Abstract
Frailty is a common geriatric syndrome often coexisting with cardiovascular diseases such as atrial fibrillation (AF) and heart failure (HF) with reduced ejection fraction (HFrEF). While catheter ablation (CA) has demonstrated efficacy in reducing major adverse cardiovascular events and improving mortality and quality of life, the influence of frailty among this population remains unknown.
The authors aimed to identify the prevalence of frailty among patients with HFrEF and AF undergoing CA and its influence on cardiovascular mortality and discharge disposition.
From January 2016 to December 2019, we used the Nationwide Inpatient Sample to identify patients with AF and HFrEF. Frailty was identified by the presence of ≥1 diagnostic cluster utilizing the Johns Hopkins Adjusted Clinical Groups with malnutrition, dementia, impaired vision, decubitus ulcer, urinary incontinence, loss of weight, poverty, barriers to access to care, difficulty walking, and falls as indicators. We compared clinical outcomes among frail vs nonfrail patients, including all-cause in-hospital mortality, major adverse cardiovascular events, other major complications, discharge disposition, and hospital length of stay using multivariable regression analysis.
Of 113,115 weighted admissions, 11,725 (10.4%) were classified as frail. Frail patients were older (median age: 76 [IQR: 15] years vs 70 [IQR: 15] years,
< 0.001) than nonfrail patients. Frailty was associated with increased odds of all-cause hospital mortality (adjusted odds ratio [aOR]: 2.64; 95% CI: 1.87-3.72;
< 0.001), major adverse cardiovascular events (aOR: 2.00; 95% CI: 1.62-2.47;
< 0.001), and nonhome discharge (aOR: 3.31; 95% CI: 2.78-3.94;
< 0.001). Frail patients also experienced longer hospital length of stay (median 9 [IQR: 10] days vs 5 [IQR: 5] days,
< 0.001) after adjustment by Poisson regression (coefficient: 0.53; 95% CI: 0.46-0.59;
< 0.001).
Frailty is associated with worse outcomes in patients with HFrEF undergoing CA for AF. The integration of frailty models in clinical practice may facilitate prognostication and risk stratification to optimize patient selection for CA.