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 (mortalityOR 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.
Maaz et al. (Thu,) studied this question.