Acute heart failure in patients with hematologic malignancies: A nationwide analysis 2016-2021

Acute heart failure affects ~9% of patients with hematological malignancies. This study aimed to evaluate the impact of acute heart failure on in-hospital mortality among patients with hematological malignancies and to identify independent predictors of mortality in this population.

The National Inpatient Sample (2016-2021) was queried for adults (⩾18 years of age) with hematological malignancies and those who experienced in-hospital mortality. Among these, we identified patients who were hospitalized with a diagnosis of acute heart failure. Univariate analysis and multivariate regression were employed to analyze the mortality risk. A p ⩽ 0.05 was considered significant.

Among 40,246 patients with hematological malignancies who died in the hospital, the univariate analysis showed a higher in-hospital mortality in the acute heart failure cohort compared to the non-acute heart failure group (8.08% versus 4.52%, p < 0.001). However, after adjusting for sociodemographic factors and comorbidities, acute heart failure was associated with a lower risk of in-hospital mortality (OR 0.87, 95% CI 0.84-0.9, p < 0.001). Predictors of mortality in the acute heart failure cohort were age >60 years, hematopoietic stem cell transplant, severe sepsis, arrhythmias, infective endocarditis, bleeding from any source, acute respiratory failure, hepatic dysfunction, metabolic encephalopathy, and invasive ventilation (all p < 0.01). On subgroup analysis, acute myeloid leukemia, chronic myeloid leukemia, chronic lymphocytic leukemia, and multiple myeloma had a higher in-hospital mortality in the acute heart failure cohort compared to the non-acute heart failure group (p < 0.001).

Acute heart failure in patients with hematological malignancies was associated with poor outcomes in the presence of severe sepsis, organ dysfunction, and the need for mechanical ventilation. Close monitoring and a multidisciplinary team approach are recommended to optimize the treatment plan for this population.