Navigating the Landscape of Cardiovascular Risk Scores: A Comparative Analysis of Eight Risk Prediction Models in a High-Risk Cohort in Lithuania.
J Clin Med
; 13(6)2024 Mar 21.
Article
en En
| MEDLINE
| ID: mdl-38542029
ABSTRACT
Background:
Numerous cardiovascular risk prediction models (RPM) have been developed, however, agreement studies between these models are scarce. We aimed to assess the inter-model agreement between eight RPMs assessing cardiovascular risk using SIGN, the Australian CVD risk score (AusCVDRisk), the Framingham Risk Score for Hard Coronary Heart Disease, the Multi-Ethnic Study of Atherosclerosis risk score, the Pooled Cohort Equation (PCE), the QRISK3 cardiovascular risk calculator, the Reynolds Risk Score, and Systematic Coronary Risk Evaluation-2 (SCORE2).Methods:
A cross-sectional study was conducted on 11,174 40-65-year-old individuals with diagnosed metabolic syndrome from a single tertiary university hospital in Lithuania. Cardiovascular risk was calculated using the eight RPMs, and the results were categorized into high, intermediate, and low-risk groups. Inter-model agreement was quantified using Cohen's Kappa coefficients.Results:
The study revealed significant heterogeneity in risk categorizations with only 1.49% of cases where all models agree on the risk category. SCORE2 predominantly categorized participants as high-risk (67.39%), while the PCE identified the majority as low-risk (62.03%). Cohen's Kappa coefficients ranged from -0.09 to 0.64, indicating varying degrees of inter-model agreement.Conclusions:
The choice of RPM can substantially influence clinical decision-making and patient management. The PCE and AusCVDRisk models exhibited the highest degree of agreement while the SCORE2 model consistently exhibited low agreement with other models.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
J Clin Med
Año:
2024
Tipo del documento:
Article
País de afiliación:
Lituania