Year: 2025
Type: article
Abstract: Risk prediction tools play a crucial role in preventing cardiovascular diseases (CVD) and type 2 diabetes (T2D). Guidelines emphasize early detection of high-risk individuals using these tools to implement lifestyle interventions and treatment strategies. Originating from landmark studies like the Framingham Heart Study, risk assessment tools have evolved and are widely adopted globally. These tools provide objective, standardized, and cost-effective assessments, supporting healthcare professionals in decision-making, improving patient outcomes, reducing unnecessary treatments and costs. They enhance clinicians’ understanding of risk factors, encourage preventive management, empower patients to participate in their healthcare, make lifestyle changes, and adhere to treatments. However, they must be regularly updated to reflect population changes and emerging risk factors. Challenges to routine use include time constraints, clinician scepticism, and the complexity of choosing from numerous available tools. In JACARDI, 42 risk assessment tools were identified: 26 for healthy individuals, 8 for T2D patients, 5 for CVD patients, 2 for mixed populations, and 1 for T1D patients. Given the wide variety of risk prediction tools, selecting the most suitable one requires careful consideration of regional demographics, healthcare resources, and system infrastructure. JACARDI provides a seven-step decision guide to help policymakers align prevention strategies with the most effective tools for their needs, ultimately improving risk assessment accuracy and shaping public health policies. The 7 steps include 1-Identify the target population, 2-Review medical history, 3-Define the risk prediction outcomes, 4-Consider regional applicability, 5-Evaluate available resources and data, 6-Select the appropriate tool, 7-Final considerations. Integrating the use of risk assessment tools into clinical practice.
Authors: L Palmieri, C Donfrancesco, HM Elonheimo, B Marcozzi, A Cardinale, C Damiano, C Lo Noce, T Dipol, H Tolonen
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,181
OpenAlex ID: W7101403108
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