Epidemiology of osteoarthritis: literature update 2022-2023.

IF 5.2 2区 医学 Q1 RHEUMATOLOGY Current opinion in rheumatology Pub Date : 2024-03-01 Epub Date: 2023-10-19 DOI:10.1097/BOR.0000000000000985
Mary Catherine C Minnig, Yvonne M Golightly, Amanda E Nelson
{"title":"Epidemiology of osteoarthritis: literature update 2022-2023.","authors":"Mary Catherine C Minnig, Yvonne M Golightly, Amanda E Nelson","doi":"10.1097/BOR.0000000000000985","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>This review highlights recently published studies on osteoarthritis (OA) epidemiology, including topics related to understudied populations and joints, imaging, and advancements in artificial intelligence (AI) methods.</p><p><strong>Recent findings: </strong>Contemporary research has improved our understanding of the burden of OA in typically understudied regions, including ethnic and racial minorities in high-income countries, the Middle East and North Africa (MENA) and Latin America. Efforts have also been made to explore the burden and risk factors in OA in previously understudied joints, such as the hand, foot, and ankle. Advancements in OA imaging techniques have occurred alongside the developments of AI methods aiming to predict disease phenotypes, progression, and outcomes.</p><p><strong>Summary: </strong>Continuing efforts to expand our knowledge around OA in understudied populations will allow for the creation of targeted and specific interventions and inform policy changes aimed at reducing disease burden in these groups. The burden and disability associated with OA is notable in understudied joints, warranting further research efforts that may lead to effective therapeutic options. AI methods show promising results of predicting OA phenotypes and progression, which also may encourage the creation of targeted disease modifying OA drugs (DMOADs).</p>","PeriodicalId":11145,"journal":{"name":"Current opinion in rheumatology","volume":"36 2","pages":"108-112"},"PeriodicalIF":5.2000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10965245/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in rheumatology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/BOR.0000000000000985","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/10/19 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"RHEUMATOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose of review: This review highlights recently published studies on osteoarthritis (OA) epidemiology, including topics related to understudied populations and joints, imaging, and advancements in artificial intelligence (AI) methods.

Recent findings: Contemporary research has improved our understanding of the burden of OA in typically understudied regions, including ethnic and racial minorities in high-income countries, the Middle East and North Africa (MENA) and Latin America. Efforts have also been made to explore the burden and risk factors in OA in previously understudied joints, such as the hand, foot, and ankle. Advancements in OA imaging techniques have occurred alongside the developments of AI methods aiming to predict disease phenotypes, progression, and outcomes.

Summary: Continuing efforts to expand our knowledge around OA in understudied populations will allow for the creation of targeted and specific interventions and inform policy changes aimed at reducing disease burden in these groups. The burden and disability associated with OA is notable in understudied joints, warranting further research efforts that may lead to effective therapeutic options. AI methods show promising results of predicting OA phenotypes and progression, which also may encourage the creation of targeted disease modifying OA drugs (DMOADs).

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
骨关节炎的流行病学:2022-2023 年文献更新。
综述目的:这篇综述重点介绍了最近发表的有关骨关节炎(OA)流行病学的研究,包括与研究不足的人群和关节、成像以及人工智能(AI)方法的进展有关的主题:当代研究提高了我们对通常研究不足地区的 OA 负担的认识,包括高收入国家、中东和北非(MENA)及拉丁美洲的少数族裔和种族。此外,研究人员还努力探索手部、足部和踝关节等以前未被充分研究的关节的 OA 负担和风险因素。OA 成像技术的进步与旨在预测疾病表型、进展和结果的人工智能方法的发展同步进行。总结:继续努力扩大我们对未充分研究人群 OA 的了解,将有助于制定有针对性的具体干预措施,并为旨在减少这些群体疾病负担的政策变化提供信息。在未充分研究的关节中,与 OA 相关的负担和残疾非常显著,因此需要进一步开展研究工作,从而找到有效的治疗方案。人工智能方法在预测 OA 表型和进展方面取得了可喜的成果,这也可能鼓励开发有针对性的改变 OA 疾病的药物(DMOADs)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Current opinion in rheumatology
Current opinion in rheumatology 医学-风湿病学
CiteScore
9.70
自引率
2.00%
发文量
89
审稿时长
6-12 weeks
期刊介绍: A high impact review journal which boasts an international readership, Current Opinion in Rheumatology offers a broad-based perspective on the most recent and exciting developments within the field of rheumatology. Published bimonthly, each issue features insightful editorials and high quality invited reviews covering two or three key disciplines which include vasculitis syndromes, medical physiology and rheumatic diseases, crystal deposition diseases and rheumatoid arthritis. Each discipline introduces world renowned guest editors to ensure the journal is at the forefront of knowledge development and delivers balanced, expert assessments of advances from the previous year.
期刊最新文献
Autoantibodies as putative biomarkers and triggers of cell dysfunctions in systemic sclerosis. Imaging in vasculitis. Polymyalgia rheumatica and giant cell arteritis: diagnosis and management. Inclusion body myositis: an update. VEXAS syndrome: an adult-onset autoinflammatory disorder with underlying somatic mutation.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1