Abstract TP123: Incidence, Predictors, and In-hospital Outcomes of Intracranial Hemorrhage in Kidney Transplant Recipients: Analysis of the National Inpatient Sample 2016-2022

Background: This study aimed to characterize the incidence, predictors, and outcomes of ICH in Kidney transplant recipients Methods: We queried theNIS (2016–2022) for adult kidney transplant recipients (ICD-10: Z94.0) admitted with ICH (I64). Demographics, comorbidities (Elixhauser index), and CKD-related variables, including chronic heart failure, were included as covariates. Outcomes assessed were in-hospital mortality,and utilization cose and LOS were used as proxy measures of severity and complications. Multivariable logistic regression was used to identify independent predictors of death and LOS. Results: A total of 2,888 hospitalizations for ICH were identified among KTR. Survey-weighted means were age 68.0 years, LOS 7.0 days, charges $103.8k , and in-hospital mortality 7.7% . In multivariable models, older age independently increased the odds of death (OR 1.015 per year, CI 1.00–1.03; p=0.011], coagulopathy (mortality OR 2.74 ; longer LOS +52.8% ) and CHF (mortality[OR 1.94; 95% CI 1.48–2.56; p<0.001]; longer LOS +38.0% ). A small race subgroup (American Indian/Alaska Native) had higher mortality (OR 3.12 , wide CI). The Uninsured/Other payer category was associated with higher mortality (OR 2.29 ), but insurance effects were otherwise less consistent than clinical factors. LOS proxy representation of severity —also included female ( +9.7% ) and ( Black +18.4% , Hispanic +14.0% , Asian/Pacific Islander +55.0% , Other +26.0% ). Urban teaching hospitals and large hospitals were associated with longer LOS ( +52.4% and +25.5% , respectively), indicating severe ICH in KTRs. Conversely, IHD (− 9.4% ) and diabetes (− 9.7% ) were associated with shorter LOS. Higher cost utilization, which is also a proxy measure of the severity of the disease, is higher with coagulopathy ( +30.6% ) and CHF ( +15.6% ). Conclusions: Coagulopathy and CHF are critical risk factors in this population, consistently marking greater resource use and higher mortality. These findings can guide bleeding-risk mitigation and heart-failure optimization.