Abstract

Introduction: Globally, stroke is the second leading cause of death. Despite the burden of illness and death, few acute interventions are available to patients with ischemic stroke. Over 1,000 potential neuroprotective therapeutics have been evaluated in preclinical models. It is important to use robust evidence synthesis methods to appropriately assess which therapies should be translated to the clinical setting for evaluation in human studies. This protocol details planned methods to conduct a systematic review to identify and appraise eligible studies and to use a network meta-analysis to synthesize available evidence to answer the following questions: in preclinical in vivo models of focal ischemic stroke, what are the relative benefits of competing therapies tested in combination with the gold standard treatment alteplase in (i) reducing cerebral infarction size, and (ii) improving neurobehavioural outcomes? Methods: We will search Ovid Medline and Embase for articles on the effects of combination therapies with alteplase. Controlled comparison studies of preclinical in vivo models of experimentally induced focal ischemia testing the efficacy of therapies with alteplase versus alteplase alone will be identified. Outcomes to be extracted include infarct size (primary outcome) and neurobehavioural measures. Risk of bias and construct validity will be assessed using tools appropriate for preclinical studies. Here we describe steps undertaken to perform preclinical network meta-analysis to synthesise all evidence for each outcome and obtain a comprehensive ranking of all treatments. This will be a novel use of this evidence synthesis approach in stroke medicine to assess pre-clinical therapeutics. Combining all evidence to simultaneously compare mutliple therapuetics tested preclinically may provide a rationale for the clinical translation of therapeutics for patients with ischemic stroke. Dissemination: Review findings will be submitted to a peer-reviewed journal and presented at relevant scientific meetings to promote knowledge transfer. Registration: PROSPERO number to be submitted following peer review.

Highlights

  • Stroke is the second leading cause of death

  • We will perform a systematic review and network meta-analysis (NMA) to address the following question: amongst in vivo models of focal ischemic stroke, what are the relative benefits of competing therapies tested in combination with the gold standard treatment alteplase[14] in (i) reducing cerebral infarction size, and (ii) improving neurobehavioural outcomes?

  • We will search the CAMARADES database which contains data extracted from existing preclinical systematic reviews on stroke[15,17,18,19,20,21,22,23,24,25,26,27,28]

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Summary

Introduction

Stroke is the second leading cause of death. Despite the burden of illness and death, few acute interventions are available to patients with ischemic stroke. It is important to use robust evidence synthesis methods to appropriately assess which therapies should be translated to the clinical setting for evaluation in human studies This protocol details planned methods to conduct a systematic review to identify and appraise eligible studies and to use a network meta-analysis to synthesize available evidence to answer the following questions: in preclinical in vivo models of focal ischemic stroke, what are the relative. Despite the enormous human and economic burden, only four acute interventions are currently used clinically: patient care in a dedicated stroke unit[3], reperfusion (by pharmacological thrombolysis or endovascular mechanical thrombectomy4), oral aspirin, and surgical decompression. In the search for novel therapies for acute stroke, more than 1,000 potential neuroprotective therapeutics (e.g. anticoagulants, calcium channel blockers, free radical scavengers, GABA mimetics, etc.) have been evaluated in preclinical models[5]. Given the multitude of therapies tested preclinically (and multiple mechanisms of action) it is difficult to assess which therapies should proceed to clinical testing

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