Background Stroke is a leading cause of death in the U.S., with mortality trends influenced by hyperlipidemia, a significant risk factor for atherosclerosis and cardiovascular disease that can lead to ischemic stroke. This analysis examines stroke-related mortality in hyperlipidemia among adults aged 25 and older from 1999 to 2023. Methods A retrospective analysis of CDC WONDER investigated trends in mortality from Stroke (ICD codes: I60-I69) among Hyperlipidemia patients (ICD codes: E78.0, E78.1, E78.3, E78.4, E78.5) aged 25 and older. Joinpoint regression analysis calculated age-adjusted mortality rates (AAMR) per 100,000 individuals, annual percentage changes (APC), Average Annual Percent Change (AAPC), and 95% confidence intervals. Results Between 1999 and 2023, stroke and hyperlipidemia caused 241,308 deaths, with AAMRs of 1.38 in 1999 and 7.46 in 2023, an AAPC of + 7.16 (95% CI: 6.66 to 8.52). Adult men had higher AAMRs than women, with increases for both sexes [AAPC: + 7.20 vs. + 7.10; p < 0.001]. Black individuals had the highest AAMRs, followed by Hispanics. AAMR rose for all races, notably for Blacks/African Americans (AAPC: + 8.63%) and adults aged 65 and above (AAPC: + 7.35%). Northeast regions have the highest AAMRs, with the Midwest showing the most significant rise (AAPC: + 7.86%). AAMRs varied by state, from 2.0 in Georgia to 9.43 in Vermont in 2023. Non-metropolitan areas had higher AAMRs (4.31) than metropolitan areas (3.54). Conclusion This analysis reveals significant demographic and racial disparities in Stroke mortality among U.S. adults with Hyperlipidemia, which highlights the urgent need for targeted, equity-focused interventions to address these disparities.

Epilepsy is one of the most common neurological diseases globally. We conducted a systematic review of the genetic markers and personalized treatment strategies used in the precision medicine treatment of epilepsy. An exhaustive electronic search was carried out on PubMed and Google Scholar, spanning from inception up to June 2023 on epilepsy and biomarkers. A total of 45 articles from PubMed and 19 articles from Google Scholar were imported and screened based on studies that focused primarily on genetic markers and precision methods for epilepsy subtyping, treatment strategies, outcomes, and adverse effects. Reviews and studies not in English were excluded. Full‐text data extraction, coding, and analysis were carried out with Microsoft Excel. For the risk of bias assessment of the final included studies, the Critical Appraisal Skills Program checklist was used. A total of 19 studies were analyzed in the review. The SLC35A2 gene saw a reduction in seizure frequency with d‐galactose treatment while the KCNQ2 gene saw improvement with phenytoin, carbamazepine, and retigabine. GRIN2D gene saw varying improvements with memantine. KCNT1 gene saw improvement with only a combination of quinidine and topiramate, quinidine was not useful when used alone. Other studies involved the identification of different markers using gene and exome sequencing. These studies collectively provide a diverse range of insights into epilepsy, with variations in study design, sample size, age groups, and diagnostic criteria, highlighting the multifaceted nature of epilepsy research. These studies contribute to our understanding of epilepsy diagnosis and management in different clinical settings, however, there were some limitations such as QT prolongation was observed with specific medications and participant heterogeneity. Small sample sizes reduced statistical power and brief durations of studies limited their ability for long‐term analysis. Although most studies had a low risk of bias, two studies demonstrated some reporting bias. Fianlly, the absence of biomarkers is a limitation that impedes the study's capacity to explore underlying biological mechanisms.

Background: Epilepsy poses significant challenges globally, with varied clinical, social, and economic impacts. Despite advances in treatment, epilepsy-related mortality remains a concern. This study aimed to analyze the demographic and regional distributions of epilepsy-related mortality in the United States (U.S.) from 1999 to 2020, identifying high-risk populations for targeted interventions. Methods: Data on death certificates were obtained from the 1999 to 2020 Centers for Disease Control and Prevention Wide-Ranging Online Study Epidemiologic Research (CDC-WONDER) database. We gathered data on demographics, place of death, and urban/rural classification. Mortality rates per 100,000 people were computed and classified according to state, year, sex, race/ethnicity, and urban/rural status. Trends were examined using Joinpoint regression. Results: A total of 12,573 deaths (age <35), 22,947 (35–64), and 21,782 (65+) were attributed to epilepsy. Mortality rates varied by age group, sex, race/ethnicity, and region. Trends showed significant increases, notably in middle-aged and older adults, with higher rates in males and nonHispani, African American populations. Conclusion: Epilepsy-related mortality exhibits demographic and regional disparities in the U.S. Understanding these patterns can guide targeted interventions to mitigate mortality risk.

Cervical cancer screening has evolved from conventional Pap smears to liquid‐based cytology and HPV DNA testing, and now increasingly leverages AI-driven image analysis. Modern AI approaches – especially convolutional neural networks (CNNs) – can automatically detect and classify cells in digital cytology and whole‐slide images. Emerging transformer‐based models further integrate multimodal data (HPV status, cytology, colposcopy images) to enhance diagnostic sensitivity and reduce missed cases. These tools markedly increase detection rates while alleviating the burden on human screeners. In practice, portable AI-assisted devices are being fielded: for example, smartphone colposcopes with embedded deep learning have demonstrated CIN2+ sensitivities (>90%) that exceed expert readers. Cloud-linked systems (e.g. MobileODT’s EVA Scope) enable centralized analytics and regular model updates, while on-device AI can operate offline for low-connectivity settings. However, limitations remain. Algorithmic bias from non-representative training data can skew performance, and the “black box” nature of deep models raises interpretability and trust issues. Regulatory and privacy gaps must be addressed – clear guidelines are needed to ensure patient data security and to define AI’s role as an adjunct (not a replacement) to clinician judgment. Moving forward, robust validation in diverse populations, human–AI collaboration in screening workflows, and equitable deployment in underserved regions are essential. By coupling AI with human expertise and broad access, these innovations can help reach WHO targets (70% screening by 2030) and accelerate progress toward global cervical cancer elimination

Background: Atrial fibrillation (AF) is a prevalent arrhythmia that frequently coexists with cardiomyopathy, leading to deteriorated cardiovascular outcomes. Analyzing the trends associated with these conditions is essential for improving prevention strategies and management practices. Methods: CDC WONDER (1999–2023) data were analyzed to assess AF with cardiomyopathy‐related mortality in patients aged ≥ 25. Using Joinpoint regression analysis, we calculated age‐adjusted mortality rates (AAMRs) per 100,000 patients and average annual percentage changes (AAPCs) to analyze mortality trends. Results: AF with cardiomyopathy is responsible for 126,377 deaths among adults aged 25 and older. Alarmingly, AAMRs have surged from 1.8 per 100,000 in 1999 to 3.0 in 2023 (AAPC: 2.11, p < 0.001). The upward trend remains pronounced, particularly between 2016 and 2021, with an annual percentage change of 6.17 ( p = 0.02). Disparities in mortality rates are striking. Men face a higher AAMR than women (3.1 vs. 1.5), and Black individuals bear the heaviest burden at 2.4, closely followed by Whites at 2.3. Regionally, Vermont stands out with the highest AAMR at 3.6, while New York reports the lowest at 1.3. Both rural and urban areas maintain equal AAMRs of 2.1, yet the increase in rural regions is particularly concerning, reflecting an AAPC of 2.44 compared to 1.78 in urban settings. Conclusion: The rising mortality rates from AF with cardiomyopathy in patients, particularly among men, Black individuals, and rural residents, demand urgent action. These concerning trends underscore a public health crisis that must be addressed.