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The adoption of the Internet of Things (IoT) in the medical sector improves health care services and guarantees continuous and efficient monitoring of patients with chronic disease. Accordingly, heterogeneous health data (medical devices and medical records) is obtained and requires to be efficiently managed and diverse risk factors should be smartly considered in order to predict and prevent complex and dangerous events. The modeling and processing of this kind of events present an emerging challenge that necessitates to be addressed. In this context, we aim to propose a semantic-driven complex event processing approach for Cardiovascular Disease (CVD) prevention for diabetic patients. Particularly, we focus on the semantic modeling of medical events; Then, we propose diverse rules for processing purposes.