ArticleHerz2015
Predictive value of the novel risk score BETTER (BiomarkErs and compuTed Tomography scorE on Risk stratification) for patients with unstable angina.
Article in Herz, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed, 2 citations in OpenAlex.
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8 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Braunwald classification and TIMI (Thrombolysis In Myocardial Infarction) risk score are used to stratify cardiovascular risk in patients with unstable angina (UA). However, these scores have a limited capacity in the practice of cardiology.
objectivesThis study sought to develop a new score, based on blood biomarkers and coronary computed tomographic angiography (CCTA) characteristics, for patients with UA. PATIENTS AND
methodsThe study group consisted of 201 patients with confirmed UA. Follow-up time was 1 year; major adverse cardiac events (MACEs) included cardiovascular death, recurrent acute coronary syndrome (ACS), and re-admission to hospital. Blood biomarkers including high-sensitivity cardiac troponin T (Hs-cTnT), high-sensitivity C-reactive protein (Hs-CRP), myeloperoxidase (MPO) N-terminal pro-B-type natriuretic peptide (NT-proBNP), and ischemia-modified albumin (IMA) were measured. CCTA characteristics such as stenosis, plaque, epicardial fat volume (EFV), and calcification were evaluated. After analysis of relationships, the novel risk BETTER (BiomarkErs and compuTed Tomography scorE on Risk stratification) score was assessed in 201 patients.
resultsIn all, 25 MACEs (12.44 %) occurred: 2 cardiac deaths (1.00 %), 13 non-fatal myocardial infarctions (6.47 %), 10 recurrent ACS and re-admission in hospital (4.96 %). Serum levels of MPO, NT-proBNP, Hs-TnT, Hs-CRP, and IMA were correlated with MACEs (r = 0.20, r = 0.40, r = 0.18, r = 0.24, p < 0.01, respectively; r = 0.12, p > 0.05). CCTA characteristics of stenosis, plaque, EFV, and calcification were significantly correlated with MACEs (r = 0.53, r = 0.57, r = 0.42, and r = 0.52, all p < 0.01 respectively) and were significantly higher in the MACEs group than in the non-MACEs group. Thus, a new risk score was created combining biomarkers and CCTA statistics into a Cox multivariable for risk prediction of 1-year MACEs: BETTER risk score = MPO•0.1 + Hs-TnT•50 + Hs-CRP•0.4 + stenosis•9 + plaque•13 + EFV•0.2. The areas under the curve (AUC) for the prediction by Hs-cTnT, Hs-CRP, and MPO were 0.536 (95 % CI 0.409-0.662), 0.745 (95 % CI 0.641-0.850), and 0.650 (95 % CI 0.541-0.760), respectively. The AUC for the prediction of CCTA characteristics of stenosis, plaque, and EFV were 0.905 (95 % CI 0.860-0.950), 0.912 (95 % CI 0.867-0.957), and 0.835 (95 % CI 0.752-0.917), respectively. In addition, the AUC was 0.621 (95 % CI 0.492-0.750) for the Braunwald classification and 0.680 (95 % CI 0.559-0.801) for the TIMI score. The AUC for the BETTER risk score was 0.937 (95 % CI 0.902-0.972).
conclusionThe BETTER risk score is new tool specifically developed for patients with UA. The score displays higher prediction accuracy in terms of discrimination and calibration than other currently available scores for risk stratification.
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