Phosphodiesterase-5 (PDE-5) Inhibitors as Therapy for Cerebrovascular Dysfunction in Chronic Traumatic Brain Injury.

Multiple phase III randomized controlled trials (RCTs) for pharmacologic interventions in traumatic brain injury (TBI) have failed despite promising results in experimental models. The heterogeneity of TBI, in terms of pathomechanisms and impacted brain structures, likely contributes to these failures. Biomarkers have been recommended to identify patients with relevant pathology (predictive biomarkers) and confirm target engagement and monitor therapy response (pharmacodynamic biomarkers). Our group focuses on traumatic cerebrovascular injury as an understudied endophenotype of TBI and is validating a predictive and pharmacodynamic imaging biomarker (cerebrovascular reactivity; CVR) in moderate-severe TBI. We aim to extend these studies to milder forms of TBI to determine the optimal dose of sildenafil for maximal improvement in CVR. We will conduct a phase II dose-finding study involving 160 chronic TBI patients (mostly mild) using three doses of sildenafil, a phosphodiesterase-5 (PDE-5) inhibitor. The study measures baseline CVR and evaluates the effect of escalating sildenafil doses on CVR improvement. A 4-week trial of thrice daily sildenafil will assess safety, tolerability, and clinical efficacy. This dual-site 4-year study, funded by the Department of Defense and registered in ClinicalTrials.gov (NCT05782244), plans to launch in June 2023. Biomarker-informed RCTs are essential for developing effective TBI interventions, relying on an understanding of underlying pathomechanisms. Traumatic microvascular injury (TMVI) is an attractive mechanism which can be targeted by vaso-active drugs such as PDE-5 inhibitors. CVR is a potential predictive and pharmacodynamic biomarker for targeted interventions aimed at TMVI. (Trial registration: NCT05782244, ClinicalTrials.gov ).

Patients' Perspectives on Life and Recovery 1 Year After COVID-19 Hospitalization.

BACKGROUND: Many patients hospitalized for COVID-19 experience prolonged symptoms months after discharge. Little is known abou t patients' personal experiences recovering from COVID-19 in the United States (US), where medically underserved populations are at particular risk of adverse outcomes. OBJECTIVE: To explore patients' perspectives on the impact of COVID-19 hospitalization and barriers to and facilitators of recovery 1 year after hospital discharge in a predominantly Black American study population with high neighborhood-level socioeconomic disadvantage. DESIGN: Qualitative study utilizing individual, semi-structured interviews. PARTICIPANTS: Adult patients hospitalized for COVID-19 approximately 1 year after discharge home who were engaged in a COVID-19 longitudinal cohort study. APPROACH: The interview guide was developed and piloted by a multidisciplinary team. Interviews were audio-recorded and transcribed. Data were coded and organized into discrete themes using qualitative content analysis with constant comparison techniques. KEY RESULTS: Of 24 participants, 17 (71%) self-identified as Black, and 13 (54%) resided in neighborhoods with the most severe neighborhood-level socioeconomic disadvantage. One year after discharge, participants described persistent deficits in physical, cognitive, or psychological health that impacted their current lives. Repercussions included financial suffering and a loss of identity. Participants reported that clinicians often focused on physical health over cognitive and psychological health, an emphasis that posed a barrier to recovering holistically. Facilitators of recovery included robust financial or social support systems and personal agency in health maintenance. Spirituality and gratitude were common coping mechanisms. CONCLUSIONS: Persistent health deficits after COVID-19 resulted in downstream consequences in participants' lives. Though participants received adequate care to address physical needs, many described persistent unmet cognitive and psychological needs. A more comprehensive understanding of barriers and facilitators for COVID-19 recovery, contextualized by specific healthcare and socioeconomic needs related to socioeconomic disadvantage, is needed to better inform intervention delivery to patients that experience long-term sequelae of COVID-19 hospitalization.

Structural brain network deviations predict recovery after traumatic brain injury.

OBJECTIVE: Traumatic brain injury results in diffuse axonal injury and the ensuing maladaptive alterations in network function are associated with incomplete recovery and persistent disability. Despite the importance of axonal injury as an endophenotype in TBI, there is no biomarker that can measure the aggregate and region-specific burden of axonal injury. Normative modeling is an emerging quantitative case-control technique that can capture region-specific and aggregate deviations in brain networks at the individual patient level. Our objective was to apply normative modeling in TBI to study deviations in brain networks after primarily complicated mild TBI and study its relationship with other validated measures of injury severity, burden of post-TBI symptoms, and functional impairment. METHOD: We analyzed 70 T1-weighted and diffusion-weighted MRIs longitudinally collected from 35 individuals with primarily complicated mild TBI during the subacute and chronic post-injury periods. Each individual underwent longitudinal blood sampling to characterize blood protein biomarkers of axonal and glial injury and assessment of post-injury recovery in the subacute and chronic periods. By comparing the MRI data of individual TBI participants with 35 uninjured controls, we estimated the longitudinal change in structural brain network deviations. We compared network deviation with independent measures of acute intracranial injury estimated from head CT and blood protein biomarkers. Using elastic net regression models, we identified brain regions in which deviations present in the subacute period predict chronic post-TBI symptoms and functional status. RESULTS: Post-injury structural network deviation was significantly higher than controls in both subacute and chronic periods, associated with an acute CT lesion and subacute blood levels of glial fibrillary acid protein (r = 0.5, p = 0.008) and neurofilament light (r = 0.41, p = 0.02). Longitudinal change in network deviation associated with change in functional outcome status (r = -0.51, p = 0.003) and post-concussive symptoms (BSI: r = 0.46, p = 0.03; RPQ: r = 0.46, p = 0.02). The brain regions where the node deviation index measured in the subacute period predicted chronic TBI symptoms and functional status corresponded to areas known to be susceptible to neurotrauma. CONCLUSION: Normative modeling can capture structural network deviations, which may be useful in estimating the aggregate and region-specific burden of network changes induced by TAI. If validated in larger studies, structural network deviation scores could be useful for enrichment of clinical trials of targeted TAI-directed therapies.