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.

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.

Background: Diabetes mellitus significantly elevates the risk of sepsis and exacerbates its clinical outcomes, leading to increased mortality rates. Despite the importance of this association, the demographic and geographic patterns influencing it remain inadequately understood. Methods: Utilizing data from CDC WONDER (1999–2020), we conducted an analysis of mortality trends among U.S. adults aged 65 and older, stratified by gender, race/ethnicity, and geographic region. Age-adjusted mortality rates (AAMRs) and annual percentage changes (APCs) were evaluated using the Joinpoint Regression methodology. Results: Between 1999 and 2020, there were a total of 287,738 deaths attributed to diabetes and sepsis. The AAMR decreased from 33.6 per 100,000 population in 1999 to 27.7 in 2014; however, it subsequently surged to 38.4 by 2020 (APC: 13.65). The male AAMRs reached a peak of 39.1 in 2005, declined to 31.2 in 2012, and then increased to 46.9 in 2020 (APC 12.29). Female AAMRs decreased from 32.6 in 1999 to 24.8 in 2018, before rising again to 31.9 in 2020 (APC 13.66). Among African Americans, mortality declined to 46.3 in 2019 but experienced a sharp increase to 65.7 in 2020 (APC 20.52). The Hispanic AAMR also increased during this period (APC 25.05). The southern region consistently exhibited the highest mortality rates, rising from 31.7 in 2018 to 42.5 in 2020 (APC 13.69), with notable rises observed in the Midwest (APC 14.59). All these trends were statistically significant ( p < 0.05). Furthermore, non-metropolitan areas consistently demonstrated higher mortality rates, with significant increases observed between 2018 and 2020. Conclusion: The mortality rates associated with diabetes-related sepsis have recently risen, particularly between 2018 and 2020, thereby highlighting significant health disparities. It is essential to implement targeted healthcare interventions.

Background: Cardiopulmonary resuscitation (CPR) is a vital intervention for managing cardiac arrest; however, enhancing survival rates remains a significant challenge. Recent advancements highlight the importance of integrating artificial intelligence (AI) to overcome existing prediction, intervention, and post-resuscitation care limitations. Methods: A thorough review of contemporary literature regarding AI applications in CPR was undertaken, explicitly examining its role in the early prediction of cardiac arrest, optimization of CPR quality, and enhancement of post-arrest outcomes. The analysis incorporated data from machine learning models, biosignal-responsive robotics, and advanced monitoring systems to showcase advancements and identify future challenges. Results: Innovations driven by AI have significantly transformed CPR practices across multiple areas. Predictive algorithms leveraging electronic health records and continuous electrocardiogram (ECG) monitoring facilitate the early identification of at-risk patients. Additionally, AI-enhanced feedback systems improve the accuracy of chest compressions and minimize variability in manual execution. Integrating AI with automated external defibrillators (AEDs) and real-time ECG analysis increases defibrillation precision and reduces interruptions during CPR. Emerging technologies, including wearable devices, immersive training simulators, and drone-delivered defibrillators, show considerable potential in addressing response time disparities during out-of-hospital cardiac arrests. Nevertheless, ethical considerations, particularly regarding data privacy and equitable access, pose significant challenges. Conclusions: Integrating AI into CPR practices can enhance prediction accuracy, procedural effectiveness, and survival rates. Addressing the ethical, legal, and technological barriers to successful implementation in clinical settings is crucial.

Background: Disparities in management of atrial fibrillation in rural and urban hospitals across the U.S. have been reported. However, studies investigating disparities regarding outcomes and complications after left atrial appendage occlusion (LAAO) based on hospital location are lacking. Objective: To evaluate differences in outcomes and complications related to LAAO among rural and urban hospitals. Methods: The National Inpatient Sample was used to identify patients who underwent LAAO implantations in the U.S. from 2016−2020. Study endpoints assessed included inpatient complications, outcomes, and resource utilization after LAAO procedures among rural and urban hospitals. Results: From 2016−2020, there were a total of 87 315 and 1985 LAAO device placements in urban and rural hospitals, respectively. Baseline characteristics were similar among both groups, with a few exceptions. After multivariable adjustment for confounders, odds of inpatient complications and mortality were similar among both groups. However, rural LAAO recipients experienced greater rates of discharge to an acute care facility (3.3% vs 2.4%, p = 0.01), as well as lower costs (aOR: 0.58, 95% CI: 0.49–0.69) and length of stay (aOR: 0.89, 95% CI: 0.81–0.98). Conclusions: A majority of LAAO implantations occurred in urban hospitals in the U.S. Baseline characteristics and adjusted odds of inpatient complications and mortality were similar in rural and urban recipients. However, important differences were described regarding resource utilization and disposition. Further investigation into the specific factors driving these inequities is encouraged to promote improved access to and outcomes of cardiovascular care for rural residents.

Respiratory Syncytial Virus (RSV) causes over 50,000 hospitalizations annually among children under five years of age, leading to long-term consequences, such as asthma. Monoclonal antibodies (mAb) have been recommended for prevention, but their limitations have prompted the search for alternative preventive measures. The recent Food and Drug Administration (FDA) approval of a maternal RSV vaccine with 80% efficacy in protecting infants up to 90 days post-birth marks a significant advancement. Our narrative review investigates the differences in RSV immunization in pregnant mothers versus infants and children, with the goal of identifying factors that influence parental decisions. This study provides insights for optimising preventive strategies, and the results highlight the importance of maternal vaccination in combating RSV in children.