Faculty Bibliography

The Yazidi community endured an unprecedented genocide by the Islamic State (ISIS) in August 2014, resulting in mass killings, kinocide, abductions, ongoing disappearances, and sexual enslavement. The intense trauma led to high prevalence rates of posttraumatic stress disorder (PTSD), depression, anxiety, and profound sleep disturbances. This comprehensive article integrates epidemiological data, neurobiological mechanisms, and clinical case reports to elucidate sleep disorders among Yazidi survivors. We detail the historical context, transgenerational trauma, specific sleep-related pathologies (insomnia, nightmares, parasomnias, and disrupted circadian rhythms), neurobiological underpinnings, cultural factors, and evidence-based interventions (e.g., Narrative Exposure Therapy (NET); Cognitive Behavioral Therapy for Insomnia (CBT-I)). Furthermore, we discuss the establishment and role of the Institute for Psychotherapy and Psychotraumatology (IPP) at the University of Duhok, outline barriers to care, and propose future research directions and policy recommendations.

IMPORTANCE/UNASSIGNED:Currently, there are no standardized outcome domains or measures in clinical trials for facial aging. Heterogeneity in outcome domains and measurement instruments across clinical trials creates difficulty in directly comparing interventions, determining superior therapies, and developing high-quality meta-analyses. OBJECTIVE/UNASSIGNED:To develop a core outcome set (COS) of essential domains to be reported in clinical trials evaluating the efficacy of interventions for facial aging. EVIDENCE REVIEW/UNASSIGNED:PubMed/Medline, Embase, Cochrane Central Register of Controlled Trials, and CINAHL were searched from September 2005 to September 2015. An updated search of the same databases was performed from September 2015 to February 2026. Studies were included if (1) they were randomized clinical trial or controlled clinical trial in design, (2) they assessed the efficacy or safety of an intervention for facial aging, (3) they were published in English, and (4) they involved human participants. Complementary sources, including patient interviews, were used to capture further relevant outcomes. Two rounds of Delphi surveys, followed by consensus meetings, were used to identify outcome domains considered most important by both patient and physician stakeholders. FINDINGS/UNASSIGNED:The final COS consists of 6 outcome domains: (1) overall convenience of treatment; (2) time to return to normal work and social activity; (3) overall assessment of focused area of treatment (at the point in time when treatment is expected to provide peak benefit); (4) duration of treatment effect; (5) severity of persistent local or systemic adverse events, including pigmentary change, skin texture change, delayed healing, scarring, and serious adverse events; and (6) patient satisfaction with treatment. CONCLUSIONS AND RELEVANCE/UNASSIGNED:The 6 outcome domains identified through a Delphi consensus are recommended for reporting in future facial aging trials to ensure that outcomes that matter most to patients and clinicians are measured and that results are comparable across interventions.

PURPOSE/UNASSIGNED:Orbital fractures are a major reason for ophthalmologic consultation in the emergency department. In this study, we studied ocular signs associated with intervention and compared 4 previously published protocols to identify which best identified higher risk patients in need of consultation. METHODS/UNASSIGNED:We performed a retrospective cross-sectional study of patients from the BALCITE (BALtimore Consultation, Inpatient, and Trauma of the Eye) database who received ophthalmologic consultation. Our primary outcomes were the ocular and orbital signs associated with receiving intervention. Our secondary outcome identified the most sensitive and specific screening algorithm for orbital fractures by comparing four existing protocols (HOPE+CT, STOP, MEE, and UTH) to our large independent cohort. RESULTS/UNASSIGNED: < 0.001). The STOP tool had the highest sensitivity of 96.3%, demonstrating a potential 29% reduction in hospital fracture consults, followed by MEE, with a sensitivity of 93.1%. The HOPE+CT tool had the highest specificity of 95.6%. CONCLUSION/UNASSIGNED:The presence of an APD and periorbital laceration are strong indicators of urgent ophthalmologic treatment in the setting of acute orbital fractures. Supportive implementation of the STOP and MEE algorithms can effectively screen orbital fracture patients to help triage in the acute setting, improve resource utilization, and reduce healthcare costs.

BACKGROUND AND AIMS/OBJECTIVE:Systemic inflammation in cardiogenic shock is associated with increased disease severity and mortality. C-reactive protein (CRP) is a widely accessible inflammatory biomarker that may aid phenotyping and risk stratification. We evaluated the association between admission CRP and in-hospital mortality in patients with cardiogenic shock. METHODS:Using a multicentre, nationally representative database, we identified adults with a discharge diagnosis of cardiogenic shock from 2015-2023 who had CRP measured within two days of hospital admission; patients with sepsis were excluded. CRP was analysed in tertiles. Inverse probability weighting (IPW) was used to assess associations with in-hospital mortality. Secondary outcomes included ICU and hospital length of stay and total cost. RESULTS:We identified 26,525 patients; median (IQR) CRP was 18.4 mg/L (5.0-67.0 mg/L). In-hospital mortality was 28.7%, 32.7%, and 42.3% across tertiles 1-3. In-hospital mortality increased by 19% for each 50-unit increase in CRP (OR 1.19; 95% CI: 1.16-1.21, p<0.001). After IPW, tertiles 2 and 3 had higher absolute mortality risks compared with tertile 1 by 3.9% (95% CI: 2.4%-5.3%) and 12.4% (95% CI: 10.9%-13.9%), respectively (both, p<0.001). Findings were consistent in sensitivity analyses restricted to day-1 CRP measurement, primary diagnoses of heart failure or myocardial infarction, and among patients requiring early mechanical circulatory support (all, p<0.05). Median ICU and hospital stay increased significantly across tertiles (all, p<0.001), total cost was not statistically different. CONCLUSIONS:In patients with cardiogenic shock, a readily available biomarker, elevated CRP was associated with higher in-hospital mortality.

Virtual urgent care (VUC) has become an increasingly utilized resource for acute care delivery. Frequent utilization of VUC may reflect unmet longitudinal care needs and contribute to fragmented care. While high-utilizer patterns are well described in emergency departments, they have not been systematically characterized in telemedicine. We evaluated a clinical decision support (CDS) nudge designed to identify and address high utilizers of VUC at a large academic health system. An electronic health record alert triggered when patients met predefined high-utilizer criteria (>3 visits in 30 days, >12 in six months, or >20 in 12 months) and prompted providers to document a structured follow-up plan using a SmartPhrase. Among 473 eligible patients, 162 (34%) received the SmartPhrase. After adjustment for baseline utilization using negative binomial regression, SmartPhrase use was associated with a 22% relative reduction in VUC visits over the subsequent 30 days (incidence rate ratio 0.78, p = .03). Bootstrapped analyses confirmed a significant reduction in the SmartPhrase group (-1.47 visits; 95% CI [-2.19 to -0.62]), while no significant change occurred in the comparison group. These findings suggest that a low-cost, workflow-integrated CDS nudge may reduce short-term telehealth overutilization by prompting structured follow-up discussions and encouraging longitudinal care planning.

INTRODUCTION/UNASSIGNED:Few populations face more disadvantage than those with lifelong intellectual and developmental disabilities (IDD) and those with serious mental illness (SMI). People with IDD may face unique challenges in the manifestation and treatment of SMI; little is known about these challenges during the widespread expansion of telehealth mental health services during the COVID-19 pandemic which disrupted service availability. METHODS/UNASSIGNED:Using Medicaid claims from Kansas, Massachusetts, New York and South Carolina, mental health service utilization patterns for three cohorts of people ages 1-45 years were studied: those with IDD, those with SMI, and those with SMI and IDD. Utilization was examined before (2018-2019) and during (2020-2021) the emergence of telehealth services for each cohort. Meta-analysis was used to compare odds of mental health service utilization by demographic subgroups. RESULTS/UNASSIGNED:The prevalence of mental health service utilization was approximately 75% for the IDD/SMI cohort, 60% for the SMI cohort, and 30% of the IDD cohort in 2018. Teens 13-17 years and young adults tended to have the highest levels of service utilization. Service utilization was driven by different diagnoses for the groups. The SMI cohort utilized services significantly more for mood and anxiety disorders, and the IDD cohort utilized services significantly more for comorbid neurodevelopmental conditions, anxiety, and trauma-related disorders. The IDD/SMI cohort utilized services more bipolar and related disorders and had a younger median age of service utilizers for trauma- and stress-related disorders than the SMI cohort. DISCUSSION/UNASSIGNED:The IDD/SMI cohort had the highest mental health service utilization rates compared to the other two cohorts, with minimal urban-rural differences, suggesting mental health services may be reaching those at the highest levels of risk for adverse outcomes. People with IDD demonstrated substantially lower rates of telehealth utilization for mental health needs; however, people in the cohort with IDD and SMI demonstrated similar or higher rates (in adults) of telehealth utilization compared to people with SMI only. Even with expanded telehealth services, the COVID-19 pandemic appeared to partially disrupt utilization across all cohorts and age groups. Findings suggest that people with IDD and SMI experience trauma- and stressor-related disorders that require treatment at younger ages than people with SMI only.

Neurons undergo extensive metabolic reprogramming during differentiation; this reprogramming leads to specific changes in the kinetics and concentrations of metabolites. We developed an in-cell NMR-based method that monitors this metabolic transformation with subminute time resolution. Undifferentiated SH-SY5Y human neuronal precursor cells were encapsulated into alginate gel beads and differentiated inside the gel. Real time pulse chase (RTPC) in-cell NMR was used to measure relative steady state concentrations of glycolysis and TCA cycle metabolites and the kinetics of metabolite production and clearance in differentiated and undifferentiated cells. Neuronal differentiation slowed glycolysis, increased TCA cycle activity and glutamate production. Fructose 1,6 bisphosphate and glutathione were identified as major biomarkers of undifferentiated and differentiated cells, respectively. The results demonstrate that RTPC-NMR analysis of neuronal cells is an effective method for studying changes in metabolite profiles induced by stress and drug-induced stimuli.

Large language models (LLMs) show great potential for clinical decision-making, yet most applications remain narrow, task-specific chat tools rather than systems integrated into clinical workflows^1,2. However, building physician copilots will require models that operate within the electronic health record (EHR), with governed access to patient data and the ability to initiate permitted EHR actions within defined safety constraints. Yet it remains unproven whether such a system can manage patient cases with physician-level performance. Here we show that MIRA (Medical Intelligence for Reasoning and Action), an autonomous artificial intelligence agent operating in a sandboxed EHR environment, can navigate a large clinical action space to obtain patient histories; order and interpret laboratory, imaging and microbiology tests; generate differential diagnoses; and formulate treatment plans such as prescribing medications, scheduling surgical procedures and planning admissions. In simulations on real patient cases spanning multiple diagnoses, MIRA outperformed physicians in diagnostic accuracy and made guideline-concordant, medication-safe and appropriate admission decisions. Compared with previous LLM applications that addressed isolated subtasks or provided free-text advice, these results suggest that an EHR-integrated artificial intelligence agent can turn clinical intent into structured, actionable EHR operations, possibly making it a more effective decision-support partner for physicians. Further work is needed to establish generalization, safety and governance through prospective, real-world studies.

Opportunistic screening leverages existing imaging examinations performed for unrelated routine clinical indications to systematically extract quantitative biomarkers. Artificial intelligence tools have made deployment at scale increasingly feasible. However, the pathway from a validated algorithm to a functioning clinical program remains poorly defined, and prospective implementation at scale is uncommon. Successful deployment requires coordinated engagement from radiologists, information technology and operational teams, and clinical care teams, each facing distinct decisions that determine whether a program functions reliably and delivers patient benefit. This article presents a practical framework for opportunistic screening implementation organized around these three stakeholder groups. We apply this framework to opportunistic CT osteoporosis screening, drawing on our experience developing such a program at a large academic medical center. The framework presented is intended to be broadly applicable across opportunistic screening applications as the field moves from algorithmic validation toward clinical translation.