Nomogram-Based model accurately predicts disease flare-ups in axial spondyloarthritis.

IF 1.4 4区 医学 Q3 ORTHOPEDICS
Lianjie Wang Apipu Thitidechnisa, Yifang Wei, Jing Chen, Hongbing Rui, Yu Huang, Qing Zheng
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引用次数: 0

Abstract

BackgroundThe accuracy of predicting axial spondyloarthritis (axSpA) flares based on clinical experience is limited.ObjectiveThe aim of this study was to evaluate the efficacy of the previously designed nomogram prediction model in forecasting disease flares among rheumatologists and medical students.MethodsPatients who met the classification criteria for axSpA were enrolled in the study. Once a low ankylosing spondylitis disease activity score (ASDAS ≤ 2.1) was achieved, patients were monitored for 12 months to observe any disease flare-ups. Investigators assessed the likelihood of axSpA recurrence using the nomogram prediction model and their clinical experience, respectively. This allowed for a comparison of the predictive efficacy of both methods among the specialists and students.ResultsThe accuracy, sensitivity, specificity, and Youden index in which disease flare-ups were predicted by the rheumatologist using clinical experience were slightly lower than those obtained using the nomogram prediction model, but the difference was not statistically significant (P > 0.05). In contrast, the indicators above by medical students using clinical experience were significantly lower compared to those predicted by the nomogram prediction model (P < 0.05).ConclusionThe nomogram prediction model is effective in predicting the probability of disease remission and flare-ups in axSpA patients with low disease activity, demonstrating good clinical practicality and usability. Medical students can also use this model to significantly enhance the accuracy of predicting axSpA flares.

基于提名图的模型可准确预测轴性脊柱关节炎的疾病复发。
背景根据临床经验预测轴性脊柱关节炎(axSpA)复发的准确性有限。目的本研究旨在评估先前设计的提名图预测模型在风湿病学家和医科学生中预测疾病复发的效果。一旦强直性脊柱炎疾病活动度评分较低(ASDAS ≤ 2.1),就对患者进行为期 12 个月的监测,以观察疾病是否复发。研究人员分别使用提名图预测模型和临床经验评估axSpA复发的可能性。结果风湿免疫科医生使用临床经验预测疾病复发的准确性、敏感性、特异性和尤登指数略低于使用提名图预测模型得出的结果,但差异无统计学意义(P > 0.05)。相比之下,医科学生利用临床经验预测的上述指标明显低于使用提名图预测模型预测的指标(P<0.05)。
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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
194
审稿时长
6 months
期刊介绍: The Journal of Back and Musculoskeletal Rehabilitation is a journal whose main focus is to present relevant information about the interdisciplinary approach to musculoskeletal rehabilitation for clinicians who treat patients with back and musculoskeletal pain complaints. It will provide readers with both 1) a general fund of knowledge on the assessment and management of specific problems and 2) new information considered to be state-of-the-art in the field. The intended audience is multidisciplinary as well as multi-specialty. In each issue clinicians can find information which they can use in their patient setting the very next day.
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