{"title":"UKA 的患者选择:如何在临床中成功诊断。","authors":"Jobe Shatrov, Philippe Neyret","doi":"10.1016/j.jisako.2024.100348","DOIUrl":null,"url":null,"abstract":"<p><p>The success of unicompartmental knee arthroplasty (UKA) for monocompartmental knee arthritis is reliant on appropriate patient selection. This article addresses the clinical challenges that may arise when attempting to identify patients likely to have favorable outcomes following UKA. Despite advancements of implant design and accuracy of surgical tools, considerable challenges persist in predicting patient specific success and satisfaction following UKA. Variation in patient characteristics, healthcare practices, and outcomes in the literature make the establishment of a strict set of universal guidelines difficult. This article will provide a comprehensive overview of the current landscape of patient selection for UKA, acknowledging the existing clinical dilemmas and challenges faced by clinicians and proposing avenues for future research including the integration of patient predictive models, advanced imaging, and artificial intelligence to enhance predictive accuracy.</p>","PeriodicalId":36847,"journal":{"name":"Journal of ISAKOS Joint Disorders & Orthopaedic Sports Medicine","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Patient Selection in UKA: How to Make the Diagnosis for Success in the Clinic.\",\"authors\":\"Jobe Shatrov, Philippe Neyret\",\"doi\":\"10.1016/j.jisako.2024.100348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The success of unicompartmental knee arthroplasty (UKA) for monocompartmental knee arthritis is reliant on appropriate patient selection. This article addresses the clinical challenges that may arise when attempting to identify patients likely to have favorable outcomes following UKA. Despite advancements of implant design and accuracy of surgical tools, considerable challenges persist in predicting patient specific success and satisfaction following UKA. Variation in patient characteristics, healthcare practices, and outcomes in the literature make the establishment of a strict set of universal guidelines difficult. This article will provide a comprehensive overview of the current landscape of patient selection for UKA, acknowledging the existing clinical dilemmas and challenges faced by clinicians and proposing avenues for future research including the integration of patient predictive models, advanced imaging, and artificial intelligence to enhance predictive accuracy.</p>\",\"PeriodicalId\":36847,\"journal\":{\"name\":\"Journal of ISAKOS Joint Disorders & Orthopaedic Sports Medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of ISAKOS Joint Disorders & Orthopaedic Sports Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jisako.2024.100348\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ORTHOPEDICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of ISAKOS Joint Disorders & Orthopaedic Sports Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.jisako.2024.100348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
Patient Selection in UKA: How to Make the Diagnosis for Success in the Clinic.
The success of unicompartmental knee arthroplasty (UKA) for monocompartmental knee arthritis is reliant on appropriate patient selection. This article addresses the clinical challenges that may arise when attempting to identify patients likely to have favorable outcomes following UKA. Despite advancements of implant design and accuracy of surgical tools, considerable challenges persist in predicting patient specific success and satisfaction following UKA. Variation in patient characteristics, healthcare practices, and outcomes in the literature make the establishment of a strict set of universal guidelines difficult. This article will provide a comprehensive overview of the current landscape of patient selection for UKA, acknowledging the existing clinical dilemmas and challenges faced by clinicians and proposing avenues for future research including the integration of patient predictive models, advanced imaging, and artificial intelligence to enhance predictive accuracy.