BACKGROUND AND PURPOSE: A total of 25% of strokes are lacunar, and these are pathophysiologically different from large artery strokes. Despite emerging evidence of a substantial impact on physical disability and dementia, little attention has been paid to the development of specific treatments. The optimal use of the animal models of lacunar stroke used to test candidate interventions is not known. METHODS: We conducted a systematic review and meta-analysis of studies testing candidate interventions in animal models of lacunar stroke. We used random-effects meta-analysis to assess the impact of study characteristics and trim and fill to seek evidence of publication bias. RESULTS: The efficacy of 43 distinct interventions was described in 57 publications. The median number of quality checklist items scored was 3 of 8 (interquartile range, 2-4). Many models reflected mechanisms of limited relevance to lacunar stroke. Meta-analysis of results from 27 studies showed that on average, infarct size and neurobehavioral outcome were improved by 34.2% (24.1-44.2) and 0.82 standardized mean difference (0.51-1.14), respectively. Four interventions improved both infarct size and neurobehavioral outcome but there were insufficient data for this finding to be considered robust. For infarct size, efficacy was lower in studies reporting blinding and higher in studies reporting randomization. For neurobehavior, efficacy was lower in randomized studies. For infarct size there was evidence of publication bias. CONCLUSIONS: No intervention has yet been tested in sufficient range and depth to support translation to clinical trial. There is limited reporting of measures to reduce the risk of bias and evidence for a substantial publications bias.
BACKGROUND AND PURPOSE: A total of 25% of strokes are lacunar, and these are pathophysiologically different from large artery strokes. Despite emerging evidence of a substantial impact on physical disability and dementia, little attention has been paid to the development of specific treatments. The optimal use of the animal models of lacunar stroke used to test candidate interventions is not known. METHODS: We conducted a systematic review and meta-analysis of studies testing candidate interventions in animal models of lacunar stroke. We used random-effects meta-analysis to assess the impact of study characteristics and trim and fill to seek evidence of publication bias. RESULTS: The efficacy of 43 distinct interventions was described in 57 publications. The median number of quality checklist items scored was 3 of 8 (interquartile range, 2-4). Many models reflected mechanisms of limited relevance to lacunar stroke. Meta-analysis of results from 27 studies showed that on average, infarct size and neurobehavioral outcome were improved by 34.2% (24.1-44.2) and 0.82 standardized mean difference (0.51-1.14), respectively. Four interventions improved both infarct size and neurobehavioral outcome but there were insufficient data for this finding to be considered robust. For infarct size, efficacy was lower in studies reporting blinding and higher in studies reporting randomization. For neurobehavior, efficacy was lower in randomized studies. For infarct size there was evidence of publication bias. CONCLUSIONS: No intervention has yet been tested in sufficient range and depth to support translation to clinical trial. There is limited reporting of measures to reduce the risk of bias and evidence for a substantial publications bias.
Authors: Gary A Rosenberg; Anders Wallin; Joanna M Wardlaw; Hugh S Markus; Joan Montaner; Leslie Wolfson; Costantino Iadecola; Berislav V Zlokovic; Anne Joutel; Martin Dichgans; Marco Duering; Reinhold Schmidt; Amos D Korczyn; Lea T Grinberg; Helena C Chui; Vladimir Hachinski Journal: J Cereb Blood Flow Metab Date: 2016-01 Impact factor: 6.200
Authors: Emmanuel Touzé; Denis Vivien; Cyrille Orset; Benoit Haelewyn; Stuart M Allan; Saema Ansar; Francesco Campos; Tae Hee Cho; Anne Durand; Mohamad El Amki; Marc Fatar; Isaac Garcia-Yébenes; Maxime Gauberti; Saskia Grudzenski; Ignacio Lizasoain; Eng Lo; Richard Macrez; Isabelle Margaill; Samaneh Maysami; Stephen Meairs; Norbert Nighoghossian; Josune Orbe; Jose Antonio Paramo; Jean-Jacques Parienti; Nancy J Rothwell; Marina Rubio; Christian Waeber; Alan R Young Journal: Stroke Date: 2016-03-31 Impact factor: 7.914
Authors: David P Archer; Andrew M Walker; Sarah K McCann; Joanna J Moser; Ramana M Appireddy Journal: Anesthesiology Date: 2017-04 Impact factor: 7.892
Authors: Jennifer A Hirst; Jeremy Howick; Jeffrey K Aronson; Nia Roberts; Rafael Perera; Constantinos Koshiaris; Carl Heneghan Journal: PLoS One Date: 2014-06-06 Impact factor: 3.240
Authors: Karen Horsburgh; Joanna M Wardlaw; Tom van Agtmael; Stuart M Allan; Mike L J Ashford; Philip M Bath; Rosalind Brown; Jason Berwick; M Zameel Cader; Roxana O Carare; John B Davis; Jessica Duncombe; Tracy D Farr; Jill H Fowler; Jozien Goense; Alessandra Granata; Catherine N Hall; Atticus H Hainsworth; Adam Harvey; Cheryl A Hawkes; Anne Joutel; Rajesh N Kalaria; Patrick G Kehoe; Catherine B Lawrence; Andy Lockhart; Seth Love; Malcolm R Macleod; I Mhairi Macrae; Hugh S Markus; Chris McCabe; Barry W McColl; Paul J Meakin; Alyson Miller; Maiken Nedergaard; Michael O'Sullivan; Terry J Quinn; Rikesh Rajani; Lisa M Saksida; Colin Smith; Kenneth J Smith; Rhian M Touyz; Rebecca C Trueman; Tao Wang; Anna Williams; Steven C R Williams; Lorraine M Work Journal: Clin Sci (Lond) Date: 2018-04-30 Impact factor: 6.124
Authors: Zsanett Bahor; Jing Liao; Malcolm R Macleod; Alexandra Bannach-Brown; Sarah K McCann; Kimberley E Wever; James Thomas; Thomas Ottavi; David W Howells; Andrew Rice; Sophia Ananiadou; Emily Sena Journal: Clin Sci (Lond) Date: 2017-10-12 Impact factor: 6.124