A nomogram to predict major adverse cardiovascular events of patients with acute chest pain, Non-ST-segment deviation, and normal troponin concentrations.
Year: 2020
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: To explore the potential indicators including patients' characteristics, electrocardiogram (ECG), echocardiography, and serological assay in predicting the major adverse cardiovascular events (MACE) within 1 year for patients with low-risk chest pain with a nomogram. PATIENTS AND METHODS: The detected indicators of patients with low-risk chest pain were obtained as the alternative predictors for MACE. After the 1-year follow-up, patients with MACE were enrolled in the MACE group while the remained patients were in the non-MACE group. A nomogram was constructed based on the multivariable Cox regression to link the independent predictors and the MACE within 1 year for patients with low-risk chest pain. RESULTS: The incidence of MACE within 1 year was 6.94% according to the follow-up result. Multivariate analysis revealed that risk factors of CAD, P-terminal force in lead V1 (PTFV1), C-reactive protein (CRP), and transmitral inflow early diastolic peak velocity (E wave) /peak early diastolic velocity (Em) (E/Em) were the independent predictors for the MACE. A nomogram incorporating these independent predictors with a good discrimination (0.79 in C-index) and calibration was constructed to predict the incidence of MACE within 1 year. It could be used to help select the patients with a high risk of MACE and develop preventive treatment strategies. CONCLUSIONS: Risk factors of CAD, PTFV1, CRP, and E/Em were the independent predictors for the MACE within 1 year in patients with low-risk chest pain. The present nomogram provides a user friendly tool in the prediction of MACE for these patients.
Source: PubMed
Institution: Fifth Tianjin Central Hospital
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W3093925847