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Background Stroke is a leading cause of morbidity and mortality worldwide, with very large healthcare and social costs, and a strong demand for alternative therapeutic approaches. Preclinical studies have shown that stem cells transplanted into the brain can lead to functional improvement. However, to date, evidence for the benefits of stem cell transplantation in people with ischemic stroke is lacking. This is the first update of the Cochrane review published in 2010. Objectives To assess the efficacy and safety of stem cell transplantation compared with control in people with ischemic stroke. Search methods We searched the Cochrane Stroke Group Trials Register (last searched August 2018), CENTRAL (last searched August 2018), MED-LINE (1966 to August 2018), Embase (1980 to August 2018), and BIOSIS (1926 to August 2018). We handsearched potentially relevant conference proceedings, screened reference lists, and searched ongoing trials and research registers (last searched August 2018). We also contacted individuals active in the field and stem cell manufacturers (last contacted August 2018). Selection criteria We included randomized controlled trials (RCTs) that recruited people with ischemic stroke, in any phase of the disease (acute, subacute or chronic), and an ischemic lesion confirmed by computerized tomography or magnetic resonance imaging scan. We included all types of stem cell transplantation, regardless of cell source (autograft, allograft, or xenograft; embryonic, fetal, or adult; from brain or other tissues), route of cell administration (systemic or local), and dosage. The primary outcome was efficacy (assessed as neurologic impairment or functional outcome) at longer term follow-up (minimum six months). Secondary outcomes included post-procedure safety outcomes (death, worsening of neurological deficit, infections, and neoplastic transformation). Data collection and analysis Two review authors independently applied the inclusion criteria, assessed trial

For a network meta-analysis, an interlinked network of nodes representing competing treatments is needed. It is often challenging to define the nodes as these typically refer to similar but rarely identical interventions. The objectives of this paper are as follows: (i) to present a series of network meta-analysis models that account for variation in the definition of the nodes and (ii) to exemplify the models where variation in the treatment definitions relates to the dose. Starting from the model that assumes each node has a 'fixed' definition, we gradually introduce terms to explain variability by assuming that each node has several subnodes that relate to different doses. The effects of subnodes are considered monotonic, linked with a 'random walk', random but exchangeable, or have a linear pattern around the treatment mean effect. Each model can be combined with different assumptions for the consistency of effects and might impact on the ranking of the treatments. Goodness of fit, heterogeneity and inconsistency were assessed. The models are illustrated in a star network for the effectiveness of fluoride toothpaste and in a full network comparing agents for multiple sclerosis. The fit and parsimony measures indicate that in the fluoride network the impact of the dose subnodes is important whereas in the multiple sclerosis network the model without subnodes is the most appropriate. The proposed approach can be a useful exploratory tool to explain sources of heterogeneity and inconsistency when there is doubt whether similar interventions should be grouped under the same node. © 2012 John Wiley & Sons, Ltd.