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评估全髋关节置换术和全膝关节置换术后患者报告结局测量预后预测模型的方法学质量:系统综述方案。

Evaluating methodological quality of prognostic prediction models on patient reported outcome measurements after total hip replacement and total knee replacement surgery: a systematic review protocol.

机构信息

Centre for Pain IMPACT, Neuroscience Research Australia (NeuRA), 139 Barker St, Randwick, NSW, 2031, Australia.

School of Health Sciences, College of Health, Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, 2038, Australia.

出版信息

Syst Rev. 2022 Aug 10;11(1):165. doi: 10.1186/s13643-022-02039-7.

Abstract

BACKGROUND

Prediction models for poor patient-reported surgical outcomes after total hip replacement (THR) and total knee replacement (TKR) may provide a method for improving appropriate surgical care for hip and knee osteoarthritis. There are concerns about methodological issues and the risk of bias of studies producing prediction models. A critical evaluation of the methodological quality of prediction modelling studies in THR and TKR is needed to ensure their clinical usefulness. This systematic review aims to (1) evaluate and report the quality of risk stratification and prediction modelling studies that predict patient-reported outcomes after THR and TKR; (2) identify areas of methodological deficit and provide recommendations for future research; and (3) synthesise the evidence on prediction models associated with post-operative patient-reported outcomes after THR and TKR surgeries.

METHODS

MEDLINE, EMBASE, and CINAHL electronic databases will be searched to identify relevant studies. Title and abstract and full-text screening will be performed by two independent reviewers. We will include (1) prediction model development studies without external validation; (2) prediction model development studies with external validation of independent data; (3) external model validation studies; and (4) studies updating a previously developed prediction model. Data extraction spreadsheets will be developed based on the CHARMS checklist and TRIPOD statement and piloted on two relevant studies. Study quality and risk of bias will be assessed using the PROBAST tool. Prediction models will be summarised qualitatively. Meta-analyses on the predictive performance of included models will be conducted if appropriate. A narrative review will be used to synthesis the evidence if there are insufficient data to perform meta-analyses.

DISCUSSION

This systematic review will evaluate the methodological quality and usefulness of prediction models for poor outcomes after THR or TKR. This information is essential to provide evidence-based healthcare for end-stage hip and knee osteoarthritis. Findings of this review will contribute to the identification of key areas for improvement in conducting prognostic research in this field and facilitate the progress in evidence-based tailored treatments for hip and knee osteoarthritis.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42021271828.

摘要

背景

预测全髋关节置换术(THR)和全膝关节置换术(TKR)后患者报告手术结局不良的模型,可为改善髋膝关节骨关节炎的适当手术护理提供一种方法。对于产生预测模型的研究,人们对其方法学问题和偏倚风险存在担忧。需要对 THR 和 TKR 中预测建模研究的方法学质量进行批判性评估,以确保其临床实用性。本系统评价旨在:(1)评估并报告预测 THR 和 TKR 后患者报告结局的风险分层和预测模型研究的质量;(2)确定方法学缺陷领域,并为未来研究提供建议;(3)综合与 THR 和 TKR 手术后患者报告结局相关的预测模型的证据。

方法

将检索 MEDLINE、EMBASE 和 CINAHL 电子数据库,以确定相关研究。两名独立审查员将进行标题和摘要以及全文筛选。我们将纳入:(1)无外部验证的预测模型开发研究;(2)具有独立数据外部验证的预测模型开发研究;(3)外部模型验证研究;(4)更新先前开发的预测模型的研究。基于 CHARMS 清单和 TRIPOD 声明制定数据提取电子表格,并在两项相关研究中进行试点。使用 PROBAST 工具评估研究质量和偏倚风险。将对纳入模型的预测性能进行汇总分析。如果数据适当,将进行荟萃分析。如果没有足够的数据进行荟萃分析,则使用叙述性综述来综合证据。

讨论

本系统评价将评估 THR 或 TKR 后不良结局预测模型的方法学质量和实用性。这些信息对于为晚期髋膝关节骨关节炎提供循证医疗保健至关重要。本综述的结果将有助于确定该领域预后研究中需要改进的关键领域,并促进基于证据的针对髋膝关节骨关节炎的个体化治疗进展。

系统评价注册

PROSPERO 注册号 CRD42021271828。

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Selecting and optimising patients for total knee arthroplasty.选择和优化全膝关节置换术患者。
Med J Aust. 2019 Feb;210(3):135-141. doi: 10.5694/mja2.12109. Epub 2019 Jan 18.

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