Mycotic aneurysms due to Trichosporon asahii in a patient with ulcerative colitis under immunosuppression.

Yeast fungi of the genus Trichosporon spp. can colonize the gastrointestinal tract in humans. In recent decades, the pathogenic role of Trichosporon asahii has been increasingly acknowledged especially in the setting of neutropenic patients with hematological malignancies. However, non-neutropenic patients who are immunosuppressed for other reasons are also at risk of developing invasive forms of this mycosis. We present the case of a 62-year-old male, with a history of ulcerative colitis under immunosuppressive treatment and previous exposure to antibiotics for various bacterial infections, who was admitted to the emergency department with a mycotic aneurysm of the abdominal aorta and left common iliac secondary to T. asahii infection. A multidisciplinary approach of the case (both early medical and surgical interventions) allowed the patient's favorable outcome. The patient was followed for more than two years with no evidence of relapse. We postulate that the diagnosis of invasive Trichosporonosis should be considered in patients with inflammatory bowel disease (IBD) under immunosuppressive treatment and with prior exposure to antibiotics.

Modeling graft loss in patients with donor-specific antibody at baseline using the Birmingham-Mayo (BirMay) predictor: Implications for clinical trials.

Predicting which renal allografts will fail and the likely cause of failure is important in clinical trial design to either enrich patient populations to be or as surrogate efficacy endpoints for trials aimed at improving long-term graft survival. This study tests our previous Birmingham-Mayo model (termed the BirMay Predictor) developed in a low-risk kidney transplant population in order to predict the outcome of patients with donor specific alloantibody (DSA) at the time of transplantation and identify new factors to improve graft loss prediction in DSA+ patients. We wanted define ways to enrich the population for future therapeutic intervention trials. The discovery set included 147 patients from Mayo Cohort and the validation set included 111 patients from the Paris Cohort-all of whom had DSA at the time of transplantation. The BirMay predictor performed well predicting 5-year outcome well in DSA+ patients (Mayo C statistic = 0.784 and Paris C statistic = 0.860). Developing a new model did not improve on this performance. A high negative predictive value of greater than 90% in both cohorts excluded allografts not destined to fail within 5 years. We conclude that graft-survival models including histology predict graft loss well, both in DSA+ cohorts as well as DSA- patients.

Predicting Individual Renal Allograft Outcomes Using Risk Models with 1-Year Surveillance Biopsy and Alloantibody Data.

The ability to predict outcomes for individual patients would be a significant advance for not only counseling, but also identifying those for whom interventions may be needed. The goals of this study were to validate an existing risk prediction score that incorporates easily obtainable clinical factors and determine if histologic findings at 1-year surveillance biopsy and/or serum donor-specific alloantibody status could improve predictability of graft loss by 5 years. We retrospectively studied 1465 adults who received a solitary kidney transplant between January of 1999 and December of 2008 and had sufficiently detailed 5-year follow-up data for modeling. In this cohort, the Birmingham risk model (incorporating recipient factors at 1 year, including age, sex, ethnicity, renal function, proteinuria, and prior acute rejection) predicted death-censored and overall graft survival (c statistics =0.84 and 0.78, respectively). The presence of glomerulitis or chronic interstitial fibrosis (g and ci scores by Banff, respectively) on 1-year biopsy specimens independently correlated with graft loss by 5 years. Adding these variables to the model for death-censored graft loss increased predictability (c statistic =0.90), improved calibration (ability to stratify risk from high to low), and reclassified risk of failure in 29% of patients. Adding the presence of donor-specific alloantibody at 1 year did not improve predictability or reclassification but did improve calibration marginally. We conclude that, at 1 year after kidney transplant, a risk model of graft survival that incorporates clinical factors and histologic findings at surveillance biopsy is highly predictive of individual risk and well calibrated.