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Harmantepe AT, Cantürk AÖ. Is YouTube Reliable to Teach Laparoscopic Gastric Bypass? Cureus 2024; 16:e62510. [PMID: 39022506 PMCID: PMC11253075 DOI: 10.7759/cureus.62510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2024] [Indexed: 07/20/2024] Open
Abstract
AIM The increasing prevalence of obesity has led to the popularity of bariatric surgery. Laparoscopic Roux-en-Y gastric bypass (LRYGB) is one of the most complex methods in bariatric surgery. The main steps of LRYGB were determined in the Delphi Consensus. This study investigated the instructiveness and reliability of YouTube videos about LRYGB based on the Delphi Consensus. METHODS In February 2024, three different searches were done in the search bar of the YouTube platform with the terms "laparoscopic gastric bypass" "laparoscopic Roux-en-Y gastric bypass" and "laparoscopic RYGB". The first 50 videos in each search were evaluated. Animations, lectures, advertisements, non-English videos, and non-surgical videos (pre-surgery, post-surgery vlog, etc.) were excluded from the study. Delphi consensus steps were used to determine the reliability of the videos. The quality of the videos was measured using the Global Quality Scale (GQS) and modified DISCERN test. RESULTS Forty-five videos were included in the evaluation. While 14 (31.1%) of these videos were classified as reliable, 31 (68.8%) were not found reliable. In reliable videos, video description, high definition (HD) resolution, GQS, and modified DISCERN were significantly higher (p-value 0.023, 0.004, 0.017, and 0.025 respectively). CONCLUSION The rate of unreliable videos was higher on the YouTube platform. We conclude that YouTube alone is insufficient to learn LRYGB.
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Affiliation(s)
- Ahmet Tarik Harmantepe
- Gastroenterology Surgery, Sakarya University Training and Research Hospital, Sakarya, TUR
| | - Alp Ömer Cantürk
- General Surgery, Sakarya University Training and Research Hospital, Sakarya, TUR
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Kaijser MA, van Ramshorst GH, van Wagensveld BA, Veeger NJGM, Pierie JPEN. A New Procedure-Based Assessment of Operative Skills in Gastric Bypass Surgery, Evaluated by Video Fragment Rating. Obes Surg 2024; 34:1113-1121. [PMID: 38400947 PMCID: PMC11026254 DOI: 10.1007/s11695-023-07020-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/16/2023] [Accepted: 12/17/2023] [Indexed: 02/26/2024]
Abstract
PURPOSE Feedback on technical and procedural skills is essential during the training of residents and fellows. The aim of this study was to assess the performance of a newly created instrument for the assessment of operative skills using laparoscopic Roux-en-Y gastric bypass (LRYGB) video fragments. MATERIALS AND METHODS A new procedure-based assessment (PBA) was created by combining LRYGB key steps with a 5-point independence scale. LRYGB performed by residents and surgeons with different levels of expertise were video recorded. Fragments of the pouch creation, gastro-jejunostomy and jejunojejunostomy, were review by 12 expert bariatric surgeons and the operative skills assessed with the PBA, Objective Structured Assessment of Technical Skill (OSATS), and the Bariatric OSATS (BOSATS). The PBA was compared to the OSATS and BOSATS. Mean scores for all items of the different assessments were summarized and compared using a T-test. RESULTS The scores of the procedural steps were combined and compared for all levels. The mean scores for beginner, intermediate, and expert level were 2.71, 3.70, and 3.90 for the PBA; for the OSATS 1.84, 2.86, and 3.44; and for the BOSATS 2.78, 3.56, and 4.19. Each of these assessments differentiated between the three skill levels (all p < 0.05). CONCLUSION The PBA discriminates well between different levels of operative skills. Similar patterns were found for the OSATS and BOSATS, showing that the randomly selected video fragments are representative samples for assessing skill level. Future research will demonstrate whether these results can be extrapolated to clinical training, and which scores allow for procedure certification.
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Affiliation(s)
- Mirjam A Kaijser
- School of Medicine, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands.
- Department of Surgery, Medical Centre Leeuwarden, Leeuwarden, The Netherlands.
- Center for Obesity Northern Netherlands, Medical Center Leeuwarden, Henri Dunantweg 2, 8934 AD, Leeuwarden, The Netherlands.
| | - Gabrielle H van Ramshorst
- Department of Gastrointestinal Surgery, Ghent University Hospital, Ghent, Belgium
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Bart A van Wagensveld
- Weight Management Center, Department of Surgery, NMC Royal Hospital, Khalifa City, Abu Dhabi, United Arab Emirates
| | - Nic J G M Veeger
- Department of Epidemiology, Medical Center Leeuwarden, Leeuwarden, The Netherlands
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jean-Pierre E N Pierie
- School of Medicine, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
- Department of Surgery, Medical Centre Leeuwarden, Leeuwarden, The Netherlands
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Dayan D. Implementation of Artificial Intelligence-Based Computer Vision Model for Sleeve Gastrectomy: Experience in One Tertiary Center. Obes Surg 2024; 34:330-336. [PMID: 38180619 DOI: 10.1007/s11695-023-07043-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 12/23/2023] [Accepted: 12/28/2023] [Indexed: 01/06/2024]
Abstract
INTRODUCTION Sleeve gastrectomy (SG) is the most common metabolic and bariatric procedure performed. Leveraging artificial intelligence (AI) for automated real-time data structuring and annotations of surgical videos has immense potential of clinical applications. This study presents initial real-world implementation of AI-based computer vision model in sleeve gastrectomy (SG) and external validation of accuracy of safety milestone annotations. METHODS A retrospective single-center study of 49 consecutive SG videos was captured and analyzed by the AI platform (December 2020-August 2023). A bariatric surgeon viewed all videos and assessed safety milestones adherence, compared to the AI annotations. Patients' data were retrieved from the bariatric unit registry. RESULTS SG total duration was 47.5 min (interquartile range 36-64). Main steps included preparation (12.2%), dissection of the greater curvature (30.8%), gastric transection (28.5%), specimen extraction (7.2%), and final inspection (14.4%). Out of body time comprised 6.9% of the total video. Safety milestones components and AI-surgeon agreements included the following: bougie insertion (100%), distance from pylorus ≥ 2 cm (100%), parallel to lesser curvature (98%), fundus mobilization (100%), and distance from esophagus ≥ 1 cm (true-100%, false-13.6%; kappa coefficient 0.2, p = 0.006). Intraoperative complications included notable hemorrhage (n = 4) and parenchymal injury (n = 1). CONCLUSIONS The AI model provides a fully automated SG video analysis. Outcomes suggest its accuracy in four of five safety milestone annotations. This data is valuable, as it reflects objective performance measures which can help us improve the surgical quality and efficiency of SG. Larger cohorts will enable SG standardization and clinical correlations with outcomes, aiming to improve patients' safety.
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Affiliation(s)
- Danit Dayan
- Division of General Surgery, Bariatric Unit, Tel Aviv Medical Center, Affiliated to Sackler Faculty of Medicine, Tel Aviv University, 6, Weizman St., Tel Aviv, Israel.
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Ma L, Gao Z, Luo H, Kou S, Lei Y, Jia V, Lan K, Sankar S, Hu J, Tian Y. Comparison of the postoperative outcome with and without intraoperative leak testing for sleeve gastrectomy: a systematic review and meta-analysis of 469 588 cases. Int J Surg 2024; 110:1196-1205. [PMID: 37988416 PMCID: PMC10871606 DOI: 10.1097/js9.0000000000000919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 11/05/2023] [Indexed: 11/23/2023]
Abstract
OBJECTIVE Postoperative staple line leakage (SLL) after sleeve gastrectomy (SG) is a rare but serious complication. Many surgeons routinely test anastomosis with an intraoperative leak test (IOLT) as part of the SG procedure. This meta-analysis aims to determine whether an IOLT plays a role in reducing the rate of postoperative staple line related complications in patients who underwent SG. METHODS The authors searched the PubMed, Web of science, the Cochrane Library, and Clinical Trials.gov databases for clinical studies assessing the application of IOLT in SG. The primary endpoint was the development of postoperative SLL. Secondary endpoints included the postoperative bleeding, 30 days mortality rates, and 30 days readmission rates. RESULTS Six studies totaling 469 588 patients met the inclusion criteria. Our review found that the SLL rate was 0.38% (1221/ 324 264) in the IOLT group and 0.31% (453/ 145 324) in the no intraoperative leak test (NIOLT) group. Postoperative SLL decreased in the NIOLT group compared with the IOLT group (OR=1.27; 95% CI: 1.14-1.42, P =0.000). Postoperative bleeding was fewer in the IOLT group than that in the NIOLT group (OR 0.79; 95% CI: 0.72-0.87, P =0.000). There was no significant difference between the IOLT group and the NIOLT group regarding 30 days mortality rates and 30 days readmission rates ( P >0.05). CONCLUSION IOLT was correlated with an increase in SLL when included as a part of the SG procedure. However, IOLT was associated with a lower rate of postoperative bleeding. Thus, IOLT should be considered in SG in the situation of suspected postoperative bleeding.
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Affiliation(s)
- Longyin Ma
- Department of General Surgery, The Affiliated Nanchong Central Hospital of North Sichuan Medical College (University)
| | - Zhenguo Gao
- Department of General Surgery, The Affiliated Nanchong Central Hospital of North Sichuan Medical College (University)
| | - Heng Luo
- Department of General Surgery, The Affiliated Nanchong Central Hospital of North Sichuan Medical College (University)
| | - Shien Kou
- Department of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China
| | - Yu Lei
- Department of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China
| | - Victor Jia
- School of Medicine, University of Michigan, Ann Arbor
| | - Ke Lan
- Department of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China
| | - Subbiah Sankar
- Department of General Surgery, The Affiliated Nanchong Central Hospital of North Sichuan Medical College (University)
| | - Jiani Hu
- Department of Radiology, Wayne State University, Detroit, Michigan, USA
| | - Yunhong Tian
- Department of General Surgery, The Affiliated Nanchong Central Hospital of North Sichuan Medical College (University)
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Gillani M, Rupji M, Devin C, Purvis L, Olson TP, Jarc A, Shields M, Liu Y, Rosen S. Quantification of Surgical Workflow during Robotic Proctectomy. RESEARCH SQUARE 2023:rs.3.rs-3462719. [PMID: 37886442 PMCID: PMC10602135 DOI: 10.21203/rs.3.rs-3462719/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Aim Assessments of surgical workflow offer insight regarding procedure variability, case complexity and surgeon proficiency. We utilize an objective method to evaluate step-by-step workflow and step transitions during robotic proctectomy (RP). Methods We annotated 31 RPs using a procedure-specific annotation card. Using Spearman's correlation, we measured strength of association of step time and step visit frequency with console time (CT) and total operative time (TOT). Results Across 31 RPs, a mean (± standard deviation) of 49.0 (± 20.3) steps occurred per procedure. Mean CT and TOT were 213 (± 90) and 283 (± 108) minutes. Posterior mesorectal dissection required most visits (8.7 ± 5.0), while anastomosis required most time (18.0 [± 8.5] minutes). Inferior mesenteric vein (IMV) ligation required least visits (1.0 ± 0.0) and lowest duration (0.9 [± 0.5] minutes). Strong correlations were seen with CT and step times for IMV dissection and ligation (ρ = 0.60 for both), lateral-to-medial splenic flexure mobilization (SFM) (ρ = 0.63), left rectal dissection (ρ = 0.64) and mesorectal division (ρ = 0.71). CT correlated strongly with medial-to-lateral and supracolic SFM visit frequency (ρ = 0.75 and ρ = 0.65). There were strong correlations with TOT and initial exposure time (ρ = 0.60), as well as visit frequency for medial-to-lateral (ρ = 0.67) and supracolic SFM (ρ = 0.65). Descending colon mobilization was nodal, rectal mobilization convergent and rectal transection divergent. Conclusion This study correlates individual surgical steps with CT and TOT through standardized annotation. It provides an objective approach to quantify workflow.
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Vu AH, Chiang J, Qian Y, Tursunova N, Nha J, Ferzli G. Do all roads lead to Rome? A retrospective analysis on surgical technique in sleeve gastrectomy. Surg Endosc 2023; 37:8064-8071. [PMID: 37488445 DOI: 10.1007/s00464-023-10298-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 07/12/2023] [Indexed: 07/26/2023]
Abstract
BACKGROUND New York University Langone Health has three accredited bariatric centers, with 10 different bariatric surgeons. This retrospective analysis compares surgeon techniques in laparoscopic or robotic sleeve gastrectomy (SG) to identify associations with perioperative morbidity and mortality. METHODS All adults who underwent SG between 2017 and 2021 at NYU Langone Health were evaluated via EMR and MBSAQIP 30-day data. We also surveyed all 10 bariatric surgeons and compared their techniques and total adverse outcomes. Bleeding, SSI, mortality, readmission, and reoperation were specifically sub-analyzed via logistic regression. RESULTS 86 (2.77%) out of 3,104 patients who underwent SG encountered an adverse event. Lower adverse outcomes were observed with a laparoscopic approach, 40-Fr bougie, buttressing, not oversewing the staple line, using hemostatic agents, stapling 3-cm from pylorus, and no routine UGI series. Lower bleeding rates were observed in a laparoscopic approach, 40-Fr bougie, buttressing, not oversewing the staple line, using hemostatic agents, stapling 3-cm from pylorus, no routine UGI series, and not proceeding with SG if hiatal hernia is present. Lower SSI rates were observed with ViSiGi™ bougie, no hemostatic agents, and routine EGD. Lower readmission rates were observed with 40-Fr bougie, buttressing, not oversewing, and stapling 3-cm from pylorus. Hemostatic agents had higher reoperation rates. It was not feasible to test for mortality given the low incidence. CONCLUSION Certain surgical techniques in SG among our bariatric surgeons had a significant effect on the rates of adverse outcomes, bleeding, readmission, reoperation, and SSI. Our findings warrant further investigation into these techniques via multivariate regression or prospective design. LIMITATIONS This study was limited by its retrospective and univariate design. We did not account for interaction. The sample size was small, and follow-up of 30 days was relatively short. We did not include patient characteristics in the model or control for surgeon skill.
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Affiliation(s)
- Alexander Hien Vu
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA.
| | - Jessica Chiang
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA
| | - Yunzhi Qian
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Nilufar Tursunova
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA
| | - Jaein Nha
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA
| | - George Ferzli
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA.
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Vu AH, Chiang J, Qian Y, Tursunova N, Nha J, Ferzli G. Do all roads lead to Rome?: A retrospective analysis on surgical technique in Roux-en-Y gastric bypass. Surg Endosc 2023; 37:7254-7263. [PMID: 37415013 DOI: 10.1007/s00464-023-10257-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 06/23/2023] [Indexed: 07/08/2023]
Abstract
BACKGROUND New York University Langone Health has three accredited bariatric centers, with altogether ten different bariatric surgeons. This retrospective analysis compares individual surgeon techniques in laparoscopic or robotic Roux-en-Y gastric bypass (RYGB) to identify potential associations with perioperative morbidity and mortality. METHODS All adult patients who underwent RYGB between 2017 and 2021 at NYU Langone Health campuses were evaluated via electronic medical records and MBSAQIP 30-day follow-up data. We surveyed all ten practicing bariatric surgeons to analyze the relationship between their techniques and total adverse outcomes. Bleeding, SSI, mortality, readmission, and reoperation were specifically sub-analyzed via logistic regression. RESULTS 54 (7.59%) out of 711 patients who underwent laparoscopic or robotic RYGB encountered an adverse outcome. Lower adverse outcomes were observed with laparoscopic approach, creating the JJ anastomosis first, flat positioning, division of the mesentery, Covidien™ laparoscopic staplers, gold staples, unidirectional JJ anastomosis, hand-sewn common enterotomy, 100-cm Roux limb, 50-cm biliopancreatic limb, and routine EGD. Lower bleeding rates were observed with flat positioning, gold staples, hand-sewn common enterotomy, 50-cm biliopancreatic limb, and routine EGD. Lower readmission rates were observed in laparoscopic, flat positioning, Covidien™ staplers, unidirectional JJ anastomosis, and hand-sewn common enterotomy. Gold staples had lower reoperation rates. Otherwise, there was no statistically significant difference in SSI. CONCLUSION Certain surgical techniques in RYGB within our bariatric surgery group had significant effects on the rates of total adverse outcomes, bleeding, readmission, and reoperation. Our findings warrant further investigation into the aforementioned techniques via multivariate regression models or prospective study design. LIMITATIONS This study was limited by the inherent nature of its retrospective and univariate statistical design. We did not account for the interaction between techniques. The sample size of surgeons was small, and follow-up of 30 days was relatively short. We did not include patient characteristics in the model or control for surgeon skill.
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Affiliation(s)
- Alexander Hien Vu
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA.
| | - Jessica Chiang
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA
| | - Yunzhi Qian
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Nilufar Tursunova
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA
| | - Jaein Nha
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA
| | - George Ferzli
- Department of General Surgery, New York University Langone Health, 150 55th Street, Brooklyn, NY, 11220, USA.
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Maier-Hein L, Eisenmann M, Sarikaya D, März K, Collins T, Malpani A, Fallert J, Feussner H, Giannarou S, Mascagni P, Nakawala H, Park A, Pugh C, Stoyanov D, Vedula SS, Cleary K, Fichtinger G, Forestier G, Gibaud B, Grantcharov T, Hashizume M, Heckmann-Nötzel D, Kenngott HG, Kikinis R, Mündermann L, Navab N, Onogur S, Roß T, Sznitman R, Taylor RH, Tizabi MD, Wagner M, Hager GD, Neumuth T, Padoy N, Collins J, Gockel I, Goedeke J, Hashimoto DA, Joyeux L, Lam K, Leff DR, Madani A, Marcus HJ, Meireles O, Seitel A, Teber D, Ückert F, Müller-Stich BP, Jannin P, Speidel S. Surgical data science - from concepts toward clinical translation. Med Image Anal 2022; 76:102306. [PMID: 34879287 PMCID: PMC9135051 DOI: 10.1016/j.media.2021.102306] [Citation(s) in RCA: 86] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 11/03/2021] [Accepted: 11/08/2021] [Indexed: 02/06/2023]
Abstract
Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data. While an increasing number of data-driven approaches and clinical applications have been studied in the fields of radiological and clinical data science, translational success stories are still lacking in surgery. In this publication, we shed light on the underlying reasons and provide a roadmap for future advances in the field. Based on an international workshop involving leading researchers in the field of SDS, we review current practice, key achievements and initiatives as well as available standards and tools for a number of topics relevant to the field, namely (1) infrastructure for data acquisition, storage and access in the presence of regulatory constraints, (2) data annotation and sharing and (3) data analytics. We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process.
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Affiliation(s)
- Lena Maier-Hein
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany; Medical Faculty, Heidelberg University, Heidelberg, Germany.
| | - Matthias Eisenmann
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Duygu Sarikaya
- Department of Computer Engineering, Faculty of Engineering, Gazi University, Ankara, Turkey; LTSI, Inserm UMR 1099, University of Rennes 1, Rennes, France
| | - Keno März
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Anand Malpani
- The Malone Center for Engineering in Healthcare, The Johns Hopkins University, Baltimore, Maryland, USA
| | | | - Hubertus Feussner
- Department of Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Stamatia Giannarou
- The Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom
| | - Pietro Mascagni
- ICube, University of Strasbourg, CNRS, France; IHU Strasbourg, Strasbourg, France
| | | | - Adrian Park
- Department of Surgery, Anne Arundel Health System, Annapolis, Maryland, USA; Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Carla Pugh
- Department of Surgery, Stanford University School of Medicine, Stanford, California, USA
| | - Danail Stoyanov
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom
| | - Swaroop S Vedula
- The Malone Center for Engineering in Healthcare, The Johns Hopkins University, Baltimore, Maryland, USA
| | - Kevin Cleary
- The Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, D.C., USA
| | | | - Germain Forestier
- L'Institut de Recherche en Informatique, Mathématiques, Automatique et Signal (IRIMAS), University of Haute-Alsace, Mulhouse, France; Faculty of Information Technology, Monash University, Clayton, Victoria, Australia
| | - Bernard Gibaud
- LTSI, Inserm UMR 1099, University of Rennes 1, Rennes, France
| | - Teodor Grantcharov
- University of Toronto, Toronto, Ontario, Canada; The Li Ka Shing Knowledge Institute of St. Michael's Hospital, Toronto, Ontario, Canada
| | - Makoto Hashizume
- Kyushu University, Fukuoka, Japan; Kitakyushu Koga Hospital, Fukuoka, Japan
| | - Doreen Heckmann-Nötzel
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hannes G Kenngott
- Department for General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Ron Kikinis
- Department of Radiology, Brigham and Women's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | | | - Nassir Navab
- Computer Aided Medical Procedures, Technical University of Munich, Munich, Germany; Department of Computer Science, The Johns Hopkins University, Baltimore, Maryland, USA
| | - Sinan Onogur
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tobias Roß
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany; Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Raphael Sznitman
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Russell H Taylor
- Department of Computer Science, The Johns Hopkins University, Baltimore, Maryland, USA
| | - Minu D Tizabi
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin Wagner
- Department for General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Gregory D Hager
- The Malone Center for Engineering in Healthcare, The Johns Hopkins University, Baltimore, Maryland, USA; Department of Computer Science, The Johns Hopkins University, Baltimore, Maryland, USA
| | - Thomas Neumuth
- Innovation Center Computer Assisted Surgery (ICCAS), University of Leipzig, Leipzig, Germany
| | - Nicolas Padoy
- ICube, University of Strasbourg, CNRS, France; IHU Strasbourg, Strasbourg, France
| | - Justin Collins
- Division of Surgery and Interventional Science, University College London, London, United Kingdom
| | - Ines Gockel
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, Leipzig University Hospital, Leipzig, Germany
| | - Jan Goedeke
- Pediatric Surgery, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Daniel A Hashimoto
- University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, Ohio, USA; Surgical AI and Innovation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Luc Joyeux
- My FetUZ Fetal Research Center, Department of Development and Regeneration, Biomedical Sciences, KU Leuven, Leuven, Belgium; Center for Surgical Technologies, Faculty of Medicine, KU Leuven, Leuven, Belgium; Department of Obstetrics and Gynecology, Division Woman and Child, Fetal Medicine Unit, University Hospitals Leuven, Leuven, Belgium; Michael E. DeBakey Department of Surgery, Texas Children's Hospital and Baylor College of Medicine, Houston, Texas, USA
| | - Kyle Lam
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Daniel R Leff
- Department of BioSurgery and Surgical Technology, Imperial College London, London, United Kingdom; Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom; Breast Unit, Imperial Healthcare NHS Trust, London, United Kingdom
| | - Amin Madani
- Department of Surgery, University Health Network, Toronto, Ontario, Canada
| | - Hani J Marcus
- National Hospital for Neurology and Neurosurgery, and UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Ozanan Meireles
- Massachusetts General Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Alexander Seitel
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dogu Teber
- Department of Urology, City Hospital Karlsruhe, Karlsruhe, Germany
| | - Frank Ückert
- Institute for Applied Medical Informatics, Hamburg University Hospital, Hamburg, Germany
| | - Beat P Müller-Stich
- Department for General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Pierre Jannin
- LTSI, Inserm UMR 1099, University of Rennes 1, Rennes, France
| | - Stefanie Speidel
- Division of Translational Surgical Oncology, National Center for Tumor Diseases (NCT/UCC) Dresden, Dresden, Germany; Centre for Tactile Internet with Human-in-the-Loop (CeTI), TU Dresden, Dresden, Germany
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Marcus HJ, Khan DZ, Borg A, Buchfelder M, Cetas JS, Collins JW, Dorward NL, Fleseriu M, Gurnell M, Javadpour M, Jones PS, Koh CH, Layard Horsfall H, Mamelak AN, Mortini P, Muirhead W, Oyesiku NM, Schwartz TH, Sinha S, Stoyanov D, Syro LV, Tsermoulas G, Williams A, Winder MJ, Zada G, Laws ER. Pituitary society expert Delphi consensus: operative workflow in endoscopic transsphenoidal pituitary adenoma resection. Pituitary 2021; 24:839-853. [PMID: 34231079 PMCID: PMC8259776 DOI: 10.1007/s11102-021-01162-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/09/2021] [Indexed: 12/19/2022]
Abstract
PURPOSE Surgical workflow analysis seeks to systematically break down operations into hierarchal components. It facilitates education, training, and understanding of surgical variations. There are known educational demands and variations in surgical practice in endoscopic transsphenoidal approaches to pituitary adenomas. Through an iterative consensus process, we generated a surgical workflow reflective of contemporary surgical practice. METHODS A mixed-methods consensus process composed of a literature review and iterative Delphi surveys was carried out within the Pituitary Society. Each round of the survey was repeated until data saturation and > 90% consensus was reached. RESULTS There was a 100% response rate and no attrition across both Delphi rounds. Eighteen international expert panel members participated. An extensive workflow of 4 phases (nasal, sphenoid, sellar and closure) and 40 steps, with associated technical errors and adverse events, were agreed upon by 100% of panel members across rounds. Both core and case-specific or surgeon-specific variations in operative steps were captured. CONCLUSIONS Through an international expert panel consensus, a workflow for the performance of endoscopic transsphenoidal pituitary adenoma resection has been generated. This workflow captures a wide range of contemporary operative practice. The agreed "core" steps will serve as a foundation for education, training, assessment and technological development (e.g. models and simulators). The "optional" steps highlight areas of heterogeneity of practice that will benefit from further research (e.g. methods of skull base repair). Further adjustments could be made to increase applicability around the world.
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Affiliation(s)
- Hani J Marcus
- Division of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK.
| | - Danyal Z Khan
- Division of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Anouk Borg
- Department of Neurosurgery, John Radcliffe Hospital, Oxford, UK
| | - Michael Buchfelder
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
| | - Justin S Cetas
- Department of Neurosurgery, Oregon Health & Science University, Portland, USA
| | - Justin W Collins
- Department of Uro-Oncology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Neil L Dorward
- Division of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Maria Fleseriu
- Department of Neurosurgery, Oregon Health & Science University, Portland, USA
- Departments of Medicine (Endocrinology), Oregon Health & Science University, Portland, USA
| | - Mark Gurnell
- Division of Clinical Endocrinology & NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Mohsen Javadpour
- Department of Neurosurgery, National Neurosurgical Centre, Beaumont Hospital, Dublin, Ireland
| | - Pamela S Jones
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Chan Hee Koh
- Division of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Hugo Layard Horsfall
- Division of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Adam N Mamelak
- Department of Neurosurgery and Pituitary Center, Cedars-Sinai Medical Center, Los Angeles, USA
| | - Pietro Mortini
- Department of Neurosurgery, San Raffaele University Health Institute Milan, Milan, Italy
| | - William Muirhead
- Division of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Nelson M Oyesiku
- Department of Neurosurgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Medicine (Endocrinology), University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Theodore H Schwartz
- Department of Neurosurgery, Weill Medical College of Cornell University, New York, USA
| | - Saurabh Sinha
- Department of Neurosurgery, Royal Hallamshire Hospital & Sheffield Children's Hospital, Sheffield, UK
| | - Danail Stoyanov
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Luis V Syro
- Department of Neurosurgery, Hospital Pablo Tobon Uribe and Clinica Medellin-Grupo Quirónsalud, Medellin, Colombia
| | - Georgios Tsermoulas
- Department of Neurosurgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK
- Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK
| | - Adam Williams
- Department of Neurosurgery, Southmead Hospital Bristol, Bristol, UK
| | - Mark J Winder
- Department of Neurosurgery, St Vincent's Public and Private Hospitals, Sydney, Australia
| | - Gabriel Zada
- Department of Neurosurgery, University of Southern California, Los Angeles, California, USA
| | - Edward R Laws
- Department of Neurosurgery, Brigham and Women's Hospital, BTM 4, 60 Fenwood Road, Boston, USA
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Zechariah S, Waller JL, De Leo G, Stallings J, Gess AJ, Lehman L. Content and Face Validation of a Novel, Interactive Nutrition Specific Physical Exam Competency Tool (INSPECT) to Evaluate Registered Dietitians' Competence: A Delphi Consensus from the United States. Healthcare (Basel) 2021; 9:healthcare9091225. [PMID: 34574998 PMCID: PMC8472113 DOI: 10.3390/healthcare9091225] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 11/16/2022] Open
Abstract
The nutrition-focused physical examination (NFPE) is an integral component of nutrition assessment performed by registered dietitian nutritionists (RDNs) to determine signs of malnutrition and other nutrition-related complications. Increased use of this essential skill among RDNs and the transformation of dietetics education to a competency-based model in the near future calls for appropriately validated tools to measure RDNs' NFPE competence. To fill the need for a validated competency tool, this study developed an Interactive Nutrition-Specific Physical Exam Competency Tool (INSPECT) utilizing the initial 70 items identified in the first phase of the study. The second phase of this study aimed to test the preliminary version of the INSPECT for content and face validity. An expert panel of 17 members provided consensus recommendations through the Delphi process. Internal consistency of the consensus was measured with Cronbach's alpha (α) and α of ≥0.70 was defined as acceptable a priori. Inter-rater agreement among the expert panel was determined using the intraclass correlation coefficient (ICC) and an a priori ICC of 0.75 to 0.9 was established as good and >0.9 as excellent agreement. The results showed acceptable face validity (α = 0.71) and excellent content validity for the INSPECT, with an internal consistency of α = 0.97 in the first round and α = 0.96 in the second round. The inter-rater agreement was also excellent with ICC = 0.95 for each of the Delphi rounds. A total of 52 items were retained from the preliminary version of the INSPECT. Open feedback from the experts allowed for the consolidation of 11 similar items for better scoring and evaluation and thus, a total of 41 items were included in the final version of the INSPECT. The final version of the INSPECT is currently being studied in real-life, multi-site clinical settings among practicing RDNs to examine construct validity, reliability, and item-level psychometric properties. Ultimately, the validated INSPECT will be available for the competency evaluation of RDNs practicing in clinical settings.
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Affiliation(s)
- Sunitha Zechariah
- College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA; (G.D.L.); (J.S.)
- Correspondence:
| | | | - Gianluca De Leo
- College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA; (G.D.L.); (J.S.)
| | - Judith Stallings
- College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA; (G.D.L.); (J.S.)
| | - Ashley J. Gess
- College of Education, Augusta University, Augusta, GA 30912, USA;
| | - Leigh Lehman
- School of Occupational Therapy, Brenau University, Gainesville, GA 30501, USA;
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11
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Zhang B, Ghanem A, Simes A, Choi H, Yoo A. Surgical workflow recognition with 3DCNN for Sleeve Gastrectomy. Int J Comput Assist Radiol Surg 2021; 16:2029-2036. [PMID: 34415503 PMCID: PMC8589754 DOI: 10.1007/s11548-021-02473-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 08/04/2021] [Indexed: 01/07/2023]
Abstract
PURPOSE Surgical workflow recognition is a crucial and challenging problem when building a computer-assisted surgery system. Current techniques focus on utilizing a convolutional neural network and a recurrent neural network (CNN-RNN) to solve the surgical workflow recognition problem. In this paper, we attempt to use a deep 3DCNN to solve this problem. METHODS In order to tackle the surgical workflow recognition problem and the imbalanced data problem, we implement a 3DCNN workflow referred to as I3D-FL-PKF. We utilize focal loss (FL) to train a 3DCNN architecture known as Inflated 3D ConvNet (I3D) for surgical workflow recognition. We use prior knowledge filtering (PKF) to filter the recognition results. RESULTS We evaluate our proposed workflow on a large sleeve gastrectomy surgical video dataset. We show that focal loss can help to address the imbalanced data problem. We show that our PKF can be used to generate smoothed prediction results and improve the overall accuracy. We show that the proposed workflow achieves 84.16% frame-level accuracy and reaches a weighted Jaccard score of 0.7327 which outperforms traditional CNN-RNN design. CONCLUSION The proposed workflow can obtain consistent and smooth predictions not only within the surgical phases but also for phase transitions. By utilizing focal loss and prior knowledge filtering, our implementation of deep 3DCNN has great potential to solve surgical workflow recognition problems for clinical practice.
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Affiliation(s)
- Bokai Zhang
- C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA.
| | - Amer Ghanem
- C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA
| | - Alexander Simes
- C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA
| | - Henry Choi
- C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA
| | - Andrew Yoo
- C-SATS, Inc. Johnson & Johnson, 1100 Olive Way, Suite 1100, Seattle, WA, 98101, USA
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12
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Ramesh S, Dall'Alba D, Gonzalez C, Yu T, Mascagni P, Mutter D, Marescaux J, Fiorini P, Padoy N. Multi-task temporal convolutional networks for joint recognition of surgical phases and steps in gastric bypass procedures. Int J Comput Assist Radiol Surg 2021; 16:1111-1119. [PMID: 34013464 PMCID: PMC8260406 DOI: 10.1007/s11548-021-02388-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 04/27/2021] [Indexed: 12/31/2022]
Abstract
PURPOSE Automatic segmentation and classification of surgical activity is crucial for providing advanced support in computer-assisted interventions and autonomous functionalities in robot-assisted surgeries. Prior works have focused on recognizing either coarse activities, such as phases, or fine-grained activities, such as gestures. This work aims at jointly recognizing two complementary levels of granularity directly from videos, namely phases and steps. METHODS We introduce two correlated surgical activities, phases and steps, for the laparoscopic gastric bypass procedure. We propose a multi-task multi-stage temporal convolutional network (MTMS-TCN) along with a multi-task convolutional neural network (CNN) training setup to jointly predict the phases and steps and benefit from their complementarity to better evaluate the execution of the procedure. We evaluate the proposed method on a large video dataset consisting of 40 surgical procedures (Bypass40). RESULTS We present experimental results from several baseline models for both phase and step recognition on the Bypass40. The proposed MTMS-TCN method outperforms single-task methods in both phase and step recognition by 1-2% in accuracy, precision and recall. Furthermore, for step recognition, MTMS-TCN achieves a superior performance of 3-6% compared to LSTM-based models on all metrics. CONCLUSION In this work, we present a multi-task multi-stage temporal convolutional network for surgical activity recognition, which shows improved results compared to single-task models on a gastric bypass dataset with multi-level annotations. The proposed method shows that the joint modeling of phases and steps is beneficial to improve the overall recognition of each type of activity.
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Affiliation(s)
- Sanat Ramesh
- Altair Robotics Lab, Department of Computer Science, University of Verona, Verona, Italy. .,ICube, University of Strasbourg, CNRS, IHU Strasbourg, France.
| | - Diego Dall'Alba
- Altair Robotics Lab, Department of Computer Science, University of Verona, Verona, Italy
| | | | - Tong Yu
- ICube, University of Strasbourg, CNRS, IHU Strasbourg, France
| | - Pietro Mascagni
- ICube, University of Strasbourg, CNRS, IHU Strasbourg, France.,Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Didier Mutter
- University Hospital of Strasbourg, IHU Strasbourg, France.,IRCAD, Strasbourg, France
| | | | - Paolo Fiorini
- Altair Robotics Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Nicolas Padoy
- ICube, University of Strasbourg, CNRS, IHU Strasbourg, France
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13
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Piquer-Garcia I, Cereijo R, Corral-Pérez J, Pellitero S, Martínez E, Taxerås SD, Tarascó J, Moreno P, Balibrea J, Puig-Domingo M, Serra D, Herrero L, Jiménez-Pavón D, Lerin C, Villarroya F, Sánchez-Infantes D. Use of Infrared Thermography to Estimate Brown Fat Activation After a Cooling Protocol in Patients with Severe Obesity That Underwent Bariatric Surgery. Obes Surg 2021; 30:2375-2381. [PMID: 32133589 DOI: 10.1007/s11695-020-04502-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
BACKGROUND In contrast to the energy-storing role of white adipose tissue (WAT), brown adipose tissue (BAT) acts as the main site of non-shivering thermogenesis in mammals and has been reported to play a role in protection against obesity and associated metabolic alterations in rodents. Infrared thermography (IRT) has been proposed as a novel non-invasive, safe, and quick method to estimate BAT thermogenic activation in humans. The aim of this study is to determine whether the IRT could be a potential new tool to estimate BAT thermogenic activation in patients with severe obesity in response to bariatric surgery. METHODS Supraclavicular BAT thermogenic activation was evaluated using IRT in a cohort of 31 patients (50 ± 10 years old, BMI = 44.5 ± 7.8; 15 undergoing laparoscopy sleeve gastrectomy and 16 Roux-en-Y gastric bypass) at baseline and 6 months after a bariatric surgery. Clinical parameters were determined at these same time points. RESULTS Supraclavicular BAT-related activity was detected in our patients by IRT after a cooling stimulus. The BAT thermogenic activation was higher at 6 months after laparoscopy sleeve gastrectomy (0.06 ± 0.1 vs 0.32 ± 0.1), while patients undergoing to a roux-en-Y gastric bypass did not change their thermogenic response using the same cooling stimulus (0.09 ± 0.1 vs 0.08 ± 0.1). CONCLUSIONS Our study postulates the IRT as a potential tool to evaluate BAT thermogenic activation in patients with obesity before and after a bariatric surgery. Further studies are needed to evaluate differences between LSG technique and RYGB on BAT activation.
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Affiliation(s)
| | - Rubén Cereijo
- Department of Biochemistry and Molecular Biomedicine, and Institute of Biomedicine, University of Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Juan Corral-Pérez
- MOVE-IT Research Group and Department of Physical Education, Faculty of Education Sciences, University of Cádiz, Cadiz, Spain.,Institute of Research and Innovation in Biomedical Sciences of the Province of Cádiz (INiBICA), University of Cádiz, Cadiz, Spain
| | - Silvia Pellitero
- Germans Trias i Pujol Research Institute, Barcelona, Spain.,Centro de Investigación Biomédica en Fisiopatología de la Diabetes y enfermedades metabólicas (CIBERDEM), ISCIII, Madrid, Spain
| | - Eva Martínez
- Germans Trias i Pujol Research Institute, Barcelona, Spain
| | - Siri D Taxerås
- Germans Trias i Pujol Research Institute, Barcelona, Spain
| | - Jordi Tarascó
- Germans Trias i Pujol Research Institute, Barcelona, Spain
| | - Pau Moreno
- Germans Trias i Pujol Research Institute, Barcelona, Spain
| | - José Balibrea
- Metabolic and Bariatric Surgery Unit, EAC-BS Center of Excellence, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Manel Puig-Domingo
- Germans Trias i Pujol Research Institute, Barcelona, Spain.,Centro de Investigación Biomédica en Fisiopatología de la Diabetes y enfermedades metabólicas (CIBERDEM), ISCIII, Madrid, Spain
| | - Dolors Serra
- Centro de Investigación Biomédica de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.,Department of Biochemistry and Physiology, School of Pharmacy, Institut de Biomedicina de la Universitat de Barcelona (IBUB),, Universitat de Barcelona, 08028, Barcelona, Spain
| | - Laura Herrero
- Centro de Investigación Biomédica de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.,Department of Biochemistry and Physiology, School of Pharmacy, Institut de Biomedicina de la Universitat de Barcelona (IBUB),, Universitat de Barcelona, 08028, Barcelona, Spain
| | - David Jiménez-Pavón
- MOVE-IT Research Group and Department of Physical Education, Faculty of Education Sciences, University of Cádiz, Cadiz, Spain.,Institute of Research and Innovation in Biomedical Sciences of the Province of Cádiz (INiBICA), University of Cádiz, Cadiz, Spain
| | - Carles Lerin
- Endocrinology department, Institut de Recerca Sant Joan de Déu, 08950, Barcelona, Spain
| | - Francesc Villarroya
- Department of Biochemistry and Molecular Biomedicine, and Institute of Biomedicine, University of Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - David Sánchez-Infantes
- Germans Trias i Pujol Research Institute, Barcelona, Spain. .,Centro de Investigación Biomédica de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain. .,Germans Trias i Pujol Research Institute (IGTP), Campus Can Ruti, Carretera de Can Ruti, Camí de les Escoles s/n, Badalona, 08916, Barcelona, Spain.
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Zerrweck C, Rodríguez NR, Sánchez H, Zurita LC, Márquez M, Herrera MF. Bariatric surgery in Mexico: training, practice and surgical trends. Updates Surg 2021; 73:1509-1514. [PMID: 33687693 DOI: 10.1007/s13304-021-01013-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Accepted: 02/22/2021] [Indexed: 01/12/2023]
Abstract
Bariatric surgery is extremely safe and effective, but several factors need to be addressed to obtain such results. Patient selection, type of training, accreditation, type of practice, and surgical trends and technique are involved in this process. Local and global standardization are ill-advised, especially in countries with high obesity prevalence, and where the bariatric practice is fast growing.An online survey with 22 questions was sent to bariatric surgeons in Mexico. Only participants with the active practice were included, and the aim was to obtain for the first time insight in bariatric surgery training, characteristics of current practice and surgical trends.Complete responses from 114 surgeons were obtained. Most were male, under 50 years-old, ≤ 10 years of experience, and practice in low-volume hospitals. Less than half had a 12-month formal training. Gastric bypass and sleeve gastrectomy were the most common procedures. Practice trends like leak tests, use of drains, preoperative weight loss, routine endoscopy, and pharmacological tromboprofilaxis are common. In surgical technique, the gastric bypass and sleeve gastrectomy confection was more homogenic when compared to the one-anastomosis gastric bypass.Complete responses from 114 surgeons were obtained. Most were male, under 50 years-old, ≤ 10 years of experience, and practice in low-volume hospitals. Less than half had a 12-month formal training. Gastric bypass and sleeve gastrectomy were the most common procedures. Practice trends like leak tests, use of drains, preoperative weight loss, routine endoscopy, and pharmacological tromboprofilaxis are common. In surgical technique, the gastric bypass and sleeve gastrectomy confection was more homogenic when compared to the one-anastomosis gastric bypass. An important number of bariatric surgeons in Mexico are young, male, and with < 10 years of practice. The most common techniques performed are gastric bypass and sleeve gastrectomy. Several practices and technique trends are similar to global consensus. Fellowship programs and Board Certification in bariatric surgery are major advances in our country, thus standardization and high-quality practice can be achieved.
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Affiliation(s)
| | | | - Hugo Sánchez
- Hospital General de Zona 1, IMSS, Mexico City, Mexico
| | | | | | - Miguel F Herrera
- Instituto Nacional de La Nutrición Salvador Zubirán, Vasco de Quiroga #15, Tlalpan 14, 000, Mexico City, Mexico.
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15
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European consensus on essential steps of Minimally Invasive Ivor Lewis and McKeown Esophagectomy through Delphi methodology. Surg Endosc 2021; 36:446-460. [PMID: 33608767 PMCID: PMC8741699 DOI: 10.1007/s00464-021-08304-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 01/09/2021] [Indexed: 12/24/2022]
Abstract
Background Minimally invasive esophagectomy (MIE) is a complex and technically demanding procedure with a long learning curve, which is associated with increased morbidity and mortality. To master MIE, training in essential steps is crucial. Yet, no consensus on essential steps of MIE is available. The aim of this study was to achieve expert consensus on essential steps in Ivor Lewis and McKeown MIE through Delphi methodology. Methods Based on expert opinion and peer-reviewed literature, essential steps were defined for Ivor Lewis (IL) and McKeown (McK) MIE. In a round table discussion, experts finalized the lists of steps and an online Delphi questionnaire was sent to an international expert panel (7 European countries) of minimally invasive upper GI surgeons. Based on replies and comments, steps were adjusted and rephrased and sent in iterative fashion until consensus was achieved. Results Two Delphi rounds were conducted and response rates were 74% (23 out of 31 experts) for the first and 81% (27 out of 33 experts) for the second round. Consensus was achieved on 106 essential steps for both the IL and McK approach. Cronbach’s alpha in the first round was 0.78 (IL) and 0.78 (McK) and in the second round 0.92 (IL) and 0.88 (McK). Conclusions Consensus among European experts was achieved on essential surgical steps for both Ivor Lewis and McKeown minimally invasive esophagectomy. Supplementary Information The online version of this article (doi:10.1007/s00464-021-08304-5) contains supplementary material, which is available to authorized users.
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Abstract
INTRODUCTION Laparoscopy is becoming the standard approach in liver surgery. As the degree of difficulty varies greatly from core skills to advanced procedures, strategies for teaching young surgeons need to be reconsidered. We here aimed to design a skills curriculum for LLR. METHODS Using the nominal group technique, 22 substeps of LLR were identified by 61 hepatobiliary surgeons. The raters were asked to rate (1) the difficulty of substeps and (2) the minimum number of times that the substep must be performed for mastery of the technique. According to the frequency of defined substeps, being estimated on the basis of high volume center experiences (n = 222 LLR; 1/2017-12/2018), the center's training capacity and defined goals for a 2-year fellowship were calculated. RESULTS Ten surgical substeps (45%) are routinely performed and can thus be taught sufficiently at centers carrying out ≥50 LLR in 2 years. As the mobilization of the right liver lobe and the dissection of the hepatic artery or portal vein is performed in only 27% and 28% of all LLR, respectively, sufficient training can only be provided at centers with ≥100 LLRs in 2 years. Mastery of complex parenchymal dissection (19%) and hilar lymphadenectomy (8%) can only be achieved in center performing ≥200 LLR in 2 years. CONCLUSION We here suggest a stepwise approach for training of hepatobiliary fellows in LLR. Based on the estimated complexity of the substeps and the size of the center, not every substep can be learned within 2 years.
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Evaluation of Online Videos of Laparoscopic Sleeve Gastrectomy Using the LAP-VEGaS Guidelines. Obes Surg 2020; 31:111-116. [PMID: 32734567 PMCID: PMC7391047 DOI: 10.1007/s11695-020-04876-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 07/20/2020] [Accepted: 07/22/2020] [Indexed: 01/23/2023]
Abstract
BACKGROUND Laparoscopic sleeve gastrectomy (LSG) is the most common bariatric surgical procedure worldwide. Educational videos of LSGs are available from online sources with YouTube® being the most popular online video repository. However, due to the unrestricted and uncontrolled nature of YouTube®, anyone can upload videos without peer review or standardization. The LAP-VEGaS guidelines were formed to guide the production of high-quality surgical videos. The aim of this study is to use the LAP-VEGaS guidelines to determine if videos of LSGs available on Youtube® are of an acceptable standard for surgical educational purposes. METHODS A YouTube® search was performed using the term laparoscopic sleeve gastrectomy. Appropriate videos were analysed by two individuals using the sixteen LAP-VEGaS guidelines. RESULTS A total of 575 videos were found, of which 202 videos were included and analysed using the LAP-VEGaS guidelines. The median video guideline score was 6/16 with 89% of videos meeting less than half of all guidelines. There was no correlation between the LAP-VEGaS score and view count. CONCLUSIONS There is an abundance of laparoscopic sleeve gastrectomy educational videos available on YouTube®; however, when analysed using the LAP-VEGaS guidelines, the majority do not meet acceptable educational standards for surgical training purposes.
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Abstract
BACKGROUND Standardization of the key measurements of a procedure's finished anatomic configuration strengthens surgical practice, research, and patient outcomes. A consensus meeting was organized to define standard versions of 25 bariatric metabolic procedures. METHODS A panel of experts in bariatric metabolic surgery from multiple continents was invited to present technique descriptions and outcomes for 4 classic, or conventional, and 21 variant and emerging procedures. Expert panel and audience discussion was followed by electronic voting on proposed standard dimensions and volumes for each procedure's key anatomic alterations. Consensus was defined as ≥ 70% agreement. RESULTS The Bariatric Metabolic Surgery Standardization World Consensus Meeting (BMSS-WOCOM) was convened March 22-24, 2018, in New Delhi, India. Discussion confirmed heterogeneity in procedure measurements in the literature. A set of anatomic measurements to serve as the standard version of each procedure was proposed. After two voting rounds, 22/25 (88.0%) configurations posed for consideration as procedure standards achieved voting consensus by the expert panel, 1 did not attain consensus, and 2 were not voted on. All configurations were voted on by ≥ 50% of 50 expert panelists. The Consensus Statement was developed from scientific evidence collated from presenters' slides and a separate literature review, meeting video, and transcripts. Review and input was provided by consensus panel members. CONCLUSIONS Standard versions of the finished anatomic configurations of 22 surgical procedures were established by expert consensus. The BMSS process was undertaken as a first step in developing evidence-based standard bariatric metabolic surgical procedures with the aim of improving consistency in surgery, data collection, comparison of procedures, and outcome reporting.
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Toolabi K, Parsaei R, Elyasinia F, Zamanian A. Reliability and Educational Value of Laparoscopic Sleeve Gastrectomy Surgery Videos on YouTube. Obes Surg 2019; 29:2806-2813. [DOI: 10.1007/s11695-019-03907-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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