Sex and Ethnic Disparities in Stroke Revascularisation Treatments and Post-Stroke Outcomes in Patients with Heart Failure: A National Inpatient Sample Study

<b>Background/Objectives</b>: We aimed to determine sex and racial/ethnic disparities in associations between Acute Ischaemic stroke (AIS) with co-morbid heart failure (HF) and in-hospital outcomes, using the US National Inpatient Sample (NIS) in this retrospective observational study based on administrative data. <b>Methods</b>: AIS admissions from January 2016 to December 2019 were extracted from the NIS. Logistic regressions analysed relationships between HF and in-hospital mortality, length of stay >4 days, thrombectomy, thrombolysis, and complications at discharge adjusted for age and comorbidities. Additional models examined interactions between HF and sex, and HF and race/ethnicity. <b>Results</b>: Among 1,744,390 AIS hospitalizations, 16.36% had HF. 69.00% were White, 17.86% Black, 7.42% Hispanic, 2.79% Asian. No significant sex or racial/ethnic differences were found for in-hospital mortality. Patients with co-morbid HF had increased odds of complications at discharge in both sexes (odds ratio (95% confidence interval) 1.32 (1.27-1.37) in women and 1.21 (1.17-1.25) in men). HF (cf. no HF) showed stronger associations with increased complications at discharge in White (1.36 (1.32-1.40)) patients, compared to other racial/ethnic groups (Black 1.08 (1.03-1.13), Hispanic 1.10 (1.01-1.20), and Asian 1.13 (0.97-1.32)). HF was not significantly associated with thrombolysis in White patients (0.98 (0.95-1.02)) but was in Black (1.20 (1.13-1.28)), Hispanic (1.27 (1.14-1.40)), and Asian (1.36 (1.14-1.62)). Additionally controlling socioeconomic variables did not change the relationships except in Hispanic patients for complications, which has become insignificant (1.07 (0.98-1.17)). <b>Conclusions</b>: The association between HF and post-stroke outcomes differs by race/ethnicity and sex, even when adjusting for key predictors of outcomes. Further research is required to identify the drivers of these disparities.