Purpose: We propose an algorithm to help guide surgeons' decisions between laparoscopic partial nephrectomy (LPN) and renal laparoscopic cryoablation (LCA) based on preoperative parameters and outcomes defined in the literature.
Patients And Methods: From July 2004 to December of 2007, we performed 51 LPNs and 22 LCAs. We formulated an algorithm between LPN and LCA based on outcomes from published series. Candidates for LPN are younger than 70 years; have few comorbidities; masses < or = 7 cm; and solitary, solid, and or cystic masses with an exophytic or mesophytic location. Candidates for LCA are 70 years old or older, with multiple comorbidities, masses < or = 3.5 cm, multiple masses, solid masses only, and include endophytic or hilar tumors. We then applied this decision tree to our series.
Results: Our results for LPN are statistically similar to the published series except there was a higher positive margin rate in our series (11.8 v 3.5%). Our LCA series had older patients (71 v 65 y), larger masses (3.2 v 2.5 cm), and a higher rate of bleeding necessitating transfusion (18%). We applied the algorithm to all 73 patients in our series. It estimated that 45 patients should undergo LPN and 28 should undergo LCA. A correlation between the predicted surgery and the surgery performed was seen, but approximately one in five patients would have a change in the surgery performed.
Conclusions: This algorithm validates decisions surgeons are already making between LPN and LCA. While not a perfect model, it can be used to help simplify decisions between these two minimally invasive procedures to achieve optimal outcomes.
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http://dx.doi.org/10.1089/end.2008.0228 | DOI Listing |
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December 2024
Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.
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Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Krakow, Poland; Department of Biochemistry and Molecular Biology, Medical University of Lublin, Lublin, Poland. Electronic address:
Brain tumors are among the most dangerous, due to their location in the organ that governs all life processes. Moreover, the high differentiation of these poses a challenge in diagnostics. Therefore, this study focused on the chemical differentiation of glioblastoma G4 (GBM) and two types of meningiomas (atypical - MAtyp and angiomatous - MAng) were done using Fourier Transform InfraRed (FTIR) spectroscopy, combined with statistical, multivariate, machine learning and rate of spectrum changes methods.
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