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The Learning Curve of Laparoscopic Liver Resection Utilising a Difficulty Score
BACKGROUND: This study aimed to quantitatively evaluate the learning curve of laparoscopic liver resection (LLR) of a single surgeon. PATIENTS AND METHODS: A retrospective review of a prospectively maintained database of liver resections was conducted. 171 patients undergoing pure LLRs between April...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Sciendo
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8884855/ https://www.ncbi.nlm.nih.gov/pubmed/34492748 http://dx.doi.org/10.2478/raon-2021-0035 |
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author | Ivanecz, Arpad Plahuta, Irena Mencinger, Matej Perus, Iztok Magdalenic, Tomislav Turk, Spela Potrc, Stojan |
author_facet | Ivanecz, Arpad Plahuta, Irena Mencinger, Matej Perus, Iztok Magdalenic, Tomislav Turk, Spela Potrc, Stojan |
author_sort | Ivanecz, Arpad |
collection | PubMed |
description | BACKGROUND: This study aimed to quantitatively evaluate the learning curve of laparoscopic liver resection (LLR) of a single surgeon. PATIENTS AND METHODS: A retrospective review of a prospectively maintained database of liver resections was conducted. 171 patients undergoing pure LLRs between April 2008 and April 2021 were analysed. The Halls difficulty score (HDS) for theoretical predictions of intraoperative complications (IOC) during LLR was applied. IOC was defined as blood loss over 775 mL, unintentional damage to the surrounding structures, and conversion to an open approach. Theoretical association between HDS and the predicted probability of IOC was utilised to objectify the shape of the learning curve. RESULTS: The obtained learning curve has resulted from thirteen years of surgical effort of a single surgeon. It consists of an absolute and a relative part in the mathematical description of the additive function described by the logarithmic function (absolute complexity) and fifth-degree regression curve (relative complexity). The obtained learning curve determines the functional dependency of the learning outcome versus time and indicates several local extreme values (peaks and valleys) in the learning process until proficiency is achieved. CONCLUSIONS: This learning curve indicates an ongoing learning process for LLR. The proposed mathematical model can be applied for any surgical procedure with an existing difficulty score and a known theoretically predicted association between the difficulty score and given outcome (for example, IOC). |
format | Online Article Text |
id | pubmed-8884855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Sciendo |
record_format | MEDLINE/PubMed |
spelling | pubmed-88848552022-03-15 The Learning Curve of Laparoscopic Liver Resection Utilising a Difficulty Score Ivanecz, Arpad Plahuta, Irena Mencinger, Matej Perus, Iztok Magdalenic, Tomislav Turk, Spela Potrc, Stojan Radiol Oncol Research Article BACKGROUND: This study aimed to quantitatively evaluate the learning curve of laparoscopic liver resection (LLR) of a single surgeon. PATIENTS AND METHODS: A retrospective review of a prospectively maintained database of liver resections was conducted. 171 patients undergoing pure LLRs between April 2008 and April 2021 were analysed. The Halls difficulty score (HDS) for theoretical predictions of intraoperative complications (IOC) during LLR was applied. IOC was defined as blood loss over 775 mL, unintentional damage to the surrounding structures, and conversion to an open approach. Theoretical association between HDS and the predicted probability of IOC was utilised to objectify the shape of the learning curve. RESULTS: The obtained learning curve has resulted from thirteen years of surgical effort of a single surgeon. It consists of an absolute and a relative part in the mathematical description of the additive function described by the logarithmic function (absolute complexity) and fifth-degree regression curve (relative complexity). The obtained learning curve determines the functional dependency of the learning outcome versus time and indicates several local extreme values (peaks and valleys) in the learning process until proficiency is achieved. CONCLUSIONS: This learning curve indicates an ongoing learning process for LLR. The proposed mathematical model can be applied for any surgical procedure with an existing difficulty score and a known theoretically predicted association between the difficulty score and given outcome (for example, IOC). Sciendo 2021-09-06 /pmc/articles/PMC8884855/ /pubmed/34492748 http://dx.doi.org/10.2478/raon-2021-0035 Text en © 2022 Arpad Ivanecz, Irena Plahuta, Matej Mencinger, Iztok Perus, Tomislav Magdalenic, Spela Turk, Stojan Potrc, published by Sciendo https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Research Article Ivanecz, Arpad Plahuta, Irena Mencinger, Matej Perus, Iztok Magdalenic, Tomislav Turk, Spela Potrc, Stojan The Learning Curve of Laparoscopic Liver Resection Utilising a Difficulty Score |
title | The Learning Curve of Laparoscopic Liver Resection Utilising a Difficulty Score |
title_full | The Learning Curve of Laparoscopic Liver Resection Utilising a Difficulty Score |
title_fullStr | The Learning Curve of Laparoscopic Liver Resection Utilising a Difficulty Score |
title_full_unstemmed | The Learning Curve of Laparoscopic Liver Resection Utilising a Difficulty Score |
title_short | The Learning Curve of Laparoscopic Liver Resection Utilising a Difficulty Score |
title_sort | learning curve of laparoscopic liver resection utilising a difficulty score |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8884855/ https://www.ncbi.nlm.nih.gov/pubmed/34492748 http://dx.doi.org/10.2478/raon-2021-0035 |
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