Lack of direct involvement of a diazepam long-term treatment in the occurrence of irreversible cognitive impairment: a pre-clinical approach

Several observational studies have found a link between the long-term use of benzodiazepines and dementia, which remains controversial. Our study was designed to assess (i) whether the long-term use of benzodiazepines, at two different doses, has an irreversible effect on cognition, (ii) and whether there is an age-dependent effect. One hundred and five C57Bl/6 male mice were randomly assigned to the 15 mg/kg/day, the 30 mg/kg/day diazepam-supplemented pellets, or the control group. Each group comprised mice aged 6 or 12 months at the beginning of the experiments and treated for 16 weeks. Two sessions of behavioral assessment were conducted: after 8 weeks of treatment and after treatment completion following a 1-week wash-out period. The mid-treatment test battery included the elevated plus maze test, the Y maze spontaneous alternation test, and the open field test. The post-treatment battery was upgraded with three additional tests: the novel object recognition task, the Barnes maze test, and the touchscreen-based paired-associated learning task. At mid-treatment, working memory was impaired in the 15 mg/kg diazepam group compared to the control group (p = 0.005). No age effect was evidenced. The post-treatment assessment of cognitive functions (working memory, visual recognition memory, spatial reference learning and memory, and visuospatial memory) did not significantly differ between groups. Despite a cognitive impact during treatment, the lack of cognitive impairment after long-term treatment discontinuation suggests that benzodiazepines alone do not cause irreversible deleterious effects on cognitive functions and supports the interest of discontinuation in chronically treated patients.

Long-Term Cognitive Decline After Stroke: An Individual Participant Data Meta-Analysis

BACKGROUND AND PURPOSE

Poststroke cognitive impairment is common, but the trajectory and magnitude of cognitive decline after stroke is unclear. We examined the course and determinants of cognitive change after stroke using individual participant data from the Stroke and Cognition Consortium.

METHODS

Nine longitudinal hospital-based cohorts from 7 countries were included. Neuropsychological test scores and normative data were used to calculate standardized scores for global cognition and 5 cognitive domains. One-step individual participant data meta-analysis was used to examine the rate of change in cognitive function and risk factors for cognitive decline after stroke. Stroke-free controls were included to examine rate differences. Based on the literature and our own data that showed short-term improvement in cognitive function after stroke, key analyses were restricted to the period beginning 1-year poststroke to focus on its long-term effects.

RESULTS

A total of 1488 patients (mean age, 66.3 years; SD, 11.1; 98% ischemic stroke) were followed for a median of 2.68 years (25th-75th percentile: 1.21-4.14 years). After an initial period of improvement through up to 1-year poststroke, decline was seen in global cognition and all domains except executive function after adjusting for age, sex, education, vascular risk factors, and stroke characteristics (-0.053 SD/year [95% CI, -0.073 to -0.033]; P<0.001 for global cognition). Recurrent stroke and older age were associated with faster decline. Decline was significantly faster in patients with stroke compared with controls (difference=-0.078 SD/year [95% CI, -0.11 to -0.045]; P<0.001 for global cognition in a subgroup analysis).

CONCLUSIONS

Patients with stroke experience cognitive decline that is faster than that of stroke-free controls from 1 to 3 years after onset. An increased rate of decline is associated with older age and recurrent stroke.

Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort

BACKGROUND

physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives.

METHODS

We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD.

RESULTS

In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046).

CONCLUSIONS

metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.

Functional connectivity and cognitive changes after donepezil treatment in healthy participants

RATIONALE

Donepezil is a potent, noncompetitive, reversible, clinically effective acetylcholinesterase inhibitor. The effects of this drug on healthy brains have seldom been investigated.

OBJECTIVES

The primary objective of the present study was to identify possible functional connectivity markers of the effect of donepezil in healthy young adult volunteers.

METHODS

The study had a double-blind, randomized, crossover design. 30 healthy adult volunteers underwent resting-state MRI scans during 15 days of donepezil or placebo treatment, in accordance with the design.

RESULTS

Results showed significant differences in intrinsic functional connectivity between donepezil and placebo, mainly in the right executive control network (RECN). More specifically, we found a decrease in the connectivity of the right inferior parietal node with other RECN nodes. Analysis using the cingulate cortex and parahippocampal regions as seeds also revealed complex modulation of functional connectivity in the donepezil condition.

CONCLUSIONS

In conclusion, donepezil treatment for 15 days may result in reorganization of resting-state networks, compared with placebo.

Use of real-world evidence in translational pharmacology research

Real-world evidence (RWE) refers to observational data gathered outside the formalism of randomized controlled trials, in real life situations, on marketed drugs. While clinical trials are the gold standards to demonstrate the efficacy and tolerability of a medicinal product, the generalizability of their results to actual use in real-life is limited by the biases induced by the very nature of clinical trials; indeed, the patients included in the trials may differ from actual users because of their concomitant diseases or treatments, or other factors excluding them from the trials. Clinical researchers and pharmaceutical industries have hence become increasingly interested in expanding and integrating RWE into clinical research, by capitalizing on the exponential growth in access to data from electronic health records, claims databases, electronic devices, software or mobile applications, registries embedded in clinical practice and social media. Meanwhile, applications of RWE may also be used for drug discovery and repurposing, for clinical developments and post-marketing studies. The aim of this review is to provide our opinion regarding the use of RWE in translational research, including non-clinical and clinical pharmacology research, at the different step of drugs development use.

Biomarkers in the Prediction of Hemorrhagic Transformation in Acute Stroke: A Systematic Review and Meta-Analysis

BACKGROUND

Hemorrhagic transformation (HT) is a complication that occurs spontaneously or after thrombolysis in acute ischemic stroke (AIS) and can increase morbidity and mortality. The association of biomarkers with the risk of HT has been variably reported. We conducted a systematic review of the literature and meta-analysis and sought to compare blood biomarkers associated with HT and its subtypes by evaluating its predictability and correlation with outcome in AIS.

METHODS

The study protocol was registered in the PROSPERO database (CRD42020201334) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Among 2,230 articles identified from Cochrane Library, PubMed, and Web of Science databases, 30 quality-appraised articles were found eligible. Meta-analysis was conducted for matrix metalloproteinase-9 (MMP-9), cellular fibronectin (c-Fn), ferritin, S100 calcium-binding protein B (S100B), and neutrophil-lymphocyte ratio (NLR). We also reviewed biomarkers for correlation with the functional outcome at 90 days from stroke onset (poor outcome modified Rankin scale >2).

RESULTS

The pooled diagnostic odds ratio (DORpooled) was the highest for baseline c-Fn levels (299.253 [95% CI, 20.508-4,366.709]), followed by MMP-9 (DORpooled, 29.571 [95% CI 17.750-49.267]) and ferritin (DORpooled, 24.032 [95% CI 2.557-225.871]). However, wide confidence intervals for ferritin and c-Fn suggested lesser reliability of the markers. Patients with MMP-9 levels ≥140 ng/mL were 29.5 times at higher risk of developing symptomatic HT after AIS (area under the curve = 0.881). S100B (DORpooled, 6.286 [95% CI, 1.861-21.230]) and NLR (DORpooled, 5.036 [95% CI, 2.898-8.749]) had lower diagnostic accuracies. Among the markers not included for meta-analysis, caveolin-1, thrombin-activated fibrinolysis inhibitor, plasminogen activator inhibitor-1, and soluble ST2 were highly sensitive. Elevated levels of MMP-9, ferritin, and NLR were found to be associated with poor functional outcomes and mortality.

CONCLUSION

Of the 5 biomarkers, there was enough evidence that MMP-9 has higher diagnostic accuracy for predicting the risk of HT before thrombolysis. MMP-9, ferritin, and NLR also predicted poor short-term outcomes.

Beneficial effects of atorvastatin on sex-specific cognitive impairment induced by a cerebral microhaemorrhage in mice

BACKGROUND AND PURPOSES

Cerebral microhaemorrhages (CMHs) are associated with cognitive decline in humans. In rodents, CMHs induces cognitive impairment in male mice along with sex-specific cortical and hippocampal changes affecting neural, glial and vascular functions. Statins, have been proposed to prevent cognitive decline. We tested here the action of atorvastatin on CMH-induced cognitive impairment in a murine model of CMH.

EXPERIMENTAL APPROACH

Using a multimodal approach combining behavioural tests, in vivo imaging, biochemistry and molecular biology, the effects of oral administration of atorvastatin on the sex-specific changes induced by a cortical CMH were studied in male and female mice (C57BL/6J) at 6-week post-induction using a collagenase-induced model.

KEY RESULTS

Atorvastatin caused specific effects according to the sex-specific CMH-induced changes. In males, atorvastatin improved the visuospatial memory, induced a local modulation of microglial response and enhanced brain-derived neurotrophic factor (BDNF)-tropomyosin receptor kinase B (trkB) and vascular endothelial growth factor (VEGF) expression in the cortex. In the hippocampus, atorvastatin increased glucose metabolism and modulated astrocytes morphology. In females, atorvastatin did not modulate visuospatial memory despite the increased expression of cortical BDNF and the decrease in the number of hippocampal astrocytes. Atorvastatin also induced a decrease in the expression of cortical oestrogen receptors but did not modify body weight nor serum cholesterol levels in both sexes.

CONCLUSION AND IMPLICATIONS

Atorvastatin modulated the sex-specific cognitive impairment induced by the CMH with a pathophysiological impact mainly within the cortical area. It could represent a promising candidate for future sex-stratified clinical trials in patients with CMH.

Strategic infarct locations for post-stroke cognitive impairment: a pooled analysis of individual patient data from 12 acute ischaemic stroke cohorts

BACKGROUND

Post-stroke cognitive impairment (PSCI) occurs in approximately half of people in the first year after stroke. Infarct location is a potential determinant of PSCI, but a comprehensive map of strategic infarct locations predictive of PSCI is unavailable. We aimed to identify infarct locations most strongly predictive of PSCI after acute ischaemic stroke and use this information to develop a prediction model.

METHODS

In this large-scale multicohort lesion-symptom mapping study, we pooled and harmonised individual patient data from 12 cohorts through the Meta-analyses on Strategic Lesion Locations for Vascular Cognitive Impairment using Lesion-Symptom Mapping (Meta VCI Map) consortium. The identified cohorts (as of Jan 1, 2019) comprised patients with acute symptomatic infarcts on CT or MRI (with available infarct segmentations) and a cognitive assessment up to 15 months after acute ischaemic stroke onset. PSCI was defined as performance lower than the fifth percentile of local normative data, on at least one cognitive domain on a multidomain neuropsychological assessment or on the Montreal Cognitive Assessment. Voxel-based lesion-symptom mapping (VLSM) was used to calculate voxel-wise odds ratios (ORs) for PSCI that were mapped onto a three-dimensional brain template to visualise PSCI risk per location. For the prediction model of PSCI risk, a location impact score on a 5-point scale was derived from the VLSM results on the basis of the mean voxel-wise coefficient (ln[OR]) within each patient's infarct. We did combined internal-external validation by leave-one-cohort-out cross-validation for all 12 cohorts using logistic regression. Predictive performance of a univariable model with only the location impact score was compared with a multivariable model with addition of other clinical PSCI predictors (age, sex, education, time interval between stroke onset and cognitive assessment, history of stroke, and total infarct volume). Testing of visual ratings was done by three clinicians, and accuracy, inter-rater reliability, and intra-rater reliability were assessed with Cohen's weighted kappa.

FINDINGS

In our sample of 2950 patients (mean age 66·8 years [SD 11·6]; 1157 [39·2%] women), 1286 (43·6%) had PSCI. We achieved high lesion coverage of the brain in our analyses (86·9%). Infarcts in the left frontotemporal lobes, left thalamus, and right parietal lobe were strongly associated with PSCI (after false discovery rate correction, q<0·01; voxel-wise ORs >20). On cross-validation, the location impact score showed good correspondence, based on visual assessment of goodness of fit, between predicted and observed risk of PSCI across cohorts after adjusting for cohort-specific PSCI occurrence. Cross-validations showed that the location impact score by itself had similar performance to the combined model with other PSCI predictors, while allowing for easy visual assessment. Therefore the univariable model with only the location impact score was selected as the final model. Correspondence between visual ratings and actual location impact score (Cohen's weighted kappa: range 0·88-0·92), inter-rater agreement (0·85-0·87), and intra-rater agreement (for a single rater, 0·95) were all high.

INTERPRETATION

To the best of our knowledge, this study provides the first comprehensive map of strategic infarct locations associated with risk of PSCI. A location impact score was derived from this map that robustly predicted PSCI across cohorts. Furthermore, we developed a quick and reliable visual rating scale that might in the future be applied by clinicians to identify individual patients at risk of PSCI.

FUNDING

The Netherlands Organisation for Health Research and Development.

Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

BACKGROUND

Balancing the risks of recurrent ischaemic stroke and intracranial haemorrhage is important for patients treated with antithrombotic therapy after ischaemic stroke or transient ischaemic attack. However, existing predictive models offer insufficient performance, particularly for assessing the risk of intracranial haemorrhage. We aimed to develop new risk scores incorporating clinical variables and cerebral microbleeds, an MRI biomarker of intracranial haemorrhage and ischaemic stroke risk.

METHODS

We did a pooled analysis of individual-patient data from the Microbleeds International Collaborative Network (MICON), which includes 38 hospital-based prospective cohort studies from 18 countries. All studies recruited participants with previous ischaemic stroke or transient ischaemic attack, acquired baseline MRI allowing quantification of cerebral microbleeds, and followed-up participants for ischaemic stroke and intracranial haemorrhage. Participants not taking antithrombotic drugs were excluded. We developed Cox regression models to predict the 5-year risks of intracranial haemorrhage and ischaemic stroke, selecting candidate predictors on biological relevance and simplifying models using backward elimination. We derived integer risk scores for clinical use. We assessed model performance in internal validation, adjusted for optimism using bootstrapping. The study is registered on PROSPERO, CRD42016036602.

FINDINGS

The included studies recruited participants between Aug 28, 2001, and Feb 4, 2018. 15 766 participants had follow-up for intracranial haemorrhage, and 15 784 for ischaemic stroke. Over a median follow-up of 2 years, 184 intracranial haemorrhages and 1048 ischaemic strokes were reported. The risk models we developed included cerebral microbleed burden and simple clinical variables. Optimism-adjusted c indices were 0·73 (95% CI 0·69-0·77) with a calibration slope of 0·94 (0·81-1·06) for the intracranial haemorrhage model and 0·63 (0·62-0·65) with a calibration slope of 0·97 (0·87-1·07) for the ischaemic stroke model. There was good agreement between predicted and observed risk for both models.

INTERPRETATION

The MICON risk scores, incorporating clinical variables and cerebral microbleeds, offer predictive value for the long-term risks of intracranial haemorrhage and ischaemic stroke in patients prescribed antithrombotic therapy for secondary stroke prevention; external validation is warranted.

FUNDING

British Heart Foundation and Stroke Association.

Replication study of plasma proteins relating to Alzheimer's pathology

INTRODUCTION

This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis.

METHODS

Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively.

RESULTS

Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis.

DISCUSSION

Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.

Prediction of Long-term Cognitive Function After Minor Stroke Using Functional Connectivity

OBJECTIVE

To determine whether functional MRI connectivity can predict long-term cognitive function 36 months after minor stroke.

METHODS

Seventy-two participants with first-ever stroke were included at baseline and followed up for 36 months. A ridge regression machine learning algorithm was developed and used to predict cognitive scores 36 months poststroke on the basis of the functional networks measured using MRI at 6 months (referred to here as the poststroke cognitive impairment [PSCI] network). The prediction accuracy was evaluated in 4 domains (memory, attention/executive, language, and visuospatial functions) and compared with clinical data and other functional networks. The models' statistical significance was probed with permutation tests. The potential involvement of cortical atrophy was assessed 6 months poststroke. A second, independent dataset (n = 40) was used to validate the results and assess their generalizability.

RESULTS

Based on the PSCI network, a machine learning model was able to predict memory, attention, visuospatial functions, and language functions 36 months poststroke (r 2: 0.67, 0.73, 0.55, and 0.48, respectively). The PSCI-based model was at least as accurate as models based on other functional networks or clinical data. Specific patterns were demonstrated for the 4 cognitive domains, with involvement of the left superior frontal cortex for memory, attention, and visuospatial functions. The cortical thickness 6 months poststroke was not correlated with cognitive function 36 months poststroke. The independent validation dataset gave similar results.

CONCLUSIONS

A machine learning model based on the PSCI network can predict long-term cognitive outcome after stroke.

Validation in French of the Montreal Cognitive Assessment 5-Minute, a brief cognitive screening test for phone administration

BACKGROUND

The prevalence of cognitive impairment and dementia is high and steadily increasing. Early detection of cognitive decline is crucial since some interventions can reduce the risk of progression to dementia. However, there is a lack of manageable scales for assessing cognitive functions outside specialized consultations. Recently, the MoCA-5min, a short version of the Montreal Cognitive assessment (MoCA), phone-administered, was validated for screening for vascular cognitive impairment. The aim of the present study was to validate the MoCA-5min in French in diverse clinical populations.

METHODS

The Cantonese version of the MoCA-5min was adapted for French language. Healthy volunteers and patients with possible or established cognitive impairment (Alzheimer's disease or related disorders, Parkinson's disease, Huntington's disease, type-2 diabetes) participated in the study. The original MoCA and the MoCA-5min were administered, by phone, with a 30-day interval. Alternate forms were used to reduce learning effects.

RESULTS

The scores of the original MoCA and MoCA-5min correlated significantly (Spearman rho=0.751, P<0.0001, 95% confidence interval 0.657 to 0.819). Internal consistency was good (Cronbach alpha=0.795). The area under the ROC curve was 0.870 and the optimal cut-off value for separating patients with and without cognitive impairment with the MoCA-5min was≤27 with 87.32% sensitivity and 76.09% specificity. Interrater and test-retest reliability were adequate.

CONCLUSION

This study demonstrates that the French version of the MoCA-5min is a valid and reliable scale for detecting cognitive impairment in different clinical populations. It is administrable by phone and thus suitable for remote assessment as well as for large-scale screening and epidemiological studies.

Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study

Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was -0.22[IQR = 0.50] for LGA-SPM8, -0.12[0.57] for LGA-SPM12, -0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies.

Plasma Aβ42 as a Biomarker of Prodromal Alzheimer's Disease Progression in Patients with Amnestic Mild Cognitive Impairment: Evidence from the PharmaCog/E-ADNI Study

It is an open issue whether blood biomarkers serve to diagnose Alzheimer's disease (AD) or monitor its progression over time from prodromal stages. Here, we addressed this question starting from data of the European FP7 IMI-PharmaCog/E-ADNI longitudinal study in amnesic mild cognitive impairment (aMCI) patients including biological, clinical, neuropsychological (e.g., ADAS-Cog13), neuroimaging, and electroencephalographic measures. PharmaCog/E-ADNI patients were classified as "positive" (i.e., "prodromal AD" n = 76) or "negative" (n = 52) based on a diagnostic cut-off of Aβ42/P-tau in cerebrospinal fluid as well as APOE ε 4 genotype. Blood was sampled at baseline and at two follow-ups (12 and 18 months), when plasma amyloid peptide 42 and 40 (Aβ42, Aβ40) and apolipoprotein J (clusterin, CLU) were assessed. Linear Mixed Models found no significant differences in plasma molecules between the "positive" (i.e., prodromal AD) and "negative" groups at baseline. In contrast, plasma Aβ42 showed a greater reduction over time in the prodromal AD than the "negative" aMCI group (p = 0.048), while CLU and Aβ40 increased, but similarly in the two groups. Furthermore, plasma Aβ42 correlated with the ADAS-Cog13 score both in aMCI patients as a whole and the prodromal AD group alone. Finally, CLU correlated with the ADAS-Cog13 only in the whole aMCI group, and no association with ADAS-Cog13 was found for Aβ40. In conclusion, plasma Aβ42 showed disease progression-related features in aMCI patients with prodromal AD.

Early epileptic seizures in ischaemic stroke treated by mechanical thrombectomy: influence of rt-PA

BACKGROUND

The epileptogenicity of recombinant tissue-plasminogen activator (rt-PA) has been suggested, but seizures were not evaluated in randomised controlled trials.

OBJECTIVE

To evaluate whether rt-PA was associated with early seizures in a cohort of consecutive patients with cerebral ischaemia.

METHOD

We included consecutive adults with ischaemic stroke due to large-vessel occlusion from the North-of-France stroke network selected for a mechanical thrombectomy (MT). Patients without contraindication received i.v. rt-PA. We evaluated stroke severity with the National Institutes of Health Stroke Scale (NIHSS), and functional status with the modified Rankin scale (mRS), and recorded epileptic seizures occurring between the end of imaging and day 7. We performed statistics using propensity analyses.

RESULTS

We included 1638 patients (783 men, 47.8%; median age 71 years; median NIHSS score 16; 1007 treated by rt-PA, 61.5%), in whom 60 (3.7%) developed early epileptic seizures. After adjustment on propensity scores, early seizures were associated with infections [adjusted odds ratio (_adjOR) 2.86; 95% confidence interval (CI) 1.37-5.95] and delay between stroke recognition and end of MT (_adjOR 1.04 for 10 min more; 95% CI 1.01-1.08), but not with rt-PA (_adjOR 1.35; 95% CI 0.55-3.33). The propensity-matched analysis of 343 pairs of patients found no difference in the occurrence of early seizures between those with and without rt-PA (p = 0.386).

CONCLUSION

We found no significant association between rt-PA and early epileptic seizures. If rt-PA has the potential for epileptogenicity, the magnitude of the effect should be modest compared to its favourable effect on functional outcome.

Modular slowing of resting-state dynamic functional connectivity as a marker of cognitive dysfunction induced by sleep deprivation

Dynamic Functional Connectivity (dFC) in the resting state (rs) is considered as a correlate of cognitive processing. Describing dFC as a flow across morphing connectivity configurations, our notion of dFC speed quantifies the rate at which FC networks evolve in time. Here we probe the hypothesis that variations of rs dFC speed and cognitive performance are selectively interrelated within specific functional subnetworks. In particular, we focus on Sleep Deprivation (SD) as a reversible model of cognitive dysfunction. We found that whole-brain level (global) dFC speed significantly slows down after 24h of SD. However, the reduction in global dFC speed does not correlate with variations of cognitive performance in individual tasks, which are subtle and highly heterogeneous. On the contrary, we found strong correlations between performance variations in individual tasks -including Rapid Visual Processing (RVP, assessing sustained visual attention)- and dFC speed quantified at the level of functional sub-networks of interest. Providing a compromise between classic static FC (no time) and global dFC (no space), modular dFC speed analyses allow quantifying a different speed of dFC reconfiguration independently for sub-networks overseeing different tasks. Importantly, we found that RVP performance robustly correlates with the modular dFC speed of a characteristic frontoparietal module.

Factors Associated with Alzheimer's Disease: An Overview of Reviews

Alzheimer's disease (AD) is a frequent pathology, with a poor prognosis, for which no curative treatment is available in 2018. AD prevention is an important issue, and is an important research topic. In this manuscript, we have synthesized the literature reviews and meta-analyses relating to modifiable risk factors associated with AD. Smoking, diabetes, high blood pressure, obesity, hypercholesterolemia, physical inactivity, depression, head trauma, heart failure, bleeding and ischemic strokes, sleep apnea syndrome appeared to be associated with an increased risk of AD. In addition to these well-known associations, we highlight here the existence of associated factors less described: hyperhomocysteinemia, hearing loss, essential tremor, occupational exposure to magnetic fields. On the contrary, some oral antidiabetic drugs, education and intellectual activity, a Mediterranean-type diet or using Healthy Diet Indicator, consumption of unsaturated fatty acids seemed to have a protective effect. Better knowledge of risk factors for AD allows for better identification of patients at risk. This may contribute to the emergence of prevention policies to delay or prevent the onset of AD.