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[Abstract] We research into the clinical, biochemical and neuroimaging factors associated with the outcome of stroke patients to generate a predictive model using machine learning techniques for prediction of mortality and morbidity 3-months after admission. The dataset consisted of patients with ischemic stroke (IS) and non-traumatic intracerebral hemorrhage (ICH) admitted to Stroke Unit of a European Tertiary Hospital prospectively registered. We identified the main variables for machine learning Random Forest (RF), generating a predictive model that can estimate patient mortality/morbidity according to the following groups: (1) IS + ICH, (2) IS, and (3) ICH. A total of 6022 patients were included: 4922 (mean age 71.9 ± 13.8 years) with IS and 1100 (mean age 73.3 ± 13.1 years) with ICH. NIHSS at 24, 48 h and axillary temperature at admission were the most important variables to consider for evolution of patients at 3-months. IS + ICH group was the most stable for mortality prediction [0.904 ± 0.025 of area under the receiver operating characteristics curve (AUC)]. IS group presented similar results, although variability between experiments was slightly higher (0.909 ± 0.032 of AUC). ICH group was the one in which RF had more problems to make adequate predictions (0.9837 vs. 0.7104 of AUC). There were no major differences between IS and IS + ICH groups according to morbidity prediction (0.738 and 0.755 of AUC) but, after checking normality with a Shapiro Wilk test with the null hypothesis that the data follow a normal distribution, it was rejected with W = 0.93546 (p-value

Neuroprotective treatments in ischemic stroke are focused to reduce the pernicious effect of excitotoxicity, oxidative stress and inflammation. However, those cellular and molecular mechanisms may also have beneficial effects, especially during the late stages of the ischemic stroke. The objective of this study was to investigate the relationship between the clinical improvement of ischemic stroke patients and the time-dependent excitotoxicity and inflammation. We included 4295 ischemic stroke patients in a retrospective study. The main outcomes were intra and extra-hospital improvement. High glutamate and IL-6 levels at 24 hours were associated with a worse intra-hospital improvement (OR:0.993, 95%CI: 0.990–0.996 and OR:0.990, 95%CI: 0.985–0.995). High glutamate and IL-6 levels at 24 hours were associated with better extra-hospital improvement (OR:1.13 95%CI, 1.07–1.12 and OR:1.14, 95%CI, 1.09–1.18). Effective reperfusion after recanalization showed the best clinical outcome. However, the long term recovery is less marked in patients with an effective reperfusion. The variations of glutamate and IL6 levels in the first 24 hours clearly showed a relationship between the molecular components of the ischemic cascade and the clinical outcome of patients. Our findings suggest that the rapid reperfusion after recanalization treatment blocks the molecular response to ischemia that is associated with restorative processes.

Mesenchymal stem cells (MSCs) are a promising clinical therapy for ischemic stroke. However, critical parameters, such as the most effective administration route, remain unclear. Intravenous (i.v.) and intraarterial (i.a.) delivery routes have yielded varied outcomes across studies, potentially due to the unknown MSCs distribution. We investigated whether MSCs reached the brain following i.a. or i.v. administration after transient cerebral ischemia in rats, and evaluated the therapeutic effects of both routes. MSCs were labeled with dextran-coated superparamagnetic nanoparticles for magnetic resonance imaging (MRI) cell tracking, transmission electron microscopy and immunohistological analysis. MSCs were found in the brain following i.a. but not i.v. administration. However, the i.a. route increased the risk of cerebral lesions and did not improve functional recovery. The i.v. delivery is safe but MCS do not reach the brain tissue, implying that treatment benefits observed for this route are not attributable to brain MCS engrafting after stroke., This study has been partially supported by grants from Axencia Galega de Innovación (Xunta de Galicia), the Instituto de Salud Carlos III (PI13/00292; PI14/01879), the Spanish Research Network on Cerebrovascular Diseases RETICS-INVICTUS (RD12/0014), Xunta de Galicia (Consellería Educación GRC2014/027), the European Commission program FEDER and Promoting Active Ageing program: Functional Nanostructures For Alzheimer’s Disease At Ultra-Early Stages” (Pana_686009), a Research and Innovation Project, funded within the EU Horizon 2020 Programme”. Furthermore, this study was also co-funded within the POCTEP (Operational Programme for Cross-border Cooperation Spain-Portugal) program (0681_INVENNTA_1_E), co-financed by the ERDF (European Regional Development Fund). T. Sobrino (CP12/03121) and F. Campos (CP14/00154) are recipients of a research contract from Miguel Servet Program of Instituto de Salud Carlos III. Finally, P. Taboada thanks Mineco and Xunta de Galicia for funding through projects MAT2013-40971-R and EM2013-046, respectively. J Trekker is the recipient of an innovation grant from the IWT-Vlaanderen.