Seizures are common in dementia and associated with accelerated cognitive decline. However, the impact of active vs remote seizures on cognition remains understudied. This study aimed to investigate the impact of active vs remote seizures on cognition in people with normal cognition and mild cognitive impairment (MCI). This longitudinal, multicenter cohort is based on National Alzheimer's Coordinating Center data of participants recruited from 39 Alzheimer's Disease Centers in the United States from September 2005 to December 2021. All participants with normal cognition and MCI and at least 2 visits were included. Primary outcome, that is, cognitive decline, was determined using Clinical Dementia Rating (CDR) from (1) normal-to-impaired (CDR ≥0.5) and (2) MCI-to-dementia (CDR ≥1) groups. The effect of active seizures (over the preceding 12 months), remote seizures (previous seizures but none over the preceding 12 months), and no seizures (controls) on cognition was assessed. Subgroups of chronic seizures at enrollment and new-onset seizures were further analyzed. Cox regression models assessed the risk of all-cause MCI and/or dementia. All models were adjusted for age, sex, education, race, hypertension, and diabetes. Of the 13,726 participants with normal cognition at enrollment (9,002 [66%] female; median age 71 years), 118 had active seizures and 226 had remote seizures. Of the 11,372 participants with MCI at enrollment (5,605 [49%] female; median age 73 years), 197 had active seizures and 226 had remote seizures. Active seizures were associated with 2.1 times higher risk of cognitive impairment (adjusted hazard ratio [aHR] 2.13, 95% CI 1.60-2.84, p < 0.001) in cognitively healthy adults (median years to decline: active seizures = ∼1, remote seizures = ∼3, no seizures = ∼3) and 1.6 times higher risk of dementia (aHR 1.58, 95% CI 1.24-2.01, p < 0.001) in those with MCI (median years to decline: active seizures = ∼1, remote seizures = ∼2, controls = ∼2). This risk was not observed with remote seizures. In this study, active seizures but not remote seizures were associated with earlier cognitive decline in both cognitively normal adults and those with MCI, independent of other dementia risk factors. Therefore, early identification and management of seizures may present a path to mitigation of cognitive decline in the aging epileptic population. A limitation is that causality cannot be confirmed in our observational longitudinal study.

Background and Purpose—: Clinical trials in spontaneous intracerebral hemorrhage (ICH) have used volume cutoffs as inclusion criteria to select populations in which the effects of interventions are likely to be the greatest. However, optimal volume cutoffs for predicting poor outcome in deep locations (thalamus versus basal ganglia) are unknown. Methods—: We conducted a 2-phase study to determine ICH volume cutoffs for poor outcome (modified Rankin Scale score of 4–6) in the thalamus and basal ganglia. Cutoffs with optimal sensitivity and specificity for poor outcome were identified in the ERICH ([Ethnic/Racial Variations of ICH] study; derivation cohort) using receiver operating characteristic curves. The cutoffs were then validated in the ATACH-2 trial (Antihypertensive Treatment of Acute Cerebral Hemorrhage-2) by comparing the c-statistic of regression models for outcome (including dichotomized volume) in the validation cohort. Results—: Of the 3000 patients enrolled in ERICH, 1564 (52%) had deep ICH, of whom 1305 (84%) had complete neuroimaging and outcome data (660 thalamic and 645 basal ganglia hemorrhages). Receiver operating characteristic curve analysis identified 8 mL in thalamic (area under the curve, 0.79; sensitivity, 73%; specificity, 78%) and 18 mL in basal ganglia ICH (area under the curve, 0.79; sensitivity, 70%; specificity, 83%) as optimal cutoffs for predicting poor outcome. The validation cohort included 834 (84%) patients with deep ICH and complete neuroimaging data enrolled in ATACH-2 (353 thalamic and 431 basal ganglia hemorrhages). In thalamic ICH, the c-statistic of the multivariable outcome model including dichotomized ICH volume was 0.80 (95% CI, 0.75–0.85) in the validation cohort. For basal ganglia ICH, the c-statistic was 0.81 (95% CI, 0.76–0.85) in the validation cohort. Conclusions—: Optimal hematoma volume cutoffs for predicting poor outcome in deep ICH vary by the specific deep brain nucleus involved. Utilization of location-specific volume cutoffs may improve clinical trial design by targeting deep ICH patients that will obtain maximal benefit from candidate therapies.

Objective: Facial weakness is a common sign of neurological diseases such as Bell's palsy and stroke. However, recognizing facial weakness still remains as a challenge, because it requires experience and neurological training. Methods: We propose a framework for facial weakness detection, which models the temporal dynamics of both shape and appearance-based features of each target frame through a bi-directional long short-term memory network (Bi-LSTM). The system is evaluated on a “in-the-wild”video dataset that is verified by three board-certified neurologists. In addition, three emergency medical services (EMS) personnel and three upper level residents rated the dataset. We compare the evaluation of the proposed algorithm with other comparison methods as well as the human raters. Results: Experimental evaluation demonstrates that: (1) the proposed algorithm achieves the accuracy, sensitivity, and specificity of 94.3%, 91.4%, and 95.7%, which outperforms other comparison methods and achieves the equal performance to paramedics; (2) the framework can provide visualizable and interpretable results that increases model transparency and interpretability; (3) a prototype is implemented as a proof-of-concept showcase to show the feasibility of an inexpensive solution for facial weakness detection. Conclusion: The experiment results suggest that the proposed framework can identify facial weakness effectively. Significance: We provide a proof-of-concept study, showing that such technology could be used by non-neurologists to more readily identify facial weakness in the field, leading to increasing coverage and earlier treatment.

BACKGROUND: Genetic association studies can reveal biology and treatment targets but have received limited attention for stroke recovery. STRONG (Stroke, Stress, Rehabilitation, and Genetics) was a prospective, longitudinal (1-year), genetic study in adults with stroke at 28 US stroke centers. The primary aim was to examine the association that candidate genetic variants have with (1) motor/functional outcomes and (2) stress-related outcomes. METHODS: For motor/functional end points, 3 candidate gene variants (ApoE ε4, BDNF [brain-derived neurotrophic factor], and a dopamine polygenic score) were analyzed for associations with change in grip strength (3 months-baseline), function (3-month Stroke Impact Scale-Activities of Daily Living), mood (3-month Patient Health Questionnaire-8), and cognition (12-month telephone-Montreal Cognitive Assessment). For stress-related outcomes, 7 variants (serotonin transporter gene–linked promoter region, ACE [angiotensin-converting enzyme], oxytocin receptor, FKBP5 [FKBP prolyl isomerase 5], FAAH [fatty acid amide hydrolase], BDNF, and COMT [catechol-O-methyltransferase]) were assessed for associations with posttraumatic stress disorder ([PTSD]; PTSD Primary Care Scale) and depression (Patient Health Questionnaire-8) at 6 and 12 months; stress-related genes were examined as a function of poststroke stress level. Statistical models (linear, negative binomial, or Poisson regression) were based on response variable distribution; all included stroke severity, age, sex, and ancestry as covariates. Stroke subtype was explored secondarily. Data were Holm-Bonferroni corrected. A secondary replication analysis tested whether the rs1842681 polymorphism (identified in the GISCOME study [Genetics of Ischaemic Stroke Functional Outcome]) was related to 3-month modified Rankin Scale score in STRONG. RESULTS: The 763 enrollees were 63.1±14.9 (mean±SD) years of age, with a median initial National Institutes of Health Stroke Scale score of 4 (interquartile range, 2–9); outcome data were available in n=515 at 3 months, n=500 at 6 months, and n=489 at 12 months. At 1 year poststroke, the rs6265 (BDNF) variant was associated with poorer cognition (0.9-point lower telephone-Montreal Cognitive Assessment score, P =1×10 ⁻⁵ ). For stress-related outcomes, rs4291 (ACE) and rs324420 (FAAH) were risk factors linking increased poststroke stress with higher 1-year depression and PTSD symptoms ( P <0.05), while rs4680 (COMT) linked poststroke stress with lower 1-year depression and PTSD. Findings were unchanged when considering stroke subtype. STRONG replicated GISCOME: rs1842681 was associated with lower 3-month modified Rankin Scale score ( P =3.2×10 ⁻⁵ ). CONCLUSIONS: This study identified genetic associations with cognitive function, depression, and PTSD 1 year poststroke. Genetic susceptibility to PTSD and depressive symptoms varied according to the amount of poststroke stress, underscoring the critical role of lived experiences in recovery. Together, the results suggest that genetic association studies provide insights into the biology of stroke recovery in humans.

Automated eye-tracking technology could enhance diagnosis for many neurological diseases, including stroke. Current literature focuses on gaze estimation through a form of calibration. However, patients with neuro-ocular abnormalities may have difficulty completing a calibration procedure due to inattention or other neurological deficits. Objective: We investigated 1) the need for calibration to measure eye movement symmetry in healthy controls and 2) the potential of eye movement symmetry to distinguish between healthy controls and patients. Methods: We analyzed fixations, smooth pursuits, saccades, and conjugacy measured by a Spearman correlation coefficient and utilized a linear mixed-effects model to estimate the effect of calibration. Results: Healthy participants (n = 18) did not differ in correlations between calibrated and non-calibrated conditions for all tests. The calibration condition did not improve the linear mixed effects model (log-likelihood ratio test p = 0.426) in predicting correlation coefficients. Interestingly, the patient group (n = 17) differed in correlations for the DOT (0.844 [95% CI 0.602, 0.920] vs. 0.98 [95% CI 0.976, 0.985]), H (0.903 [95% CI 0.746, 0.958] vs. 0.979 [95% CI 0.971, 0.986]), and OKN (0.898 [95% CI 0.785, 0.958] vs. 0.993 [95% CI 0.987, 0.996]) tests compared to healthy controls along the x-axis. These differences were not observed along the y-axis. Significance: This study suggests that automated eye tracking can be deployed without calibration to measure eye movement symmetry. It may be a good discriminator between normal and abnormal eye movement symmetry. Validation of these findings in larger populations is required.

Stroke genetic research has made substantial progress in the past decade. Its recovery application, however, remains behind, in part due to its reliance on the modified Rankin Scale (mRS) score as a measure of poststroke outcome. The mRS does not map well to biological processes because numerous psychosocial factors drive much of what the mRS captures. Second, the mRS contains multiple disparate biological events into a single measure further limiting its use for biological discovery. This led us to investigate the effect of distinct stroke recovery phenotypes on genetic variation associations with Genome-Wide Association Studies (GWASs) by repurposing the NIH Stroke Scale (NIHSS) and its subscores. In the Vitamin Intervention for Stroke Prevention cohort, we estimated changes in cognition, motor, and global impairments over 2 years using specific measures. We included genotyped participants with a total NIHSS score greater than zero at randomization and excluded those with recurrent stroke during the trial. A GWAS linear mixed-effects model predicted score changes, with participant as a random effect, and included initial score, age, sex, treatment group, and the first 5 ancestry principal components. In total, 1,270 participants (64% male) were included with a median NIHSS score of 2 (interquartile range [IQR] 1-3) and median age 68 (IQR 59-75) years. At randomization, 20% had cognitive deficits (NIHSS Cog-4 score >0) and 70% had ≥1 motor deficits (impairment score >1). At 2 years, these percentages improved to 7.2% with cognitive deficits and 30% with motor deficits. GWAS identified novel suggestive gene-impairment associations (p < 5e^-6) for cognition (CAMK2D, EVX2, LINC0143, PTPRM, SGMS1, and SMAD2), motor (ACBD6, KDM4B, MARK4, PTPRS, ROBO1, and ROBO2), and global (MSR1 and ROBO2) impairments. Defining domain-specific stroke recovery phenotypes and using longitudinal clinical trial designs can help detect novel genes associated with chronic recovery. These data support the use of granular endpoints to identify genetic associations related to stroke recovery.