Advocate Illinois Masonic Medical Center is a 408-bed non-profit teaching hospital located in Chicago. Founded in 1897, the hospital operates a Level I trauma center and Level III Perinatal Center. Its license number is 0005165. The hospital is a part of Advocate Aurora Health. Each year, the hospital provides services for 18,000 inpatients, more than 152,000 outpatients and 41,000 emergency patients. Approximately 300 physicians are trained each year through its affiliations with the University of Illinois College of Medicine, the Chicago Medical School and the Chicago College of Osteopathic Medicine.
Spontaneous coronary artery dissection (SCAD) is an increasingly recognized cause of acute coronary syndrome, especially in younger patients and women. Anemia, a common comorbidity in patients with cardiovascular disease, may modulate outcomes in SCAD, but its influence remains poorly defined. We identified adult hospitalizations for SCAD in the Nationwide Inpatient Sample (2016–2022), stratified by anemia status. Multivariable logistic regression models were constructed to examine the relationship between anemia and in-hospital outcomes, while adjusting for demographics, comorbidities, and hospital characteristics. The primary outcome was all-cause in-hospital mortality. Secondary outcomes included cardiac arrest (CA), mechanical circulatory support (MCS), cardiogenic shock (CS), heart failure reduced ejection fraction (HFrEF), heart failure preserved ejection fraction (HFpEF), blood transfusion (BT), vasopressor use (VU), mechanical ventilation (MV), acute kidney injury (AKI), atrial fibrillation (AF), length of stay (LOS) and total hospital charges (THC). Among 63,450 SCAD hospitalizations, 24.8
Cardiovascular disease is the leading cause of death worldwide, accounting for about a third of all deaths. Traditional risk factors like hypertension, diabetes, dyslipidemia, and obesity are well known, but iron also plays a crucial role in heart health. Iron is essential for oxygen transport, mitochondrial function, and heart muscle activity, and both deficiency and overload can harm cardiovascular outcomes. This review examines studies on iron metabolism, regulation via the hepcidin-ferroportin pathway, myocardial energy, oxidative stress, and clinical trials of iron supplementation or reduction in heart failure, chronic kidney disease, the elderly, women, and athletes. Iron deficiency affects over 60
Preoperative psychological stress is a highly prevalent but mostly underrecognized factor influencing perioperative physiology and postoperative outcomes. This narrative review synthesizes current evidence on the known mechanisms connecting preoperative stress to adverse surgical outcomes, with particular emphasis on HPA axis functioning, cortisol dynamics, inflammatory signaling and pain modulation. Elevated preoperative anxiety affects a substantial proportion of surgical patients and is consistently associated with increased analgesic and anesthetic requirements, higher postoperative pain intensity, greater risk of chronic postsurgical pain, neuropsychiatric complications, metabolic dysregulation and postoperative infections. Stress-related elevations in cortisol and pro-inflammatory cytokines, particularly interleukin-6, appear to mediate these effects through interactions with immune, metabolic, and central nervous system pathways. Stress-related pain modulation is reflected not only in experimental models but also in clinically measurable outcomes, underscoring its relevance for perioperative care. Despite growing recognition of these associations, standardized strategies for integrating stress assessment and biomarkers into perioperative risk stratification remain limited. Given that preoperative stress is potentially modifiable, targeted psychological, analgesic, and metabolic interventions may represent valuable opportunities to improve recovery, reduce complications, and prevent pain chronification.
Background The use of mortality data in public health research has surged with the rise of open-access databases such as CDC WONDER. However, caution is needed when defining the relationship between ICD codes and when transitioning from older to newer versions of the data. This review provides a practical, step-by-step guide to using the CDC WONDER mortality database. Methods We outline key functionalities of the CDC WONDER interface, explain mortality rate calculations, and describe best practices for configuring queries using underlying and multiple causes of death. The review further introduces Joinpoint regression to identify temporal trend changes and compares forecasting approaches using traditional ARIMA models and modern deep learning architectures. Results Using illustrative examples and visual guides, we demonstrate how data interpretations can vary significantly depending on query configuration, Boolean logic (AND vs. OR), and coding practices. We highlight the strengths and limitations of different analytical strategies and show how misinterpretation can arise from common errors, such as misunderstanding age adjustment or combining ICD codes without appropriate logic. Conclusion CDC WONDER is a powerful tool for mortality analysis, but its effective use requires a clear understanding of its data structure, coding logic, and statistical tools. Joinpoint regression and forecasting models complement WONDER data by enabling trend segmentation and future projections. This guide empowers researchers to use these tools accurately, improving the rigor and reproducibility of public health research.
Caffeine, predominantly consumed through coffee and tea, has received growing attention for its potential cardioprotective actions. Evidence suggests a non-linear association between habitual intake and cardiovascular risk, with moderate consumption offering the most favorable profile. Given that caffeine is often ingested within complex beverage matrices, distinguishing the effects of pure caffeine from those of coffee components and preparation methods is essential for accurate interpretation. This study synthesizes findings from epidemiological research, Mendelian randomization analyses, mechanistic experiments, and clinical trials to evaluate caffeine’s cardiovascular impact. We assess key outcomes such as coronary artery disease, heart failure, stroke, hypertension, and arrhythmias. Mechanistic pathways are explored, including adenosine receptor antagonism, modulation of autonomic tone, influences on endothelial function and arterial stiffness, anti-inflammatory and antioxidant effects, and indirect metabolic actions on glucose and lipid regulation. Additional analyses examine how genetics, comorbid conditions, and concomitant medications may modify individual responses. Integrated evidence from observational studies demonstrates a non-linear, J-shaped association between coffee and caffeine intake and cardiovascular outcomes, with moderate consumption associated with the lowest observed risk; however, Mendelian randomization analyses generally do not support a clear causal protective effect of caffeine. Pure caffeine and coffee-derived effects diverge in several respects: unfiltered coffee may elevate lipid levels due to diterpenes, whereas filtered coffee generally has neutral lipid effects. Habitual use is shown to attenuate the acute pressor response through tolerance development. Variability in cardiovascular responses is influenced by genetic polymorphisms, baseline blood pressure phenotype, concurrent illnesses, and interacting medications. Overall, moderate caffeine intake generally appears safe for cardiovascular health. The cardioprotective links seen in epidemiological studies may be affected by coffee components, how it is prepared, and residual behavioral confounding, while solid evidence for a direct protective effect of caffeine is still limited. Remaining uncertainties highlight the need for future trials that isolate caffeine’s dose–response from coffee matrices, incorporate genotype-based stratification, evaluate baseline hemodynamic phenotypes, and use standardized clinical endpoints. Such work is essential to clarify causal pathways and optimize the clinical relevance of caffeine-related recommendations.
