Research Awards Recipients

Lay Summary

Chronic disease prevention is a policy priority and pillar of healthcare in Canada. Chronic kidney disease (CKD) is an incurable, progressive condition affecting an estimated 276 million persons worldwide in 2016 (13% of adults in Canada); an increase of 87% since 1990. This is attributable to global increases in key CKD risk factors such in diabetes, hypertension, obesity and an aging population; however, the development of CKD is not universal and remains variable. The ability to improve CKD awareness and accurately predict high risk individuals for disease surveillance remain major impediments to reduce or prevent the major adverse health outcomes associated with CKD. In the general population, kidney disease awareness is poor (below 10%) and this lack of awareness hampers disease prevention strategies. For healthcare providers there is uncertainty identifying patients at risk for progression and who may benefit from evidence-based therapies. This need not be the case as with the recent widespread availability of key laboratory tests, clinical and lifestyle data, the development of new onset CKD is a predictable event.
 
Dr. Sood proposes to develop a survey-based prediction equation targeting the general population to identify individuals at risk for incident CKD called PREDICT-CKD lifestyle.

His project has three objectives:

1. Develop a predictive algorithm using self-reported lifestyle data to predict new onset CKD (termed PREDICT-CKD lifestyle);
2. Validate PREDICT-CKD lifestyle internally;
3. Integrate PREDICT-CKD lifestyle into educational knowledge translation tools that will engage and allow the general public to determine their individual CKD risk.

 
This proposed study will be unique as it targets the general population and aims to improve CKD awareness.  To date Dr. Sood has established an international research team consisting of world leaders in kidney disease, prediction analytics, and administrative data. Furthermore, they have developed inclusion/exclusion criteria, estimated sample size, performed a systematic review to identify candidate predictor variables from existing prediction models and identified validated study outcomes. To improve uptake and usability of PREDICT-CKD lifestyle, it will be widely disseminated by knowledge translation partnerships using freely available web-based systems to broadly reach end-users. The PREDICT-CKD lifestyle equation aligns with identified research priorities of patients, healthcare workers, and policy makers. The timely, accurate, and reliable self-identification of individuals at risk of CKD would facilitate disease awareness and the targeting of lifestyle-based preventative therapies.