Faculty Bibliography

BACKGROUND AND PURPOSE/OBJECTIVE:Patients with intracranial stenosis-related large-vessel occlusion (ICAS-LVO) may experience better outcomes with stent placement compared with stand-alone mechanical thrombectomy (MT). This study evaluates the safety and clinical outcomes of self-expanding stents (SES) versus balloon-mounted stents (BMS) in patients with ICAS-LVO treated with MT and stent placement. MATERIALS AND METHODS/METHODS:This secondary analysis of the Registry of Emergent Large-Vessel Occlusion Due to Intracranial Stenosis, a multicenter observational study, included patients with ICAS-LVO from 25 stroke centers who underwent stent placement. Patients were stratified by stent type (SES or BMS). The primary end point was 90-day mRS = 0-2. Secondary outcomes included successful reperfusion, recurrent stroke, and infarct volume. Symptomatic intracranial hemorrhage was the primary safety outcome. Inverse probability-weighting was adjusted for confounders. RESULTS:= .001), particularly in patients without prestenting angioplasty (14% versus 1%). CONCLUSIONS:SES and BMS demonstrated comparable safety and clinical outcomes in patients with ICAS-LVO. However, SES were linked to higher rates of restenosis and recurrent strokes, potentially influenced by the absence of prestenting angioplasty. Further research is needed to refine stent-placement strategies in this population.

BACKGROUND:In many parts of the world including India, the prevalence of autoimmune inflammatory diseases such as neuromyelitis optica spectrum disorders (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and multiple sclerosis (MS) is rising. A diagnosis is often delayed due to insufficient diagnostic tools. Machine learning (ML) models have accurately differentiated eyes of patients with MS from those of healthy controls (HCs) using optical coherence tomography (OCT)-based retinal images. Examining OCT characteristics may allow for early differentiation of these conditions. The objective of this study was to determine feasibility of ML analyses to distinguish between patients with different autoimmune inflammatory diseases, other ocular diseases, and HCs based on OCT measurements of the peripapillary retinal nerve fiber layer (pRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layers (INLs). METHODS:Eyes of people with MS (n = 99 patients), NMOSD (n = 40), MOGAD (n = 74), other ocular diseases (OTHER, n = 16), and HCs (n = 54) from the Mangalore Demyelinating Disease Registry were included. Support vector machine (SVM) classification models incorporating age, pRNFL, GCIPL, and INL were performed. Data were split into training (70%) and testing (30%) data and accounted for within-patient correlations. Cross-validation was used in training to choose the best parameters for the SVM model. Accuracy and area under receiver operating characteristic curves (AUROCs) were used to assess model performance. RESULTS:The SVM models distinguished between eyes of patients with each condition (i.e., MOGAD vs NMOSD, NMOSD vs HC, MS vs OTHER, etc) with strong discriminatory power demonstrated from the AUROCs for these comparisons ranging from 0.81 to 1.00. These models also performed with moderate to high accuracy, ranging from 0.66 to 0.81, with the exception of the MS vs NMOSD comparison, which had an accuracy of 0.53. CONCLUSIONS:ML models are useful for distinguishing between autoimmune inflammatory diseases and for distinguishing these from HCs and other ocular diseases based on OCT measures. This study lays the groundwork for future deep learning studies that use analyses of raw OCT images for identifying eyes of patients with such disorders and other etiologies of optic neuropathy.

IMPORTANCE/UNASSIGNED:Open-label trials of antiseizure medications (ASMs) and devices suggest seizure reduction in focal treatment-resistant epilepsy (FTRE) may demonstrate treatment-related disease-modifying effects. Understanding FTRE trends can provide insight into treatment responses. OBJECTIVE/UNASSIGNED:To determine whether seizure frequency in FTRE improves over time. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:The Human Epilepsy Project 2 was a prospective, observational, multicenter study of patients with FTRE from May 2018 to September 2021 who were followed up for 18 to 36 months at 10 US-based comprehensive epilepsy centers. Analysis was performed from 2021 to 2024. Study data included seizure frequency, medication use, device use, surgeries tracked using daily electronic diaries, monthly check-ins, medical record review, and case report forms. Eligibility criteria included focal epilepsy diagnosis, age between 16 and 65 years, and failure of 4 or more ASMs (≥2 due to seizure control failure). Participants were recruited as a volunteer sample. EXPOSURES/UNASSIGNED:Participants were treated with multiple interventions at their physicians' discretion. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was seizure frequency trends, evaluated by quantifying seizure freedom rates and frequency reductions. Medication and device treatment responses were assessed by tracking ASM and device changes. RESULTS/UNASSIGNED:Of 196 approached participants, 146 met eligibility criteria and were included in the study. Mean (SD) participant age was 40 (12) years, and epilepsy was diagnosed at a mean (SD) age of 19.8 (13.6) years. The cohort had 84 (57.5%) female participants. A total of 35 participants had implantable devices; 1 had epilepsy surgery during the study. Of 146 participants, 128 provided sufficient seizure data for analysis, and 2 were excluded as outliers. Seizure frequency was reduced in 86 participants (68.3%) during the second half of study participation compared to the first half. In the overall cohort, mean modeled monthly seizure frequency percentage reduction was 68.73% (95% CI, 52.92%-84.54%). From 0 to 12 months (cohort 1), mean modeled percentage reduction was 67.76% (95% CI, 19.42%-116.09%); for 12 to 24 months (cohort 2), 36.00% (95% CI, 9.27%-53.46%); and for longer than 24 months (cohort 3), 66.03% (95% CI, 48.25%-83.80%) (all P < .001). An ASM was added in 69 participants (54.7%), of whom 46 (66.7%) experienced seizure frequency reduction, including seizure freedom. Seizure trajectories in participants with devices did not significantly differ from those without devices. CONCLUSIONS AND RELEVANCE/UNASSIGNED:Findings from the HEP2 study imply that FTRE improves over time, ASM additions had low probability of achieving seizure freedom but contributed to seizure reduction, and device-treated participants exhibited similar seizure trajectories to those without devices. Whether improvements reflected the natural history of FTRE or active management remains unclear, but our findings suggest cautious interpretation of open-label studies positing disease-modifying effects and further research into FTRE treatment response.

OBJECTIVE:To update the 2016 American Headache Society (AHS) guideline on parenteral pharmacologic therapies for the management of migraine attacks in the emergency department (ED). METHODS:We conducted a systematic review and meta-analysis using the same methodology as the 2016 guideline. The original search strategy was repeated and expanded to include studies of nerve blocks and sphenopalatine ganglion (SPG) blocks. We searched Medline, Embase, Cochrane, clinicaltrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform through February 10, 2025. Eligible studies were randomized controlled trials (RCTs) involving adults diagnosed with migraine, treated in the ED with intravenous (IV), intramuscular (IM), subcutaneous (SC), or nerve block (including SPG block) interventions. Two reviewers independently screened titles/abstracts and full texts; a third reviewer resolved disagreements. Data were extracted using a standardized form and verified by a second reviewer. Risk of bias was assessed using the American Academy of Neurology (AAN) criteria. Where applicable, meta-analyses were performed. Efficacy was categorized as highly likely, likely, or possibly effective or ineffective. Clinical recommendations were developed using the AAN guideline development process. RESULTS:The search identified 26 new RCTs evaluating 20 injectable treatments. Of these, 12 were rated class I (low risk of bias), 9 class II, and 4 class III. Prochlorperazine IV, dexketoprofen IV, sumatriptan SC, and greater occipital nerve blocks (GONB) were considered highly likely to be effective based on multiple class I studies. Chlorpromazine IV, metoclopramide IV, eptinezumab IV, ketorolac IV, and supraorbital nerve blocks (SONB) were considered likely effective based on one class I or multiple class II studies. Hydromorphone IV, propofol IV, and paracetamol IV were considered likely ineffective based on class I or multiple class II studies. After review of the evidence and a consensus process, recommendations were made for each intervention. CONCLUSIONS:Prochlorperazine IV and GONB must be offered to eligible adults presenting to the ED with a migraine attack for treatment of headache requiring parenteral therapy (level A - must offer) in those without contraindications, while hydromorphone IV must not be offered (level A - must not offer). Treatments that should be offered when appropriate (level B - should offer) include dexketoprofen IV, ketorolac IV, metoclopramide IV, sumatriptan SC, and SONB. Chlorpromazine IV, dexamethasone IV, and valproate IV may be offered (level C - may offer). Paracetamol IV may not be offered (level C - should not offer). Eptinezumab should be offered (level B) only for patients matching the clinical trial population but is rated level U - no recommendation for an ED-specific population. Additional evidence is needed for caffeine, granisetron, ibuprofen, ketamine, lidocaine, normal saline, propofol, and SPG blocks, all currently rated level U - no recommendation.

OBJECTIVE:Central to the development of novel antiseizure medications (ASMs) is testing of antiseizure activity in preclinical models. Although various well-established models exist, their predictive validity across the spectrum of clinical epilepsies has been less clear. We sought to establish the translational concordance of commonly used preclinical models to define models with the highest predictive clinical validity for focal onset seizures (FOS). METHODS:The Praxis Analysis of Concordance (PAC) framework was implemented to assess the translational concordance between preclinical and clinical ASM response for 32 US Food and Drug Administration-approved ASMs. Preclinical ASM responses in historically used seizure models were collected. Protective indices based on reported median tolerability and median efficacy values were calculated for each ASM in each preclinical model. A weighted scale representing relative antiseizure effect was used to grade preclinical ASM response for each seizure model. Data depth was further scored based on the number of evaluated ASMs with publicly available data. Established reports of clinical ASM use in patients with FOS were similarly evaluated, and a weighted scale representing prescribing patterns and perceived efficacy was used to grade clinical ASM response. To assess the predictive validity of preclinical models, a unified translational scoring matrix was developed to assign a concordance score spanning the spectrum from complete discordance (-1) to complete concordance (1) between preclinical and clinical ASM responses. Scores were summed and normalized to generate a global translational concordance score. RESULTS:The preclinical models with the highest translational concordance and greatest data depth for FOS were rodent maximal electroshock seizure (MES), mouse audiogenic seizure, mouse 6 Hz (32 mA), and rat amygdala kindling. SIGNIFICANCE/CONCLUSIONS:The PAC-FOS framework highlights mouse MES, mouse audiogenic, and mouse 6 Hz (32 mA) as three acute seizure models consistently demonstrating high predictive validity for FOS. We provide a pragmatic decision tree approach to support efficient resource utilization for novel ASM discovery for FOS.

RATIONALE AND OBJECTIVES/OBJECTIVE:To evaluate the performance, stability, and decision-making behavior of large language models (LLMs) for title and abstract screening for radiology systematic reviews, with attention to prompt framing, confidence calibration, and model robustness under disagreement. MATERIALS AND METHODS/METHODS:We compared five LLMs (GPT-4o, GPT-4o mini, Gemini 1.5 Pro, Gemini 2.0 Flash, Llama 3.3 70B) on two imaging-focused systematic reviews (n = 5438 and n = 267 abstracts) using binary and ternary classification tasks, confidence scoring, and reclassification of true and synthetic disagreements. Disagreements were framed as either "LLM vs human" or "human vs human." We also piloted autonomous PubMed retrieval using OpenAI and Gemini Deep Research tools. RESULTS:LLMs achieved high specificity and variable sensitivity across reviews and tasks, with F1 scores ranging from 0.389 to 0.854. Ternary classification showed low abstention rates (<5%) and modest sensitivity gains. Confidence scores were significantly higher for correct predictions. In disagreement tasks, models more often selected the human label when disagreements were framed as "LLM vs human," consistent with authority bias. GPT-4o showed greater resistance to this effect, while others were more prone to defer to perceived human input. In the autonomous search task, OpenAI achieved moderate recall and high precision; Gemini's recall was poor but precision remained high. CONCLUSION/CONCLUSIONS:LLMs hold promise for systematic review screening tasks but require careful prompt design and circumspect human-in-the-loop oversight to ensure robust performance.

BACKGROUND:. However, the microstructural alterations driving these differences are unclear. Here, we assess associations of MK and KFA with neurite orientation dispersion and density imaging (NODDI) and magnetization transfer imaging (MTI) metrics, which provide a more specific characterization of tissue microstructure. METHOD/METHODS:(75 SCD) ages 55-88 were included in the analysis. Participants were defined as SCD if they endorsed problems with their memory and in the control group otherwise. Diffusion images were processed to obtain MK, Radial Kurtosis (RK), Axial Kurtosis (AK) and KFA from DKI and Neurite Density (ND) and Orientation Dispersion (OD), a marker of neurite organization, from NODDI. MTI was used to calculate the Magnetization Transfer Ratio (MTR), a marker of myelin and potentially amyloid aggregation. Mean metric values were calculated for bilateral amygdala (Figure 1). Between-group comparisons were conducted using Wilcoxon rank-sum tests, corrected for multiple testing. Associations between DKI, NODDI, and MTR metrics were examined using linear models corrected for age and sex. RESULT/RESULTS:SCD had lower KFA, higher MK, and higher RK in the right amygdala (Table 1). KFA had a weak negative correlation with ND, while MK and RK had strong positive correlations (Figure 2A-C). Only MK had a weak positive correlation with OD (Figure 2D-F). Neither KFA, MK, nor RK correlated with MTR (Figure 2G-I). CONCLUSION/CONCLUSIONS:DKI metrics are more sensitive to amygdala changes in SCD than NODDI metrics or MTR. Lower KFA, higher MK, and higher RK were associated with higher ND but not MTR, suggestive of dendritic or glial branching. Higher MK was additionally associated with higher OD, potentially indicating reduced neurite organization. Further analyses on the impact of these amygdala changes on SCD related neuropsychiatric symptoms are needed. References 1. Flaherty R, Sui YV, Li M, et al. Alzheimers Dement. 2024;20(S9):e093982. 2. Shafto MA, Tyler LK, Dixon M, et al. BMC Neurol. 2014;14(1):1-25.

OBJECTIVE:To examine the associations of LRRK2 p.G2019S, GBA1 p.N409S, polygenic risk scores (PRS), and APOE E4 on PD penetrance, risk, and symptoms. METHODS:We conducted a US-based observational case-control study using data from the 23andMe Inc. and Fox Insight Genetic Substudy (FIGS) databases. The total cohort included 7,586,842 participants (n = 35,163 PD); 8791 LRRK2 p.G2019S carriers (565 with PD), 37,427 GBA1 p.N409S carriers (524 with PD), 244 dual LRRK2/GBA1 carriers (37 with PD), and 7.5 million noncarriers (34,037 with PD). PRS was calculated from the most recently published European genome-wide association study. Survival models estimated the cumulative incidence of PD. Logistic regressions estimated the relative odds of reporting motor and non-motor symptoms according to genetic exposure. RESULTS:By the age of 80 years, the cumulative incidence of PD was 30% for dual carriers, 24% for LRRK2 p.G2019S carriers, 4% for GBA1 p.N409S carriers, and 2% for noncarriers. Higher PRS was associated with increased penetrance of the variants and earlier time to PD diagnosis. GBA1 p.N409S PD was associated with the highest burden of non-motor symptoms, including REM sleep behavior disorder and cognitive/memory deficits, and LRRK2 p.G2019S with the lowest. APOE E4 dosage was associated with greater odds of reporting hallucinations and cognitive impairment in addition to carrier status. INTERPRETATION/CONCLUSIONS:Our findings support the use of genetic screening to enrich candidate selection for neuroprotective trials and better define outcome measures based on genetics.