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About two-thirds of patients with minor strokes are discharged home. However, these patients may have difficulties returning to their usual living activities. To investigate the factors associated with successful home discharge, our aim was to provide a decision tree (based on clinical data) that could identify if a patient discharged home could return to pre-stroke activities and to perform an external validation of this decision tree on an independent cohort. Two cohorts of patients with minor strokes gathered from stroke registries at the Hôpital Pitié-Salpêtrière and University Hospital Bern were included in this study (n = 105 for the construction cohort coming from France; n = 100 for the second cohort coming from Switzerland). The decision tree was built using the classification and regression tree (CART) analysis on the construction cohort. It was then applied to the validation cohort. Accuracy, sensitivity, specificity, false positive, and false-negative rates were reported for both cohorts. In the construction cohort, 60 patients (57%) returned to their usual, pre-stroke level of independence. The CART analysis produced a decision tree with the Montreal Cognitive Assessment (MoCA) as the first decision point, followed by discharge NIHSS score or age, and then by the occupational status. The overall prediction accuracy to the favorable outcome was 80% in the construction cohort and reached 72% accuracy in the validation cohort. This decision tree highlighted the role of cognitive function as a crucial factor for patients to return to their usual activities after a minor stroke. The algorithm may help clinicians to tailor planning of patients' discharge.

The relationship between stroke topography and functional outcome has largely been studied with binary manual lesion segmentations. However, stroke topography may be better characterized by continuous variables capable of reflecting the severity of ischemia, which may be more pertinent for long-term outcome. Diffusion Tensor Imaging (DTI) constitutes a powerful means of quantifying the degree of acute ischemia and its potential relation to functional outcome. Our aim was to investigate whether using more clinically pertinent imaging parameters with powerful machine learning techniques could improve prediction models and thus provide valuable insight on critical brain areas important for long-term outcome. Eighty-seven thrombolyzed patients underwent a DTI sequence at 24 h post-stroke. Functional outcome was evaluated at 3 months post-stroke with the modified Rankin Score and was dichotomized into good (mRS ≤ 2) and poor (mRS > 2) outcome. We used support vector machines (SVM) to classify patients into good vs. poor outcome and evaluate the accuracy of different models built with fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity asymmetry maps, and lesion segmentations in combination with lesion volume, age, recanalization status, and thrombectomy treatment. SVM classifiers built with axial diffusivity maps yielded the best accuracy of all imaging parameters (median [IQR] accuracy = 82.8 [79.3–86.2]%), compared to that of lesion segmentations (76.7 [73.3–82.8]%) when predicting 3-month functional outcome. The analysis revealed a strong contribution of clinical variables, notably – in descending order – lesion volume, thrombectomy treatment, and recanalization status, in addition to the deep white matter at the crossroads of major white matter tracts, represented by brain regions where model weights were highest. Axial diffusivity is a more appropriate imaging marker to characterize stroke topography for predicting long-term outcome than binary lesion segmentations. Keywords: Acute stroke, Prediction, Prognosis, Functional outcome, Diffusion tensor imaging

BackgroundRecently, the concept of 'clinically relevant penumbra' was defined as an area saved by arterial recanalization and correlated with stroke outcome. This clinically relevant penumbra was located in the subcortical structures, especially the periventricular white matter. Our aims were to confirm this hypothesis, to investigate the impact of admission hyperglycemia and of insulin treatment on the severity of ischemic damages in this area and to study the respective contributions of infarct volume and ischemic damage severity of the clinically relevant penumbra on 3-month outcome.MethodsWe included 99 patients from the INSULINFARCT trial. Voxel-Based Analysis was carried on the Apparent Diffusion Coefficient (ADC) maps obtained at day one to localize the regions, which were more damaged in patients i) with poor clinical outcomes at three months and ii) without arterial recanalization. We determined the intersection of the detected areas, which represents the clinically relevant penumbra and investigated whether hyperglycemic status and insulin regimen affected the severity of ischemic damages in this area. We performed logistic regression to examine the contribution of infarct volume or early ADC decrease in this strategic area on 3-month outcome.FindingsLower ADC values were found in the corona radiata in patients with poor prognosis (p< 0.0001) and in those without arterial recanalization (p< 0.0001). The tracking analysis showed that lesions in this area interrupted many important pathways. ADC values in this area were lower in hyperglycemic than in normoglycemic patients (average decrease of 41.6 ± 20.8 x10(-6) mm2/s) and unaffected by the insulin regimen (p: 0.10). ADC values in the clinically relevant penumbra, but not infarct volumes, were significant predictors of 3-month outcome.ConclusionThese results confirm that the deep hemispheric white matter is part of the clinically relevant penumbra and show that hyperglycaemia exacerbates the apparition of irreversible ischemic damage within 24 hours in this area. However, early intensive insulin therapy fails to protect this area from infarction.Trial registrationClinicalTrials.gov NCT00472381.

Fractional anisotropy (FA) is an effective marker of motor outcome at the chronic stage of stroke yet proves to be less efficient at early time points. This study aims to determine which diffusion metric in which location is the best marker of long-term stroke outcome after thrombolysis with diffusion tensor imaging (DTI) at 24 hours post-stroke. Twenty-eight thrombolyzed patients underwent DTI at 24 hours post-stroke onset. Ipsilesional and contralesional FA, mean (MD), axial (AD), and radial (RD) diffusivities values were calculated in different Regions-of-Interest (ROIs): (1) the white matter underlying the precentral gyrus (M1), (2) the corona radiata (CoRad), (3) the posterior limb of the internal capsule (PLIC) and (4) the cerebral peduncles (CP). NIHSS scores were acquired at admission, day 1, and day 7; modified Rankin Scores (mRS) at 3 months. Significant decreases were found in FA, MD, and AD of the ipsilesional CoRad and M1. MD and AD were also significantly lower in the PLIC. The ratio of ipsi and contralesional AD of the CoRad (CoRad-rAD) was the strongest diffusion parameter correlated with motor NIHSS scores on day 7 and with the mRS at 3 months. A Receiver-Operator Curve analysis yielded a model for the CoRad-rAD to predict good outcome based on upper limb NIHSS motor scores and mRS with high specificity and sensitivity. FA values were not correlated with clinical outcome. In conclusion, axial diffusivity of the CoRad from clinical DTI at 24 hours post-stroke is the most appropriate diffusion metric for quantifying stroke damage to predict outcome, suggesting the importance of early axonal damage.

BackgroundMotor outcome after stroke is associated with reorganisation of cortical networks and corticospinal tract (CST) integrity. However, the relationships between motor severity, CST damage, and functional brain connectivity are not well understood. Here, the main objective was to study the effect of CST damage on the relationship between functional motor network connectivity and hand motor function in two groups of stroke patients: the severely (n=8) and the mildly impaired (n=14).MethodsTwenty-two carotid stroke patients with motor deficits were studied with magnetic resonance imaging (MRI) at 3 weeks, at 3 and 6 months. Healthy subjects (n=28) were scanned once. The CST injury was assessed by fractional anisotropy values. Functional connectivity was studied from a whole-hand grip task fMRI in a cortical and cerebellar motor network. Functional connectivity indexes were computed between these regions at each time point. The relationship between hand motor strength, ipsilesional CST damage and functional connectivity from the primary motor cortex (M1) was investigated using global and partial correlations.FindingsIn mildly impaired patients, cortico-cortical connectivity was disturbed at three weeks but returned to a normal pattern after 3 months. Cortico-cerebellar connectivity was still decreased at 6 months. In severely impaired patients, the cortico-cortical connectivity tended to return to a normal pattern, but the cortico-cerebellar connectivity was totally abolished during the follow-up. In the entire group of patients, the hand motor strength was correlated to the ipsilesional functional connectivity from M1. Partial correlations revealed that these associations were not anymore significant when the impact of CST damage was removed, except for the ipsilesional M1-contralateral cerebellum connectivity.ConclusionFunctional brain connectivity changes can be observed, even in severely impaired patients with no recovery. Upper limb function is mainly explained by the CST damage and by the ipsilesional cortico-cerebellar connectivity.

Identification of drug-induced liver disease (DILI) is difficult, even among hospitalized patients. The aim of this pilot study was to assess the impact of a specific strategy for DILI screening.We prospectively compared the number of acute DILI cases identified in one week of a proactive strategy based on centralized elevated ALT values to those identified with a standard of care strategy for 24-week period based on referral cases to the hepatology unit. In the centralized strategy, a designated study biochemist identified patients with ALT greater than 3 times the upper limit of normal values (ULN) and notified the designated hepatologists, who then went to the patients' wards, analyzed the charts, and if necessary, interviewed the identified patients. During these two periods, patients with possible DILI were included after signing an informed consent in an ongoing European diagnostic study (SAFE-T consortium).During the 24-week period of the standard strategy, 12 (0.04%) patients out of a total of 28,145 were identified as having possible DILI, and 11 of these accepted to be included in the protocol. During the one-week proactive period, 7 patients out of a total of 1407 inpatients (0.498%) [odds ratio vs. standard = 12.1 (95% CI, 3.9-32.3); P3 ULN by designated biochemists and hepatologists identified 12 times more acute cases of drug-induced liver disease than the standard strategy. This pilot cohort is registered on the number AP-HP P110201/1/08-03-2011 and AFSSAPS B110346-70.

BackgroundThe clinical relevance of MR scanning in children with autism is still an open question and must be considered in light of the evolution of this technology. MRI was judged to be of insufficient value to be included in the standard clinical evaluation of autism according to the guidelines of the American Academy of Neurology and Child Neurology Society in 2000. However, this statement was based on results obtained from small samples of patients and, more importantly, included mostly insufficient MRI sequences. Our main objective was to evaluate the prevalence of brain abnormalities in a large group of children with a non-syndromic autistic disorder (AD) using T1, T2 and FLAIR MRI sequences.MethodologyMRI inspection of 77 children and adolescents with non-syndromic AD (mean age 7.4+/-3.6) was performed. All met the DSM-IV and ADI -R criteria for autism. Based on recommended clinical and biological screenings, we excluded patients with infectious, metabolic or genetic diseases, seizures or any other neurological symptoms. Identical MRI inspections of 77 children (mean age 7.0+/-4.2) without AD, developmental or neurological disorders were also performed. All MRIs were acquired with a 1.5-T Signa GE (3-D T1-FSPGR, T2, FLAIR coronal and axial sequences). Two neuroradiologists independently inspected cortical and sub-cortical regions. MRIs were reported to be normal, abnormal or uninterpretable.Principal findingsMRIs were judged as uninterpretable in 10% (8/77) of the cases. In 48% of the children (33/69 patients), abnormalities were reported. Three predominant abnormalities were observed, including white matter signal abnormalities (19/69), major dilated Virchow-Robin spaces (12/69) and temporal lobe abnormalities (20/69). In all, 52% of the MRIs were interpreted as normal (36/69 patients).ConclusionsAn unexpectedly high rate of MRI abnormalities was found in the first large series of clinical MRI investigations in non-syndromic autism. These results could contribute to further etiopathogenetic research into autism.