Functional Connectivity And Regional Homogeneity Alterations In Migraine Patients: A Protocol of Systematic Review And Meta-Analysis

Advances in Machine Learning & Artificial Intelligence Pub Date : 2021-12-21 DOI:10.21203/rs.3.rs-1150880/v1

Yuzhong Cui, Q. Xu, Yu-Ting Li, Yanguo Zhang, Jing-Ting Sun, Ze-Yang Li, Min-Hua Ni, Teng Ma, Lin-Feng Yan, G. Cui, Wen Wang, Zhuanghong Chen

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Abstract

Objective: There are numerous functional magnetic resonance imaging (fMRI) studies examining the cerebral function of migraine patients using regional homogeneity (ReHo) and functional connectivity (FC) measurements. However, these studies generally report inconsistent conclusions. We will performed a systematic review and meta-analysis of this body of literature, aiming to identify consistent conclusions regarding cerebral functional changes in migraine patients and to describe potential future directions.Methods: Two investigators will independently screen studies published in online databases (i.e., Medline, Cochrane Library, PubMed, and Web of Science) from the database inception to June 1, 2021. By discussing with a third investigator, any disagreement will be resolved and will attain consensus. A coordinate-based meta-analysis will then be performed with an activation likelihood estimate (ALE) random-effects model.Results: The cerebral FC and ReHo altered regions in migraine patients will be elucidated in this meta-analysis.Conclusion: This study will reveal cerebral functional changes of migraine patients based on current literature to identify consistent conclusions and to describe potential future direction.Registration number: CRD42021257300.

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偏头痛患者的功能连通性和区域同质性改变:一个系统回顾和荟萃分析的方案

目的:有许多功能性磁共振成像(fMRI)研究使用区域均匀性(ReHo)和功能连通性(FC)测量来检查偏头痛患者的大脑功能。然而，这些研究通常报告不一致的结论。我们将对这些文献进行系统回顾和荟萃分析，旨在确定偏头痛患者脑功能改变的一致结论，并描述潜在的未来发展方向。方法:两名研究者将独立筛选从数据库建立到2021年6月1日在在线数据库(即Medline、Cochrane Library、PubMed和Web of Science)中发表的研究。通过与第三方调查员的讨论，任何分歧都将得到解决并达成共识。然后使用激活似然估计(ALE)随机效应模型进行基于坐标的元分析。结果:本荟萃分析将阐明偏头痛患者的大脑FC和ReHo改变区域。结论:本研究将在现有文献的基础上揭示偏头痛患者的脑功能变化，以确定一致的结论并描述潜在的未来方向。注册号:CRD42021257300。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Advances in Machine Learning & Artificial Intelligence

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