Assessment of Quality Outcomes and Learning Curve for Robot-Assisted Minimally Invasive McKeown Esophagectomy
Background This study aimed to identify the results of the quality assessment and the learning curve of robot-assisted minimally invasive McKeown esophagectomy (RAMIE-MK). Methods The study retrospectively reviewed the data of 400 consecutive patients with esophageal cancer who underwent RAMIE-MK by...
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| Veröffentlicht in: | Annals of surgical oncology 2021-02, Vol.28 (2), p.676-684 |
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| container_title | Annals of surgical oncology |
| container_volume | 28 |
| creator | Yang, Yang Li, Bin Hua, Rong Zhang, Xiaobin Jiang, Haoyao Sun, Yifeng Veronesi, Giulia Ricciardi, Sara Casiraghi, Monica Durand, Marion Caso, Raul Sarkaria, Inderpal S. Li, ZhiGang |
| description | Background
This study aimed to identify the results of the quality assessment and the learning curve of robot-assisted minimally invasive McKeown esophagectomy (RAMIE-MK).
Methods
The study retrospectively reviewed the data of 400 consecutive patients with esophageal cancer who underwent RAMIE-MK by a single surgeon from November 2015 to March 2019. Cumulative summation analysis of the learning curve was performed. The patients were divided into decile cohorts of 40 cases to minimize demographic deviations and to maximize the power of detecting statistically significant changes in performance.
Results
The 90-day mortality rate for all the patients was 0.5% (2 cases). The authors’ experience was divided into the ascending phase (40 cases), the plateau phase (175 cases), and the descending phase (185 cases). After 40 cases, significant improvements in operative time (328 vs. 251 min;
P
= 0.019), estimated blood loss (350 vs. 200 ml;
P
= 0.031), and conversion rates (12.5% vs. 2.5%;
P
|
| doi_str_mv | 10.1245/s10434-020-08857-0 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2428063529</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2476734716</sourcerecordid><originalsourceid>FETCH-LOGICAL-c441t-f93a2a5171cdc60ae0e0fdb90fd300f25207fd33f6d31199c1d93b8113fed3853</originalsourceid><addsrcrecordid>eNp9kU1v1DAQhi1ERT_gD3BAlrhwCR1_xEmO1arQiq0qEJwtrzNeUiX24kmK9t9j2AJSD73YI_t5X8_4Zey1gPdC6vqcBGilK5BQQdvWTQXP2Imoy5E2rXheajBt1UlTH7NTojsA0SioX7BjJRsJoM0Jmy6IkGjCOPMU-OfFjcO857fL7NOExF3s-RpdjkPc8tWS75GHlPmXtElzVbQDzdjzmyEOkxvHPb-O946GQt34T5h-Rn5JaffdbdHPadq_ZEfBjYSvHvYz9u3D5dfVVbW-_Xi9ulhXXmsxV6FTTrpaNML33oBDQAj9piuLAgiyltCUUgXTKyG6zou-U5tWCBWwV22tzti7g-8upx8L0myngTyOo4uYFrJSyxaMqmVX0LeP0Lu05Fi6K1RjGqUbYQolD5TPiShjsLtcJs57K8D-DsMewrAlDPsnDAtF9ObBetlM2P-T_P39AqgDQOUqbjH_f_sJ21-dP5Us</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2476734716</pqid></control><display><type>article</type><title>Assessment of Quality Outcomes and Learning Curve for Robot-Assisted Minimally Invasive McKeown Esophagectomy</title><source>MEDLINE</source><source>SpringerLink Journals - AutoHoldings</source><creator>Yang, Yang ; Li, Bin ; Hua, Rong ; Zhang, Xiaobin ; Jiang, Haoyao ; Sun, Yifeng ; Veronesi, Giulia ; Ricciardi, Sara ; Casiraghi, Monica ; Durand, Marion ; Caso, Raul ; Sarkaria, Inderpal S. ; Li, ZhiGang</creator><creatorcontrib>Yang, Yang ; Li, Bin ; Hua, Rong ; Zhang, Xiaobin ; Jiang, Haoyao ; Sun, Yifeng ; Veronesi, Giulia ; Ricciardi, Sara ; Casiraghi, Monica ; Durand, Marion ; Caso, Raul ; Sarkaria, Inderpal S. ; Li, ZhiGang ; Written on behalf of the AME Thoracic Surgery Collaborative Group ; Written on behalf of the AME Thoracic Surgery Collaborative Group</creatorcontrib><description>Background
This study aimed to identify the results of the quality assessment and the learning curve of robot-assisted minimally invasive McKeown esophagectomy (RAMIE-MK).
Methods
The study retrospectively reviewed the data of 400 consecutive patients with esophageal cancer who underwent RAMIE-MK by a single surgeon from November 2015 to March 2019. Cumulative summation analysis of the learning curve was performed. The patients were divided into decile cohorts of 40 cases to minimize demographic deviations and to maximize the power of detecting statistically significant changes in performance.
Results
The 90-day mortality rate for all the patients was 0.5% (2 cases). The authors’ experience was divided into the ascending phase (40 cases), the plateau phase (175 cases), and the descending phase (185 cases). After 40 cases, significant improvements in operative time (328 vs. 251 min;
P
= 0.019), estimated blood loss (350 vs. 200 ml;
P
= 0.031), and conversion rates (12.5% vs. 2.5%;
P
< 0.001) were observed. After 80 cases, a decrease in the rates of anastomotic leakage (22.5% vs. 8.1%;
P
= 0.001) and vocal cord palsy (31.3% vs. 18.4%;
P
= 0.024) was observed. The number of harvested lymph nodes increased after 40 cases (13 vs. 23;
P
< 0.001), especially for lymph nodes along the recurrent laryngeal nerve (3.0 vs. 6.0;
P
< 0.001).
Conclusions
The learning phase of RAMIE-MK consists of 40 cases, and quality outcomes can be improved after 80 procedures. Several turning points related to the optimization of surgical outcomes can be used as benchmarks for surgeons performing RAMIE-MK.</description><identifier>ISSN: 1068-9265</identifier><identifier>EISSN: 1534-4681</identifier><identifier>DOI: 10.1245/s10434-020-08857-0</identifier><identifier>PMID: 32720046</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Anastomotic leak ; Esophageal cancer ; Esophageal Neoplasms - surgery ; Esophagectomy ; Esophagus ; Gastrointestinal surgery ; Humans ; Learning ; Learning Curve ; Lymph nodes ; Lymphatic system ; Medicine ; Medicine & Public Health ; Oncology ; Paralysis ; Quality control ; Retrospective Studies ; Robotic surgery ; Robotic Surgical Procedures ; Robotics ; Statistical analysis ; Surgery ; Surgical Oncology ; Thoracic Oncology</subject><ispartof>Annals of surgical oncology, 2021-02, Vol.28 (2), p.676-684</ispartof><rights>Society of Surgical Oncology 2020</rights><rights>Society of Surgical Oncology 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c441t-f93a2a5171cdc60ae0e0fdb90fd300f25207fd33f6d31199c1d93b8113fed3853</citedby><cites>FETCH-LOGICAL-c441t-f93a2a5171cdc60ae0e0fdb90fd300f25207fd33f6d31199c1d93b8113fed3853</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1245/s10434-020-08857-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1245/s10434-020-08857-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32720046$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, Yang</creatorcontrib><creatorcontrib>Li, Bin</creatorcontrib><creatorcontrib>Hua, Rong</creatorcontrib><creatorcontrib>Zhang, Xiaobin</creatorcontrib><creatorcontrib>Jiang, Haoyao</creatorcontrib><creatorcontrib>Sun, Yifeng</creatorcontrib><creatorcontrib>Veronesi, Giulia</creatorcontrib><creatorcontrib>Ricciardi, Sara</creatorcontrib><creatorcontrib>Casiraghi, Monica</creatorcontrib><creatorcontrib>Durand, Marion</creatorcontrib><creatorcontrib>Caso, Raul</creatorcontrib><creatorcontrib>Sarkaria, Inderpal S.</creatorcontrib><creatorcontrib>Li, ZhiGang</creatorcontrib><creatorcontrib>Written on behalf of the AME Thoracic Surgery Collaborative Group</creatorcontrib><creatorcontrib>Written on behalf of the AME Thoracic Surgery Collaborative Group</creatorcontrib><title>Assessment of Quality Outcomes and Learning Curve for Robot-Assisted Minimally Invasive McKeown Esophagectomy</title><title>Annals of surgical oncology</title><addtitle>Ann Surg Oncol</addtitle><addtitle>Ann Surg Oncol</addtitle><description>Background
This study aimed to identify the results of the quality assessment and the learning curve of robot-assisted minimally invasive McKeown esophagectomy (RAMIE-MK).
Methods
The study retrospectively reviewed the data of 400 consecutive patients with esophageal cancer who underwent RAMIE-MK by a single surgeon from November 2015 to March 2019. Cumulative summation analysis of the learning curve was performed. The patients were divided into decile cohorts of 40 cases to minimize demographic deviations and to maximize the power of detecting statistically significant changes in performance.
Results
The 90-day mortality rate for all the patients was 0.5% (2 cases). The authors’ experience was divided into the ascending phase (40 cases), the plateau phase (175 cases), and the descending phase (185 cases). After 40 cases, significant improvements in operative time (328 vs. 251 min;
P
= 0.019), estimated blood loss (350 vs. 200 ml;
P
= 0.031), and conversion rates (12.5% vs. 2.5%;
P
< 0.001) were observed. After 80 cases, a decrease in the rates of anastomotic leakage (22.5% vs. 8.1%;
P
= 0.001) and vocal cord palsy (31.3% vs. 18.4%;
P
= 0.024) was observed. The number of harvested lymph nodes increased after 40 cases (13 vs. 23;
P
< 0.001), especially for lymph nodes along the recurrent laryngeal nerve (3.0 vs. 6.0;
P
< 0.001).
Conclusions
The learning phase of RAMIE-MK consists of 40 cases, and quality outcomes can be improved after 80 procedures. Several turning points related to the optimization of surgical outcomes can be used as benchmarks for surgeons performing RAMIE-MK.</description><subject>Anastomotic leak</subject><subject>Esophageal cancer</subject><subject>Esophageal Neoplasms - surgery</subject><subject>Esophagectomy</subject><subject>Esophagus</subject><subject>Gastrointestinal surgery</subject><subject>Humans</subject><subject>Learning</subject><subject>Learning Curve</subject><subject>Lymph nodes</subject><subject>Lymphatic system</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Oncology</subject><subject>Paralysis</subject><subject>Quality control</subject><subject>Retrospective Studies</subject><subject>Robotic surgery</subject><subject>Robotic Surgical Procedures</subject><subject>Robotics</subject><subject>Statistical analysis</subject><subject>Surgery</subject><subject>Surgical Oncology</subject><subject>Thoracic Oncology</subject><issn>1068-9265</issn><issn>1534-4681</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp9kU1v1DAQhi1ERT_gD3BAlrhwCR1_xEmO1arQiq0qEJwtrzNeUiX24kmK9t9j2AJSD73YI_t5X8_4Zey1gPdC6vqcBGilK5BQQdvWTQXP2Imoy5E2rXheajBt1UlTH7NTojsA0SioX7BjJRsJoM0Jmy6IkGjCOPMU-OfFjcO857fL7NOExF3s-RpdjkPc8tWS75GHlPmXtElzVbQDzdjzmyEOkxvHPb-O946GQt34T5h-Rn5JaffdbdHPadq_ZEfBjYSvHvYz9u3D5dfVVbW-_Xi9ulhXXmsxV6FTTrpaNML33oBDQAj9piuLAgiyltCUUgXTKyG6zou-U5tWCBWwV22tzti7g-8upx8L0myngTyOo4uYFrJSyxaMqmVX0LeP0Lu05Fi6K1RjGqUbYQolD5TPiShjsLtcJs57K8D-DsMewrAlDPsnDAtF9ObBetlM2P-T_P39AqgDQOUqbjH_f_sJ21-dP5Us</recordid><startdate>20210201</startdate><enddate>20210201</enddate><creator>Yang, Yang</creator><creator>Li, Bin</creator><creator>Hua, Rong</creator><creator>Zhang, Xiaobin</creator><creator>Jiang, Haoyao</creator><creator>Sun, Yifeng</creator><creator>Veronesi, Giulia</creator><creator>Ricciardi, Sara</creator><creator>Casiraghi, Monica</creator><creator>Durand, Marion</creator><creator>Caso, Raul</creator><creator>Sarkaria, Inderpal S.</creator><creator>Li, ZhiGang</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>20210201</creationdate><title>Assessment of Quality Outcomes and Learning Curve for Robot-Assisted Minimally Invasive McKeown Esophagectomy</title><author>Yang, Yang ; Li, Bin ; Hua, Rong ; Zhang, Xiaobin ; Jiang, Haoyao ; Sun, Yifeng ; Veronesi, Giulia ; Ricciardi, Sara ; Casiraghi, Monica ; Durand, Marion ; Caso, Raul ; Sarkaria, Inderpal S. ; Li, ZhiGang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c441t-f93a2a5171cdc60ae0e0fdb90fd300f25207fd33f6d31199c1d93b8113fed3853</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Anastomotic leak</topic><topic>Esophageal cancer</topic><topic>Esophageal Neoplasms - surgery</topic><topic>Esophagectomy</topic><topic>Esophagus</topic><topic>Gastrointestinal surgery</topic><topic>Humans</topic><topic>Learning</topic><topic>Learning Curve</topic><topic>Lymph nodes</topic><topic>Lymphatic system</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Oncology</topic><topic>Paralysis</topic><topic>Quality control</topic><topic>Retrospective Studies</topic><topic>Robotic surgery</topic><topic>Robotic Surgical Procedures</topic><topic>Robotics</topic><topic>Statistical analysis</topic><topic>Surgery</topic><topic>Surgical Oncology</topic><topic>Thoracic Oncology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Yang</creatorcontrib><creatorcontrib>Li, Bin</creatorcontrib><creatorcontrib>Hua, Rong</creatorcontrib><creatorcontrib>Zhang, Xiaobin</creatorcontrib><creatorcontrib>Jiang, Haoyao</creatorcontrib><creatorcontrib>Sun, Yifeng</creatorcontrib><creatorcontrib>Veronesi, Giulia</creatorcontrib><creatorcontrib>Ricciardi, Sara</creatorcontrib><creatorcontrib>Casiraghi, Monica</creatorcontrib><creatorcontrib>Durand, Marion</creatorcontrib><creatorcontrib>Caso, Raul</creatorcontrib><creatorcontrib>Sarkaria, Inderpal S.</creatorcontrib><creatorcontrib>Li, ZhiGang</creatorcontrib><creatorcontrib>Written on behalf of the AME Thoracic Surgery Collaborative Group</creatorcontrib><creatorcontrib>Written on behalf of the AME Thoracic Surgery Collaborative Group</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Annals of surgical oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Yang</au><au>Li, Bin</au><au>Hua, Rong</au><au>Zhang, Xiaobin</au><au>Jiang, Haoyao</au><au>Sun, Yifeng</au><au>Veronesi, Giulia</au><au>Ricciardi, Sara</au><au>Casiraghi, Monica</au><au>Durand, Marion</au><au>Caso, Raul</au><au>Sarkaria, Inderpal S.</au><au>Li, ZhiGang</au><aucorp>Written on behalf of the AME Thoracic Surgery Collaborative Group</aucorp><aucorp>Written on behalf of the AME Thoracic Surgery Collaborative Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessment of Quality Outcomes and Learning Curve for Robot-Assisted Minimally Invasive McKeown Esophagectomy</atitle><jtitle>Annals of surgical oncology</jtitle><stitle>Ann Surg Oncol</stitle><addtitle>Ann Surg Oncol</addtitle><date>2021-02-01</date><risdate>2021</risdate><volume>28</volume><issue>2</issue><spage>676</spage><epage>684</epage><pages>676-684</pages><issn>1068-9265</issn><eissn>1534-4681</eissn><abstract>Background
This study aimed to identify the results of the quality assessment and the learning curve of robot-assisted minimally invasive McKeown esophagectomy (RAMIE-MK).
Methods
The study retrospectively reviewed the data of 400 consecutive patients with esophageal cancer who underwent RAMIE-MK by a single surgeon from November 2015 to March 2019. Cumulative summation analysis of the learning curve was performed. The patients were divided into decile cohorts of 40 cases to minimize demographic deviations and to maximize the power of detecting statistically significant changes in performance.
Results
The 90-day mortality rate for all the patients was 0.5% (2 cases). The authors’ experience was divided into the ascending phase (40 cases), the plateau phase (175 cases), and the descending phase (185 cases). After 40 cases, significant improvements in operative time (328 vs. 251 min;
P
= 0.019), estimated blood loss (350 vs. 200 ml;
P
= 0.031), and conversion rates (12.5% vs. 2.5%;
P
< 0.001) were observed. After 80 cases, a decrease in the rates of anastomotic leakage (22.5% vs. 8.1%;
P
= 0.001) and vocal cord palsy (31.3% vs. 18.4%;
P
= 0.024) was observed. The number of harvested lymph nodes increased after 40 cases (13 vs. 23;
P
< 0.001), especially for lymph nodes along the recurrent laryngeal nerve (3.0 vs. 6.0;
P
< 0.001).
Conclusions
The learning phase of RAMIE-MK consists of 40 cases, and quality outcomes can be improved after 80 procedures. Several turning points related to the optimization of surgical outcomes can be used as benchmarks for surgeons performing RAMIE-MK.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>32720046</pmid><doi>10.1245/s10434-020-08857-0</doi><tpages>9</tpages></addata></record> |
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| ispartof | Annals of surgical oncology, 2021-02, Vol.28 (2), p.676-684 |
| issn | 1068-9265 1534-4681 |
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| source | MEDLINE; SpringerLink Journals - AutoHoldings |
| subjects | Anastomotic leak Esophageal cancer Esophageal Neoplasms - surgery Esophagectomy Esophagus Gastrointestinal surgery Humans Learning Learning Curve Lymph nodes Lymphatic system Medicine Medicine & Public Health Oncology Paralysis Quality control Retrospective Studies Robotic surgery Robotic Surgical Procedures Robotics Statistical analysis Surgery Surgical Oncology Thoracic Oncology |
| title | Assessment of Quality Outcomes and Learning Curve for Robot-Assisted Minimally Invasive McKeown Esophagectomy |
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