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Predicting Clinical Outcome in Expanded Criteria Donor Kidney Transplantation: A Retrospective Cohort Study.

ABSTRACT: Background:The gaps in organ supply and demand necessitate the use of expanded criteria donor (ECD) kidneys.Objective:To identify which pre-transplant and post-transplant predictors are most informative regarding short- and long-term ECD transplant outcomes.Design:Retrospective cohort study.Setting:Single center, Quebec, Canada.Patients:The patients were 163 consecutive first-time ECD kidney only transplant recipients who underwent transplantation at McGill University Health Centre (MUHC) between January 1, 2008 and December 31, 2014 and had frozen section wedge procurement biopsies.Measurements:Short-term graft outcomes, including delayed graft function and 1-year estimated glomerular filtration rate (eGFR), as well as long-term outcomes including all-cause graft loss (defined as return to dialysis, retransplantation, and death with function).Methods:Pre-transplant donor, recipient, and transplant characteristics were assessed as predictors of transplant outcomes. The added value of post-transplant predictors, including longitudinal eGFR, was also assessed using time-varying Cox proportional hazards models.Results:In univariate analyses, among the pre-transplant donor characteristics, histopathologic variables did not show evidence of association with delayed graft function, 1-year post-transplant eGFR or all cause graft loss. Recipient age was associated with all-cause graft loss (hazard ratio: 1.038 [95% confidence interval: 1.002-1.075] and the model produced only modest discrimination (C-index: 0.590; standard error [SE]: 0.045). Inclusion of time-dependent post-transplant eGFR improved the model’s prediction accuracy (C-index: 0.711; SE = 0.047). Pre-transplant ECD characteristics were not associated with long-term survival, whereas post-transplant characteristics allowed better model discrimination.Limitations:Single-center study, small sample size, and potential incomplete capture of all covariate data.Conclusions:Incorporation of dynamic prediction models into electronic health records may enable timely mitigation of ECD graft failure risk and/or facilitate planning for renal replacement therapies. Histopathologic findings on preimplantation biopsies have a limited role in predicting long-term ECD outcomes.Trial registration:Not applicable.

SUBMITTER: Saha-Chaudhuri P

PROVIDER: S-EPMC7315672 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Fungal Endocarditis (FE), a relatively rare disease, has a high rate of mortality and is associated with multiple morbidities. Aspergillus endocarditis (AE) is severe form of FE. Incidence of AE has increased and is expected to rise due to an increased frequency of invasive procedures, cardiac devices and prosthetic valves together with increased use of immune system suppressors. AE lacks most of the clinical criteria used to diagnose infective endocarditis (IE), where blood culture is almost always negative, and fever may be absent. Diagnosis is usually late and in many cases is made post-mortem. Late or mistaken diagnosis of AE contribute to delayed and incorrect management of patients. In the current study we aimed to describe the clinical, laboratory and imaging characteristics of AE, to identify predictors of early diagnosis of this serious infection. METHODS:Patients with definite/possible IE, as diagnosed by the Kasr Al-Ainy IE Working Group from February 2005 through June 2016, were reviewed in this study. We compared the demographic, clinical, laboratory and imaging criteria of AE patients to non-fungal IE patients. RESULTS:This study included 374 patients with IE in which FE accounted for 43 cases. Aspergillus was the most common fungus (31 patients; 8.3%) in the patient group. Lack of fever and acute limb ischemia at presentation were significantly associated with AE (p < 0.001, p = 0.014, respectively). Health care associated endocarditis (HAE) and prosthetic valve endocarditis (PVE) were the only significant risk factors associated with AE (p < 0.001 for each). Mitral, non-valvular, and aortotomy site vegetations, as well as aortic abscess/pseudoaneurysm, were significantly associated with AE (p = 0.022, p = 0.004, p < 0.001, and p < 0.001, respectively). Through multivariate regression analysis, HAE, PVE, aortic abscess/pseudoaneurysm, and lack of fever were strongly linked to AE. The probability of an IE patient having AE with HAE, PVE, and aortic abscess/pseudoaneurysm, but no fever, was 0.92. In contrast, the probability of an IE patient having AE with fever, native valve IE, but no health-care associated IE and no abscess/pseudoaneurysm, was 0.003. Severe sepsis and mortality in the Aspergillus group were higher as compared to the non-fungal group (p = 0.098 and 0.097, respectively). Thirteen AE patients died during hospitalization. PVE, the use of single versus dual antifungal agents, severe heart failure, and severe sepsis were significant predictors of mortality (p = 0.008, 0.012, 0.003, and 0.01, respectively). CONCLUSION:To our knowledge, this is the first study to address diagnostic criteria for AE. Through multivariate regression analysis, absence of fever, HAE, PVE, and aortic abscess/pseudoaneurysm were strong predictors of AE. Use of these criteria my lead to earlier diagnoses of AE. Early treatment of AE patients with voriconazole in combination with other antifungal agents may be possible based on the previously mentioned criteria, which may facilitate better patient outcomes.

Project description:Acute kidney injury (AKI) is a frequent complication of liver transplantation and is associated with increased mortality. We identified the incidence and modifiable risk factors for AKI after living-donor liver transplantation (LDLT) and constructed risk scoring models for AKI prediction. We retrospectively reviewed 538 cases of LDLT. Multivariate logistic regression analysis was used to evaluate risk factors for the prediction of AKI as defined by the RIFLE criteria (RIFLE = risk, injury, failure, loss, end stage). Three risk scoring models were developed in the retrospective cohort by including all variables that were significant in univariate analysis, or variables that were significant in multivariate analysis by backward or forward stepwise variable selection. The risk models were validated by way of cross-validation. The incidence of AKI was 27.3% (147/538) and 6.3% (34/538) required postoperative renal replacement therapy. Independent risk factors for AKI by multivariate analysis of forward stepwise variable selection included: body-mass index >27.5 kg/m2 [odds ratio (OR) 2.46, 95% confidence interval (CI) 1.32-4.55], serum albumin <3.5 mg/dl (OR 1.76, 95%CI 1.05-2.94), MELD (model for end-stage liver disease) score >20 (OR 2.01, 95%CI 1.17-3.44), operation time >600 min (OR 1.81, 95%CI 1.07-3.06), warm ischemic time >40 min (OR 2.61, 95%CI 1.55-4.38), postreperfusion syndrome (OR 2.96, 95%CI 1.55-4.38), mean blood glucose during the day of surgery >150 mg/dl (OR 1.66, 95%CI 1.01-2.70), cryoprecipitate > 6 units (OR 4.96, 95%CI 2.84-8.64), blood loss/body weight >60 ml/kg (OR 4.05, 95%CI 2.28-7.21), and calcineurin inhibitor use without combined mycophenolate mofetil (OR 1.87, 95%CI 1.14-3.06). Our risk models performed better than did a previously reported score by Utsumi et al. in our study cohort. Doses of calcineurin inhibitor should be reduced by combined use of mycophenolate mofetil to decrease postoperative AKI. Prospective randomized trials are required to address whether artificial modification of hypoalbuminemia, hyperglycemia and postreperfusion syndrome would decrease postoperative AKI in LDLT.

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Predicting Clinical Outcome in Expanded Criteria Donor Kidney Transplantation: A Retrospective Cohort Study.

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