Introduction The clinical manifestations of cardiac sarcoidosis vary greatly from asymptomatic presentation to significant life threatening arrhythmias . While severe heart failure and resultant cardiogenic shock are rare manifestations of cardiac sarcoidosis, prompt intervention is imperative. This retrospective study investigates the outcomes of cardiogenic shock in patients with cardiac sarcoidosis. Methodology National Inpatient Sample (2015-2020) was queried to identify all patients hospitalized for cardiogenic shock . They were classified into those with cardiac sarcoidosis and those without based on 10-CM codes. We applied discharge weight (DISCWT) provided in the database to generate the national estimates. Pearson Chi-square test for categorical variables and Student's t-tests/one-way ANOVA for continuous variables were applied to compare the baseline demographics and hospital characteristics. The categorical and continuous variables were expressed in percentages and median ± IQR respectively. Multivariable logistic regression model was used to assess the independent association of sarcoidosis with in-hospital outcomes of cardiogenic shock after adjusting for confounders . Results Of 599,260 patients admitted for cardiogenic shock, 0.49% (n=2,955) had sarcoidosis. Sarcoidosis patients, with a median age of 61 years compared to 67 in non-sarcoid patients, had higher African American (48.60% vs 14.45%, P<.001)ethnicity .They also had higher prevalence of comorbidities such as COPD, hypertension, CHF, and CKD, while obesity, hyperlipidemia, and prior MI were more common in non-sarcoid patients . Sarcoidosis was associated with higher incidence of ventricular tachycardia (aOR 1.219, 95% CI 1.115-1.332, P<0.001) and heart transplantations(aOR-2.22,95%c CI 1.84-2.67,P<0.001). Conversely, sarcoidosis was associated with lower odds of multiorgan failure, cardiac arrest, PCI and CABG .No significant difference was observed in in-hospital mortality, AKI requiring dialysis and utilization of ECMO between sarcoid and non-sarcoid patients. Sarcoidosis patients were more likely to be discharged to home health care and experienced longer hospital stays (median 9 days vs 7 days) with higher total hospitalisation costs ($36,841.47 vs $31,605.32). Conclusion Patients admitted for cardiogenic shock from cardiac sarcoidosis had no difference in mortality rates when compared to their counterparts without cardiac sarcoidosis. However, the increased prevalence of ventricular arrhythmias among individuals with sarcoidosis warrants heightened vigilance and specialized management strategies for this patient population.

Background As survival rates in gynecological oncology improve, the management of comorbid conditions like atrial fibrillation (AF) becomes increasingly important. This study aims to fill a knowledge gap by examining in-hospital outcomes of AF ablation in patients with a history of gynecological cancer. Methods A retrospective analysis of the National Inpatient Sample Database from 2016 to 2020 was conducted. We identified patients admitted for AF ablation with a history of gynecological malignancies (ovarian, cervical, breast, endometrial cancers) and compared them with non-cancer counterparts. We examined procedural complications, mortality rates, and lengths of hospital stay. Regression analysis was employed to evaluate mortality odds and hospital stay durations. Results Of 7,759,827 patients undergoing AF ablation, 37,509.99 had gynecological cancer. The mean age for patients with gynecological malignancies was 64 years, and 98.8% were female. The majority (82.8%) were Caucasian, and 83% were covered by Medicaid. Comorbidities varied between groups, with no significant difference in ablation outcomes between patients with and without gynecological cancer. Significant predictors of In-hospital mortality include prior stroke, private insurance and electrolyte imbalance prior to ablation. Conclusion Gynecological malignancies do not significantly impact mortality or procedural outcomes in AF ablation. These findings highlight the feasibility of safe and effective AF management in patients with gynecological cancer, emphasizing the importance of personalized treatment strategies in this unique patient population.

Background Tetralogy of Fallot (ToF)presents unique challenges in pregnancy, as it affects both maternal and fetal outcomes. Despite advancements in care, pregnant women with this congenital heart defect still face increased risks of adverse events. Understanding the clinical outcomes of Tetralogy of Fallot in pregnancy is crucial for optimizing maternal and fetal health, guiding management strategies, and improving overall prognosis.This study attempts to investigate the clinical outcomes of Tetralogy of Fallot in pregnancy . Methodology Utilizing the National Inpatient Sample from 2016 to 2020, we retrospectively evaluated adult deliveries, delineating patients by the presence or absence of Tetralogy of Fallot. Our primary outcome was in-hospital mortality. Secondary outcomes included obstetric and cardiac complications such as preeclampsia, perip-artum cardiomyopathy, cardiac arrhythmias, and new-onset heart failure, alongside metrics of healthcare utilization reflected by length of stay and total hospitalization costs. Results Of the total number of pregnancies identified from the years 2016 to 2020, 375 patients had Tetralogy of Fallot . Majority of the ToF patients were caucasian(55.3%), followed by Hispanic(21.7%) and Black(15.7%). 53.5% pregnancies amongst ToF patients were paid out of pocket while 43% were paid by Medicaid . Most of these deliveries took place in large teaching hospitals(50.5%). Geographical distribution saw highest occurrence of ToF deliveries in the South(34%), followed by West (26.4%) and Midwest(21.5%). 8% of the ToF patients were smokers .Concomitant uncorrected valvular disease was seen in 18.7% of the study population while obesity(5.3%) and hypothyroidism (5.3%)were identified as the most common comorbidities. Hypertension was seen in 2.7%.There was a statistically significant incidence of new onset heart failure (aOR-30.62, p<0.001) and arrhythmias (aOR- 8.81, p<0.01) in ToF pregnancies. Although the incidence of preeclampsia was higher in ToF patients, it was not found to be statistically significant . Conclusions With higher incidence of heart failure and arrhythmias, ToF pregnancies should be treated as high risk pregnancies . It is imperative to impart adequate perinatal care to those patients with ToF to optimize maternal and fetal outcomes.

Background While Ventricular Septal Defects (VSD) are common congenital anomalies, the nuances of their impact on pregnancy-related cardiovascular outcomes remain underexplored. This study bridges the knowledge gap, assessing the influence of maternal VSD on a breadth of cardiovascular outcomes and related health dynamics during pregnancy and delivery. Methods In our retrospective analysis of the National Inpatient Sample from 2016 to 2020, we identified pregnant women with Ventricular Septal Defect (VSD) and investigated delivery outcomes using mixed-effect multivariate regression, controlling for hospital characteristics and patient demographics. The primary endpoint was in-hospital mortality, while secondary outcomes encompassed both obstetric and cardiac complications—including preeclampsia, peripartum cardiomyopathy, cardiac arrhythmias, and new-onset heart failure—and healthcare utilization, as indicated by the length of hospital stay and total hospitalization costs. Results From 17.8 million patients, 450 met the inclusion criteria for VSD. In this group, mortality was 0.1%, and New Heart failure was 0.3%, with rates of myocardial infarction, stroke, and cardiovascular death similar to the non-CTD group, showing no statistical significance. No incidences of postpartum myocardial infarction or thromboembolic events were reported. Conclusion Contrary to prevailing assumptions, VSD presence in pregnant women was not synonymous with adverse delivery outcomes. The data suggest a more nuanced risk profile for pregnant women with VSD, with potential for favorable outcomes under vigilant management. These insights may recalibrate clinical perspectives on maternal VSD and inform future research in maternal-fetal health strategies.

Background Congenital cardiac septal defects are birth defects in the heart's septum leading to abnormal blood flow which includes a conglomerate of atrial septal defects (ASD), ventricular septal defects (VSD), Tetralogy of Fallot (ToF) and other undefined congenital septal defects. Our study attempts to understand the clinical outcomes of these defects during pregnancy which is essential for optimizing patient care. Methodology Utilizing the National Inpatient Sample from 2016-2020, we retrospectively evaluated adult deliveries, delineating patients by the presence or absence of congenital cardiac septal defects. Our primary outcome was in-hospital mortality. Secondary outcomes included obstetric and cardiac complications like preeclampsia, peripartum cardiomyopathy, cardiac arrhythmias, heart failure, acute kidney injury and pulmonary edema . Results Between 2016 and 2020, 9225 pregnant women were identified with congenital cardiac septal defects. The demographic profile revealed a predominant Caucasian representation (65.9%),with Hispanic and Black following at 14.7% and 13.6%, respectively. 83.7% of the cases took place in large teaching hospitals. The highest prevalence of these deliveries was observed in the South of USA (34%), with the Western (23.4%) and Midwestern (22.4%) regions trailing. Comorbidities commonly associated included obesity (12.4%),valvular disease (9.8%), depression (9.2%), hypothyroidism (5.9%), electrolyte disorders (2.7%), anemia (2.6%) and hypertension (1.4%). 16% of the women were smokers. A stark increase in mortality (aOR = 19.8, p<0.001) was observed in pregnancies complicated by these defects. There was a significant increase in the incidence of acute kidney injury (aOR = 7.2, p<0.001), pulmonary edema (aOR = 7.7, p<0.001), and pre-eclampsia (aOR = 1.5, p<0.001). Additionally, cardiovascular complications were higher in the septal defect cohort including peripartum cardiomyopathy (aOR = 20.4, p<0.001), cardiogenic shock (aOR = 24.2, p=0.002), arrhythmias (aOR = 8.5, p<0.001) and heart failure (aOR= 38.1,p<0.001). Conclusion Pregnancy in women with congenital cardiac septal defects poses complex clinical challenges, as evidenced by the outcomes of this study . Despite advancements in cardiac care, careful monitoring and multidisciplinary collaboration remain paramount in ensuring favorable outcomes.

Introduction: Patients with diabetes mellitus (DM) experience diverse cardiovascular outcomes; this study aimed to evaluate the racial disparities in cardiovascular outcomes among patients with diabetes mellitus. Method: We conducted a retrospective cohort study using the National Inpatient Sample (NIS) database 2016-2021 and ICD 10 code and identified patients with DM, categorized them based on their race. Baseline characteristics were compared using Pearson's χ2 tests and univariable linear regression. The cardiovascular outcomes were examined using multivariable logistic regression. Group comparisons were carried out using Wilcoxson signed-rank test for continuous and Pearson's χ2 tests for categorical variables. Result: We analyzed data from 47,384,595 hospitalizations for DM across racial groups in the US between 2016 and 2021. Baseline characteristics of DM among racial groups over the study period is illustrated in Table 1. The mean age was oldest among Whites (67.7 years) and Asian/Pacific Islanders (68.1 years). Cardiovascular outcomes differed across groups (Table 2). In-hospital mortality was highest among Asian/Pacific Islanders (4.3%) and lowest among Blacks (2.9%, p<0.001). Heart failure was most prevalent in Blacks (34.2%), while myocardial infarction rates were highest among Asian/Pacific Islanders (6.3%, p<0.001). Blacks and Native Americans had higher rates of ESRD (15.6% and 15.2%) than other groups, especially compared to Whites (5.8%). Amputation rates were also higher among Native Americans (6.7%) and Blacks (4.8%) than Whites (3.3%). After adjusting for demographics, hospital characteristics and comorbidities, racial minorities remained at higher risk for adverse outcomes compared to Whites. Blacks (aOR 2.19, 95%CI 2.16-2.21), Hispanics (aOR 2.54, 95%CI 2.50-2.58), Asian/Pacific Islanders (aOR 2.56, 95%CI 2.51-2.61) and Native Americans (aOR 2.87, 95%CI 2.72-3.01) all had over double the odds of ESRD. Blacks, Hispanics and Native Americans also had significantly higher adjusted odds of amputation. However, Blacks (aOR 0.66, 95%CI 0.64-0.69) and Hispanics (aOR 0.89, 95%CI 0.86-0.93) had lower odds of in-hospital mortality than Whites. Conclusion: This study highlights racial disparities in cardiovascular outcomes among hospitalizations of patients with DM. Further research should be done to explore contributing factors to these disparities to improve and curb these outcomes.

Percutaneous coronary intervention (PCI) for chronic total occlusions (CTO) presents increasing complexity in the presence of pulmonary arterial hypertension (PAH). This study aims to delineate the influence of PAH on in-hospital mortality and readmission rates among patients undergoing CTO-PCI, addressing a notable gap in current research. Analyzing data from the National Readmission Database (2016-2020), we identified patients admitted for CTO and undergoing PCI, subsequently stratifying them based on PAH diagnosis. Multivariate regression analysis was employed to examine the impact of PAH on primary (in- hospital mortality) and secondary (readmission rates) outcomes. Our findings indicated pronounced impact of PAH in the CTO-PCI patient cohort. Patients with PAH exhibited higher in-hospital mortality (1.1%) compared to non- PAH patients (0.7%). Also, the readmission rate was significantly higher in the PAH group (10.2% vs. 7% in non-PAH patients). PAH patients were older (mean age 72 vs. 66, p = 0.001) and had a higher prevalence of comorbid conditions such as congestive heart failure, electrolyte derangement, diabetes mellitus, acute kidney injury and longer hospital stays. This study reported heightened risks associated with PAH in patients undergoing CTO-PCI. This finding should be a call for enhanced clinical vigilance in care of this patients. Further research works in this field would help to develop guidelines in the care of the demographic.

Mechanical circulatory support (MCS) has markedly improved the management of advanced heart failure. However, rehospitalization (RH) remains a significant challenge in MCS patients. This study leverages machine learning to identify critical predictors of RH, aiding in risk stratification and treatment optimization. Utilizing the MedaMACS dataset, which includes demographic and clinical data on 171 MCS patients, we deployed four machine learning models: logistic regression, random forest, support vector machine, and multi-layer perceptron. The models were trained and evaluated using MedaMACS data. Feature importance scores were assigned to each variable in the random forest model, determining their predictive power for RH. Logistic regression and support vector machine models demonstrated the highest accuracy in RH prediction, with an Area Under the Curve (AUC) of 0.85 each, outperforming the random forest (AUC = 0.71) and multi-layer perceptron (AUC = 0.65) models. The random forest analysis identified key RH predictors, such as systemic blood pressure, ventricular assist device (VAD) related factors, and aortic insufficiency. Our findings underscore the efficacy of logistic regression and support vector machine models in predicting RH risk in MCS patients. The identification of crucial predictive factors like systemic blood pressure and VAD-specific issues provides valuable insights for clinicians. This study paves the way for more effective, personalized treatment strategies, potentially reducing RH rates in this patient population.

Mechanical circulatory support (MCS) has markedly improved the management of advanced heart failure. However, rehospitalization (RH) remains a significant challenge in MCS patients. This study leverages machine learning to identify critical predictors of RH, aiding in risk stratification and treatment optimization. Utilizing the MedaMACS dataset, which includes demographic and clinical data on 171 MCS patients, we deployed four machine learning models: logistic regression, random forest, support vector machine, and multi-layer perceptron. The models were trained and evaluated using MedaMACS data. Feature importance scores were assigned to each variable in the random forest model, determining their predictive power for RH. Logistic regression and support vector machine models demonstrated the highest accuracy in RH prediction, with an Area Under the Curve (AUC) of 0.85 each, outperforming the random forest (AUC = 0.71) and multi-layer perceptron (AUC = 0.65) models. The random forest analysis identified key RH predictors, such as systemic blood pressure, ventricular assist device (VAD) related factors, and aortic insufficiency. Our findings underscore the efficacy of logistic regression and support vector machine models in predicting RH risk in MCS patients. Identifying crucial predictive factors like systemic blood pressure and VAD-specific issues provides valuable insights for clinicians. This study paves the way for more effective, personalized treatment strategies, potentially reducing RH rates in this patient population.

Extracorporeal Membrane Oxygenation (ECMO) in critical care cardiology has increased, yet its clinical outcomes in pulmonary embolism (PE) remain partially understood. This study scrutinizes the in -hospital outcomes of ECMO in patients with unstable PE. Utilizing data from the National Readmission Database from 2016 to 2020, we identified patients presenting with unstable PE, dividing them based on ECMO treatment. Multivariate regression analysis was employed to evaluate ECMO's impact on primary (in-hospital mortality) and secondary outcomes (readmission rates and complications). Table I shows baseline characteristics, and Table II shows the outcome. In patients with pulmonary embolism (PE), those receiving Extracorporeal Membrane Oxygenation (ECMO) showed higher in-hospital mortality (45% vs. 5%, p < 0.0000) and acute kidney injury (AKI) (69.4% vs. 22%, p < 0.000) compared to non-ECMO patients. ECMO treatment resulted in longer hospital stays (22 vs. 5 days, p < 0.000) and higher hospitalization costs. The 30-day readmission rate was lower in ECMO patients (2.9% vs. 7%, p < 0.0000). Major predictors of readmission and mortality included age, AKI, and LOS. ECMO use in unstable PE is associated with higher in-hospital mortality, increased complications, particularly AKI, and a longer LOS, albeit with a lower readmission rate likely due to the high mortality rate in the index admission. This study underscores the need for careful patient selection and highlights the risk factors that may influence outcomes in ECMO-managed PE patients.

Introduction: Post-myocardial infarction (MI) pericarditis, particularly after percutaneous coronary intervention (PCI), presents with distinct clinical, laboratory, and electrocardiographic features. Despite its unique presentation, no dedicated diagnostic tools exist for this condition in the post-PCI setting, highlighting the need for a tailored approach. This study aims to develop and validate the first comprehensive clinical scoring system specifically designed to accurately diagnose post-MI pericarditis following PCI, utilizing data available at admission. Methods: In this diagnostic case-control study, we compared 60 patients with confirmed post-PCI pericarditis (verified by echocardiography) from our PCI Registry with 120 control patients with various diagnoses from our hospital database. We evaluated 26 potential predictors, including clinical characteristics, chest pain descriptors, and additional diagnostic tests. Independent predictors for the scoring model were identified using stepwise logistic regression. Results: Among the 17 initial variables associated with pericarditis, five independent predictors were identified: age, chest pain exacerbation with thoracic movement, rising troponin levels, diffuse ST-segment elevation, and C-reactive protein levels. These predictors were incorporated into a scoring system based on their regression coefficients. The model demonstrated excellent discrimination, with a C-statistic of 0.97 (95% CI: 0.93-1.0). A score above 6 points yielded a sensitivity of 95% (95% CI: 85-100) and specificity of 86% (95% CI: 78-93), with positive and negative likelihood ratios of 7.2 (95% CI: 4.2-12) and 0.05 (95% CI: 0.01-0.2), respectively, Figure 1. Conclusion: We have developed the first multivariate scoring system specifically designed to identify post-MI pericarditis in patients undergoing PCI. Its promising accuracy has the potential to enhance early recognition, streamline diagnostic processes, and ultimately improve patient outcomes.