clinical complications.
Measuring cardiovascular Outcomes of Depression in reFerred Youth (MODIFY)
Principal Investigator: Korczak DJ.
Co-Investigators: McCrindle B, Birken C, Cleverley K, Cost K, Kirkpatrick S, Parry M, Szatmari P, Vaillancourt T.
Funding: Canadian Institutes of Health Research (CIHR) (2019 – 2024)
Abstract: Depression is a serious and recurrent chronic disorder that affects 5-8% of children. Individuals with depression are at increased risk of experiencing heart disease (heart attack and stroke). Heart disease is the leading cause of death for people suffering from depression. Research has shown that early manifestations of heart disease can be detected years, even decades, before a person with depression experiences symptoms. Population-based studies have shown that depressed adolescents are at increased risk of heart disease compared with non-depressed youth, and demonstrate early signs of heart disease in research studies. Studies have also found sex differences in the association between depression and heart disease, in that the relationship is stronger, and the role of obesity is more central, for depressed women compared with depressed men. How depression is related to heart disease biologically, and whether markers of increased heart disease risk vary with an individual’s mood, however, is not known. This is important because prevention interventions are more likely to be effective when they are targeted to key factors, early in the course of illness, and directed at those most likely to benefit. This study will determine the relationship between depressive symptoms and early markers of heart disease over a 12 month period. We will study 300 adolescents with depression who are referred to a clinical research program in Toronto. We will investigate indicators of early heart disease, eating behaviours, (for example, eating when feeling upset) and their relationship to depressive symptom burden among depressed youth. This will help physicians determine which young people are at risk of heart disease, identify critical periods for identification, and allow physicians to make early suggestions in order to prevent heart disease among this high-risk group of adolescents.
Vascular events In noncardiac Surgery patIents cOhort evaluatioN study-2 (VISION-2)
Principal Investigators: McGillion M, Doyle T, Peter E, Scott T.
Co-Investigators: Alvarado K, Andrews G, Bessissow A, Bhandari M, Bhavnani S, Biccard B, Buckley N, Busse J, Carroll S, Cheng, D, Choiniere M, Conen D, Cortes O, Cowan D, Devereaux PJ, Alvarado K, Andrews G, Bessissow A, Bhandari M, Bhavnani S, Biccard B, Buckley N, Busse J, Carroll S, Cheng, D, Choiniere M, Conen D, Cortes O, Cowan D, Devereaux PJ, Downey B, Duceppe E, Dvirnik N, Fergusson D, Garg A, Gilron I, Graham M, Guyatt G, Johnson A, Karanicolas P, Kavsak P, Kessler Borges F, Lalu M, Lamy A, Lavis J, MacDermid J, Marcucci M, Martin J, Mazer D, McManus B, McAlister F, Metcalfe K, Mrkobrada M, Ouellette C, Parlow J, Parry M, Pare G, Patel A, Paul J, Petch J, Roshanov P, Samavi R, Schunemann H, Sessler D, Srinathan S, Tandon V, Tarride J, Vanstone M, Watt-Watson J, Whitlock R, Xie F, Yang S.
Funding: Canadian Institutes of Health Research (CIHR) (2020 – 2022)
Abstract: Over 10% of all patients who have surgery (aged 45 and above) will suffer a major complication and over 1.5% of all adults will die within 30 days after surgery. The most common major complications are injury to the heart muscle, bleeding, and infection. These complications happen on the surgical ward or at home, after hospital discharge. We need better ways of monitoring patients so that we know, ahead of time, if they are going to develop complications and so we act early to stop the complications from happening. In this study, we will use a new monitoring device called Vitaliti- a lightweight device worn around the neck that can monitor patients’ vital signs and heartbeat continually, while they go about their day. One thousand patients aged 45 years or older who have surgery (not including heart surgery), and who are at risk for serious complications will wear the Vitaliti device on the surgical ward until they are released from hospital. We will know which patients are at risk of complications because we will do a blood test before surgery that tells us about risk. We will also look for other things that put people at risk such as disease of the veins and arteries. When patients wear the Vitaliti device, it will send constant readings of their vital signs and heartbeat to our hospital monitoring centre. We will use a type of artificial intelligence called machine learning to study these readings. We will look for slight changes in vital signs that may lead to heart muscle injury, bleeding and infection. Once we know what these signs are, we can then develop an alert system to warn us so we can stop the complications before they happen. At present, patients die from infection and other serious complications after surgery. This work is an opportunity to make a real difference in patient care after surgery.
Gender Outcomes INternational Group: to Further Well-being Development Study
Principal Investigators: L. Pilote (Canada), C. Norris (Canada), V. Raparelli (Canada)
Co-Investigators: M. Abrahamowicz (Canada), S. Bacon (Canada), J. Fishman (Canada), K. Humphries (Canada), E. Jonson (Cyprus), A. Kautzky-Willer (Austria), K. Kublickiene (Sweden), M. Parry (Canada) (Co-Lead of KTE), J. Patrikios Cyprus), Sapir-Pichhadze (Canada), A. Stephanou (Cyprus), M. Trinidad Herrero (Spain)
Funding: GENDER-NET Plus ERA-NET Cofund (2018 – 2021)
BACKGROUND AND OBJECTIVE: Beyond biological sex, gender is increasingly recognized as a pivotal determinant of health. However, there are no standardized gender measurements. We hypothesize that gender-related factors and their effect will vary substantially between countries and diseases. The overarching aims of this large Consortium are to integrate sex and gender dimensions in applied health research, to evaluate their impact on clinical cost-sensitive outcomes and patients reported outcomes related to quality of life in noncommunicable diseases including cardiovascular disease, metabolic disease, chronic kidney disease and neurological disease. We also aim to construct innovative ways to disseminate the application of gender measurement towards personalized approaches to chronic disease prevention, diagnosis and treatment.
METHODS: With a five-country transatlantic network comprised of 30 investigators, we will benchmark innovative solutions to measure gender in retrospective cohorts. Based on consensus, we will develop a framework to identify gender-related factors, as well as cost-sensitive and patients reported outcomes and measure their associations in 32 accessible cohorts of patients affected by cardiovascular, chronic kidney and neurological diseases and metabolic syndrome. Large database analysis and when appropriate machine learning approaches will allow the derivation of pan and within country disease specific gender scores which will be validated through e-Health and m-Health applications in prospective disease groups. Educational modules will be developed to promote awareness, implementation and dissemination.
Transformation of Indigenous Primary Healthcare Delivery (FORGE AHEAD): Enhancement and Adaptation of Community-Driven Innovations and Scale-Up Toolkits
Principal Investigator: S. Harris
Co-Investigators: O. Bhattacharyya, E. Barre, K. Dawson, R. Dyck, M. Green, A. Hanley, B. Lavallee, M. Parry, S. Reichert, J. Salsberg, B. Te Hiwi, A. Thind, S. Tobe, A. Walsh, J. Wylie, M. Zwarenstein
Funding: Canadian Institutes of Health Research Team Grant: Pathways to Health Equity for Aboriginal People – Implementation Research Team Grants, Component 2 (2017 – 2020)
BACKGROUND AND OBJECTIVE: In Canada, there are significant disparities between the health status of Indigenous peoples and the general population with respect to diabetes mellitus. The overarching goal of this research is to improve the health and health equity of Indigenous peoples by strengthening the effectiveness of scalability of the TransFORmation of IndiGEnous PrimAry HEAlthcare (FORGE AHEAD) Quality Improvement (QI) Strategy.
METHODS: An implementation science approach of examining what works, for whom, and under what contexts will be used to guide this research. The research goal will be achieved and will be operationalized using a PR approach that simultaneously ensures culturally sensitive processes and KT/E throughout.
Transformation of Indigenous Primary Healthcare Delivery (FORGE AHEAD): Community-Driven Innovations and Strategic Scale-up Toolkits
Principal Investigator: S. Harris
Co-Investigators: O. Bhattacharyya, E. Baxter, H. McDonald, E. Barre, K. Dawson, D. Dannenbaum, R. Dyck, J. Episkenew, M. Green, A. Hanley, A. Katz, B. Lavallee, A. McComber, A. Macaulay, M. Parry, S. Reichert, J. Salsberg, A. Thind, S. Tobe, E. Toth, A. Walsh, J. Wylie, J. Wortman, M. Zwarenstein, L. Houle, T. Jacobs, K. Kandukur, R. Littlechild, I. McComb, D. Montour, J. Morach, M. Nose, T. O’Keefe, D. Redmond, D. Spade, C. Tischer, S. Zeiler
Funding: Canadian Institutes of Health Research Planning Grant and a Canadian Institutes of Health Research Community-Based Primary Health Care Team Grant (2013 – 2018)
BACKGROUND AND OBJECTIVE: Given the dramatic rise and impact of chronic disease and gaps in care in Indigenous peoples in Canada, a shift from the existing episodic healthcare model most common in First Nations communities, to one that integrates prevention and chronic disease management is required. Five key objectives are to: 1) assess the current healthcare delivery and funding models in Indigenous communities in Canada, 2) assess community and clinical readiness to address and change chronic disease care, 3) enhance patient access to available community resources for chronic disease care, 4) implement and evaluate community and clinic quality improvement initiatives to improve chronic disease management, and 5) develop sustainable strategies and scale-up toolkits for improved chronic management in First Nations communities.
METHODS: A series of inter-related and progressive projects using a participatory research approach that simultaneously ensures culturally appropriate processes and integrates knowledge translation by involving relevant stakeholders throughout the entire program.
Diabetes and its Related Complications
Principal Investigators: G. Lewis, JP. Despres, P. Rochon, F. Sullivan, A. Brown, J. McGavock, J. Cafazzo, A. Carpentier, F. Legare, M. Brent, D. Maberley, B. Perkins, P. Fernyhough, M. Farkouh, M. Belanger
Co-Investigators: A. Paterson, B. Lamarche, G. Anderson, K. Gregory-Evans, H. Lee-Gosselin, L. MacCallum, M. Parry, D. Cherney, J. Maman, P. Harvey, H. Witteman, D. Prowten, B. Goldstein, J. Hux, M. Campbell, M. Tennant, A. Cruess, B. Zee, G. Fantus, A. Dart, M. Hillmer, , N. Calcutt, D. Zochodne, R. Dobrowsky, L. Kotra, S. Desroches, C. Whiteside, S. Seabrooke, R. Gilbert, R. Mason, S. Lagosky, E. Grunfeld, D. Manca, N. Drummond, L. Lipscombe, G. Booth, B. Shah, P. Segal, I. Halperin, G. Mukerji, M. Wolfs, M. Greiver, M. Mamdani, K. Sabihuddin, M. Ouimet, B. Lavallee, C. Chartrand, R. Rabasa-Lhoret, A. Haidar, S. Desroches, M. Campbell, D. Yuen, A. Advani, PM. Geraldes, A. Paterson, K. Connelly, CH. Cunningham, V. Montori, C. Jose, D. Sissmore, R. Gray, D. Prowten, B. Goldstein
Funding: SPOR Networks in Chronic Disease, Canadian Institutes of Health Research (2016 – 2022)
BACKGROUND AND OBJECTIVE: Individuals with diabetes, representing approximately 10% of Canadians, are concerned about their risk of complications (blindness, limb amputations, kidney and heart failure, and hypoglycemia). These complications are often under diagnosed and ineffectively treated. This SPOR Network will redefine interventions for early diagnosis and customized treatments that will transform healthcare for all individuals with diabetes.
METHODS: We have a team of experts in biomedical, clinical, population and health services research, education, and knowledge translation will conduct projects to establish a platform for a national registry to evaluate access to and implementation of effective methods for diagnosing complications, design a unique Canadian Risk Calculator, a smartphone app, identify biomarkers associated with risk of complications, and evaluate diet and lifestyle interventions. By aligning biomedical, clinical, population health and health services research and education with what matters most to patients we will bridge the knowledge translation gap with real impact on chronic disease outcomes.
Technology-Enabled Remote Monitoring and Self-Management: Vision for Patient Empowerment Following Cardiac and Vascular Surgery
Principal Investigator: M. McGillion, PJ Devereaux, D. Bender, A. Lamy, A. Turner, S. Carroll, J. Yost, E. Peter, P Ritvo
Co-Investigators: M. Parry and the SMArTVIEW Team
Funding: CIHR eHealth Innovation Partnership and Hamilton Health Sciences (HHS) Grants (2015 – 2019)
BACKGROUND AND OBJECTIVE: Tens of thousands of cardiac and vascular surgeries (CaVS) are performed on seniors each year to improve survival, relieve disease symptoms, and improve health-related quality of life (HRQL). However, chronic postsurgical pain (CPSP), undetected or delayed detection of hemodynamic compromise, complications, and related poor functional status are major problems for substantial numbers of patients during the recovery process. The objectives are to (1) refine SMArTVIEW via high-fidelity user testing and (2) examine the effectiveness of SMArTVIEW via a randomized controlled trial (RCT).
METHODS: CaVS patients and clinicians will engage in two cycles of focus groups and usability testing at each site; feedback will be elicited about expectations and experience of SMArTVIEW, in context. The data will be used to refine the SMArTVIEW eHealth delivery program. Upon transfer to the surgical ward (ie, post-intensive care unit [ICU]), 256 CaVS patients will be reassessed postoperatively and randomly allocated via an interactive Web randomization system to the intervention group or usual care. The SMArTVIEW intervention will run from surgical ward day 2 until 8 weeks following surgery. Outcome assessments will occur on postoperative day 30; at week 8; and at 3, 6, 9, and 12 months.