Research Paper Volume 13, Issue 11 pp 15061—15077
Development and validation of a nomogram for predicting stroke risk in rheumatoid arthritis patients
- 1 Department of Clinical Epidemiology and Evidence-Based Medicine, The First Affiliated Hospital, China Medical University, Shenyang, China
- 2 Department of Medical Record Management Center, The First Affiliated Hospital, China Medical University, Shenyang, China
- 3 Department of Rheumatology, The First Affiliated Hospital, China Medical University, Shenyang, China
- 4 Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang, China
Received: November 16, 2020 Accepted: April 29, 2021 Published: June 3, 2021https://doi.org/10.18632/aging.203071
How to Cite
Copyright: © 2021 Xin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
We developed and validated a nomogram to predict the risk of stroke in patients with rheumatoid arthritis (RA) in northern China. Out of six machine learning algorithms studied to improve diagnostic and prognostic accuracy of the prediction model, the logistic regression algorithm showed high performance in terms of calibration and decision curve analysis. The nomogram included stratifications of sex, age, systolic blood pressure, C-reactive protein, erythrocyte sedimentation rate, total cholesterol, and low-density lipoprotein cholesterol along with the history of traditional risk factors such as hypertensive, diabetes, atrial fibrillation, and coronary heart disease. The nomogram exhibited a high Hosmer–Lemeshow goodness-for-fit and good calibration (P > 0.05). The analysis, including the area under the receiver operating characteristic curve, the net reclassification index, the integrated discrimination improvement, and clinical use, showed that our prediction model was more accurate than the Framingham risk model in predicting stroke risk in RA patients. In conclusion, the nomogram can be used for individualized preoperative prediction of stroke risk in RA patients.