Faculty Bibliography

BACKGROUND:Health insurance in the United States varies in coverage of essential diagnostic tests, therapies, and specialists. Health disparities between privately and publicly insured patients with MS have not been comprehensively assessed. The objective of this study is to evaluate the impact of public versus private insurance on longitudinal brain outcomes in MS. METHODS:Lesional, thalamic, and gray and white matter volumes were extracted from longitudinal MRI of 710 MS patients. Baseline volumes and atrophy rates of lesional, thalamic, and gray and white matter volumes were compared across insurance groups. RESULTS:After image quality assessment, 376 (284 private / 92 public), 638 (499 / 139), and 331 (250 / 81), patients were in MS lesion, thalamic, gray and white matter analyses respectively. Baseline lesion volume was higher for publicly insured patients but increased at a slightly higher rate in those privately insured (p = 0.01). Baseline gray matter measurements were lower for patients with public insurance, but thalamic (p < 0.01) and gray matter (p < 0.01) atrophy rates were slightly higher in the private insurance group. CONCLUSION/CONCLUSIONS:Insurance type was associated with lesion, thalamic, and gray matter volumes. The results suggest that patients with public insurance may present with more advanced disease.

OBJECTIVES/OBJECTIVE:To determine the proportion of individuals with detectable antigen in plasma or serum after SARS-CoV-2 infection and the association of antigen detection with postacute sequelae of COVID-19 (PASC) symptoms. METHODS:Plasma and serum samples were collected from adults participating in four independent studies at different time points, ranging from several days up to 14 months post-SARS-CoV-2 infection. The primary outcome measure was to quantify SARS-CoV-2 antigens, including the S1 subunit of spike, full-length spike, and nucleocapsid, in participant samples. The presence of 34 commonly reported PASC symptoms during the postacute period was determined from participant surveys or chart reviews of electronic health records. RESULTS:Of the 1569 samples analysed from 706 individuals infected with SARS-CoV-2, 21% (95% CI, 18-24%) were positive for either S1, spike, or nucleocapsid. Spike was predominantly detected, and the highest proportion of samples was spike positive (20%; 95% CI, 18-22%) between 4 and 7 months postinfection. In total, 578 participants (82%) reported at least one of the 34 PASC symptoms included in our analysis ≥1 month postinfection. Cardiopulmonary, musculoskeletal, and neurologic symptoms had the highest reported prevalence in over half of all participants, and among those participants, 43% (95% CI, 40-45%) on average were antigen-positive. Among the participants who reported no ongoing symptoms (128, 18%), antigen was detected in 28 participants (21%). The presence of antigen was associated with the presence of one or more PASC symptoms, adjusting for sex, age, time postinfection, and cohort (OR, 1.8; 95% CI, 1.4-2.2). DISCUSSION/CONCLUSIONS:The findings of this multicohort study indicate that SARS-CoV-2 antigens can be detected in the blood of a substantial proportion of individuals up to 14 months after infection. While approximately one in five asymptomatic individuals was antigen-positive, roughly half of all individuals reporting ongoing cardiopulmonary, musculoskeletal, and neurologic symptoms were antigen-positive.

Epilepsy care generates multiple sources of high-dimensional data, including clinical, imaging, electroencephalographic, genomic, and neuropsychological information, that are collected routinely to establish the diagnosis and guide management. Thanks to high-performance computing, sophisticated graphics processing units, and advanced analytics, we are now on the cusp of being able to use these data to significantly improve individualized care for people with epilepsy. Despite this, many clinicians, health care providers, and people with epilepsy are apprehensive about implementing Big Data and accompanying technologies such as artificial intelligence (AI). Practical, ethical, privacy, and climate issues represent real and enduring concerns that have yet to be completely resolved. Similarly, Big Data and AI-related biases have the potential to exacerbate local and global disparities. These are highly germane concerns to the field of epilepsy, given its high burden in developing nations and areas of socioeconomic deprivation. This educational paper from the International League Against Epilepsy's (ILAE) Big Data Commission aims to help clinicians caring for people with epilepsy become familiar with how Big Data is collected and processed, how they are applied to studies using AI, and outline the immense potential positive impact Big Data can have on diagnosis and management.

BACKGROUND:Resting-state electroencephalography (rsEEG) is usually obtained to assess seizures in comatose patients with traumatic brain injury (TBI). We aim to investigate rsEEG measures and their prediction of early recovery of consciousness in patients with TBI. METHODS:This is a retrospective study of comatose patients with TBI who were admitted to a trauma center (October 2013 to January 2022). Demographics, basic clinical data, imaging characteristics, and EEGs were collected. We calculated the following using 10-min rsEEGs: power spectral density, permutation entropy (complexity measure), weighted symbolic mutual information (wSMI, global information sharing measure), Kolmogorov complexity (Kolcom, complexity measure), and heart-evoked potentials (the averaged EEG signal relative to the corresponding QRS complex on electrocardiography). We evaluated the prediction of consciousness recovery before hospital discharge using clinical, imaging, and rsEEG data via a support vector machine. RESULTS:We studied 113 of 134 (84%) patients with rsEEGs. A total of 73 (65%) patients recovered consciousness before discharge. Patients who recovered consciousness were younger (40 vs. 50 years, p = 0.01). Patients who recovered also had higher Kolcom (U = 1688, p = 0.01), increased beta power (U = 1,652 p = 0.003) with higher variability across channels (U = 1534, p = 0.034) and epochs (U = 1711, p = 0.004), lower delta power (U = 981, p = 0.04), and higher connectivity across time and channels as measured by wSMI in the theta band (U = 1636, p = 0.026; U = 1639, p = 0.024) than those who did not recover. The area under the receiver operating characteristic curve for rsEEG was higher than that for clinical data (using age, motor response, pupil reactivity) and higher than that for the Marshall computed tomography classification (0.69 vs. 0.66 vs. 0.56, respectively; p < 0.001). CONCLUSIONS:We describe the rsEEG signature in recovery of consciousness prior to discharge in comatose patients with TBI. rsEEG measures performed modestly better than the clinical and imaging data in predicting recovery.

PURPOSE OF REVIEW/OBJECTIVE:Chronic pain affects nearly two billion people worldwide, surpassing heart disease, diabetes, and cancer in terms of economic costs. Lower back pain alone is the leading cause of years lived with disability worldwide. Despite limited treatment options, regenerative medicine, particularly extracellular vesicles (EVs) and exosomes, holds early promise for patients who have exhausted other treatment options. EVs, including exosomes, are nano-sized structures released by cells, facilitating cellular communication through bioactive molecule transfer, and offering potential regenerative properties to damaged tissues. Here, we review the potential of EVs and exosomes for the management of chronic pain. RECENT FINDINGS/RESULTS:In osteoarthritis, various exosomes, such as those derived from synovial mesenchymal stem cells, human placental cells, dental pulp stem cells, and bone marrow-derived mesenchymal stem cells (MSCs), demonstrate the ability to reduce inflammation, promote tissue repair, and alleviate pain in animal models. In intervertebral disc disease, Wharton's jelly MSC-derived EVs enhance cell viability and reduce inflammation. In addition, various forms of exosomes have been shown to reduce signs of inflammation in neurons and alleviate pain in neuropathic conditions in animal models. Although clinical applications of EVs and exosomes are still in the early clinical stages, they offer immense potential in the future management of chronic pain conditions. Clinical trials are ongoing to explore their therapeutic potential further, and with more research the potential applicability of EVs and exosomes will be fully understood.

The replication crisis in experimental psychology and neuroscience has received much attention recently. This has led to wide acceptance of measures to improve scientific practices, such as preregistration and registered reports. Less effort has been devoted to performing and reporting the results of systematic tests of the functioning of the experimental setup itself. Yet, inaccuracies in the performance of the experimental setup may affect the results of a study, lead to replication failures, and importantly, impede the ability to integrate results across studies. Prompted by challenges we experienced when deploying studies across six laboratories collecting electroencephalography (EEG)/magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and intracranial EEG (iEEG), here we describe a framework for both testing and reporting the performance of the experimental setup. In addition, 100 researchers were surveyed to provide a snapshot of current common practices and community standards concerning testing in published experiments' setups. Most researchers reported testing their experimental setups. Almost none, however, published the tests performed or their results. Tests were diverse, targeting different aspects of the setup. Through simulations, we clearly demonstrate how even slight inaccuracies can impact the final results. We end with a standardized, open-source, step-by-step protocol for testing (visual) event-related experiments, shared via protocols.io. The protocol aims to provide researchers with a benchmark for future replications and insights into the research quality to help improve the reproducibility of results, accelerate multicenter studies, increase robustness, and enable integration across studies.

Ensuring reliability of Large Language Models (LLMs) in clinical tasks is crucial. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting clinical information, focusing on cognitive tests like MMSE and CDR. Our data consisted of 135,307 clinical notes (Jan 12th, 2010 to May 24th, 2023) mentioning MMSE, CDR, or MoCA. After applying inclusion criteria 34,465 notes remained, of which 765 underwent ChatGPT (GPT-4) and LlaMA-2, and 22 experts reviewed the responses. ChatGPT successfully extracted MMSE and CDR instances with dates from 742 notes. We used 20 notes for fine-tuning and training the reviewers. The remaining 722 were assigned to reviewers, with 309 each assigned to two reviewers simultaneously. Inter-rater-agreement (Fleiss' Kappa), precision, recall, true/false negative rates, and accuracy were calculated. Our study follows TRIPOD reporting guidelines for model validation. For MMSE information extraction, ChatGPT (vs. LlaMA-2) achieved accuracy of 83% (vs. 66.4%), sensitivity of 89.7% (vs. 69.9%), true-negative rates of 96% (vs 60.0%), and precision of 82.7% (vs 62.2%). For CDR the results were lower overall, with accuracy of 87.1% (vs. 74.5%), sensitivity of 84.3% (vs. 39.7%), true-negative rates of 99.8% (98.4%), and precision of 48.3% (vs. 16.1%). We qualitatively evaluated the MMSE errors of ChatGPT and LlaMA-2 on double-reviewed notes. LlaMA-2 errors included 27 cases of total hallucination, 19 cases of reporting other scores instead of MMSE, 25 missed scores, and 23 cases of reporting only the wrong date. In comparison, ChatGPT's errors included only 3 cases of total hallucination, 17 cases of wrong test reported instead of MMSE, and 19 cases of reporting a wrong date. In this diagnostic/prognostic study of ChatGPT and LlaMA-2 for extracting cognitive exam dates and scores from clinical notes, ChatGPT exhibited high accuracy, with better performance compared to LlaMA-2. The use of LLMs could benefit dementia research and clinical care, by identifying eligible patients for treatments initialization or clinical trial enrollments. Rigorous evaluation of LLMs is crucial to understanding their capabilities and limitations.

PURPOSE/OBJECTIVE:Defects in the gene encoding selenocysteine insertion sequence binding protein 2, SECISBP2, result in global impaired selenoprotein synthesis manifesting a complex syndrome with characteristic serum thyroid function tests due to impaired thyroid hormone metabolism. Knowledge about this multisystemic defect remains limited. METHODS:Genetic and laboratory investigations were performed in affected members from 6 families presenting with short stature and failure to thrive. RESULTS:Four probands presented a complex neurodevelopmental profile, including absent speech, autistic features, and seizures. Pediatric neurological evaluation prompted genetic investigations leading to the identification of SECISBP2 variants before knowing the characteristic thyroid tests in 2 cases. Thyroid hormone treatment improved motor development, whereas speech and intellectual impairments persisted. This defect poses great diagnostic and treatment challenges for clinicians, as illustrated by a case that escaped detection for 20 years because SECISBP2 was not included in the neurodevelopmental genetic panel, and his complex thyroid status prompted antithyroid treatment instead. CONCLUSION/CONCLUSIONS:This syndrome uncovers the role of selenoproteins in humans. The severe neurodevelopmental disabilities manifested in 4 patients with SECISBP2 deficiency highlight an additional phenotype in this multisystem disorder. Early diagnosis and treatment are required, and long-term evaluation will determine the full spectrum of manifestations and the impact of therapy.

Familial dysautonomia (FD) is a rare genetic neurodevelopmental and neurodegenerative disorder. In addition to the autonomic and peripheral sensory neuropathies that challenge patient survival, one of the most debilitating symptoms affecting patients' quality of life is progressive blindness resulting from the steady loss of retinal ganglion cells (RGCs). Within the FD community, there is a concerted effort to develop treatments to prevent the loss of RGCs. However, the mechanisms underlying the death of RGCs are not well understood. To study the mechanisms underlying RGC death, Pax6-cre;Elp1^loxp/loxp male and female mice and postmortem retinal tissue from an FD patient were used to explore the neuronal and non-neuronal cellular pathology associated with the FD optic neuropathy. Neurons, astrocytes, microglia, Müller glia, and endothelial cells were investigated using a combination of histological analyses. We identified a novel disruption of cellular homeostasis and gliosis in the FD retina. Beginning shortly after birth and progressing with age, the FD retina is marked by astrogliosis and perturbations in microglia, which coincide with vascular remodeling. These changes begin before the onset of RGC death, suggesting alterations in the retinal neurovascular unit may contribute to and exacerbate RGC death. We reveal for the first time that the FD retina pathology includes reactive gliosis, increased microglial recruitment to the ganglion cell layer (GCL), disruptions in the deep and superficial vascular plexuses, and alterations in signaling pathways. These studies implicate the neurovascular unit as a disease-modifying target for therapeutic interventions in FD.

PURPOSE/OBJECTIVE:We previously reported that single doses of the norepinephrine transporter inhibitor, atomoxetine, increased standing blood pressure (BP) and ameliorated symptoms in patients with neurogenic orthostatic hypotension (nOH). We aimed to evaluate the effect of atomoxetine over four weeks in patients with nOH. METHODS:A randomized, double-blind, placebo-controlled crossover clinical trial between July 2016 and May 2021 was carried out with an initial open-label, single-dose phase (10 or 18 mg atomoxetine), followed by a 1-week wash-out, and a subsequent double-blind 4-week treatment sequence (period 1: atomoxetine followed by placebo) or vice versa (period 2). The trial included a 2-week wash-out period. The primary endpoint was symptoms of nOH as measured by the orthostatic hypotension questionnaire (OHQ) assessed at 2 weeks. RESULTS:A total of 68 patients were screened, 40 were randomized, and 37 completed the study. We found no differences in the OHQ composite score between atomoxetine and placebo at 2 weeks (-0.3 ± 1.7 versus -0.4 ± 1.5; P = 0.806) and 4 weeks (-0.6 ± 2.4 versus -0.5 ± 1.6; P = 0.251). There were no differences either in the OHSA scores at 2 weeks (3 ± 1.9 versus 4 ± 2.1; P = 0.062) and at 4 weeks (3 ± 2.2 versus 3 ± 2.0; P = 1.000) or in the OH daily activity scores (OHDAS) at 2 weeks (4 ± 3.0 versus 5 ± 3.1, P = 0.102) and 4 weeks (4 ± 3.0 versus 4 ± 2.7, P = 0.095). Atomoxetine was well-tolerated. CONCLUSIONS:While previous evidence suggested that acute doses of atomoxetine might be efficacious in treating nOH; results of this clinical trial indicated that it was not superior to placebo to ameliorate symptoms of nOH. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov; NCT02316821.