Bush Wiberg (guitarroof8)

Preoperative estimation of new baseline glomerular filtration rate after partial nephrectomy or radical nephrectomy for renal cell carcinoma has important clinical implications. However, current predictive models are either complex or lack external validity. We aimed to develop and validate a simple equation to estimate postoperative new baseline glomerular filtration rate. For development and internal validation of the equation, a cohort of 7,860 patients with renal cell carcinoma undergoing partial nephrectomy/radical nephrectomy (2005-2015) at the Veterans Affairs National Health System was analyzed. Based on preliminary analysis of 94,327 first-year postoperative glomerular filtration rate measurements, new baseline glomerular filtration rate was defined as the final glomerular filtration rate within 3 to 12 months after surgery Multivariable linear regression analyses were applied to develop the equation using two-thirds of the renal cell carcinoma Veterans Administration cohort. The simplest modelglomerular filtration rate ≥45 ml/minute/1.73 m from receiver operating characteristic analyses were 0.90 (0.88, 0.91) and 0.90 (0.89, 0.91) in the internal/external validation cohorts, respectively. Our study provides a validated equation to accurately predict postoperative new baseline glomerular filtration rate in patients being considered for radical nephrectomy or partial nephrectomy that can be easily implemented in daily clinical practice. Our study provides a validated equation to accurately predict postoperative new baseline glomerular filtration rate in patients being considered for radical nephrectomy or partial nephrectomy that can be easily implemented in daily clinical practice. Automated performance metrics provide a novel approach to the assessment of surgical performance. Herein, we present a construct validation of automated performance metrics during robotic assisted partial nephrectomy. Automated performance metrics (instrument motion tracking/system events) and synchronized surgical videos from da Vinci® Si systems during robotic assisted partial nephrectomy were recorded using a system data recorder. Each case was segmented into 7 steps colon mobilization, ureteral identification/dissection, hilar dissection, exposure of tumor within Gerota's fascia, intraoperative ultrasound/tumor scoring, tumor excision, and renorrhaphy. find more Automated performance metrics from each step were compared between expert (≥150 cases) and trainee (<150 cases) surgeons by Mann-Whitney U test (continuous variables) and Pearson's chi-squared test (categorical variables). Clinical outcomes were collected prospectively and correlated to automated performance metrics and R.E.N.A.L. (radius, exophytic/ of tumor complexity and may serve as predictors of clinical outcomes. These data help establish a standardized metric for surgeon assessment and training during robotic assisted partial nephrectomy. Experts are more efficient and directed in their movement during robotic assisted partial nephrectomy. Automated performance metrics during key steps correlate with objective measures of tumor complexity and may serve as predictors of clinical outcomes. These data help establish a standardized metric for surgeon assessment and training during robotic assisted partial nephrectomy. Active surveillance for patients with low and intermediate risk prostate cancers is becoming a more utilized option in recent years. However, the use of magnetic resonance imaging and imaging-targeted biopsy for monitoring grade progression has been poorly studied in this population. We aim to define the utility of magnetic resonance imaging-targeted biopsy and systematic biopsy in an active surveillance population. Between July 2007 and January 2020, patients with diagnosed prostate cancer who elected active surveillance were monitored with prostate magnetic resonance imagi