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Title
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Learning curves for urological procedures: a systematic review
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Author
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Abstract
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| Objective To determine the number of cases a urological surgeon must complete to achieve proficiency for various urological procedures. Patient and Methods The MEDLINE, EMBASE and PsycINFO databases were systematically searched for studies published up to December 2011. Studies pertaining to learning curves of urological procedures were included. Two reviewers independently identified potentially relevant articles. Procedure name, statistical analysis, procedure setting, number of participants, outcomes and learning curves were analysed. Results Forty-four studies described the learning curve for different urological procedures. The learning curve for open radical prostatectomy ranged from 250 to 1000 cases and for laparoscopic radical prostatectomy from 200 to 750 cases. The learning curve for robot-assisted laparoscopic prostatectomy (RALP) has been reported to be 40 procedures as a minimum number. Robot-assisted radical cystectomy has a documented learning curve of 16-30 cases, depending on which outcome variable is measured. Irrespective of previous laparoscopic experience, there is a significant reduction in operating time (P = 0.008), estimated blood loss (P = 0.008) and complication rates (P = 0.042) after 100 RALPs. Conclusions The available literature can act as a guide to the learning curves of trainee urologists. Although the learning curve may vary among individual surgeons, a consensus should exist for the minimum number of cases to achieve proficiency. The complexities associated with defining procedural competence are vast. The majority of learning curve trials have focused on the latest surgical techniques and there is a paucity of data pertaining to basic urological procedures. |
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Language
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English
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Source (journal)
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BJU international / British Association of Urological Surgeons. - Oxford, 1999, currens
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Publication
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Oxford
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2014
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ISSN
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1464-4096
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DOI
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10.1111/BJU.12315
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Volume/pages
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114
:4
(2014)
, p. 617-629
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ISI
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000343007100026
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Pubmed ID
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24053179
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Full text (Publisher's DOI)
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