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The Learning Curve of Computer-Assisted Free Flap Jaw Reconstruction Surgery Using 3D-Printed Patient-Specific Plates: A Cumulative Sum Analysis

BACKGROUND: Computer-assisted jaw reconstruction (CAJR) has benefits in reducing operation time and improving reconstruction accuracy, compared to conventional freehand jaw reconstruction. However, no information is available regarding learning curves in CAJR with the use of 3D-printed patient-speci...

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Autores principales: Zhu, Wang-yong, Choi, Wing Shan, Wong, May Chun Mei, Pu, Jingya Jane, Yang, Wei-fa, Su, Yu-xiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481918/
https://www.ncbi.nlm.nih.gov/pubmed/34604076
http://dx.doi.org/10.3389/fonc.2021.737769
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author Zhu, Wang-yong
Choi, Wing Shan
Wong, May Chun Mei
Pu, Jingya Jane
Yang, Wei-fa
Su, Yu-xiong
author_facet Zhu, Wang-yong
Choi, Wing Shan
Wong, May Chun Mei
Pu, Jingya Jane
Yang, Wei-fa
Su, Yu-xiong
author_sort Zhu, Wang-yong
collection PubMed
description BACKGROUND: Computer-assisted jaw reconstruction (CAJR) has benefits in reducing operation time and improving reconstruction accuracy, compared to conventional freehand jaw reconstruction. However, no information is available regarding learning curves in CAJR with the use of 3D-printed patient-specific surgical plates (PSSP). The purpose of this study was to assess surgical outcomes and learning curve for the first 58 consecutive CAJR using 3D-printed PSSP performed by a single surgical team in a single institution. METHODS: In a prospective study, consecutive patients who underwent free flap CAJR using 3D-printed PSSP were included. The determination of proficiency, based on the cumulative sum of surgical success (no major adjustment of 3D-printed PSSP, flap survival) passing the acceptable boundary line of cumulative sum analysis, was the primary outcome. To find out any potential factors influencing the learning curve, baseline characteristics of patients were compared before and after proficiency achievement. Secondary outcomes included inflexion points of the total operation time, blood loss, length of hospital stay, and bone graft deviation, measured by the cumulative sum analysis. RESULTS: From December 2016 to November 2020, 58 consecutive cases underwent surgery performed by a single surgical team. The overall surgical success rate was 94.8% (55/58). A three-stage learning curve of primary outcome was observed. The proficiency was achieved after 23 cases. The proportions of advanced tumor staging and concomitant surgery after obtaining proficiency were significantly higher than those before achieving proficiency (p = 0.046 and p < 0.001, respectively). Mean values of operation time, intraoperative blood loss, length of hospital stay, and bone graft deviation were 532.5 ± 119.2 min, 1,006.8 ± 547.2 ml, 16.1 ± 6.3 days, and 0.9 ± 1.2 mm, respectively. Two trends of learning curve were observed in the CUSUM analyses of total operation time, length of hospital stay, and bone graft deviation, in which the first and second inflexion points occurred between 8 and 17 cases and between 43 and 46 cases, respectively. CONCLUSION: Our results revealed a three-stage learning curve of CAJR with the use of PSSP, including initial learning, plateau, and overlearning. Based on CUSUM analysis, the surgical proficiency was achieved after 23 cases, and total operation time, length of hospital stay, and bone graft deviation stabilized after 8–17 cases.
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spelling pubmed-84819182021-10-01 The Learning Curve of Computer-Assisted Free Flap Jaw Reconstruction Surgery Using 3D-Printed Patient-Specific Plates: A Cumulative Sum Analysis Zhu, Wang-yong Choi, Wing Shan Wong, May Chun Mei Pu, Jingya Jane Yang, Wei-fa Su, Yu-xiong Front Oncol Oncology BACKGROUND: Computer-assisted jaw reconstruction (CAJR) has benefits in reducing operation time and improving reconstruction accuracy, compared to conventional freehand jaw reconstruction. However, no information is available regarding learning curves in CAJR with the use of 3D-printed patient-specific surgical plates (PSSP). The purpose of this study was to assess surgical outcomes and learning curve for the first 58 consecutive CAJR using 3D-printed PSSP performed by a single surgical team in a single institution. METHODS: In a prospective study, consecutive patients who underwent free flap CAJR using 3D-printed PSSP were included. The determination of proficiency, based on the cumulative sum of surgical success (no major adjustment of 3D-printed PSSP, flap survival) passing the acceptable boundary line of cumulative sum analysis, was the primary outcome. To find out any potential factors influencing the learning curve, baseline characteristics of patients were compared before and after proficiency achievement. Secondary outcomes included inflexion points of the total operation time, blood loss, length of hospital stay, and bone graft deviation, measured by the cumulative sum analysis. RESULTS: From December 2016 to November 2020, 58 consecutive cases underwent surgery performed by a single surgical team. The overall surgical success rate was 94.8% (55/58). A three-stage learning curve of primary outcome was observed. The proficiency was achieved after 23 cases. The proportions of advanced tumor staging and concomitant surgery after obtaining proficiency were significantly higher than those before achieving proficiency (p = 0.046 and p < 0.001, respectively). Mean values of operation time, intraoperative blood loss, length of hospital stay, and bone graft deviation were 532.5 ± 119.2 min, 1,006.8 ± 547.2 ml, 16.1 ± 6.3 days, and 0.9 ± 1.2 mm, respectively. Two trends of learning curve were observed in the CUSUM analyses of total operation time, length of hospital stay, and bone graft deviation, in which the first and second inflexion points occurred between 8 and 17 cases and between 43 and 46 cases, respectively. CONCLUSION: Our results revealed a three-stage learning curve of CAJR with the use of PSSP, including initial learning, plateau, and overlearning. Based on CUSUM analysis, the surgical proficiency was achieved after 23 cases, and total operation time, length of hospital stay, and bone graft deviation stabilized after 8–17 cases. Frontiers Media S.A. 2021-09-16 /pmc/articles/PMC8481918/ /pubmed/34604076 http://dx.doi.org/10.3389/fonc.2021.737769 Text en Copyright © 2021 Zhu, Choi, Wong, Pu, Yang and Su https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Zhu, Wang-yong
Choi, Wing Shan
Wong, May Chun Mei
Pu, Jingya Jane
Yang, Wei-fa
Su, Yu-xiong
The Learning Curve of Computer-Assisted Free Flap Jaw Reconstruction Surgery Using 3D-Printed Patient-Specific Plates: A Cumulative Sum Analysis
title The Learning Curve of Computer-Assisted Free Flap Jaw Reconstruction Surgery Using 3D-Printed Patient-Specific Plates: A Cumulative Sum Analysis
title_full The Learning Curve of Computer-Assisted Free Flap Jaw Reconstruction Surgery Using 3D-Printed Patient-Specific Plates: A Cumulative Sum Analysis
title_fullStr The Learning Curve of Computer-Assisted Free Flap Jaw Reconstruction Surgery Using 3D-Printed Patient-Specific Plates: A Cumulative Sum Analysis
title_full_unstemmed The Learning Curve of Computer-Assisted Free Flap Jaw Reconstruction Surgery Using 3D-Printed Patient-Specific Plates: A Cumulative Sum Analysis
title_short The Learning Curve of Computer-Assisted Free Flap Jaw Reconstruction Surgery Using 3D-Printed Patient-Specific Plates: A Cumulative Sum Analysis
title_sort learning curve of computer-assisted free flap jaw reconstruction surgery using 3d-printed patient-specific plates: a cumulative sum analysis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481918/
https://www.ncbi.nlm.nih.gov/pubmed/34604076
http://dx.doi.org/10.3389/fonc.2021.737769
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