Prognosis Prediction Models for Post-stroke Depression: a Protocol for Systematic Review, Meta-analysis, and Critical Appraisal

Overview

Journal Syst Rev

Publisher Biomed Central

Date 2024 May 22

PMID 38778417

Authors

Lu Zhou

Lei Wang

Gao Liu

Enli Cai

Affiliations

Soon will be listed here.

Abstract

Introduction: Post-stroke depression (PSD) is a prevalent complication that has been shown to have a negative impact on rehabilitation outcomes and quality of life and poses a significant risk for suicidal intention. However, models for discriminating and predicting PSD in stroke survivors for effective secondary prevention strategies are inadequate as the pathogenesis of PSD remains unknown. Prognostic prediction models that exhibit greater rule-in capacity have the potential to mitigate the issue of underdiagnosis and undertreatment of PSD. Thus, the planned study aims to systematically review and critically evaluate published studies on prognostic prediction models for PSD.

Methods And Analysis: A systematic literature search will be conducted in PubMed and Embase through Ovid. Two reviewers will complete study screening, data extraction, and quality assessment utilizing appropriate tools. Qualitative data on the characteristics of the included studies, methodological quality, and the appraisal of the clinical applicability of models will be summarized in the form of narrative comments and tables or figures. The predictive performance of the same model involving multiple studies will be synthesized with a random effects meta-analysis model or meta-regression, taking into account heterogeneity.

Ethics And Dissemination: Ethical approval is considered not applicable for this systematic review. Findings will be shared through dissemination at academic conferences and/or publication in peer-reviewed academic journals.

Systematic Review Registration: PROSPERO CRD42023388548.

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