Testing the reciprocal relationship between depressive symptoms and insomnia.

BACKGROUND: Although the importance of sleep difficulties in emotional disorders has long been acknowledged, the nature of the potential reciprocal relationship between sleep and depressive symptoms is not yet well understood. The coronavirus disease 19 pandemic provided a unique opportunity to study the interrelation of these symptoms over a period marked by increases in sleep and psychological difficulties. METHODS: Using online data collection, we followed 1200 adults (59% male) through 1 year of the pandemic. Measures of sleep disturbance and depressive symptoms were assessed at eight time points. Factor analysis of the items from these two measures suggested separate insomnia and depressive symptom factors. A random intercept cross-lagged panel model was used to assess within-person relationships between factor analysis-informed subscales of insomnia and depressive symptoms. RESULTS: Depressive symptoms predicted subsequent changes in insomnia symptoms; however, insomnia did not predict changes in depressive symptoms. CONCLUSIONS: Our findings suggest the impact of depressive symptoms on insomnia is evident, but the reverse is not. Implications of this finding along with the need for research addressing depressive symptoms and insomnia as treatment targets are discussed.

Intense Arm Rehabilitation Therapy Improves the Modified Rankin Scale Score: Association Between Gains in Impairment and Function.

OBJECTIVE: To evaluate the effect of intensive rehabilitation on the modified Rankin Scale (mRS), a measure of activities limitation commonly used in acute stroke studies, and to define the specific changes in body structure/function (motor impairment) most related to mRS gains. METHODS: Patients were enrolled >90 days poststroke. Each was evaluated before and 30 days after a 6-week course of daily rehabilitation targeting the arm. Activity gains, measured using the mRS, were examined and compared to body structure/function gains, measured using the Fugl-Meyer (FM) motor scale. Additional analyses examined whether activity gains were more strongly related to specific body structure/function gains. RESULTS: At baseline (160 ± 48 days poststroke), patients (n = 77) had median mRS score of 3 (interquartile range, 2-3), decreasing to 2 [2-3] 30 days posttherapy (p < 0.0001). Similarly, the proportion of patients with mRS score ≤2 increased from 46.8% at baseline to 66.2% at 30 days posttherapy (p = 0.015). These findings were accounted for by the mRS score decreasing in 24 (31.2%) patients. Patients with a treatment-related mRS score improvement, compared to those without, had similar overall motor gains (change in total FM score, p = 0.63). In exploratory analysis, improvement in several specific motor impairments, such as finger flexion and wrist circumduction, was significantly associated with higher likelihood of mRS decrease. CONCLUSIONS: Intensive arm motor therapy is associated with improved mRS in a substantial fraction (31.2%) of patients. Exploratory analysis suggests specific motor impairments that might underlie this finding and may be optimal targets for rehabilitation therapies that aim to reduce activities limitations. CLINICAL TRIAL: Clinicaltrials.gov identifier: NCT02360488. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that for patients >90 days poststroke with persistent arm motor deficits, intensive arm motor therapy improved mRS in a substantial fraction (31.2%) of patients.

Social Network Structure Is Related to Functional Improvement From Home-Based Telerehabilitation After Stroke.

Objective: Telerehabilitation (TR) is now, in the context of COVID-19, more clinically relevant than ever as a major source of outpatient care. The social network of a patient is a critical yet understudied factor in the success of TR that may influence both engagement in therapy programs and post-stroke outcomes. We designed a 12-week home-based TR program for stroke patients and evaluated which social factors might be related to motor gains and reduced depressive symptoms. Methods: Stroke patients (n = 13) with arm motor deficits underwent supervised home-based TR for 12 weeks with routine assessments of motor function and mood. At the 6-week midpoint, we mapped each patient's personal social network and evaluated relationships between social network metrics and functional improvements from TR. Finally, we compared social networks of TR patients with a historical cohort of 176 stroke patients who did not receive any TR to identify social network differences. Results: Both network size and network density were related to walk time improvement (p = 0.025; p = 0.003). Social network density was related to arm motor gains (p = 0.003). Social network size was related to reduced depressive symptoms (p = 0.015). TR patient networks were larger (p = 0.012) and less dense (p = 0.046) than historical stroke control networks. Conclusions: Social network structure is positively related to improvement in motor status and mood from TR. TR patients had larger and more open social networks than stroke patients who did not receive TR. Understanding how social networks intersect with TR outcomes is crucial to maximize effects of virtual rehabilitation.

A Feasibility Study of Expanded Home-Based Telerehabilitation After Stroke.

Introduction: High doses of activity-based rehabilitation therapy improve outcomes after stroke, but many patients do not receive this for various reasons such as poor access, transportation difficulties, and low compliance. Home-based telerehabilitation (TR) can address these issues. The current study evaluated the feasibility of an expanded TR program. Methods: Under the supervision of a licensed therapist, adults with stroke and limb weakness received home-based TR (1 h/day, 6 days/week) delivered using games and exercises. New features examined include extending therapy to 12 weeks duration, treating both arm and leg motor deficits, patient assessments performed with no therapist supervision, adding sensors to real objects, ingesting a daily experimental (placebo) pill, and generating automated actionable reports. Results: Enrollees (n = 13) were median age 61 (IQR 52-65.5), and 129 (52-486) days post-stroke. Patients initiated therapy on 79.9% of assigned days and completed therapy on 65.7% of days; median therapy dose was 50.4 (33.3-56.7) h. Non-compliance doubled during weeks 7-12. Modified Rankin scores improved in 6/13 patients, 3 of whom were >3 months post-stroke. Fugl-Meyer motor scores increased by 6 (2.5-12.5) points in the arm and 1 (-0.5 to 5) point in the leg. Assessments spanning numerous dimensions of stroke outcomes were successfully implemented; some, including a weekly measure that documented a decline in fatigue (p = 0.004), were successfully scored without therapist supervision. Using data from an attached sensor, real objects could be used to drive game play. The experimental pill was taken on 90.9% of therapy days. Automatic actionable reports reliably notified study personnel when critical values were reached. Conclusions: Several new features performed well, and useful insights were obtained for those that did not. A home-based telehealth system supports a holistic approach to rehabilitation care, including intensive rehabilitation therapy, secondary stroke prevention, screening for complications of stroke, and daily ingestion of a pill. This feasibility study informs future efforts to expand stroke TR. Clinical Trial Registration: Clinicaltrials.gov, # NCT03460587.

Electroencephalography Measures are Useful for Identifying Large Acute Ischemic Stroke in the Emergency Department.

BACKGROUND: Early diagnosis of stroke optimizes reperfusion therapies, but behavioral measures have incomplete accuracy. Electroencephalogram (EEG) has high sensitivity for immediately detecting brain ischemia. This pilot study aimed to evaluate feasibility and utility of EEG for identifying patients with a large acute ischemic stroke during Emergency Department (ED) evaluation, as these data might be useful in the prehospital setting. METHODS: A 3-minute resting EEG was recorded using a dense-array (256-lead) system in patients with suspected acute stroke arriving at the ED of a US Comprehensive Stroke Center. RESULTS: An EEG was recorded in 24 subjects, 14 with acute cerebral ischemia (including 5 with large acute ischemic stroke) and 10 without acute cerebral ischemia. Median time from stroke onset to EEG was 6.6 hours; and from ED arrival to EEG, 1.9 hours. Delta band power (P = .004) and the alpha/delta frequency band ratio (P = .0006) each significantly distinguished patients with large acute ischemic stroke (n = 5) from all other patients with suspected stroke (n = 19), with the best diagnostic utility coming from contralesional hemisphere signals. Larger infarct volume correlated with higher EEG power in the alpha/delta frequency band ratio within both the ipsilesional (r = -0.64, P = .013) and the contralesional (r = -0.78, P = .001) hemispheres. CONCLUSIONS: Within hours of stroke onset, EEG measures (1) identify patients with large acute ischemic stroke and (2) correlate with infarct volume. These results suggest that EEG measures of brain function may be useful to improve diagnosis of large acute ischemic stroke in the ED, findings that might be useful to pre-hospital applications.

Efficacy of Home-Based Telerehabilitation vs In-Clinic Therapy for Adults After Stroke: A Randomized Clinical Trial.

IMPORTANCE: Many patients receive suboptimal rehabilitation therapy doses after stroke owing to limited access to therapists and difficulty with transportation, and their knowledge about stroke is often limited. Telehealth can potentially address these issues. OBJECTIVES: To determine whether treatment targeting arm movement delivered via a home-based telerehabilitation (TR) system has comparable efficacy with dose-matched, intensity-matched therapy delivered in a traditional in-clinic (IC) setting, and to examine whether this system has comparable efficacy for providing stroke education. DESIGN, SETTING, AND PARTICIPANTS: In this randomized, assessor-blinded, noninferiority trial across 11 US sites, 124 patients who had experienced stroke 4 to 36 weeks prior and had arm motor deficits (Fugl-Meyer [FM] score, 22-56 of 66) were enrolled between September 18, 2015, and December 28, 2017, to receive telerehabilitation therapy in the home (TR group) or therapy at an outpatient rehabilitation therapy clinic (IC group). Primary efficacy analysis used the intent-to-treat population. INTERVENTIONS: Participants received 36 sessions (70 minutes each) of arm motor therapy plus stroke education, with therapy intensity, duration, and frequency matched across groups. MAIN OUTCOMES AND MEASURES: Change in FM score from baseline to 4 weeks after end of therapy and change in stroke knowledge from baseline to end of therapy. RESULTS: A total of 124 participants (34 women and 90 men) had a mean (SD) age of 61 (14) years, a mean (SD) baseline FM score of 43 (8) points, and were enrolled a mean (SD) of 18.7 (8.9) weeks after experiencing a stroke. Among those treated, patients in the IC group were adherent to 33.6 of the 36 therapy sessions (93.3%) and patients in the TR group were adherent to 35.4 of the 36 assigned therapy sessions (98.3%). Patients in the IC group had a mean (SD) FM score change of 8.36 (7.04) points from baseline to 30 days after therapy (P < .001), while those in the TR group had a mean (SD) change of 7.86 (6.68) points (P < .001). The covariate-adjusted mean FM score change was 0.06 (95% CI, -2.14 to 2.26) points higher in the TR group (P = .96). The noninferiority margin was 2.47 and fell outside the 95% CI, indicating that TR is not inferior to IC therapy. Motor gains remained significant when patients enrolled early (<90 days) or late (≥90 days) after stroke were examined separately. CONCLUSIONS AND RELEVANCE: Activity-based training produced substantial gains in arm motor function regardless of whether it was provided via home-based telerehabilitation or traditional in-clinic rehabilitation. The findings of this study suggest that telerehabilitation has the potential to substantially increase access to rehabilitation therapy on a large scale. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02360488.

Predicting Gains With Visuospatial Training After Stroke Using an EEG Measure of Frontoparietal Circuit Function.

The heterogeneity of stroke prompts the need for predictors of individual treatment response to rehabilitation therapies. We previously studied healthy subjects with EEG and identified a frontoparietal circuit in which activity predicted training-related gains in visuomotor tracking. Here we asked whether activity in this same frontoparietal circuit also predicts training-related gains in visuomotor tracking in patients with chronic hemiparetic stroke. Subjects (n = 12) underwent dense-array EEG recording at rest, then received 8 sessions of visuomotor tracking training delivered via home-based telehealth methods. Subjects showed significant training-related gains in the primary behavioral endpoint, Success Rate score on a standardized test of visuomotor tracking, increasing an average of 24.2 ± 21.9% (p = 0.003). Activity in the circuit of interest, measured as coherence (20-30 Hz) between leads overlying ipsilesional frontal (motor cortex) and parietal lobe, significantly predicted training-related gains in visuomotor tracking change, measured as change in Success Rate score (r = 0.61, p = 0.037), supporting the main study hypothesis. Results were specific to the hypothesized ipsilesional motor-parietal circuit, as coherence within other circuits did not predict training-related gains. Analyses were repeated after removing the four subjects with injury to motor or parietal areas; this increased the strength of the association between activity in the circuit of interest and training-related gains. The current study found that (1) Eight sessions of training can significantly improve performance on a visuomotor task in patients with chronic stroke, (2) this improvement can be realized using home-based telehealth methods, (3) an EEG-based measure of frontoparietal circuit function predicts training-related behavioral gains arising from that circuit, as hypothesized and with specificity, and (4) incorporating measures of both neural function and neural injury improves prediction of stroke rehabilitation therapy effects.

A Home-Based Telerehabilitation Program for Patients With Stroke.

BACKGROUND: Although rehabilitation therapy is commonly provided after stroke, many patients do not derive maximal benefit because of access, cost, and compliance. A telerehabilitation-based program may overcome these barriers. We designed, then evaluated a home-based telerehabilitation system in patients with chronic hemiparetic stroke. METHODS: Patients were 3 to 24 months poststroke with stable arm motor deficits. Each received 28 days of telerehabilitation using a system delivered to their home. Each day consisted of 1 structured hour focused on individualized exercises and games, stroke education, and an hour of free play. RESULTS: Enrollees (n = 12) had baseline Fugl-Meyer (FM) scores of 39 ± 12 (mean ± SD). Compliance was excellent: participants engaged in therapy on 329/336 (97.9%) assigned days. Arm repetitions across the 28 days averaged 24,607 ± 9934 per participant. Arm motor status showed significant gains (FM change 4.8 ± 3.8 points, P = .0015), with half of the participants exceeding the minimal clinically important difference. Although scores on tests of computer literacy declined with age ( r = -0.92; P < .0001), neither the motor gains nor the amount of system use varied with computer literacy. Daily stroke education via the telerehabilitation system was associated with a 39% increase in stroke prevention knowledge ( P = .0007). Depression scores obtained in person correlated with scores obtained via the telerehabilitation system 16 days later ( r = 0.88; P = .0001). In-person blood pressure values closely matched those obtained via this system ( r = 0.99; P < .0001). CONCLUSIONS: This home-based system was effective in providing telerehabilitation, education, and secondary stroke prevention to participants. Use of a computer-based interface offers many opportunities to monitor and improve the health of patients after stroke.

Connectivity measures are robust biomarkers of cortical function and plasticity after stroke.

Valid biomarkers of motor system function after stroke could improve clinical decision-making. Electroencephalography-based measures are safe, inexpensive, and accessible in complex medical settings and so are attractive candidates. This study examined specific electroencephalography cortical connectivity measures as biomarkers by assessing their relationship with motor deficits across 28 days of intensive therapy. Resting-state connectivity measures were acquired four times using dense array (256 leads) electroencephalography in 12 hemiparetic patients (7.3 ± 4.0 months post-stroke, age 26-75 years, six male/six female) across 28 days of intensive therapy targeting arm motor deficits. Structural magnetic resonance imaging measured corticospinal tract injury and infarct volume. At baseline, connectivity with leads overlying ipsilesional primary motor cortex (M1) was a robust and specific marker of motor status, accounting for 78% of variance in impairment; ipsilesional M1 connectivity with leads overlying ipsilesional frontal-premotor (PM) regions accounted for most of this (R(2) = 0.51) and remained significant after controlling for injury. Baseline impairment also correlated with corticospinal tract injury (R(2) = 0.52), though not infarct volume. A model that combined a functional measure of connectivity with a structural measure of injury (corticospinal tract injury) performed better than either measure alone (R(2) = 0.93). Across the 28 days of therapy, change in connectivity with ipsilesional M1 was a good biomarker of motor gains (R(2) = 0.61). Ipsilesional M1-PM connectivity increased in parallel with motor gains, with greater gains associated with larger increases in ipsilesional M1-PM connectivity (R(2) = 0.34); greater gains were also associated with larger decreases in M1-parietal connectivity (R(2) = 0.36). In sum, electroencephalography measures of motor cortical connectivity-particularly between ipsilesional M1 and ipsilesional premotor-are strongly related to motor deficits and their improvement with therapy after stroke and so may be useful biomarkers of cortical function and plasticity. Such measures might provide a biological approach to distinguishing patient subgroups after stroke.