Predictors Of Very Late Onset Infection In Kidney Transplant Recipients At Least Ten Years Post Transplant

Although there have been improved outcomes for kidney transplant recipients, infection is still a leading cause of morbidity and mortality for long-term kidney transplant survivors (LTKS). This thesis and study aims to investigate the epidemiology of very late onset infections (\u3e10 years post-transplant), or VLOI and clinical markers that can predict these infections. A single-center, retrospective study of a cohort of patients (≥18 years old) who underwent kidney transplantation between 2003-2009 and survived for at least 10 years post transplantation was conducted. The primary outcome studied was the occurrence of VLOI. The data collected included transplant data, patient co-morbidities, and clinical data regarding VLOI. Multivariate analysis was used to analyze risk factors for VLOI and a predictive nomogram of infection risk was generated. There were 327 LTKS in our cohort. Of those, there were a total of 192 VLOI among 99 LTKS. Urinary tract infections (n = 82, 43%), lower respiratory tract infections (n = 41, 21%), and gastrointestinal infections (n = 24, 13%) were the most common types of infections recorded. VLOI were most commonly due to bacterial infections (n = 152, 78%). There were 13 (7%) opportunistic infections as well. Of the 99 LTKS with at least one VLOI, half developed sepsis (as defined by SIRS criteria + source for infection) while 10% died within 30 days after diagnosis. Although not statistically significant, there was a trend towards increased mortality at comparable timepoints for LTKS with a VLOI compared to those without (p = 0.068). Independent risk factors for incidence of VLOI included older age at time of transplant, longer follow-up from time of transplant (independent of age), lower absolute lymphocyte count, and diabetes. In summary, VLOI occurred in 30% of LTKS. These were typically due to bacterial infections and occasionally due to opportunistic pathogens. Sepsis and death were common outcome in this cohort. A predictive model incorporating determined risk factors could be utilized to identify the survivors of kidney transplant who are at greatest risk for VLOI