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前交叉韧带手术与登记数据的范围综述

Scoping Review on ACL Surgery and Registry Data.

作者信息

Kaarre Janina, Zsidai Bálint, Narup Eric, Horvath Alexandra, Svantesson Eleonor, Hamrin Senorski Eric, Grassi Alberto, Musahl Volker, Samuelsson Kristian

机构信息

Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Sahlgrenska Sports Medicine Center (SSMC), Gothenburg, Sweden.

出版信息

Curr Rev Musculoskelet Med. 2022 Oct;15(5):385-393. doi: 10.1007/s12178-022-09775-2. Epub 2022 Jul 13.

Abstract

PURPOSE OF REVIEW

To present an overview of registry-based anterior cruciate ligament (ACL) research, as well as provide insight into the future of ACL registries.

RECENT FINDINGS

During the past decades, the ACL registries have had an important role in increasing our understanding of patients with ACL injuries and their treatment. The registry data has deepened our understanding of factors that have been associated with an increased risk of sustaining an ACL injury and for evaluation of treatment factors and their impact on patient-related outcomes. Recently, registry-based ACL research using artificial intelligence (AI) and machine learning (ML) has shown potential to create clinical decision-making tools and analyzing outcomes. Thus, standardization of collected data between the registries is needed to facilitate the further collaboration between registries and to facilitate the interpretation of results and subsequently improve the possibilities for implementation of AI and ML in the registry-based research. Several studies have been based on the current ACL registries providing an insight into the epidemiology of ACL injuries as well as outcomes following ACL reconstruction. However, the current ACL registries are facing future challenges, and thus, new methods and techniques are needed to ensure further good quality and clinical applicability of study findings based on ACL registry data.

摘要

综述目的

概述基于注册库的前交叉韧带(ACL)研究,并深入了解ACL注册库的未来发展。

最新研究结果

在过去几十年中,ACL注册库在增进我们对ACL损伤患者及其治疗的理解方面发挥了重要作用。注册库数据加深了我们对与ACL损伤风险增加相关因素的理解,并有助于评估治疗因素及其对患者相关结局的影响。最近,基于注册库的ACL研究利用人工智能(AI)和机器学习(ML)显示出创建临床决策工具和分析结局的潜力。因此,需要对注册库之间收集的数据进行标准化,以促进注册库之间的进一步合作,并便于结果的解释,进而提高在基于注册库的研究中实施AI和ML的可能性。多项研究基于当前的ACL注册库,深入了解了ACL损伤的流行病学以及ACL重建后的结局。然而,当前的ACL注册库面临着未来的挑战,因此,需要新的方法和技术来确保基于ACL注册库数据的研究结果具有更高的质量和临床适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7e/9463418/dedefdf19ac6/12178_2022_9775_Fig1_HTML.jpg

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