Chronic Kidney Disease (CKD) is associated with a high risk of both ischemic and haemorrhagic strokes, a three-fold mortality rate and five-fold healthcare spending. Real-time monitoring of the stroke risk in CKD patients could support optimal therapeutic strategies and promote a more personalized therapeutic approach.

Biotricity is developing Bioflux-AI, an innovative system for real-time monitoring and prediction of stroke episodes in CKD patients. Bioflux-AI combines an FDA-approved, high-precision, small mobile cardiac telemetry (MCT) device with AI-driven algorithms specifically trained for the prediction of stroke in stage 4 and 5 CKD patients.

Biotricity has previously generated and validated algorithms for the automated detection of ECG abnormalities, including Atrial Fibrillation (AF). Given the strong association of AF with increased risk of blood clot formation and hence, ischemic stroke in CKD patients, Biotricity proposes to combine the detection of this arrhythmia with other stroke risk factors of CKD patients (age, weight, height, BMI, CKD status, diabetes, heart disease) and ECG parameters to predict stroke risk in real-time.

To this aim, in this SBIR Phase I project a convolutional neural network algorithm, which will incorporate all these risk factors, will be developed, trained and validated. The accomplishment of this feasibility study will pave the road for further development and optimization of the AI-based algorithm for stroke prediction in CKD patients, while widening the application to a larger patient demographic, validating the predictive algorithm for patients with other chronic diseases.