Predictive value of the novel risk score BETTER (BiomarkErs and compuTed Tomography scorE on Risk stratification) for

Y Xia1, Y Xia, K Xu

  • 1Institute of Cardiovascular Disease Research, Xuzhou Medical College, 84 West Huaihai Road, 221006, Xuzhou, Jiangsu, China.

Herz
|August 31, 2014
PubMed

Insights

A new risk score, BETTER, combining blood biomarkers and CCTA imaging, shows higher accuracy in predicting major adverse cardiac events in unstable angina patients than existing methods. This tool improves cardiovascular risk stratification.

Area of Science:

  • Cardiology
  • Biomarkers
  • Medical Imaging

Background:

  • Current risk stratification scores like Braunwald classification and TIMI risk score have limitations for unstable angina (UA) patients.
  • Accurate cardiovascular risk assessment is crucial for managing UA.
  • Need for improved risk stratification tools in cardiology practice.

Purpose of the Study:

  • To develop and validate a novel risk score for patients with unstable angina (UA).
  • The new score integrates blood biomarkers and coronary computed tomographic angiography (CCTA) characteristics.
  • To enhance the prediction accuracy of major adverse cardiac events (MACEs).

Main Methods:

  • A cohort of 201 patients with confirmed UA was studied over a 1-year follow-up period.
  • Blood biomarkers (Hs-cTnT, Hs-CRP, MPO, NT-proBNP, IMA) and CCTA characteristics (stenosis, plaque, EFV, calcification) were analyzed.
  • The novel BETTER (Biomarkers and cT Tomography scorE on Risk stratification) score was developed using Cox multivariable analysis.

Main Results:

  • The BETTER risk score demonstrated a superior Area Under the Curve (AUC) of 0.937 compared to Braunwald (0.621) and TIMI (0.680) scores.
  • CCTA characteristics showed strong correlation with MACEs (AUCs ranging from 0.835 to 0.912).
  • Biomarkers also correlated with MACEs, with Hs-CRP (AUC 0.745) and MPO (AUC 0.650) showing notable predictive value.

Conclusions:

  • The BETTER risk score is a novel and effective tool for risk stratification in UA patients.
  • It offers higher prediction accuracy in discrimination and calibration compared to existing scores.
  • This score can aid clinicians in better managing cardiovascular risk in UA.
Abstract

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