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The learning curve and factors affecting warm ischemia time during robot-assisted partial nephrectomy

INTRODUCTION: The learning curve for robotic partial nephrectomy was investigated for an experienced laparoscopic surgeon and factors associated with warm ischemia time (WIT) were assessed. MATERIALS AND METHODS: Between 2007 and 2014, one surgeon completed 171 procedures. Operative time, blood loss...

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Autores principales: Dube, Hitesh, Bahler, Clinton D., Sundaram, Chandru P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4495497/
https://www.ncbi.nlm.nih.gov/pubmed/26166966
http://dx.doi.org/10.4103/0970-1591.156916
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author Dube, Hitesh
Bahler, Clinton D.
Sundaram, Chandru P.
author_facet Dube, Hitesh
Bahler, Clinton D.
Sundaram, Chandru P.
author_sort Dube, Hitesh
collection PubMed
description INTRODUCTION: The learning curve for robotic partial nephrectomy was investigated for an experienced laparoscopic surgeon and factors associated with warm ischemia time (WIT) were assessed. MATERIALS AND METHODS: Between 2007 and 2014, one surgeon completed 171 procedures. Operative time, blood loss, complications and ischemia time were examined to determine the learning curve. The learning curve was defined as the number of procedures needed to reach the targeted goal for WIT, which most recently was 20 min. Statistical analyses including multivariable regression analysis and matching were performed. RESULTS: Comparing the first 30 to the last 30 patients, mean ischemia time (23.0–15.2 min, P < 0.01) decreased while tumor size (2.4–3.4 cm, P = 0.02) and nephrometry score (5.9–7.0, P = 0.02) increased. Body mass index (P = 0.87), age (P = 0.38), complication rate (P = 0.16), operating time (P = 0.78) and estimated blood loss (P = 0.98) did not change. Decreases in ischemia time corresponded with revised goals in 2011 and early vascular unclamping with the omission of cortical renorrhaphy in selected patients. A multivariable analysis found nephrometry score, tumor diameter, cortical renorrhaphy and year of surgery to be significant predictors of WIT. CONCLUSIONS: Adoption of robotic assistance for a surgeon experienced with laparoscopic surgery was associated with low complication rates even during the initial cases of robot-assisted partial nephrectomy. Ischemia time decreased while no significant changes in blood loss, operating time or complications were seen. The largest decrease in ischemia time was associated with adopting evidence-based goals and new techniques, and was not felt to be related to a learning curve.
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spelling pubmed-44954972015-07-12 The learning curve and factors affecting warm ischemia time during robot-assisted partial nephrectomy Dube, Hitesh Bahler, Clinton D. Sundaram, Chandru P. Indian J Urol Original Article INTRODUCTION: The learning curve for robotic partial nephrectomy was investigated for an experienced laparoscopic surgeon and factors associated with warm ischemia time (WIT) were assessed. MATERIALS AND METHODS: Between 2007 and 2014, one surgeon completed 171 procedures. Operative time, blood loss, complications and ischemia time were examined to determine the learning curve. The learning curve was defined as the number of procedures needed to reach the targeted goal for WIT, which most recently was 20 min. Statistical analyses including multivariable regression analysis and matching were performed. RESULTS: Comparing the first 30 to the last 30 patients, mean ischemia time (23.0–15.2 min, P < 0.01) decreased while tumor size (2.4–3.4 cm, P = 0.02) and nephrometry score (5.9–7.0, P = 0.02) increased. Body mass index (P = 0.87), age (P = 0.38), complication rate (P = 0.16), operating time (P = 0.78) and estimated blood loss (P = 0.98) did not change. Decreases in ischemia time corresponded with revised goals in 2011 and early vascular unclamping with the omission of cortical renorrhaphy in selected patients. A multivariable analysis found nephrometry score, tumor diameter, cortical renorrhaphy and year of surgery to be significant predictors of WIT. CONCLUSIONS: Adoption of robotic assistance for a surgeon experienced with laparoscopic surgery was associated with low complication rates even during the initial cases of robot-assisted partial nephrectomy. Ischemia time decreased while no significant changes in blood loss, operating time or complications were seen. The largest decrease in ischemia time was associated with adopting evidence-based goals and new techniques, and was not felt to be related to a learning curve. Medknow Publications & Media Pvt Ltd 2015 /pmc/articles/PMC4495497/ /pubmed/26166966 http://dx.doi.org/10.4103/0970-1591.156916 Text en Copyright: © Indian Journal of Urology http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Dube, Hitesh
Bahler, Clinton D.
Sundaram, Chandru P.
The learning curve and factors affecting warm ischemia time during robot-assisted partial nephrectomy
title The learning curve and factors affecting warm ischemia time during robot-assisted partial nephrectomy
title_full The learning curve and factors affecting warm ischemia time during robot-assisted partial nephrectomy
title_fullStr The learning curve and factors affecting warm ischemia time during robot-assisted partial nephrectomy
title_full_unstemmed The learning curve and factors affecting warm ischemia time during robot-assisted partial nephrectomy
title_short The learning curve and factors affecting warm ischemia time during robot-assisted partial nephrectomy
title_sort learning curve and factors affecting warm ischemia time during robot-assisted partial nephrectomy
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4495497/
https://www.ncbi.nlm.nih.gov/pubmed/26166966
http://dx.doi.org/10.4103/0970-1591.156916
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