Optical coherence tomography (OCT) with retinal segmentation analysis is a valuable tool in assessing axonal loss and neuro-degeneration in multiple sclerosis (MS) by in-vivo imaging, delineation and quantification of retinal layers. There is evidence of deep retinal involvement in MS beyond the inner retinal layers. The ultra-structural retinal changes in MS in different MS phenotypes can reflect differences in the pathophysiologic mechanisms. There is limited data on the pattern of deeper retinal layer involvement in progressive MS (PMS) versus relapsing remitting MS (RRMS). We have compared the OCT segmentation analysis in patients with relapsing-remitting MS and progressive MS. Cross-sectional study of 113 MS patients (226 eyes) (29 PMS, 84 RRMS) and 38 healthy controls (72 eyes). Spectral domain OCT (SDOCT) using the macular cube acquisition protocol (Cirrus HDOCT 5000; Carl Zeiss Meditec) and segmentation of the retinal layers for quantifying the thicknesses of the retinal layers. Segmentation of the retinal layers was carried out utilizing Orion software (Voxeleron, USA) for quantifying the thicknesses of individual retinal layers. The retinal nerve finer layer (RNFL) (p = 0.023), the ganglion-cell/inner plexiform layer (GCIPL) (p = 0.006) and the outer plexiform layer (OPL) (p = 0.033) were significantly thinner in PMS compared to RRMS. There was significant negative correlation between the outer nuclear layer (ONL) and EDSS (r = -0.554, p = 0.02) in PMS patients. In RRMS patients with prior optic neuritis, the GCIPL correlated negatively (r = -0.317; p = 0.046), while the photoreceptor layer (PR) correlated positively with EDSS (r = 0.478; p = 0.003). Patients with PMS exhibit more atrophy of both the inner and outer retinal layers than RRMS. The ONL in PMS and the GCIPL and PR in RRMS can serve as potential surrogate of disease burden and progression (EDSS). The specific retinal layer predilection and its correlation with disability may reflect different pathophysiologic mechanisms and various stages of progression in MS.

Background: Neuroimaging has a pivotal role in the diagnosis, management, and prognostication of acute ischemic stroke (AIS). Developments have improved the ability to identify large vessel occlusions (LVO), delineate salvageable tissue, and guide acute therapeutic interventions. This review aimed to provide an overview of neuroimaging modalities used in AIS evaluation, highlighting their practical applications, recent advancements, and limitations. Methods: We conducted a narrative review of the literature, focusing on non-contrast CT (NCCT), CT angiography (CTA), CT perfusion (CTP), MRI, MR angiography (MRA), digital subtraction angiography (DSA), and transcranial Doppler ultrasonography (TCD). Additionally, we examined emerging trends, such as virtual NCCT, sonothrombolysis and direct-to-angio suite (DTAS) approach. Key aspects, including diagnostic accuracy, clinical utility, and emerging technologies were evaluated. Findings: NCCT remains the cornerstone for initial AIS assessment due to its availability and its ability to assist in rapid decision making. CTA and CTP are integral for detecting LVO and assessing penumbra, respectively, with automated systems enhancing speed and accuracy. MRI helps identify early ischemic changes and rule out stroke mimics. MRA and DSA provide detailed vascular assessments, while TCD offers hemodynamic monitoring and a potential therapeutic role. Limitations include variability in perfusion imaging, MRI availability, and operator dependency in TCD. Emerging techniques like dual-energy CT and AI-driven algorithms enhance diagnostic precision. Conclusion: Neuroimaging is essential for effective AIS management, with each modality carrying variable strengths and limitations. Continued advancements, standardization and a multi-modal approach are needed to optimize outcomes. Clinical-radiological correlation remains indispensable to reach accurate diagnosis and treatment.

Background: Alzheimer’s disease (AD) is the fifth leading cause of death for Americans older than 65. Though fluctuations have been noticed over the past two decades, the mortality of Alzheimer’s patients increased considerably during the COVID-19 pandemic. This study aims to explore the temporal trends in AD-associated mortality (ADAM) and disparities in these trends, and we aim to discern changes to these trends during the COVID-19 pandemic. Methods: The CDC WONDER Multiple Cause-of-Death Public Use Records from 1999 to 2022 were used to extract population data on deaths related to AD and stratify them based on age, biological sex, race, ethnicity, place of death, census region, and state. ICD-10 codes G30.0, G30.1, G30.8, and G30.9 were used to identify AD-related mortality. Statistical analysis was performed using the Joinpoint Regression Program version 5.0.2. Results: We confirmed an increase in mortality rate in all races, sexes, places of death, age groups above 65, and states/census regions. Interestingly, the age-adjusted mortality rate (AAMR) of AD was consistently higher in females compared to males. Non-Hispanic whites had the highest AD mortality by race and ethnicity. At the intersection of race and biological sex, White females had the highest AAMR with AD. Lastly, we noted an increase in AD mortality at hospice facilities as compared to other places of death. Conclusions: Our findings demonstrate that the number of deaths due to AD was exacerbated by the recent pandemic and that White females were disproportionately affected. The disparities relating to ADAM uncovered in this study may assist healthcare administrators and policymakers in their decisions. Additionally, the findings might help initiate larger studies focusing on these disparities to explore novel risk/prognostic factors for AD.

Background: Parkinson’s disease (PD) is a progressive neurodegenerative condition characterized by the degradation of dopaminergic pathways in the brain. As the population in the United States continues to age, it is essential to understand the trends in mortality related to PD. This analysis of PD’s mortality characterizes temporal shifts, examines demographic and regional differences, and provides machine-learning predictions. Methods: PD-related deaths in the United States were gathered from CDC WONDER. Age-adjusted mortality rates (AAMR) were collected, and trends were analyzed based on gender, race, region, age, and place of death. Annual percent change and average annual percent change were calculated using Joinpoint Regression program. Forecasts were obtained using the optimal Autoregressive Integrated Moving Average (ARIMA) model. Results: Overall mortality rate due to Parkinson’s increased from 1999 to 2022. Male gender, White race, Southern region, and older ages were associated with higher mortality compared to other groups. Deaths at home decreased and hospice deaths increased during the study period. Conclusions: This study highlights the increasing rate of PD AAMR and how it may become even more prevalent with time, emphasizing the value of increasing knowledge surrounding the disease and its trends to better prepare health systems and individual families for the burden of PD.

The prevalence and incidence of myasthenia gravis (MG) have been increasing, globally and in the United States. The literature lacks data on MG-related mortality (MGRM) and its trends in the United States. We aimed to examine nationwide demographic and geographic trends of MGRM from 1999 to 2022. This retrospective population-based study used data regarding MG-related deaths (MGRD) from Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research mortality records. The International Classification of Diseases (ICD) code, G70.0, was used to identify MG. We stratified deaths by sex, age groups (25-64 years and older than 64 years), race and ethnicity, and geographical location. Joinpoint regression was performed to examine trends in age-adjusted mortality rates (AAMRs). Sensitivity analysis was performed using MG as an underlying cause of death (UCD). During the study period, there were 37,075 MGRD (89.6% were older than 64 years, and 44.7% were female individuals). From 1999 to 2022, the MG-related AAMR increased significantly from 6.21 (95% CI 5.58-6.58) per 1 million population to 9.51 (95% CI 9.14-9.88) per 1 million population, with an average annual percent change of +2.42 (95% CI 1.98-2.87). The increase in MGRM was observed regardless of age group, sex, region, or race and ethnicity. The MG-related AAMR increased by 66.3% in male individuals and 29.6% in female individuals over the study period. For individuals aged 65 years or older, there was a concerning increase in MG-related AAMR by 82.35% from 28.23 to 47.36. There was a peak in MGRM during the coronavirus disease 2019 pandemic (2020-2022), and sensitivity analysis revealed that the trend in MGRM remained consistent as both UCD and contributing cause of death. The rising MGRM over the 23-year period is concerning and warrants investigation into the underlying causes for this trend. This increase was most prominent in older and male individuals. The growing burden of MG in the United States and globally might pose a serious challenge to health care in the future. Limitations of this study include reliance on ICD codes. Future work needs to take these trends and disparities into consideration and focus on improving MGRM.