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Pandanaboyana, Sanjay

0000-0003-3099-2197

Mayo Clinic

Freeman Hospital

Citations 3

Expert Clinical Consensus on Body Surface Gastric Mapping Phenotypes for Gastroduodenal Disorders: ‘Auckland Classification’ v1.0
Varghese, Chris , Dachs, Nicky , Schamberg, Gabriel , Abell, Thomas, Al‐Haddad, Mohammad, Angeli, Timothy R. , Ayubi, Homira , Bashashati, Mohammad , Bulat, Robert, Calder, Stefan, Cederwall, Christopher Brian, Chang, Bianca W. , Cheng, Leo K. , Clarke, John, Daker, Charlotte , Du, Peng, Erickson, Jon, Eriksson, Sven, Fikree, Asma , Foong, Daphne , Fox, Mark, Goenka, Mahesh, Haidry, R, Holtman, Gerald, Hobson, Anthony , Koloski, Natasha, Kuo, Braden, Law, Mikaela, Levinthal, D., Liu, Joy , Mathur, Prateek , Moshiree, Baharak, Ngo, Catherine, Nguyen, Linda, Oblizajek, Nicholas R. , Parkman, Henry P., Podboy, Alexander, Rezaie, Ali, Simmonds, Sam , Sivakumar, Jonathan , Sirimongkolkasem, Jarongkorn , Sonu, Irene, Stocker, Abigail, Sujka, Joseph, Tack, Jan, Weinstein, Douglas, Windsor, John, Zarate‐Lopez, Natalia, Andrews, Christopher N., O'Grady, Greg, Clarke, John O. , Angeli-Gordon, Timothy R , Chang, Bianca , Cheng, Leo K , Daker, Charlotte , Ghoshal, Uday C , Hasler, W L , Ho, Vincent , Keszthelyi, Daniel , Khalsa, Sahib S , Liu, Joy J , Neshatian, Leila , Oblizajek, Nicholas R , Pandanaboyana, Sanjay , Sharma, Amol , Wang, Xiao Jing , Xu, William , Varghese, Chris , Clarke, J , Schamberg, Gabriel , Al‐Haddad, Mohammad , Ayazi, Shahin , Bulat, Robert, Calder, Stefan , Cederwall, Chris, Du, Peng , Erickson, Jonathan C. , Ghoshal, Uday C. , Hasler, William L. , Hayee, Bu , Ho, Vincent , Huang, I‐Hsuan , Khalsa, Sahib S. , Kuo, Braden , Kunkel, David C. , Law, Mikaela , Levinthal, David J. , Moshiree, Baharak , Neshatian, Leila , Parkman, Henry P. , Podboy, Alexander , Rezaie, Ali , Sonu, Irene S. , Stocker, Abigail, Sujka, Joseph , Tack, Jan , Verdonk, Charles , Wang, Xiao Jing , Wongjarupong, Nicha , Xu, William , Andrews, Christopher N. , Gharibans, Armen A.

Neurogastroenterology & Motility | July 1, 2026 | Volume: 38 | Issue: 7 | Pages: No page available

10.1111/nmo.70377 Get It

ABSTRACT Introduction Chronic gastroduodenal disorders remain challenging to manage, and new diagnostic approaches are needed to better delineate underlying causes and guide therapeutic decisions. Body Surface Gastric Mapping (BSGM) technologies combine high‐resolution gastric myoelectrical activity measurements with symptom and psychological profiling to provide mechanistic insights into gastric motor and sensory dysfunction. An International Working Group convened to derive the first consensus classification of BSGM phenotypes (the “Auckland Classification”). Methods A Technical Group conducted a systematic literature and clinical database review to identify objective test biomarkers and candidate disease mechanisms. Evidence was synthesized across 50 studies (primarily in gastroparesis, chronic nausea and vomiting, and functional dyspepsia), and BSGM phenotypes were mapped to existing treatment guidelines. Subsequently, iterative review and development of consensus was performed by a Consensus Group composed of international clinical experts familiar with BSGM. Eleven statements underlying the classification were then derived and circulated as a final survey to establish agreement. Results Six BSGM phenotypes were endorsed: three defined by myoelectrical abnormalities (Dysrhythmic, High Frequency, and Low Meal Response) and three by characteristic symptom associations (Sensorimotor, Continuous, and Delayed Onset Symptoms). Published studies plausibly linked these phenotypes to mechanisms including interstitial cell of Cajal depletion, vagal impairment, hypomotility, visceral hypersensitivity, gut‐brain dysregulation, and small bowel dysfunction. Phenotypes were also mapped to existing mechanism‐based treatment guidelines. Ten out of the eleven statements had > 80% agreement. Conclusions The Auckland Classification, derived by international consensus, presents a structured framework for BSGM‐defined patient phenotypes. Evidence and mechanism‐based treatment options are suggested for each phenotype to provide a foundation for research, further validation, and a pathway for integrating BSGM into clinical care.
Learning Curves and Complexity Evolution in Robotic Liver Surgery
Kuemmerli, Christoph , Hess, Gabriel Fridolin , Billeter, Adrian T. , Benedetto, Fabrizio Di , Odorizzi, Roberta, Sucandy, Iswanto , Aegerter, Noa L. E., Berchtold, Caroline , Bernardi, L. , Cristaudi, Alessandra , Balzano, E , Koh, Ye-Xin, Lin, Charles Chung-Wei, Fukumori, Daisuke , Tschuor, Christoph , White, Steve, Kroge, P Von, Heumann, Asmus , Meyere, Céline De, D’hondt, M, Haak, Fabian, Stättner, Stefan, Primavesi, Florian, Morgül, Haluk , Andreou, A, Ratti, F, Esquer, Ignacio Sánchez, Robles-Campos, Ricardo, Lopez-Lopez, Victor, Wakabayashi, Go , Nebbia, Martina, Rahbari, Nuh N., Ferretti, Stefano, Ettore, Giuseppe , Croner, RS , Dong, Y, Starlinger, P, Nickel, F, Müller, Beat P., Hess, Gabriel F , Guidetti, Cristiano , di Benedetto, Fabrizio , Sucandy, Iswanto , Aegerter, Noa L E , Berchtold, Caroline , Bernardi, Lorenzo , Cristaudi, Alessandra , Balzano, Emanuele , Ghinolfi, Davide , Goh, Brian K P , Fukumori, Daisuke , Tschuor, Christoph , Pandanaboyana, Sanjay , De Meyere, Celine , Seehofer, Daniel , Esquer, Ignacio Sánchez , Müller, Philip C , Koh, Ye-Xin , Lin, Charles Chung-Wei, Tschuor, Christoph , Kroge, Philipp H. von , D’Hondt, Mathieu , Haak, Fabian , Stättner, Stefan , Primavesi, Florian , Ratti, Francesca , Robles-Campos, Ricardo, López‐López, Víctor , Wakabayashi, Taiga , Nebbia, Martina , Gilg, Stefan , Birgin, Emrullah , Ferretti, Stefano , Ettore, Giuseppe Maria, Rahimli, Mirhasan , Nickel, Felix , Müller-Stich, Beat Peter

Annals of Surgery | June 17, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1097/sla.0000000000007123 Get It

Objective: To evaluate the institutional learning curve of robotic liver resection (RLR), its association with surgical complexity and outcomes in an international multicenter cohort. Summary of Background Data: RLR is increasingly adopted worldwide, but the dynamics of the learning process and its impact on surgical outcomes remain poorly defined. Methods: This international, multicenter, retrospective cohort study included consecutive patients who underwent RLR between 06/2013 and 12/2024 across 22 expert centers. Based on the first 150 cases at each center, three phases were used to define the learning curve: operative time for competency, major complications for proficiency, and textbook outcome for mastery. Risk-adjusted generalized additive models were used to assess the learning process. Benchmark performance was compared to international reference values. Results: Among 2,331 patients, the most common indications were hepatocellular carcinoma (36%), benign lesions (23%) and colorectal liver metastases (21%). Operative time decreased after achieving competency (case #62), from 240 to 220 minutes ( P <0.001). Major morbidity reached a plateau during the proficiency phase (cases #63–138; 9% vs. 11%, P =0.144), while progression to mastery (cases #139–150) was associated with a higher rate of textbook outcome (76% vs. 87%, P =0.021). In contrast, conversion (5.1% vs. 4.9% vs. 2%), bile leak (4.0% vs. 5.3% vs. 3.8%), and 90-day mortality (0.7% vs. 0.9% vs. 0.9%) remained low and stable across all learning phases. Importantly, benchmark criteria for operative time, hospital stay, and textbook outcome were met across all complexity groups, including during the early learning phase. Conclusions: Robotic liver surgery shows progressive outcome improvement with early achievement of benchmark-level results and stable performance across increasing complexity. These findings indicate that, in experienced centers, RLR can be safely implemented and integrated into clinical practice, supporting its key role in modern hepatobiliary surgery.
International Multidisciplinary Consensus Report on Definitions, Diagnostic Criteria, and Management of Fatty Pancreas: A Joint Statement Endorsed by EPC, APA, EASD, EASL, ESGAR, ESGE, ESP, ESPCG, ESPEN, ESPGHAN, IAP, JPS, KPBA, LAPSG, and UEG
Marchegiani, Giovanni, Hegyi, Peter, Archibugi, Livia, Valente, Roberto, Capurso, Gabriele, Witt, Heiko, Bonovas, Stefanos , Maisonneuve, Patrick, Verbeke, Caroline S., Dominguez‐Muñoz, J. Enrique, Scheers, Isabelle, Czakó, László, Wagner, R, Rebours, Vinciane, Öhlund, Daniel, Gubergrits, N. B. , Engjom, Trond , Neeße, Albrecht , Apte, Minoti V. , Braren, Rickmer, Bunduc, Stefania, Ceyhan, Güralp Onur, Chouhan, Manil Dinesh, Couvelard, Anne, Iglesia, Daniel de la, Drewes, Asbjørn Mohr, Sarasqueta, A. Farina, Francque, Sven, Frøkjær, Jens Brøndum, Iglesias‐Garcia, Julio, Garg, Pramod, Gerst, Felicia, Gulbinas, Antanas, Gürcinar, Ibrahim Halil, Heni, Martin , Jonas, E G, Kitano, M., Krag, Aleksander, Laukkarinen, J., Lipp, Mónika, Loveček, M., Martignoni, Marc E., Masip, Etna , Matsumoto, Ryotaro , Mozhynа, T. L. , Nosáková, Lenka, Ockenga, Johann , Pandanaboyana, Sanjay, Panić, Nikola , Papachristou, Georgios, Pasqua, Analía V. , Pawlak, Katarzyna Monika, Regel, Ivonne , Regnér, Sara, Singh, Vijay Kumar , Smits, M., Sung, Min Je , Tacelli, Matteo, Teutsch, Brigitta, Udrescu, Mihaela, Wilschanski, Michael , Yavas, Aslihan, Zamboni, G., Löhr, J. Matthias, Singh, Vijay , Drewes, Asbjørn Mohr , Regnér, Sara , Krag, Aleksander , Marchegiani, Giovanni , Pawlak, Katarzyna M. , Marchegiani, Giovanni , Hegyi, Peter , Archibugi, Livia , Bonovas, Stefanos , Verbeke, Caroline S , de-Madaria, Enrique , Wagner, Robert , Rebours, Vinciane , Öhlund, Daniel , Neesse, Albrecht , Bezmarević, Mihailo , Bunduc, Stefania , Iglesia, Daniel de la , Drenth, Joost P H , Gürcinar, Ibrahim Halil , Jonas, Eduard , Kitano, Masayuki , Obmann, Verena , Pandanaboyana, Sanjay , Pasqua, Analia Verónica , Pawlak, Katarzyna M , Regnér, Sara , Seicean, Andrada , Sung, Min Je , Taylor, Roy , Singh, Vijay P , Krag, Aleksander , Vujasinović, Miroslav , Demir, İhsan Ekin , Hegyi, Péter , Valente, Roberto, Capurso, Gabriele , Piovani, Daniele , Rosendahl, Jonas , Maisonneuve, Patrick , Karçaaltıncaba, Muşturay , Domínguez‐Muñoz, J. Enrique , Scheers, Isabelle , Czakó, László , Idılman, Ilkay S. , Overbeek, Kasper A. , Braren, Rickmer , Chouhan, Manil Dinesh , Couvelard, Anne , Cros, Jerome F. , de‐Madaria, Enrique , Drenth, Joost P.H. , Fracasso, Pierluigi , Francque, Sven , Frøkjær, Jens Brøndum , Iglesias‐García, Julio , Garg, Pramod, Gulbinas, Antanas , Hyun, Jong Jin , Jonas, Eduard , Kiriukova, Mariia A. , Laukkarinen, Johanna , Loveček, Martin , Molven, Anders , Nosáková, Lenka , Obmann, Verena Carola , Papachristou, Georgios I. , Peláez‐Luna, Mario , Robinson, Stuart Michael , Smits, Mark M. , Tacelli, Matteo , Teutsch, Brigitta , Udrescu, Mihaela, Yavas, Aslihan , Zamboni, Giulia Angela, Löhr, J.-Matthias

United European Gastroenterology Journal | February 14, 2026 | Volume: 14 | Issue: 1 | Pages: No page available

10.1002/ueg2.70185 Get It

ABSTRACT This international, multidisciplinary consensus report represents the first effort to systematically define and characterize fatty pancreas. A key outcome of this endeavor was the recommendation to adopt “fatty pancreas” as the standardized and inclusive term to describe all forms of fat accumulation in the pancreas. This terminological consensus provides a critical foundation for unified reporting and clinical communication. Another major contribution of the report is the consensus on diagnostic imaging findings, which was based on radiological and endoscopic modalities. The proposed criteria aim to enhance consistency in clinical assessment and support the development of standardized research protocols. In addition to establishing terminology and diagnostic frameworks, the report also synthesizes current knowledge across a wide range of relevant domains. These include the etiology and epidemiology of fatty pancreas, as well as its associations with alcohol consumption, smoking, acute and chronic pancreatitis, pancreatic exocrine insufficiency, type 2 diabetes mellitus, and surgical outcomes. The potential links between fatty pancreas and neoplastic conditions such as intraductal papillary mucinous neoplasms and pancreatic cancer are also addressed, alongside the current understanding of its metabolic implications (beta‐cell function and glucose homeostasis) and treatment strategies. Throughout the consensus process, a consistent theme emerged: the limited availability of high‐quality, prospective clinical data. Therefore, many of the recommendations in this report are based on expert consensus rather than strong empirical evidence. As such, the statements require rigorous prospective validation before they can be adopted into routine clinical practice. This underscores a critical need for further research, particularly studies aimed at clarifying causal relationships, validating diagnostic tools, and determining the clinical relevance of fatty pancreas across diverse patient populations. This report serves as both a summary of our current understanding and a roadmap for future investigations, aiming to close existing knowledge gaps and guide evidence‐based clinical practice in this emerging field.