Introduction: Sarcoidosis is an inflammatory disease characterized by granulomas, the etiology of which remains unclear. This study examines sarcoidosis-related mortality trends in the United States from 1999 to 2020, with a focus on disparities pertaining to patient sex, geographical location, and urbanization status. Methods: We analyzed death certificate data from the CDC WONDER database, using ICD-10 code D86. Age-adjusted mortality rates (AAMR) per 1,000,000 people were calculated. Trends were analyzed using Joinpoint regression models to determine annual percentage changes (APC). Results: A total of 37,956 Sarcoidosis-related deaths were documented from 1999 to 2020 in the United States. The AAMR increased from 3.9 in 1999 to 6.4 in 2020. Significant mortality increases were observed from 1999–2001 and again from 2018–2020. Mortality rates were consistently higher among women compared to men. A significant difference in AAMR was observed across states, with highest mortality in the South region and lowest in the West region. Urbanization trends shifted from higher AAMR rates in metropolitan to non-metropolitan areas post-2018. Non-Hispanic Black individuals experienced the highest mortality rates throughout the study period. Conclusions: This study highlights significant racial and geographic disparities in sarcoidosis-related mortality. Women, Black patients, and those residing in non-metropolitan areas are at the highest risk for Sarcoidosis associated mortality. Targeted public health interventions are required to address these prevalent disparities.

Background and aim: Artificial intelligence has emerged as a transformative tool in healthcare, enhancing diagnostic accuracy, advancing genetic studies, and improving personalized medicine by reducing human error. However, its integration also raises ethical concerns such as potential bias, privacy issues, and uncertainties over decision-making authority. This study aims to evaluate the attitudes and concerns of physicians regarding the use of AI in healthcare, and to explore how these perceptions may impact its implementation in clinical practice. Subject and methods: A nation-wide cross-sectional study was conducted using an online questionnaire, based on standardized General Attitude Towards Artificial Intelligence Scale (GAAIS) and self-devised questions, aimed at collecting data about demographic details, attitude and fears of the physicians regarding AI. Using the convenience sampling technique, a sample of 393 physicians was selected. Independent-samples t-tests, one-way ANOVA, and multiple linear regression were used to analyze differences between variables. Results: The overall attitude on positive subscale of GAAIS was above neutral (mean = 3.46; SD = 0.59) with men showing a significantly better attitude than women on this subscale (MD = 0.22; CI 0.10–0.33; P = < 0.001), while the attitude on negative subscale of GAAIS was slightly below neutral (mean = 2.76; SD = 0.61). Some degree of fear regarding AI was also observed among physicians (mean = 2.66; SD = 0.67). Conclusion: Physicians have mixed views on AI, with concerns over ethical issues associated with it but not fearing replacement by it in near future. Men have a more positive attitude towards it. Integrating AI-focused curricula into medical education, along with conducting longitudinal and prospective studies, is essential to address physicians’ concerns and fully understand AI’s clinical impact.

Objectives Ventricular tachycardia (VT) in ischemic heart disease (IHD) carries a high risk of sudden cardiac death. Treatment typically involves catheter ablation or antiarrhythmic drugs (AADs), but the optimal approach is uncertain. This meta-analysis compared the safety of these treatments for VT in IHD patients. Methods This meta-analysis included all studies comparing catheter ablation with AADs in IHD patients with symptomatic VT. Databases searched included PubMed, Google Scholar, Embase, and Cochrane Library up to June 9, 2024. Primary outcomes analyzed were recurrent VT, mortality, and heart failure; secondary outcomes included hospitalizations for VT, VT storm, and appropriate anti-tachycardia pacing (AATP). Risk ratios (RR) with 95% confidence intervals (CI) were calculated using a random-effects model. Quality and bias were assessed using the Cochrane ROB 2 tool, and heterogeneity with Higgins I² statistic. Results Three studies with 430 participants were included. No significant difference was found between ablation and AADs for recurrent VT (RR = 1.08; 95%CI = 0.70–1.65; p = 0.74; I²=0%), mortality (RR = 0.98; 95%CI = 0.67–1.42; p = 0.90; I²=0%), and AATP (RR = 1.00; 95%CI = 0.84–1.20; p = 0.97; I²=0%).Heart failure (RR = 0.75; 95%CI = 0.50–1.11; p = 0.15; I²=0%), VT storm (RR = 0.77; 95%CI = 0.55–1.09; p = 0.14; I²=0%), and hospitalizations for VT (RR = 0.59; 95% CI = 0.30–1.15; p = 0.12; I²=62%) were lower with ablation but not significantly. Conclusion While no significant differences emerged, ablation showed a trend toward reducing heart failure and hospitalizations, suggesting potential advantages in managing VT-related complications in IHD. Further large-scale studies are needed to confirm these benefits.

Background Vitamin D has immunomodulatory effects, yet its influence on SARS-CoV-2 vaccine–induced antibody responses remain unclear. This study assessed the humoral immunogenicity of a Pfizer–BioNTech COVID-19 booster and whether baseline serum vitamin D levels correlate with post-booster IgG titers. Materials and Methods In this single-arm quasi‐experimental study (ERB #169/06/01/2022/S1 ERB), 54 eligible medical students received a Pfizer–BioNTech booster. Vitamin D levels and IgG titers were assessed on baseline and four weeks post-intervention. Statistical analyses included paired t-tests for pre-post IgG changes, Pearson’s correlation between vitamin D levels and IgG change, and multivariate logistic regression adjusted for gender, baseline vitamin D, BMI, and sunlight exposure. Significance was set at p < 0.05. Results The cohort (n = 54) exhibited a significant overall increase in IgG titers after booster (Δ = 4.7 ± 11.3 AU/mL, p = 0.003). Males showed a significant rise (Δ = 3.7 ± 9.9 AU/mL, p = 0.028), whereas females did not (p = 0.061). No significant correlation was found between baseline vitamin D and IgG change in the total sample (r = 0.185, p = 0.18). Stratified analysis demonstrated a positive correlation in males (r = 0.451, p = 0.05) and a non-significant negative correlation in females (r = − 0.157, p = 0.56). Logistic regression did not identify significant predictors of booster effectiveness. Conclusions The Pfizer–BioNTech booster elicits a robust IgG response in healthy young adults. Baseline vitamin D status did not uniformly influence antibody increases, though a male-specific positive association warrants further investigation. Larger, controlled studies are needed to clarify vitamin D’s role in modulating post-vaccination immunity.