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Background: Clinical and neuroimaging measures incompletely explain behavioral deficits in the acute stroke setting. We hypothesized that electroencephalography (EEG)-based measures of neural function would significantly improve prediction of acute stroke deficits. Methods: Patients with acute stroke (n=50) seen in the emergency department of a university hospital from 2017 to 2018 underwent standard evaluation followed by a 3-minute recording of EEG at rest using a wireless, 17-electrode, dry-lead system. Artifacts in EEG recordings were removed offline and then spectral power was calculated for each lead pair. A primary EEG metric was DTABR, which is calculated as a ratio of spectral power: [(Delta*Theta)/(Alpha*Beta)]. Bivariate analyses and least absolute shrinkage and selection operator (LASSO) regression identified clinical and neuroimaging measures that best predicted initial National Institutes of Health Stroke Scale (NIHSS) score. Multivariable linear regression was then performed before versus after adding EEG findings to these measures, using initial NIHSS score as the dependent measure. Results: Age, diabetes status, and infarct volume were the best predictors of initial NIHSS score in bivariate analyses, confirmed using LASSO regression. Combined in a multivariate model, these 3 explained initial NIHSS score (adjusted r 2 =0.47). Adding any of several different EEG measures to this clinical model significantly improved prediction; the greatest amount of additional variance was explained by adding contralesional DTABR (adjusted r 2 =0.60, P Conclusions: EEG measures of neural function significantly add to clinical and neuroimaging for explaining initial NIHSS score in the acute stroke emergency department setting. A dry-lead EEG system can be rapidly and easily implemented. EEG contains information that may be useful early after stroke.

Background and Purpose: Clinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility of electroencephalography for acute stroke/transient ischemic attack (TIA) and for LVO. Methods: Patients (n=100) with suspected acute stroke in an emergency department underwent clinical exam then electroencephalography using a dry-electrode system. Four models classified patients, first as acute stroke/TIA or not, then as acute stroke with LVO or not: (1) clinical data, (2) electroencephalography data, (3) clinical+electroencephalography data using logistic regression, and (4) clinical+electroencephalography data using a deep learning neural network. Each model used a training set of 60 randomly selected patients, then was validated in an independent cohort of 40 new patients. Results: Of 100 patients, 63 had a stroke (43 ischemic/7 hemorrhagic) or TIA (13). For classifying patients as stroke/TIA or not, the clinical data model had area under the curve=62.3, whereas clinical+electroencephalography using deep learning neural network model had area under the curve=87.8. Results were comparable for classifying patients as stroke with LVO or not. Conclusions: Adding electroencephalography data to clinical measures improves diagnosis of acute stroke/TIA and of acute stroke with LVO. Rapid acquisition of dry-lead electroencephalography is feasible in the emergency department and merits prehospital evaluation.

Introduction: High doses of activity-based rehabilitation therapy help but many patients do not receive this, e.g., due to access, cost, and low compliance. Home-based telerehabilitation (TR) can address these issues. A prior study found 6 weeks of TR targeting arm motor deficits after stroke comparably efficacious vs. therapy delivered in-clinic. Here, we evaluated a program expanded in TR dose and scope. Methods: Adults with stroke and arm motor deficits saw a licensed OT/PT who performed a live exam then supervised home-based TR (6 days/week, 1 hour/day) through games, exercises, and education. New features examined herein included (a) extending therapy to 12 weeks, (b) treating both arm and leg motor deficits, (c) augmented reality games, (d) wireless smart devices, (e) ingesting a daily experimental (placebo) pill, (f) using functional objects, (g) evaluating social networks, and (h) automated actionable reports. Results: Patients (n=13) were median age 61 [IQR=52-65.5], and 129 [52-486] days post-stroke. Patients initiated therapy on 79.9% of the 72 assigned days and completed >30 min on 65.7% of days, for a 12-week total therapy dose of 50.4 [33.3 - 56.7] hours. Non-compliant days during weeks 7-12 were double those of weeks 1-6. Modified Rankin scores improved by 1 level in 6/13 patients, 3 of whom were > 3month post-stroke. Fugl-Meyer motor scores increased by 6 [2.5-12.5] points in the arm and 1 [-0.5 - 5] point in the leg, mainly in weeks 1-6. Geriatric Depression Scale scores fell from 3 [1-5] at baseline (3/13 with depression) to 1 [0-4] (0/13 with depression) at week 12. Augmented reality gaming and functional objects were well received. Communication with smart devices was challenging. The experimental pill was taken, with photo verification, on 90.9% of days. Enrollees had large social networks. Automatic reports reliably notified study personnel when compliance was low or behavioral scores were concerning. Conclusions: High doses of home-based TR targeting arm and leg motor deficits are feasible and improve functional outcomes, motor deficits, and mood. The current system automates experimental pill ingestion and actionable reports to clinicians. Compliance declined over time, suggesting the need for novel approaches to extended periods of TR.

Background: Improvements are needed in prehospital diagnosis of stroke. The electroencephalogram (EEG) changes immediately after brain ischemia, and advances in EEG technology enable rapid acquisition in the acute care setting. We hypothesized that EEG data increase the accuracy with which patients are correctly classified as having acute stroke or not, and so performed a study in the Emergency Department (ED) as an initial step towards evaluating prehospital utility of EEG. Methods: Patients with suspected stroke in a comprehensive stroke center ED underwent a 3 min EEG using a wireless, dry-electrode system; data were analyzed offline. A model was developed to classify patients as stroke/TIA vs non-stroke using a training set of 60 randomly selected patients. The model was then tested in an independent validation cohort of 40 new patients. EEG variables were selected using Lasso regression. Four models were examined, the first three using logistic regression: [1] clinical data only; [2] EEG data only; [3] combined clinical and EEG data; [4] a deep learning neural network model using clinical and EEG data. Results: Of the 100 ED patients (mean age 64.5 ± 15.7), 63 were ultimately discharged with a diagnosis of stroke (43 ischemic, 7 hemorrhagic) or TIA (13). Median time from last known well (LKW) to EEG was 9.4 hours; from ED arrival to EEG, 3.7 hours. Median time to prepare/place EEG leads then initiate recording was 9 min, shortened during the study (p Conclusions: The data support the feasibility of using a dry lead EEG system to rapidly acquire EEG in the acute stroke ED setting and suggest utility to improve prehospital stroke diagnosis once acquisition and analysis approaches are appropriately streamlined. EEG captures a signal that is diagnostically useful, independent from clinical measures, and improves the precision with which acute stroke can be diagnosed.

Background Transcranial direct current stimulation (tDCS) has become an important non-invasive brain stimulation tool for basic human brain physiology and cognitive neuroscience, with potential applications in cognitive and motor rehabilitation. To date, tDCS studies have employed a fixed stimulation level, without considering the impact of individual anatomy and physiology on the efficacy of the stimulation. This approach contrasts with the standard procedure for transcranial magnetic stimulation (TMS) where stimulation levels are usually tailored on an individual basis. Objective/Hypothesis The present study tests whether the efficacy of tDCS-induced changes in corticospinal excitability varies as a function of individual differences in sensitivity to TMS. Methods We performed an archival review to examine the relationship between the TMS intensity required to induce 1 mV motor-evoked potentials (MEPs) and the efficacy of (fixed-intensity) tDCS over the primary motor cortex (M1). For the latter, we examined tDCS-induced changes in corticospinal excitability, operationalized by comparing MEPs before and after anodal or cathodal tDCS. For comparison, we performed a similar analysis on data sets in which MEPs had been obtained before and after paired associative stimulation (PAS), a non-invasive brain stimulation technique in which the stimulation intensity is adjusted on an individual basis. Results MEPs were enhanced following anodal tDCS. This effect was larger in participants more sensitive to TMS as compared to those less sensitive to TMS, with sensitivity defined as the TMS intensity required to produce MEPs amplitudes of the size of 1 mV. While MEPs were attenuated following cathodal tDCS, the magnitude of this attenuation was not related to TMS sensitivity nor was there a relationship between TMS sensitivity and responsiveness to PAS. Conclusion Accounting for variation in individual sensitivity to non-invasive brain stimulation may enhance the utility of tDCS as a tool for understanding brain–behavior interactions and as a method for clinical interventions.

Background Transcranial direct current stimulation (tDCS) can enhance cognitive function in healthy individuals, with promising applications as a therapeutic intervention. Despite this potential, variability in the efficacy of tDCS has been a considerable concern. Objective /Hypothesis: Given that tDCS is always applied at a set intensity, we examined whether individual differences in sensitivity to brain stimulation might be one variable that modulates the efficacy of tDCS in a motor learning task. Methods In the first part of the experiment, single-pulse transcranial magnetic stimulation (TMS) over primary motor cortex (M1) was used to determine each participant's resting motor threshold (rMT). This measure was used as a proxy of individual sensitivity to brain stimulation. In an experimental group of 28 participants, 2 mA tDCS was then applied during a motor learning task with the anodal electrode positioned over left M1. Another 14 participants received sham stimulation. Results M1-Anodal tDCS facilitated learning relative to participants who received sham stimulation. Of primary interest was a within-group analysis of the experimental group, showing that the rate of learning was positively correlated with rMT: Participants who were more sensitive to brain stimulation as operationalized by our TMS proxy (low rMT), showed faster adaptation. Conclusions Methodologically, the results indicate that TMS sensitivity can predict tDCS efficacy in a behavioral task, providing insight into one source of variability that may contribute to replication problems with tDCS. Theoretically, the results provide further evidence of a role of sensorimotor cortex in adaptation, with the boost from tDCS observed during acquisition.

In a large community-randomized trial, biannual azithromycin distributions significantly reduced postneonatal childhood mortality in sub-Saharan African sites. Here, we present a prespecified secondary analysis showing that much of the protective effect was in the first 3 months postdistribution. Distributing more frequently than biannually could be considered if logistically feasible. Clinical Trials Registration. NCT02047981.

Background Antibiotic exposure can alter the gut microbiome. We evaluate the effects of azithromycin on the gut microbiome diversity of children from an antibiotic-naive community in Niger. Methods A population-based sample of 80 children aged 1-60 months in the Dosso region of Niger was randomized to receive a single dose of either oral azithromycin or placebo. Fecal samples were collected immediately before treatment and 5 days after treatment for 16S rRNA gene sequencing. The prespecified outcome was α-diversity (inverse Simpson's α-diversity index), with secondary outcomes of β and γ Simpson's and Shannon's diversities. Results At 5 days after treatment, 40 children aged 1-60 months were analyzed in the azithromycin-treated group and 40 children in the placebo-treated group. Diversity of the gut microbiome was significantly lower in the treated group (inverse Simpson's α-diversity, 5.03; 95% confidence interval [CI], 4.08-6.14) than in the placebo group (6.91; 95% CI, 5.82-8.21; P = .03). Similarly, the Shannon's α-diversity was lower in the treated group (10.60; 95% CI, 8.82-12.36) than the placebo group (15.42; 95% CI, 13.24-17.80; P = .004). Simpson's community-level (γ) diversity decreased with azithromycin exposure from 17.72 (95% CI, 13.80-20.21) to 10.10 (95% CI, 7.80-11.40; P = .00008), although β-diversity was not significantly reduced (2.56, 95% CI, 1.88-3.12; to 2.01, 95% CI, 1.46-2.51; P = .26). Conclusions Oral administration of azithromycin definitively decreases the diversity of the gut microbiome of children in an antibiotic-naive community. Clinical Trials Registration NCT02048007.

Closure of medium-to-large-size defects of the scalp are often associated with unacceptable aesthetic results, wound break down, alopecia, and excessive scarring. The authors present 2 cases of double-opposing unilobar rotation flaps for the reconstruction of large, that is, at least 7 cm diameter, full thickness defects of the scalp. Unlike previously described double flap closures of scalp defects, the double-opposing unilobar rotation flap design are true rotation flaps, which require a Burow triangle excisions and which have a versatility in both width and length of design to accommodate closure of large defects of the scalp. Some of the advantages of this technique are the retention of hair-bearing skin without distortion of the follicle position, an aesthetically pleasing scar, minimal tension at the wound closure site, and the versatility as well as simplicity of the technique.

In this study, we examined the dynamics of inhibitory preparatory processes, using a delayed response task in which a cue signaled a left or right index finger (Experiment 1) or hand (Experiment 2) movement in advance of an imperative signal. In Experiment 1, we varied the duration of the delay period (200, 500, and 900 ms). When transcranial magnetic stimulation (TMS) was applied 100 ms before the imperative, motor evoked potentials (MEPs) elicited in the first dorsal interosseous were strongly inhibited. For delays of 500 ms or longer, this inhibition was greater when the targeted muscle was selected compared with when it was not selected. In contrast, the magnitude of inhibition just after the cue was inversely related to the duration of the delay period, and the difference between the selected and nonselected conditions was attenuated. In Experiment 2, TMS and peripheral nerve stimulation procedures were used during a 300-ms delay period. MEPs in the flexor carpi radialis for both selected and nonselected conditions were inhibited, but without any change in the H-reflex. Taken together, these results reveal the dual influence of temporal constraints associated with anticipation and urgency on inhibitory processes recruited during response preparation.