We developed and validated a nomogram to predict coronary heart disease (CHD) in patients with rheumatoid arthritis (RA) in northern China. We analyzed a cohort of RA patients admitted to the Department of Rheumatology and Immunology of the First Affiliated Hospital of China Medical University from 2011 to 2017. To select a high-performance model for clinical data prediction, we evaluated the F1-scores of six machine learning models. Based on the results, we selected multivariable logistic regression analysis for the development of a prediction model. We then generated an individualized prediction nomogram that included age, sex, hypertension, anti-cyclic citrullinated peptide antibody positivity, the erythrocyte sedimentation rate, and serum LDL-cholesterol, triglyceride and HDL-cholesterol levels. The prediction model exhibited better discrimination than the Framingham Risk Score in predicting CHD in RA patients. The area under the curve of the prediction model was 0.77, with a sensitivity of 63.9% and a specificity of 77.2%. The nomogram exhibited good calibration and clinical usefulness. In conclusion, our prediction model was more accurate than the Framingham Risk Score in predicting CHD in RA patients. Our nomogram combining various risk factors can be used for the individualized preoperative prediction of CHD in patients with RA.
Characteristics and Trends of Adult Acute Lymphoblastic Leukemia in a Large, Public Safety-Net Hospital.
March 23, 2020
June 11, 2020
- ACC 2020The American College of Cardiology decided to cancel ACC.20/WCC due to COVID-19, which was scheduled to take place March 28-30 in Chicago. However, ACC.20/WCC Virtual Meeting continues to release cutting edge science and practice changing updates for cardiovascular professionals on demand and free through June 2020.
- ENDO: 2020ENDO 2020 Annual Conference has been canceled due to COVID-19. Here are highlights of emerging data that has still been released. Keep an eye out for ENDO Online 2020, which will take place from June 8 to 22.