Background: Clinical outcomes among older adults hospitalized with heart failure with preserved ejection fraction (HFpEF) in the setting of metabolically healthy obesity (MHO) remain insufficiently explored. This study aimed to evaluate whether MHO status is associated with different rates of major adverse cardiac and cerebrovascular events (MACCEs) during HFpEF-related hospitalizations compared to patients without MHO. Methods: Data from the 2019 National Inpatient Sample (NIS) database was analyzed using relevant ICD-10 codes to identify HFpEF admissions in older adults. Propensity score matching (1:1) was applied to generate balanced cohorts of patients with and without MHO. Multivariable adjustments were performed to assess primary outcomes, including MACCEs, all-cause mortality (ACM), acute myocardial infarction (AMI), dysrhythmia, cardiac arrest (CA), and stroke. Statistical significance was set at p < 0.05. Results: Each MHO cohort included 22,405 patients with a median age of 75 years. The MHO+ group demonstrated a significantly higher risk of dysrhythmia (OR 1.32, 95% CI 1.21–1.43, p < 0.001). Interestingly, an “obesity paradox” was observed, as the MHO+ cohort had lower odds of MACCEs (OR 0.70, 95% CI 0.61–0.81, p < 0.001), ACM (OR 0.66, 95% CI 0.54–0.82, p < 0.001), and AMI (OR 0.71, 95% CI 0.59–0.86, p = 0.001) compared to MHO−. No significant differences were found for CA or stroke between the groups. Conclusions: Although the MHO+ group had an elevated risk of dysrhythmia, they exhibited more favorable outcomes in terms of MACCEs, ACM, and AMI—supporting the concept of an “obesity paradox.” Further research is needed to better understand the role of MHO as a comorbid condition in patients with HFpEF.

Background: Heart failure with preserved ejection fraction (HFpEF) is a major cause of hospitalization and mortality in older adults. Sudden cardiac arrest (SCA) is a leading cause of death in this population, yet national trends in incidence, outcomes, and disparities remain poorly defined. Methods: We performed a retrospective cohort study using the National Inpatient Sample from 2016 to 2020. Hospitalizations for patients aged ≥65 years with HFpEF and in-hospital cardiac arrest (CA) were identified using ICD-10-CM codes. Demographics, comorbidities, hospital outcomes, and temporal trends were examined. The primary outcome was in-hospital mortality. Secondary outcomes included length of stay, hospital charges, and discharge disposition. Results: Among 7,738,108 HFpEF admissions, 93,440 (1.2%) involved CA. Incidence rose from 1.1% in 2016 to 1.5% in 2020 (36% relative increase). The median age was 81 years; 54% were female, 70% White, 19% Black, and 8% Hispanic. CA incidence increased across all groups, with the largest relative rises among Native American (1.0% to 1.9%), Black (1.7% to 2.3%), and Hispanic patients (1.4% to 2.0%). In-hospital mortality was high, increasing from 58.2% to 61.7% over the study period (p < 0.001). Mortality rose most steeply among Black and low-income patients. Comorbidity patterns shifted toward greater metabolic complexity, including higher rates of complicated diabetes, hypertension, hyperlipidemia, and obesity. Conclusions: Elderly patients hospitalized with HFpEF are experiencing rising rates of in-hospital CA and persistently high mortality, with marked racial and socioeconomic disparities. These findings highlight the need for better risk stratification, targeted metabolic and inflammatory therapies, and more equitable care delivery.

Radiation therapy (RT) is associated with cardiovascular complications, such as atrial fibrillation (AF). The prevalence of AF in patients with cancer rece

Background: Secondary pulmonary hypertension (SPH) predicts poor outcomes in obstructive sleep apnea (OSA) patients. This study examines sex/racial disparities, predictors, and inpatient mortality in SPH-related OSA hospitalizations. Methods: We used the National Inpatient Sample (2019) and ICD-10 codes to identify OSA-related hospitalizations with SPH. The burden of SPH and disparities by sex/race were assessed. We also compared the odds and predictors of in-hospital mortality in OSA patients with vs. without SPH. Results: Of total adult OSA hospitalizations (n = 2,317,136, median age of 66 [56–74] years, and males: 57.2%), 9.4% (218,795/2,317,136) had SPH. Females vs. males (11.3% vs. 8.1%) and Blacks vs. other race groups (13.5%) with OSA had a higher prevalence of SPH. The SPH cohort often consisted of females (51 vs. 41.9%), Blacks (20.9 vs. 14.0%), Medicare-insured (73.4 vs. 60.6%), and non-elective admissions (89.2 vs. 74.4%) vs. the non-SPH cohort. The SPH cohort also had a higher burden of complicated HTN (52.9 vs. 36.3%), DM with complications (42.7 vs. 32.4%), COPD (52.5 vs. 36.9%), history of prior MI (11.4 vs. 9.6%), and venous thromboembolism (10.4 vs. 8.4%). However, in-hospital mortality was more likely to be in males (OR 1.12; 95%CI 1.00–1.25, p = 0.048) vs. females, and OSA patients with metastatic cancer (OR 2.73; 95%CI 2.04–3.65) and solid non-metastatic tumors (OR 1.65; 95%CI 1.26–2.15) (p < 0.001). Conclusions: The prevalence of SPH with OSA was greater in females and Blacks, whereas males and Whites had higher subsequent inpatient mortality. More prospective studies are needed to understand the role of comorbidities on survival outcomes.

Background: Non-group 1 pulmonary hypertension, also known as secondary pulmonary hypertension (SPH), is predominantly observed among females. However, there is a significant lack of data concerning factors associated with hospitalization among patients diagnosed with SPH. This study aims to provide clinicians with vital insights for the identification of high-risk groups and for the more effective management of contributory risk factors within the female population affected by SPH. Methods: Using the 2019 National Inpatient Sample, we identified female admissions with SPH (n = 648,190), accounting for 3.8% of the total 17,236,228 female admissions. An Artificial Neural Network (ANN) analysis was conducted to evaluate predictive factors. We randomly allocated 3,319,543 patients into training and testing datasets at a ratio of 70:30, comprising 2,323,696 (70%) for training and 995,847 (30%) for testing, to calibrate and validate the performance of the ANN algorithm. Model performance was assessed by comparing misclassification rates between training and testing sets and by the area under the receiver operating characteristic curve (AUC); only internal validation was performed. Results: Females hospitalized with SPH were generally of older age, with a median of 75 years compared to 58 years, and more frequently identified as White (67.7% versus 65.5%) or Black (20.5% versus 15.5%) relative to those without SPH. They also demonstrated a higher prevalence of most atherosclerotic cardiovascular disease (ASCVD) risk factors or their equivalents, including complicated hypertension (50.6% versus 17.8%), diabetes with chronic complications (30.6% versus 13.7%), and hyperlipidemia (50.8% versus 29.2%), as well as other comorbidities such as COPD (43.4% versus 20.2%) and CKD (43.3% versus 14.0%), and exhibited increased all-cause mortality (4.5% versus 1.8%) (p < 0.001). Our ANN model achieved an AUC of 0.823, indicating good predictive capability. The rates of incorrect predictions were comparable in both the testing and training cohorts, at 3.8% each. The factors most strongly associated with a coded SPH diagnosis included age at admission, complicated hypertension, chronic kidney disease, chronic obstructive pulmonary disease, uncomplicated hypertension, prior VTE, race, arthropathies, and AIDS. Conclusions: Our ANN model identified demographic and comorbidity factors associated with a coded SPH diagnosis among hospitalized females, with good discrimination (AUC = 0.823). Because the model classifies the presence of an existing diagnosis rather than predicting future hospitalization, and was validated only internally, external and prospective validation is required before clinical application. Once validated, these factors could support individualized, sex-specific risk stratification for high-risk female populations, consistent with the goals of personalized medicine.