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本文引用的文献

1
Development of a machine learning algorithm to identify surgical candidates for hip and knee arthroplasty without in-person evaluation.开发一种机器学习算法,以在无需当面评估的情况下识别髋关节和膝关节置换手术的候选者。
Arch Orthop Trauma Surg. 2023 Sep;143(9):5985-5992. doi: 10.1007/s00402-023-04827-9. Epub 2023 Mar 11.
2
Large Database and Registry Research in Joint Arthroplasty and Orthopaedics.关节置换术与骨科领域的大型数据库及登记研究
J Bone Joint Surg Am. 2022 Oct 19;104(20):1775-1777. doi: 10.2106/JBJS.22.00405.
3
Length of Stay Increases 90-day Readmission Rates in Patients Undergoing Primary Total Joint Arthroplasty.初次全关节置换术后患者的住院时间延长会增加 90 天再入院率。
J Am Acad Orthop Surg Glob Res Rev. 2022 Mar 16;6(3):e21.00271. doi: 10.5435/JAAOSGlobal-D-21-00271.
4
The rise of registry-based research: a bibliometric analysis.基于注册的研究的兴起:文献计量分析。
Acta Orthop. 2021 Oct;92(5):628-632. doi: 10.1080/17453674.2021.1937459. Epub 2021 Jun 18.
5
Research trends and hotspots of high tibial osteotomy in two decades (from 2001 to 2020): a bibliometric analysis.20 年来(2001 年至 2020 年)胫骨高位截骨术的研究趋势和热点:文献计量分析。
J Orthop Surg Res. 2020 Nov 9;15(1):512. doi: 10.1186/s13018-020-01991-1.
6
Risk Factors for Periprosthetic Joint Infection Following Primary Total Hip Arthroplasty: A 15-Year, Population-Based Cohort Study.初次全髋关节置换术后假体周围关节感染的危险因素:一项长达 15 年的基于人群的队列研究。
J Bone Joint Surg Am. 2020 Mar 18;102(6):503-509. doi: 10.2106/JBJS.19.00537.
7
Quality Measures in Total Hip and Total Knee Arthroplasty.全髋关节和全膝关节置换术的质量措施。
J Am Acad Orthop Surg. 2019 Mar 15;27(6):219-226. doi: 10.5435/JAAOS-D-17-00283.
8
Projected Volume of Primary Total Joint Arthroplasty in the U.S., 2014 to 2030.2014 年至 2030 年美国初次全关节置换术预估量。
J Bone Joint Surg Am. 2018 Sep 5;100(17):1455-1460. doi: 10.2106/JBJS.17.01617.
9
The Incidence and Economic Burden of In-Hospital Venous Thromboembolism in the United States.美国住院患者静脉血栓栓塞症的发病率及经济负担
J Arthroplasty. 2017 Apr;32(4):1063-1066. doi: 10.1016/j.arth.2016.10.020. Epub 2016 Oct 21.
10
Hospital Discharge within 2 Days Following Total Hip or Knee Arthroplasty Does Not Increase Major-Complication and Readmission Rates.全髋关节或膝关节置换术后2天内出院不会增加主要并发症和再入院率。
J Bone Joint Surg Am. 2016 Sep 7;98(17):1419-28. doi: 10.2106/JBJS.15.01109.

美国大数据在关节置换术研究中的应用:趋势与热点的文献计量分析

The utilization of US-based large data in arthroplasty research: Bibiliometric analysis of trends and hotspots.

作者信息

Nham Fong H, Kassis Eliana, El-Othmani Mouhanad M

机构信息

Department of Orthopaedic Surgery and Sports Medicine, Detroit Medical Center, Detroit, MI, 48201, USA.

PeriOpti, Ann Arbor, MI, 48103, USA.

出版信息

J Orthop. 2023 Oct 29;46:128-138. doi: 10.1016/j.jor.2023.10.028. eCollection 2023 Dec.

DOI:10.1016/j.jor.2023.10.028
PMID:37994364
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10659997/
Abstract

BACKGROUND

The accessibility of digital information has expanded orthopaedic surgery with expanded role of Big Databases. The increasing interest have led to creation of large databases with increasing utilization in retrospective studies. The aim of this study is to identify Big Database research and predict future hotspots.

METHODS

Big Database publications between 1982 and 2022 were identified from the Web of Science Core Collection of Clarivate Analytics. Bibliometric indicators were obtained and imported for further analysis with VOSviewer and Bibliometrix to identify previous and ongoing trends within this field.

RESULTS

Bibliometric sourcing identified 811 total articles that was associated with major databases. Twenty-eight countries published manuscript in the field with the United States as the largest contributor. The most relevant institutions were Cleveland Clinic and Harvard University. Mont MA was the most productive and influential author. Co-occurrence visualization and thematic map identified niche and major themes within the literature.

CONCLUSIONS

Large Database research continue to show an increasing trend since 2011 with contributions globally. United States institutions and authors are the leading contributors in big database research. This study identifies previous, current, and developing trends within this field for future hotspot development.

摘要

背景

数字信息的可获取性借助大型数据库作用的扩大,推动了骨科手术的发展。人们日益浓厚的兴趣促使大型数据库不断创建,且在回顾性研究中的应用也越来越多。本研究旨在识别大型数据库研究并预测未来热点。

方法

从科睿唯安的《科学引文索引》核心合集中识别1982年至2022年间的大型数据库出版物。获取文献计量指标并导入VOSviewer和Bibliometrix进行进一步分析,以识别该领域过去和当前的趋势。

结果

文献计量来源共识别出811篇与大型数据库相关的文章。28个国家发表了该领域的手稿,其中美国贡献最大。最相关的机构是克利夫兰诊所和哈佛大学。Mont MA是产量最高、影响力最大的作者。共现可视化和主题地图确定了文献中的细分领域和主要主题。

结论

自2011年以来,大型数据库研究在全球范围内的贡献持续呈现增长趋势。美国的机构和作者是大型数据库研究的主要贡献者。本研究确定了该领域过去、当前和未来热点发展的趋势。