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Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
Published on: September 26, 2018
Cardiovascular risk
1General Practice and Primary Care Research Unit, University of Cambridge, UK. rap55@medschl.cam.ac.uk
Insights
Identifying individuals at risk of cardiovascular disease (CVD) is crucial. This review explores CVD risk factors, prediction tools, and their use in guiding treatment decisions for better patient outcomes.
Area of Science:
- Cardiology
- Preventive Medicine
- Public Health
Background:
- Cardiovascular disease (CVD) presents a significant and escalating global health challenge.
- Effective identification and risk stratification of individuals susceptible to CVD are paramount.
Purpose of the Study:
- To review the concept of cardiovascular risk, encompassing traditional and novel risk factors.
- To examine clinical scoring systems and their application in informing therapeutic interventions.
- To discuss the implications of risk assessment in clinical decision-making and resource allocation.
Main Methods:
- Comprehensive literature review of cardiovascular risk factors and prediction models.
- Analysis of established and emerging biomarkers for risk assessment.
- Evaluation of clinical scoring systems like Framingham, SCORE, and QRISK.
Main Results:
- Traditional risk factors (ageing, hypertension, dyslipidemia) remain powerful predictors and therapeutic targets.
- Novel biomarkers (inflammatory, genetic) show potential but require further validation for improved risk prediction.
- Current risk prediction algorithms exhibit limitations in predictive accuracy and raise uncertainties regarding optimal application.
Conclusions:
- Despite limitations, risk scores offer objective quantification and transparency in risk assessment.
- Integration of risk assessment into guidelines aids equitable resource distribution and enhances clinical decision-making quality.
- Further research is needed to refine risk prediction models and leverage novel biomarkers for targeted therapies.
Abstract:
Cardiovascular disease is a major, growing, worldwide problem. It is important that individuals at risk of developing cardiovascular disease can be effectively identified and appropriately stratified according to risk. This review examines what we understand by the term risk, traditional and novel risk factors, clinical scoring systems, and the use of risk for informing prescribing decisions. Many different cardiovascular risk factors have been identified. Established, traditional factors such as ageing are powerful predictors of adverse outcome, and in the case of hypertension and dyslipidaemia are the major targets for therapeutic intervention. Numerous novel biomarkers have also been described, such as inflammatory and genetic markers. These have yet to be shown to be of value in improving risk prediction, but may represent potential therapeutic targets and facilitate more targeted use of existing therapies. Risk factors have been incorporated into several cardiovascular disease prediction algorithms, such as the Framingham equation, SCORE and QRISK. These have relatively poor predictive power, and uncertainties remain with regards to aspects such as choice of equation, different risk thresholds and the roles of relative risk, lifetime risk and reversible factors in identifying and treating at-risk individuals. Nonetheless, such scores provide objective and transparent means of quantifying risk and their integration into therapeutic guidelines enables equitable and cost-effective distribution of health service resources and improves the consistency and quality of clinical decision making.
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