Enhancing behavioral sleep care with digital technology: study protocol for a hybrid type 3 implementation-effectiveness randomized trial.

BACKGROUND: Insomnia affects almost one in four military service members and veterans. The first-line recommended treatment for insomnia is cognitive-behavioral therapy for insomnia (CBTI). CBTI is typically delivered in-person or online over one-to-four sessions (brief versions) or five-to-eight sessions (standard versions) by a licensed doctoral or masters-level clinician with extensive training in behavioral sleep medicine. Despite its effectiveness, CBTI has limited scalability. Three main factors inhibit access to and delivery of CBTI including restricted availability of clinical expertise; rigid, resource-intensive treatment formats; and limited capacities for just-in-time monitoring and treatment personalization. Digital technologies offer a unique opportunity to overcome these challenges by providing scalable, personalized, resource-sensitive, adaptive, and cost-effective approaches for evidence-based insomnia treatment. METHODS: This is a hybrid type 3 implementation-effectiveness randomized trial using a scalable evidence-based digital health software platform, NOCTEM™'s Clinician-Operated Assistive Sleep Technology (COAST™). COAST includes a clinician portal and a patient app, and it utilizes algorithms that facilitate detection of sleep disordered patterns, support clinical decision-making, and personalize sleep interventions. The first aim is to compare three clinician- and system-centered implementation strategies on the reach, adoption, and sustainability of the COAST digital platform by offering (1) COAST only, (2) COAST plus external facilitation (EF: assistance and consultation to providers by NOCTEM's sleep experts), or (3) COAST plus EF and internal facilitation (EF/IF: assistance/consultation to providers by NOCTEM's sleep experts and local champions). The second aim is to quantify improvements in insomnia among patients who receive behavioral sleep care via the COAST platform. We hypothesize that reach, adoption, and sustainability and the magnitude of improvements in insomnia will be superior in the EF and EF/IF groups relative to the COAST-only group. DISCUSSION: Digital health technologies and machine learning-assisted clinical decision support tools have substantial potential for scaling access to insomnia treatment. This can augment the scalability and cost-effectiveness of CBTI without compromising patient outcomes. Engaging providers, stakeholders, patients, and decision-makers is key in identifying strategies to support the deployment of digital health technologies that can promote quality care and result in clinically meaningful sleep improvements, positive systemic change, and enhanced readiness and health among service members. TRIAL REGISTRATION: ClinicalTrials.gov NCT04366284 . Registered on 28 April 2020.

Transcriptome analysis of synaptoneurosomes identifies neuroplasticity genes overexpressed in incipient Alzheimer's disease.

In Alzheimer's disease (AD), early deficits in learning and memory are a consequence of synaptic modification induced by toxic beta-amyloid oligomers (oAbeta). To identify immediate molecular targets downstream of oAbeta binding, we prepared synaptoneurosomes from prefrontal cortex of control and incipient AD (IAD) patients, and isolated mRNAs for comparison of gene expression. This novel approach concentrates synaptic mRNA, thereby increasing the ratio of synaptic to somal mRNA and allowing discrimination of expression changes in synaptically localized genes. In IAD patients, global measures of cognition declined with increasing levels of dimeric Abeta (dAbeta). These patients also showed increased expression of neuroplasticity related genes, many encoding 3'UTR consensus sequences that regulate translation in the synapse. An increase in mRNA encoding the GluR2 subunit of the alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) was paralleled by elevated expression of the corresponding protein in IAD. These results imply a functional impact on synaptic transmission as GluR2, if inserted, maintains the receptors in a low conductance state. Some overexpressed genes may induce early deficits in cognition and others compensatory mechanisms, providing targets for intervention to moderate the response to dAbeta.

Understanding hippocampal sclerosis in the elderly: epidemiology, characterization, and diagnostic issues.

Hippocampal sclerosis (HS) is a pathologic term used to describe severe loss of neurons and reactive gliosis without cystic cavitation in the CA1 sector of the hippocampus. In late life, HS is associated with hippocampal atrophy, severe amnesia, and slowly progressive dementia without clinical seizure activity. HS is difficult to distinguish clinically from Alzheimer's disease and is often diagnosed postmortem. In autopsy series, HS may be found without significant other pathology (2%-4% of cases), but it occurs frequently in combination with other vascular and neurodegenerative disorders (12%-20% of cases). HS is found bilaterally in 50% of cases and unilaterally in 50% of cases, with similar predilection for the right versus left hemisphere. The pathogenesis of HS is unknown and may be multifactorial in origin, possibly due to anoxic/ischemic injury or TDP-43-related neurodegeneration. Little is known about the prevention and treatment of late-life HS, although circumstantial evidence suggests the importance of identifying and treating vascular risk factors.