Seizure Assessment and Forecasting With Efficient Rapid-EEG: A Retrospective Multicenter Comparative Effectiveness Study.

BACKGROUND AND OBJECTIVES: Approximately 30% of critically ill patients have seizures, and more than half of these seizures do not have an overt clinical correlate. EEG is needed to avoid missing seizures and prevent overtreatment with antiseizure medications. Conventional-EEG (cEEG) resources are logistically constrained and unable to meet their growing demand for seizure detection even in highly developed centers. Brief EEG screening with the validated 2HELPS2B algorithm was proposed as a method to triage cEEG resources, but it is hampered by cEEG requirements, primarily EEG technologists. Seizure risk-stratification using reduced time-to-application rapid response-EEG (rrEEG) systems (∼5 minutes) could be a solution. We assessed the noninferiority of the 2HELPS2B score on a 1-hour rrEEG compared to cEEG. METHODS: A multicenter retrospective EEG diagnostic accuracy study was conducted from October 1, 2021, to July 31, 2022. Chart and EEG review performed with consecutive sampling at 4 tertiary care centers, included records of patients ≥18 years old, from January 1, 2018, to June 20, 2022. Monte Carlo simulation power analysis yielded n = 500 rrEEG; for secondary outcomes n = 500 cEEG and propensity-score covariate matching was planned. Primary outcome, noninferiority of rrEEG for seizure risk prediction, was assessed per area under the receiver operator characteristic curve (AUC). Noninferiority margin (0.05) was based on the 2HELPS2B validation study. RESULTS: A total of 240 rrEEG with follow-on cEEG were obtained. Median age was 64 (interquartile range 22); 42% were female. 2HELPS2B on a 1-hour rrEEG met noninferiority to cEEG (AUC 0.85, 95% CI 0.78-0.90, p = 0.001). Secondary endpoints of comparison with a matched contemporaneous cEEG showed no significant difference in AUC (0.89, 95% CI 0.83-0.94, p = 0.31); in false negative rate for the 2HELPS2B = 0 group (p = 1.0) rrEEG (0.021, 95% CI 0-0.062), cEEG (0.016, 95% CI 0-0.048); nor in survival analyses. DISCUSSION: 2HELPS2B on 1-hour rrEEG is noninferior to cEEG for seizure prediction. Patients with low-risk (2HELPS2B = 0) may be able to forgo prolonged cEEG, allowing for increased monitoring of at-risk patients. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that rrEEG is noninferior to cEEG in calculating the 2HELPS2B score to predict seizure risk.

Implications of Large Language Models for Quality and Efficiency of Neurologic Care: Emerging Issues in Neurology.

Large language models (LLMs) are advanced artificial intelligence (AI) systems that excel in recognizing and generating human-like language, possibly serving as valuable tools for neurology-related information tasks. Although LLMs have shown remarkable potential in various areas, their performance in the dynamic environment of daily clinical practice remains uncertain. This article outlines multiple limitations and challenges of using LLMs in clinical settings that need to be addressed, including limited clinical reasoning, variable reliability and accuracy, reproducibility bias, self-serving bias, sponsorship bias, and potential for exacerbating health care disparities. These challenges are further compounded by practical business considerations and infrastructure requirements, including associated costs. To overcome these hurdles and harness the potential of LLMs effectively, this article includes considerations for health care organizations, researchers, and neurologists contemplating the use of LLMs in clinical practice. It is essential for health care organizations to cultivate a culture that welcomes AI solutions and aligns them seamlessly with health care operations. Clear objectives and business plans should guide the selection of AI solutions, ensuring they meet organizational needs and budget considerations. Engaging both clinical and nonclinical stakeholders can help secure necessary resources, foster trust, and ensure the long-term sustainability of AI implementations. Testing, validation, training, and ongoing monitoring are pivotal for successful integration. For neurologists, safeguarding patient data privacy is paramount. Seeking guidance from institutional information technology resources for informed, compliant decisions, and remaining vigilant against biases in LLM outputs are essential practices in responsible and unbiased utilization of AI tools. In research, obtaining institutional review board approval is crucial when dealing with patient data, even if deidentified, to ensure ethical use. Compliance with established guidelines like SPIRIT-AI, MI-CLAIM, and CONSORT-AI is necessary to maintain consistency and mitigate biases in AI research. In summary, the integration of LLMs into clinical neurology offers immense promise while presenting formidable challenges. Awareness of these considerations is vital for harnessing the potential of AI in neurologic care effectively and enhancing patient care quality and safety. The article serves as a guide for health care organizations, researchers, and neurologists navigating this transformative landscape.

The online educational tool "Roadmap to EEGs" significantly improved trainee performance in recognizing EEG patterns.

OBJECTIVE: We created a framework to assess the competency-based EEG curriculum, outlined by the International League Against Epilepsy (ILAE) through a video-based online educational resource ("Roadmap to EEGs") and assessed its effectiveness and feasibility in improving trainees' knowledge. METHODS: Ten video-based e-learning modules addressed seven key topics in EEG and epileptology (normal EEG, normal variants, EEG artifacts, interictal epileptiform discharges (IED), focal seizures, idiopathic generalized epilepsy (IGE), and developmental and epileptic encephalopathies (DEE)). We posted the educational videos on YouTube for free access. Pre- and post-tests, each comprising 20 multiple-choice questions, were distributed to institution leadership and advertised on social media platforms to reach a global audience. The tests were administered online to assess the participants' knowledge. Pre- and post-test questions showed different EEG samples to avoid memorization and immediate recall. After completing the post-test, participants were asked to respond to 7 additional questions assessing their confidence levels and recommendations for improvement. RESULTS: A total of 52 complete and matched pre- and post-test responses were collected. The probability of a correct response was 73% before teaching (95% CI: 70%-77%) and 81% after teaching (95% CI: 78%-84%). The odds of a correct response increased significantly by 59% (95% CI: 28%-98%, p < .001). For participants having >4 weeks of EEG training, the probability of a correct response was 76% (95% CI: .72-.79) and 81% after teaching (95% CI: .78-.84). The odds of answering correctly increased by 44% (95% CI: 15%-80%, p = .001). Participants felt completely confident in independently interpreting and identifying EEG findings after completing the teaching modules (17.1% before vs. 37.8% after, p-value < .0001). 86.5% of participants expressed a high likelihood of recommending the module to other trainees. SIGNIFICANCE: The video-based online educational resource allows participants to acquire foundational knowledge in EEG/epilepsy, and participants to review previously learned EEG/epilepsy information.

A single institution anesthetic experience with catheterization of pediatric pulmonary hypertension patients.

Cardiac catheterization remains the gold standard for the diagnosis and management of pediatric pulmonary hypertension (PH). There is lack of consensus regarding optimal anesthetic and airway regimen. This retrospective study describes the anesthetic/airway experience of our single center cohort of pediatric PH patients undergoing catheterization, in which obtaining hemodynamic data during spontaneous breathing is preferential. A total of 448 catheterizations were performed in 232 patients. Of the 379 cases that began with a natural airway, 274 (72%) completed the procedure without an invasive airway, 90 (24%) received a planned invasive airway, and 15 (4%) required an unplanned invasive airway. Median age was 3.4 years (interquartile range [IQR] 0.7-9.7); the majority were either Nice Classification Group 1 (48%) or Group 3 (42%). Vasoactive medications and cardiopulmonary resuscitation were required in 14 (3.7%) and eight (2.1%) cases, respectively; there was one death. Characteristics associated with use of an invasive airway included age <1 year, Group 3, congenital heart disease, trisomy 21, prematurity, bronchopulmonary dysplasia, WHO functional class III/IV, no PH therapy at time of case, preoperative respiratory support, and having had an intervention (p < 0.05). A composite predictor of age <1 year, Group 3, prematurity, and any preoperative respiratory support was significantly associated with unplanned airway escalation (26.7% vs. 6.9%, odds ratio: 4.9, confidence interval: 1.4-17.0). This approach appears safe, with serious adverse event rates similar to previous reports despite the predominant use of natural airways. However, research is needed to further investigate the optimal anesthetic regimen and respiratory support for pediatric PH patients undergoing cardiac catheterization.

A disrupted compartment boundary underlies abnormal cardiac patterning and congenital heart defects.

Failure of septation of the interventricular septum (IVS) is the most common congenital heart defect (CHD), but mechanisms for patterning the IVS are largely unknown. We show that a Tbx5+/Mef2cAHF+ progenitor lineage forms a compartment boundary bisecting the IVS. This coordinated population originates at a first- and second heart field interface, subsequently forming a morphogenetic nexus. Ablation of Tbx5+/Mef2cAHF+ progenitors cause IVS disorganization, right ventricular hypoplasia and mixing of IVS lineages. Reduced dosage of the CHD transcription factor TBX5 disrupts boundary position and integrity, resulting in ventricular septation defects (VSDs) and patterning defects, including Slit2 and Ntn1 misexpression. Reducing NTN1 dosage partly rescues cardiac defects in Tbx5 mutant embryos. Loss of Slit2 or Ntn1 causes VSDs and perturbed septal lineage distributions. Thus, we identify essential cues that direct progenitors to pattern a compartment boundary for proper cardiac septation, revealing new mechanisms for cardiac birth defects.

Improving Neurology Clinical Care With Natural Language Processing Tools.

The integration of natural language processing (NLP) tools into neurology workflows has the potential to significantly enhance clinical care. However, it is important to address the limitations and risks associated with integrating this new technology. Recent advances in transformer-based NLP algorithms (e.g., GPT, BERT) could augment neurology clinical care by summarizing patient health information, suggesting care options, and assisting research involving large datasets. However, these NLP platforms have potential risks including fabricated facts and data security and substantial barriers for implementation. Although these risks and barriers need to be considered, the benefits for providers, patients, and communities are substantial. With these systems achieving greater functionality and the pace of medical need increasing, integrating these tools into clinical care may prove not only beneficial but necessary. Further investigation is needed to design implementation strategies, mitigate risks, and overcome barriers.

Evaluating adult care in Dravet syndrome upon transferring from pediatrics in the U.S.: A caregiver-based survey study.

Patients with Dravet syndrome (DS) and their caregivers must navigate a complex process upon transitioning from pediatric to adult healthcare settings. Our study examines the state of care transfer of patients with DS in the U.S. A 34-question e-survey evaluating patient demographics, clinical features, and details of the transfer process was sent to caregivers of adults with DS (≥18 years old) residing in the U.S. through the Dravet Syndrome Foundation. Forty-six responses were included in the analysis. Twenty-nine patients (n = 29/46) did not undergo transfer of care - mostly because they were still followed by pediatric neurologists/epileptologists (71%), whereas 17 (n = 17/46) underwent transfer of care. Adult neurology/epilepsy teams providing care never/rarely included a multidisciplinary team (71%), addressed patients' self-advocacy capabilities (53%), or legal guardianship/end-of-life decision-making (59%). Adult neurology/epilepsy teams were considered very much attentive/available (63%), attentive and accommodating to patients with behavioral/cognitive issues (50%), and knowledgeable about caring for patients with intellectual disability/behavioral issues (63%), collaborating with caregivers (75%), and DS - especially in adults (50%). Most caregivers (62.5%) rated the transfer process as good, very good, or excellent. Patients with DS and their caregivers would benefit from more accessible transition programs, which would be ideally equipped to deliver care tailored to these patients' needs.

Stromal Senescence following Treatment with the CDK4/6 Inhibitor Palbociclib Alters the Lung Metastatic Niche and Increases Metastasis of Drug-Resistant Mammary Cancer Cells.

BACKGROUND: CDK4/6 inhibitors (CDKi) have improved disease control in hormone-receptor-positive, HER2-negative metastatic breast cancer, but most patients develop progressive disease. METHODS: We asked whether host stromal senescence after CDK4/6 inhibition affects metastatic seeding and growth of CDKi-resistant mammary cancer cells by using the p16-INK-ATTAC mouse model of inducible senolysis. RESULTS: Palbociclib pretreatment of naïve mice increased lung seeding of CDKi-resistant syngeneic mammary cancer cells, and this effect was reversed by depletion of host senescent cells. RNA sequencing analyses of lungs from non-tumor-bearing p16-INK-ATTAC mice identified that palbociclib downregulates immune-related gene sets and gene expression related to leukocyte migration. Concomitant senolysis reversed a portion of these effects, including pathway-level enrichment of TGF-ß- and senescence-related signaling. CIBERSORTx analysis revealed that palbociclib alters intra-lung macrophage/monocyte populations. Notably, lung metastases from palbociclib-pretreated mice revealed senescent endothelial cells. Palbociclib-treated endothelial cells exhibit hallmark senescent features in vitro, upregulate genes involved with the senescence-associated secretory phenotype, leukocyte migration, and TGF-ß-mediated paracrine senescence and induce tumor cell migration and monocyte trans-endothelial invasion in co-culture. CONCLUSIONS: These studies shed light on how stromal senescence induced by palbociclib affects lung metastasis, and they describe palbociclib-induced gene expression changes in the normal lung and endothelial cell models that correlate with changes in the tumor microenvironment in the lung metastatic niche.

EEG-based grading of immune effector cell-associated neurotoxicity syndrome.

CAR-T cell therapy is an effective cancer therapy for multiple refractory/relapsed hematologic malignancies but is associated with substantial toxicity, including Immune Effector Cell Associated Neurotoxicity Syndrome (ICANS). Improved detection and assessment of ICANS could improve management and allow greater utilization of CAR-T cell therapy, however, an objective, specific biomarker has not been identified. We hypothesized that the severity of ICANS can be quantified based on patterns of abnormal brain activity seen in electroencephalography (EEG) signals. We conducted a retrospective observational study of 120 CAR-T cell therapy patients who had received EEG monitoring. We determined a daily ICANS grade for each patient through chart review. We used visually assessed EEG features and machine learning techniques to develop the Visual EEG-Immune Effector Cell Associated Neurotoxicity Syndrome (VE-ICANS) score and assessed the association between VE-ICANS and ICANS. We also used it to determine the significance and relative importance of the EEG features. We developed the Visual EEG-ICANS (VE-ICANS) grading scale, a grading scale with a physiological basis that has a strong correlation to ICANS severity (R = 0.58 [0.47-0.66]) and excellent discrimination measured via area under the receiver operator curve (AUC = 0.91 for ICANS ≥ 2). This scale shows promise as a biomarker for ICANS which could help to improve clinical care through greater accuracy in assessing ICANS severity.

Cell Layers: uncovering clustering structure in unsupervised single-cell transcriptomic analysis.

Motivation: Unsupervised clustering of single-cell transcriptomics is a powerful method for identifying cell populations. Static visualization techniques for single-cell clustering only display results for a single resolution parameter. Analysts will often evaluate more than one resolution parameter but then only report one. Results: We developed Cell Layers, an interactive Sankey tool for the quantitative investigation of gene expression, co-expression, biological processes and cluster integrity across clustering resolutions. Cell Layers enhances the interpretability of single-cell clustering by linking molecular data and cluster evaluation metrics, providing novel insight into cell populations. Availability and implementation: https://github.com/apblair/CellLayers.

Nitric oxide-releasing biomaterials for promoting wound healing in impaired diabetic wounds: State of the art and recent trends.

Impaired diabetic wounds are serious pathophysiological complications associated with persistent microbial infections including failure in the closure of wounds, and the cause of a high frequency of lower limb amputations. The healing of diabetic wounds is attenuated due to the lack of secretion of growth factors, prolonged inflammation, and/or inhibition of angiogenic activity. Diabetic wound healing can be enhanced by supplying nitric oxide (NO) endogenously or exogenously. NO produced inside the cells by endothelial nitric oxide synthase (eNOS) naturally aids wound healing through its beneficial vasculogenic effects. However, during hyperglycemia, the activity of eNOS is affected, and thus there becomes an utmost need for the topical supply of NO from exogenous sources. Thus, NO-donors that can release NO are loaded into wound healing patches or wound coverage matrices to treat diabetic wounds. The burst release of NO from its donors is prevented by encapsulating them in polymeric hydrogels or nanoparticles for supplying NO for an extended duration of time to the diabetic wounds. In this article, we review the etiology of diabetic wounds, wound healing strategies, and the role of NO in the wound healing process. We further discuss the challenges faced in translating NO-donors as a clinically viable nanomedicine strategy for the treatment of diabetic wounds with a focus on the use of biomaterials for the encapsulation and in vivo controlled delivery of NO-donors.

Single-Cell RNA Sequencing with Spatial Transcriptomics of Cancer Tissues.

Single-cell RNA sequencing (RNA-seq) techniques can perform analysis of transcriptome at the single-cell level and possess an unprecedented potential for exploring signatures involved in tumor development and progression. These techniques can perform sequence analysis of transcripts with a better resolution that could increase understanding of the cellular diversity found in the tumor microenvironment and how the cells interact with each other in complex heterogeneous cancerous tissues. Identifying the changes occurring in the genome and transcriptome in the spatial context is considered to increase knowledge of molecular factors fueling cancers. It may help develop better monitoring strategies and innovative approaches for cancer treatment. Recently, there has been a growing trend in the integration of RNA-seq techniques with contemporary omics technologies to study the tumor microenvironment. There has been a realization that this area of research has a huge scope of application in translational research. This review article presents an overview of various types of single-cell RNA-seq techniques used currently for analysis of cancer tissues, their pros and cons in bulk profiling of transcriptome, and recent advances in the techniques in exploring heterogeneity of various types of cancer tissues. Furthermore, we have highlighted the integration of single-cell RNA-seq techniques with other omics technologies for analysis of transcriptome in their spatial context, which is considered to revolutionize the understanding of tumor microenvironment.