风湿病的损害:当代国际观点和临床、放射学和机器学习的评分

IF 1 Q4 RHEUMATOLOGY
Samar Tharwat , Iman I. El-Gazzar , Rawhya El Shereef , Faten Ismail , Fatma Ali , Hanan Taha , Ahmed Elsaman , Amany El-Bahnasawy , Yousra Hisham , Marwa Amer , Amany El Najjar , Hanan M. Fathi , Nahla Eesa , Reem H. Mohammed , Noha M. Khalil , Nouran M. Shahaat , Nevin Hammam , Samar Fawzy
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引用次数: 0

摘要

在风湿病中,损害是一个主要问题,反映了不可逆的器官瘢痕或组织退化。在确定总体结果时,对损害进行量化或测量其严重程度是必不可少的。损伤显著影响长期预后和生活质量。风湿病(RD)是一种重大的健康负担。器官损伤一直与死亡率增加有关。监测损伤是评估患者和评估治疗效果的关键。适当的评估和早期发现损害为通过有效的药物和方案改变病程铺平了道路,可以减少器官损害,改善预后并降低死亡率。除了系统性红斑狼疮和血管炎外,大多数rd缺乏既定的损伤指标,因此需要开发有效的评分和预测模型来预测疾病早期的损伤累积。随着医疗大数据可用性的增加,对机器学习的更好理解可能有助于为rd患者开发有意义的精准医疗。本文介绍了最新的临床和放射损伤评分和指数,以及机器学习在关键rd中的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Damage in rheumatic diseases: Contemporary international standpoint and scores emerging from clinical, radiological and machine learning

In rheumatic diseases, damage is a major concern and reflects irreversible organ scarring or tissue degradation. Quantifying damage or measuring its severity is an indispensable concern in determining the overall outcome. Damage considerably influences both longterm prognosis and quality of life. Rheumatic diseases (RD) represent a significant health burden. Organ damage is consistently associated with increased mortality. Monitoring damage is critical in the evaluation of patients and in appraising treatment efficacy. Proper assessment and early detection of damage paves way for modifying the disease course with effective medications and regimens may reduce organ damage, improve outcomes and decrease mortality. With the exception of systemic lupus erythematosus and vasculitis, most RDs lack an established damage index making it an ongoing demand to develop effective scores and prediction models for damage accrual early in the disease course. A better understanding of machine learning with the increasing availability of medical large data may facilitate the development of meaningful precision medicine for patients with RDs. An updated spectrum of clinical and radiological damage scores and indices as well as the role of machine learning are presented in this review for the key RDs.

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来源期刊
Egyptian Rheumatologist
Egyptian Rheumatologist RHEUMATOLOGY-
CiteScore
2.00
自引率
22.20%
发文量
77
审稿时长
39 weeks
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