SummaryBackground and objectives The aims of this study were to determine the frequency of venous thromboembolic events in a large cohort of patients with idiopathic membranous nephropathy and to identify predisposing risk factors.Design, setting, participants, & measurements We studied patients with biopsy-proven membranous nephropathy from the Glomerular Disease Collaborative Network (n=412) and the Toronto Glomerulonephritis Registry (n=486) inception cohorts. The cohorts were pooled after establishing similar baseline characteristics (total n=898). Clinically apparent and radiologically confirmed venous thromboembolic events were identified. Potential risk factors were evaluated using multivariable logistic regression models.Results Sixty-five (7.2%) subjects had at least one venous thromboembolic event, and this rate did not differ significantly between registries. Most venous thromboembolic events occurred within 2 years of first clinical assessment (median time to VTE = 3.8 months). After adjusting for age, sex, proteinuria, and immunosuppressive therapy, hypoalbuminemia at diagnosis was the only independent predictor of a venous thromboembolic event. Each 1.0 g/dl reduction in serum albumin was associated with a 2.13-fold increased risk of VTE. An albumin level ,2.8 g/dl was the threshold below which risk for a venous thromboembolic event was greatest.Conclusions We conclude that clinically apparent venous thromboembolic events occur in about 7% of patients with membranous nephropathy. Hypoalbuminemia, particularly ,2.8 g/dl, is the most significant independent predictor of venous thrombotic risk.

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Background/Aims: Depending on the specific definition, acute kidney injury (AKI) occurs in 7–40% of patients undergoing cardiac surgery. Even small changes in serum creatinine (SCr) levels are associated with increased mortality after cardiac surgery. However, there are no current methods for preventing AKI after cardiac surgery. Erythropoietin (EPO) has been shown to elicit tissue-protective effects in various experimental models. In this pilot trial, we evaluated the effectiveness of EPO in the prevention of AKI after coronary artery bypass grafting (CABG). Methods: 71 patients scheduled for elective CABG randomly received either 300 U/kg of EPO or saline intravenously before surgery. AKI was defined as a 50% increase in SCr levels over baseline within the first 5 postoperative days. Estimated glomerular filtration rate (eGFR) was calculated from the Cockcroft-Gault equation. Results: Of 71 patients, 13 developed postoperative AKI: 3 of the 36 patients in the EPO group (8%) and 10 of the 35 patients in the placebo group (29%; p = 0.035). The increase in postoperative SCr concentration and the decline in postoperative eGFR were significantly lower in the EPO group than in the placebo group. Conclusions: In our small, pilot trial, prophylactic administration of EPO prevents AKI and improves postoperative renal function. These data are preliminary and require confirmation in a larger clinical trial.

We generalize the standard method of solving inverse optimization problems to allow for the solution of inverse problems that would otherwise be ill posed or infeasible. In multiobjective linear optimization, given a solution that is not a weakly efficient solution to the forward problem, our method generates objective function weights that make the given solution a near-weakly efficient solution. Our generalized inverse optimization model specializes to the standard model when the given solution is weakly efficient and retains the complexity of the underlying forward problem. We provide a novel interpretation of our inverse formulation as the dual of the well-known Benson's method and by doing so develop a new connection between inverse optimization and Pareto surface approximation techniques. We apply our method to prostate cancer data obtained from Princess Margaret Cancer Centre in Toronto, Canada. We demonstrate that clinically acceptable treatments can be generated using a small number of objective functions and inversely optimized weights—current treatments are designed using a complex formulation with a large parameter space in a trial-and-error reoptimization process. We also show that our method can identify objective functions that are most influential in treatment plan optimization.