Priorities and Outcomes for Youth-Adult Transitions in Hospital Care: Perspectives of Inpatient Clinical Leaders at US Children’s Hospitals

ObjectivesAdults with chronic conditions originating in childhood experience ongoing hospitalizations; however, efforts to guide youth-adult transitions rarely address transitioning to adult-oriented inpatient care. Our objectives were to identify perceptions of clinical leaders on important and feasible inpatient transition activities and outcomes, including when, how, and for whom inpatient transition processes are needed.MethodsClinical leaders at US children's hospitals were surveyed between January and July 2016. Questionnaires were used to assess 21 inpatient transition activities and 13 outcomes. Perceptions about feasible and important outcome measures and appropriate patients and settings for activities were summarized. Each transition activity was categorized into one of the Six Core Elements (policy, tracking, readiness, planning, transfer, or completion). Associations between perceived transition activity importance or feasibility, hospital characteristics, and transition activity performance were evaluated.ResultsIn total, 96 of 195 (49.2%) children's hospital leaders responded. The most important and feasible activities were identifying patients needing or overdue for transition, discussing transition timing with youth and/or families, and informing youth and/or families that future stays would be at an adult facility. Feasibility, but not importance, ratings were associated with current performance of transition activities. Inpatient transition activities were perceived to be important for children with medical and/or social complexity or high hospital use. Emergency department visits and patient experience during transition were top outcome measurement priorities.ConclusionsChildren's hospital clinical leaders rated inpatient youth-adult transition activities and outcome measures as important and feasible; however, feasibility may ultimately drive implementation. This work should be used to inform initial research and quality improvement priorities, although additional stakeholder perspectives are needed

Brain-Computer Interface Therapy after Stroke Affects Patterns of Brain-Behavior Relationships in Corticospinal Motor Fibers

Background. Brain-computer interface (BCI) devices are being investigated for their application in stroke rehabilitation, but little is known about how structural changes in the motor system relate to behavioral measures with the use of these systems. Objective. This study examined relationships among diffusion tensor imaging (DTI)-derived metrics and with behavioral changes in stroke patients with and without BCI training. Methods. Stroke patients (n=19) with upper extremity motor impairment were assessed using Stroke Impact Scale (SIS), Action Research Arm Test (ARAT), Nine-Hole Peg Test (9-HPT), and DTI scans. Ten subjects completed four assessments over a control period during which no training was administered. Seventeen subjects, including eight who completed the control period, completed four assessments over an experimental period during which subjects received interventional BCI training. Fractional anisotropy (FA) values were extracted from each corticospinal tract (CST) and transcallosal motor fibers for each scan. Results. No significant group by time interactions were identified at the group level in DTI or behavioral measures. During the control period, increases in contralesional CST FA and in asymmetric FA (aFA) correlated with poorer scores on SIS and 9-HPT. During the experimental period (with BCI training), increases in contralesional CST FA were correlated with improvements in 9-HPT while increases in aFA correlated with improvements in ARAT but with worsening 9-HPT performance; changes in transcallosal motor fibers positively correlated with those in the contralesional CST. All correlations p<0.05 corrected. Conclusions. These findings suggest that the integrity of the contralesional CST may be used to track individual behavioral changes observed with BCI training after stroke

Machine Learning Classification to Identify the Stage of Brain-Computer Interface Therapy for Stroke Rehabilitation Using Functional Connectivity

Interventional therapy using brain-computer interface (BCI) technology has shown promise in facilitating motor recovery in stroke survivors; however, the impact of this form of intervention on functional networks outside of the motor network specifically is not well-understood. Here, we investigated resting-state functional connectivity (rs-FC) in stroke participants undergoing BCI therapy across stages, namely pre- and post-intervention, to identify discriminative functional changes using a machine learning classifier with the goal of categorizing participants into one of the two therapy stages. Twenty chronic stroke participants with persistent upper-extremity motor impairment received neuromodulatory training using a closed-loop neurofeedback BCI device, and rs-functional MRI (rs-fMRI) scans were collected at four time points: pre-, mid-, post-, and 1 month post-therapy. To evaluate the peak effects of this intervention, rs-FC was analyzed from two specific stages, namely pre- and post-therapy. In total, 236 seeds spanning both motor and non-motor regions of the brain were computed at each stage. A univariate feature selection was applied to reduce the number of features followed by a principal component-based data transformation used by a linear binary support vector machine (SVM) classifier to classify each participant into a therapy stage. The SVM classifier achieved a cross-validation accuracy of 92.5% using a leave-one-out method. Outside of the motor network, seeds from the fronto-parietal task control, default mode, subcortical, and visual networks emerged as important contributors to the classification. Furthermore, a higher number of functional changes were observed to be strengthening from the pre- to post-therapy stage than the ones weakening, both of which involved motor and non-motor regions of the brain. These findings may provide new evidence to support the potential clinical utility of BCI therapy as a form of stroke rehabilitation that not only benefits motor recovery but also facilitates recovery in other brain networks. Moreover, delineation of stronger and weaker changes may inform more optimal designs of BCI interventional therapy so as to facilitate strengthened and suppress weakened changes in the recovery process

DTI Measures Track and Predict Motor Function Outcomes in Stroke Rehabilitation Utilizing BCI Technology

Tracking and predicting motor outcomes is important in determining effective stroke rehabilitation strategies. Diffusion tensor imaging (DTI) allows for evaluation of the underlying structural integrity of brain white matter tracts and may serve as a potential biomarker for tracking and predicting motor recovery. In this study, we examined the longitudinal relationship between DTI measures of the posterior limb of the internal capsule (PLIC) and upper-limb motor outcomes in 13 stroke patients (median 20-month post-stroke) who completed up to 15 sessions of intervention using brain-computer interface (BCI) technology. Patients’ upper-limb motor outcomes and PLIC DTI measures including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) were assessed longitudinally at four time points: pre-, mid-, immediately post- and one-month-post intervention. DTI measures and ratios of each DTI measure comparing the ipsilesional and contralesional PLIC were correlated with patients’ motor outcomes to examine the relationship between structural integrity of the PLIC and patients’ motor recovery. We found that lower diffusivity and higher FA values of the ipsilesional PLIC were significantly correlated with better upper-limb motor function. Baseline DTI ratios were significantly correlated with motor outcomes measured immediately post and one-month-post BCI interventions. A few patients achieved improvements in motor recovery meeting the minimum clinically important difference (MCID). These findings suggest that upper-limb motor recovery in stroke patients receiving BCI interventions relates to the microstructural status of the PLIC. Lower diffusivity and higher FA measures of the ipsilesional PLIC contribute towards better motor recovery in the stroke-affected upper-limb. DTI-derived measures may be a clinically useful biomarker in tracking and predicting motor recovery in stroke patients receiving BCI interventions