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1000
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Abstract/Summary
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Background!#!Minimally invasive single-port surgery is always associated with large incisions up to 2-3 cm, complicated handling due to the lack of triangulation, and instrument crossing. The aim of this prospective study was to report how medical students without any laparoscopic experience perform several laparoscopic tasks (rope pass, paper cut, peg transfer, recapping, and needle threading) with the new SymphonX single-port platform and to examine the learning curves in comparison to the laparoscopic multi-port technique.!##!Methods!#!A set of 5 laparoscopic skill tests (Rope Pass, Paper cut, Peg Transfer, Recapping, Needle Thread) were performed with 3 repetitions. Medical students performed all tests with both standard laparoscopic instruments and the new platform. Time and errors were recorded.!##!Results!#!A total of 114 medical students (61 females) with a median age of 23 years completed the study. All subjects were able to perform the skill tests with both standard laparoscopic multi-port and the single-port laparoscopic system and were able to significantly improve their performance over the three trials for all five tasks-rope pass (p < 0.001), paper cut (p < 0.001), peg transfer (p < 0.001), needle threading (p < 0.001), and recapping (p < 0.001). In 3 out of 5 tasks, medical students performed the tasks faster using the standard multi-port system-rope pass (p < 0.001), paper cut (p < 0.001), and peg transfer (p < 0.001). In the task recapping, medical students performed the task faster using the new single-port system (p = 0.003). In the task needle threading, there was no significant difference between the standard multi-port system and the new single-port system (p > 0.05).!##!Conclusion!#!This is the first study analyzing learning curves of the commercially available SymphonX platform for abdominal laparoscopic surgery when used by novices. The learning curve and the error rate are promising.
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1000
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Hinweis
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DeepGreen-ID: a56251c341b44aa8a39dbb48b32e259c ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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