Background: Frailty, with a high prevalence of 40–80% in heart failure, may have a significant bearing on outcomes in patients. This study utilizes the Hospital Frailty Risk Score (HFRS), a validated tool derived from the administrative International Classification of Diseases, 10th Revision, Clinical Modifications (ICD-10-CM) codes, in investigating the mortality, morbidity, and healthcare resource utilization among heart failure hospitalizations using the Nationwide Inpatient Sample (NIS). Methods: A retrospective analysis of the 2021 NIS database was assessed to identify adult patients hospitalized with heart failure. These patients were stratified by the HFRS into three groups: low frailty (LF: 15). The outcomes analyzed included inpatient mortality, length of stay (LOS), hospitalization charges, and complications including cardiogenic shock, cardiac arrest, acute kidney injury, and acute respiratory failure. These outcomes were adjusted for age, race, gender, the Charlson comorbidity score, hospital location, region, and teaching status. Multivariate logistic and linear regression analyses were used to assess the association between frailty and clinical outcomes. STATA/MP 18.0 was used for statistical analysis. Results: Among 1,198,988 heart failure admissions, 47.5% patients were in the LF group, whereas the IF and HF groups had 51.1% and 1.4% patients, respectively. Compared to the LF group, the IF group showed a 4-fold higher (adjusted OR = 4.60, p < 0.01), and the HF group had an 11-fold higher (adjusted OR 10.90, p < 0.01) mortality. Frail patients were more likely to have a longer length of stay (4.24 days, 7.18 days, and 12.1 days in the LF, IF, and HF groups) and higher hospitalization charges (USD 49,081, USD 84,472, and USD 129,516 in the LF, IF, and HF groups). Complications were also noticed to be significantly (p < 0.01) higher with increasing frailty from the LF to HF groups. These included cardiogenic shock (1.65% vs. 4.78% vs. 6.82%), cardiac arrest (0.37% vs. 1.61% vs. 3.16%), acute kidney injury (19.2% vs. 54.9% vs. 74.6%), and acute respiratory failure (29.6% vs. 51.2% vs. 60.3%). Conclusions: This study demonstrates the application of HFRS in a national dataset as a predictor of outcome and resource utilization measures in heart failure admissions. Stratifying patients based on HFRS can help in holistic assessment, aid prognostication, and guide targeted interventions in heart failure.

Background/Objectives: Heart failure presents a significant public health challenge, affecting millions in the US, with projections of increasing prevalence and economic burdens. Obstructive sleep apnea (OSA) is highly prevalent among HF patients. This study analyzes the impact of OSA on the outcomes in patients admitted with acute decompensated heart failure. Methods: We conducted a retrospective cohort study using the National Inpatient Sample database (NIS) 2020, focusing on patients admitted with acute heart failure. Patient outcomes were compared between those with and without a secondary diagnosis of OSA, identified via validated ICD-10 codes. Subgroup analysis was conducted between heart failure patients with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF). Results: Among 65,649 patients with acute heart failure, 4595 (7%) patients were found to have OSA. The patients with OSA were more likely to be male, older in age and had a higher burden of comorbidities. No significant differences were observed in mortality between heart failure patients with and without OSA. In HFrEF patients, OSA was associated with longer hospital stays (6.45 days vs. 5.79 days, p < 0.001), higher rates of acute kidney injury (AKI) (adjusted odds ratio 1.28, 95% CI: 1.07–1.54, p = 0.007), and atrial fibrillation (adjusted odds ratio 1.35, 95% CI: 1.13–1.61, p = 0.001). In HFpEF patients, an association between OSA and AF was observed (adjusted odds ratio 1.20, 95% CI: 1.01–1.42, p = 0.03). Conclusions: OSA is associated with poor in-hospital outcomes in patients admitted with acute heart failure. HFrEF subgroup is especially vulnerable, with OSA leading to a significant increase in healthcare utilization and complication rates in these patients. This nationwide study underscores the importance of timely identification and treatment of OSA in heart failure to alleviate healthcare burdens and improve patient outcomes.

Background: Obesity presents a significant global health impact and is linked to cardiovascular diseases. While obesity often exacerbates the severity of cardiovascular conditions, an “obesity paradox” has previously been observed, where patients with higher body mass index (BMI) exhibit improved in-hospital and long-term outcomes in certain contexts. As minimally invasive procedures such as percutaneous coronary intervention (PCI) continue to become more relevant, understanding the impact of different patient characteristics on clinical outcomes becomes increasingly important. Methods: A comprehensive analysis was conducted using a large cohort of patients who underwent PCI. In this study, we identified patients who underwent PCI in the year 2020 using the International Classification of Disease (ICD) codes. Patients were categorized into five groups based on their Body Mass Index (BMI). This study aimed to examine the impact of BMI on inpatient outcomes among patients undergoing PCI, focusing on mortality, length of stay, and hospitalization costs across different BMI categories. Results: Our analysis revealed a U-shaped relationship between BMI and inpatient outcomes. Patients with a BMI ≥ 25 demonstrated significantly reduced inpatient mortality (adjusted odds ratio 0.31, 95% CI: 0.18 to 0.54 for BMI 25–29.9 group and adjusted odds ratio 0.32, 95% CI: 0.20 to 0.51 for the BMI 30–39.9 group, with p ≤ 0.001); shorter hospital stays (BMI of 25 or higher with mean reduction of −2.40 to −3.66 days, with p ≤ 0.001); and lower hospitalization costs with a cost reduction of −$40,881 (95% CI: −$64,540 to −$17,223) for the BMI 25–29.9 group, −$57,900 (95% CI: −$80,308 to −$35,492) for the BMI 30–39.9 group, and −$41,463 (95% CI: −$65,151 to −$17,775) for the BMI ≥40 group compared to those with normal BMI (20–24.9). However, these benefits diminished for patients with a BMI ≥ 40, where no significant differences in mortality or cost reductions were observed. Conclusions: These findings underscore the complexity of the obesity paradox and its limitations in extreme obesity. This study highlights the need for tailored management strategies in PCI patients with varying BMI profiles.

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