Abstract：
OBJECTIVE: Accurately predicting the implant size in total knee arthroplasties could increase the efficiency of the operation, decrease the costs associated with the procedure and result in improved patient outcomes. To substantiate its continued use, digital templating must demonstrate itself to be an accurate tool in predicting component size in order for surgeons to confidently use it to optimize the procedure.
METHODS: A systematic literature review was performed and identified 16 studies within the Pubmed, Ebsco and Ovid-Embase databases, with 1189 TKR prostheses included for analysis. A quality of evidence assessment was performed on each study depending on the study design. A random effects meta-analysis model was used to pool overall implant accuracy and the reported inter-rater agreement when performing digital templating and displayed in a forest plot. Meta-regression was used analyze potential factors that may affect the accuracy of digital templating.
RESULTS: The pooled proportion of accurate templates with 0 margin of error was found to be 56% (52-61, 95CI), which increases to 96% (0.94-0.98, 95CI) when allowing for a 1 size margin of error. Subgroup analysis between femoral and tibial components concluded no statistically significant difference.
CONCLUSIONS: This study supports the continued use of digital templating for planning total knee arthroplasties and recommends further subgroup analysis of patient age, body mass index and sex against accuracy. This review was registered in the International Prospective Register of Systematic Reviews Database under ID: CRD420222367461. No funding was provided for the completion of this systematic review.
BACKGROUND: Templating in the preoperative planning of total knee arthroplasties is a vital step in ensuring maximum operative efficiency. A method that can accurately predict the required implant size within 1 size could improve theatre turnover, decrease costs and benefit patient outcomes. The current literature on the accuracy of digital templating in total knee arthroplasties lacks a systematic review calculating the overall accuracy of the process, this study aims to address this gap.
METHODS: A systematic literature review was performed and identified 16 studies within the Pubmed, Ebsco and Ovid-Embase databases, with 1189 TKR prostheses included for analysis. A quality of evidence assessment was performed on each study depending on the study design. A random effects meta-analysis model was used to pool overall implant accuracy and the reported inter-rater agreement when performing digital templating and displayed in a forest plot. Meta-regression was used analyze potential factors that may affect the accuracy of digital templating.
RESULTS: The pooled proportion of accurate templates with 0 margin of error was found to be 56% (52-61, 95CI), which increases to 96% (0.94-0.98, 95CI) when allowing for a 1 size margin of error. Subgroup analysis between femoral and tibial components concluded no statistically significant difference.
CONCLUSIONS: This study supports the continued use of digital templating for planning total knee arthroplasties and recommends further subgroup analysis of patient age, body mass index and sex against accuracy. This review was registered in the International Prospective Register of Systematic Reviews Database under ID: CRD420222367461. No funding was provided for the completion of this systematic review.
BACKGROUND: Templating in the preoperative planning of total knee arthroplasties is a vital step in ensuring maximum operative efficiency. A method that can accurately predict the required implant size within 1 size could improve theatre turnover, decrease costs and benefit patient outcomes. The current literature on the accuracy of digital templating in total knee arthroplasties lacks a systematic review calculating the overall accuracy of the process, this study aims to address this gap.
摘要：
目的：准确预测全膝关节置换术中的植入物大小可以提高手术效率，降低与手术相关的成本，并改善患者的预后。为了证实其持续使用，数字模板必须证明自己是预测组件尺寸的准确工具，以便外科医生自信地使用它来优化程序。
方法：进行了系统的文献综述，确定了Pubmed中的16项研究，Ebsco和Ovid-Embase数据库,包括1189个TKR假体进行分析。根据研究设计对每项研究进行证据质量评估。在执行数字模板并在森林图中显示时，使用随机效应元分析模型来汇集整体植入物的准确性和报告的评分者之间的协议。使用Meta回归分析可能影响数字模板准确性的潜在因素。
结果：发现误差幅度为0的精确模板的合并比例为56％（52-61，95CI），当允许1大小的误差幅度时，它增加到96%(0.94-0.98，95CI)。亚组剖析得出股骨和胫骨组件之间无统计学差别。
结论：本研究支持继续使用数字模板来规划全膝关节置换术，并建议对患者年龄进行进一步的亚组分析，体重指数和性别对准确性。该评价在国际前瞻性系统评价注册数据库中注册，ID：CRD420222367461。没有为完成这一系统审查提供资金。
背景：全膝关节置换术术前计划中的模板是确保最大手术效率的重要步骤。一种能够在1个尺寸内准确预测所需植入物尺寸的方法可以改善手术室周转，降低成本并使患者受益。关于全膝关节置换术中数字模板准确性的现有文献缺乏系统的评价，这项研究旨在解决这一差距。
方法：进行了系统的文献综述，确定了Pubmed中的16项研究，Ebsco和Ovid-Embase数据库,包括1189个TKR假体进行分析。根据研究设计对每项研究进行证据质量评估。在执行数字模板并在森林图中显示时，使用随机效应元分析模型来汇集整体植入物的准确性和报告的评分者之间的协议。使用Meta回归分析可能影响数字模板准确性的潜在因素。
结果：发现误差幅度为0的精确模板的合并比例为56％（52-61，95CI），当允许1大小的误差幅度时，它增加到96%(0.94-0.98，95CI)。亚组剖析得出股骨和胫骨组件之间无统计学差别。
结论：本研究支持继续使用数字模板来规划全膝关节置换术，并建议对患者年龄进行进一步的亚组分析，体重指数和性别对准确性。该评价在国际前瞻性系统评价注册数据库中注册，ID：CRD420222367461。没有为完成这一系统审查提供资金。
背景：全膝关节置换术术前计划中的模板是确保最大手术效率的重要步骤。一种能够在1个尺寸内准确预测所需植入物尺寸的方法可以改善手术室周转，降低成本并使患者受益。关于全膝关节置换术中数字模板准确性的现有文献缺乏系统的评价，这项研究旨在解决这一差距。
