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  • Title: Laparoscopic partial nephrectomy: predictors of prolonged warm ischemia.
    Author: Lifshitz DA, Shikanov S, Jeldres C, Deklaj T, Karakiewicz PI, Zorn KC, Eggener SE, Shalhav AL.
    Journal: J Urol; 2009 Sep; 182(3):860-5. PubMed ID: 19616257.
    Abstract:
    PURPOSE: The kidney is often exposed to warm ischemia during laparoscopic partial nephrectomy. Warm ischemia time is associated with acute and possible long-term renal damage, particularly beyond a 30-minute threshold. We evaluated patient and tumor characteristics that might predict prolonged warm ischemia time. MATERIALS AND METHODS: A prospective institutional database was searched for patients who underwent laparoscopic partial nephrectomy with renal vessel clamping. Warm ischemia time was treated as a continuous and a categorical (more or less than 30 minutes) variable. The association between warm ischemia time, and preoperative and surgical parameters was evaluated using linear and logistic regression analysis. The latter analysis was used to develop and internally validate a preoperative nomogram to predict warm ischemia time longer than 30 minutes. RESULTS: On multivariate linear regression analysis tumor size (coefficient 1.6, 95% CI 0.7-2.6, p = 0.001), body mass index (coefficient 0.3, 95% CI 0.1-0.5, p = 0.005) and central tumor location (coefficient 3.7, 95% CI 0.5-7, p = 0.02) were independent predictors of longer warm ischemia time. Patients with 2 or more of certain risk factors, including body mass index greater than 30 kg/m(2), tumor greater than 4 cm and a centrally located tumor, were 5 times more likely to have warm ischemia time greater than 30 minutes than patients without the risk factors (p = 0.002). A nomogram incorporating predictors of longer warm ischemia time showed 75.4% accuracy. CONCLUSIONS: Greater tumor size, central tumor location and higher body mass index are associated with longer warm ischemia time. By incorporating these 3 risk factors into a nomogram prolonged warm ischemia time (greater than 30 minutes) can be accurately predicted preoperatively.
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