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2. Scientific Evidence for the Updated Guidelines on Indications for Metabolic and Bariatric Surgery (IFSO/ASMBS)

Author

De Luca, Maurizio, Shikora, Scott, Eisenberg, Dan, Angrisani, Luigi, Parmar, Chetan, Alqahtani, Aayed, Aminian, Ali, Aarts, Edo, Brown, Wendy, Cohen, Ricardo V., Di Lorenzo, Nicola, Faria, Silvia L., Goodpaster, Kasey P. S., Haddad, Ashraf, Herrera, Miguel, Rosenthal, Raul, Himpens, Jacques, Iossa, Angelo, Kermansaravi, Mohammad, Kow, Lilian, Kurian, Marina, Chiappetta, Sonja, LaMasters, Teresa, Mahawar, Kamal, Merola, Giovanni, Nimeri, Abdelrahman, O’Kane, Mary, Papasavas, Pavlos, Piatto, Giacomo, Ponce, Jaime, Prager, Gerhard, Pratt, Janey S. A., Rogers, Ann M., Salminen, Paulina, Steele, Kimberley E., Suter, Michel, Tolone, Salvatore, Vitiello, Antonio, Zappa, Marco, and Kothari, Shanu N.

Published
2024
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3. Revision/Conversion Surgeries After One Anastomosis Gastric Bypass—An Experts’ Modified Delphi Consensus

Author

Kermansaravi, Mohammad, Chiappetta, Sonja, Parmar, Chetan, Carbajo, Miguel A., Musella, Mario, Chevallier, Jean-Marc, Ribeiro, Rui, Ramos, Almino C., Weiner, Rudolf, Nimeri, Abdelrahman, Aarts, Edo, Abbas, Syed Imran, Bashir, Ahmad, Behrens, Estuardo, Billy, Helmuth, Cohen, Ricardo V., Caina, Daniel, De Luca, Maurizio, Dillemans, Bruno, Fobi, Mathias A. L., Neto, Manoel Galvao, Gawdat, Khaled, ElFawal, Mohamad Hayssam, Kasama, Kazunori, Kassir, Radwan, Khan, Amir, Kow, Lilian, Kular, Kul Deepak Singh, Lakdawala, Muffazal, Layani, Laurent, Lee, Wei-Jei, Luque-de-León, Enrique, Mahawar, Kamal, Almomani, Hazem, Miller, Karl, González, Juan Carlos Olivares, Prasad, Arun, Rheinwalt, Karl, Rutledge, Robert, Safadi, Bassem, Salminen, Paulina, Shabbir, Asim, Taskin, Halit Eren, Verboonen, Jose Sergio, Vilallonga, Ramon, Wang, Cunchuan, Shikora, Scott A., and Prager, Gerhard

Published
2024
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4. Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study

Author

Saux, Patrick, Bauvin, Pierre, Raverdy, Violeta, Teigny, Julien, Verkindt, Hélène, Soumphonphakdy, Tomy, Debert, Maxence, Jacobs, Anne, Jacobs, Daan, Monpellier, Valerie, Lee, Phong Ching, Lim, Chin Hong, Andersson-Assarsson, Johanna C, Carlsson, Lena, Svensson, Per-Arne, Galtier, Florence, Dezfoulian, Guelareh, Moldovanu, Mihaela, Andrieux, Severine, Couster, Julien, Lepage, Marie, Lembo, Erminia, Verrastro, Ornella, Robert, Maud, Salminen, Paulina, Mingrone, Geltrude, Peterli, Ralph, Cohen, Ricardo V, Zerrweck, Carlos, Nocca, David, Roux, Carel W Le, Caiazzo, Robert, Preux, Philippe, and Pattou, François

Subjects
Computer Science - Machine Learning, Statistics - Applications
Abstract

Background Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develop a model using machine learning to provide individual preoperative prediction of 5-year weight loss trajectories after surgery. Methods In this multinational retrospective observational study we enrolled adult participants (aged $\ge$18 years) from ten prospective cohorts (including ABOS [NCT01129297], BAREVAL [NCT02310178], the Swedish Obese Subjects study, and a large cohort from the Dutch Obesity Clinic [Nederlandse Obesitas Kliniek]) and two randomised trials (SleevePass [NCT00793143] and SM-BOSS [NCT00356213]) in Europe, the Americas, and Asia, with a 5 year followup after Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric band. Patients with a previous history of bariatric surgery or large delays between scheduled and actual visits were excluded. The training cohort comprised patients from two centres in France (ABOS and BAREVAL). The primary outcome was BMI at 5 years. A model was developed using least absolute shrinkage and selection operator to select variables and the classification and regression trees algorithm to build interpretable regression trees. The performances of the model were assessed through the median absolute deviation (MAD) and root mean squared error (RMSE) of BMI. Findings10 231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30 602 patient-years. Among participants in all 12 cohorts, 7701 (75$\bullet$3%) were female, 2530 (24$\bullet$7%) were male. Among 434 baseline attributes available in the training cohort, seven variables were selected: height, weight, intervention type, age, diabetes status, diabetes duration, and smoking status. At 5 years, across external testing cohorts the overall mean MAD BMI was 2$\bullet$8 kg/m${}^2$ (95% CI 2$\bullet$6-3$\bullet$0) and mean RMSE BMI was 4$\bullet$7 kg/m${}^2$ (4$\bullet$4-5$\bullet$0), and the mean difference between predicted and observed BMI was-0$\bullet$3 kg/m${}^2$ (SD 4$\bullet$7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery. InterpretationWe developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions., Comment: The Lancet Digital Health, 2023

Published
2023
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7. Metabolic and Bariatric Surgery in Patients with Obesity Class V (BMI > 60 kg/m2): a Modified Delphi Study

Author

Ponce de Leon-Ballesteros, Guillermo, Pouwels, Sjaak, Romero-Velez, Gustavo, Aminian, Ali, Angrisani, Luigi, Bhandari, Mohit, Brown, Wendy, Copaescu, Catalin, De Luca, Maurizio, Fobi, Mathias, Ghanem, Omar M., Hasenberg, Till, Herrera, Miguel F., Herrera-Kok, Johnn H., Himpens, Jacques, Kow, Lilian, Kroh, Matthew, Kurian, Marina, Musella, Mario, Narwaria, Mahendra, Noel, Patrick, Pantoja, Juan P., Ponce, Jaime, Prager, Gerhard, Ramos, Almino, Ribeiro, Rui, Ruiz-Ucar, Elena, Salminen, Paulina, Shikora, Scott, Small, Peter, Stier, Christine, Taha, Safwan, Taskin, Eren Halit, Torres, Antonio, Vaz, Carlos, Vilallonga, Ramon, Verboonen, Sergio, Zerrweck, Carlos, Zundel, Natan, and Parmar, Chetan

Published
2024
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12. A randomized, controlled multicenter feasibility pilot trial on imaging confirmed uncomplicated acute appendicitis: Appendectomy vs. symptomatic treatment in pediatric patients (the APPSYPP) trial study protocol

Author

Puputti, Jenny, Suominen, Janne S., Luoto, Topi, Hiltunen, Pauliina, Ripatti, Liisi, Nikoskelainen, Marianna, Nuutinen, Susanna, Sinikumpu, Juha-Jaakko, Tahkola, Esko, Porela-Tiihonen, Susanna, Hurme, Saija, Salminen, Paulina, and Pakarinen, Mikko P.

Published
2022
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16. Development of the International Federation for Surgery of Obesity and Metabolic Disorders-European Chapter (IFSO-EC) Grade-Based Guidelines on the Surgical Treatment of Obesity Using Multimodal Strategies: Design and Methodological Aspects.

Author

De Luca, Maurizio, Belluzzi, Amanda, Salminen, Paulina, Bueter, Marco, Pujol-Rafols, Juan, Sakran, Nasser, Stier, Christine, Taskin, Halit Eren, Chiappetta, Sonja, Carrano, Francesco Maria, Di Lorenzo, Nicola, Nienhuijs, Simon, Puy, Ramón Vilallonga, Stenberg, Erik, Emous, Marloes, Prager, Gerhard, Himpens, Jacques, Felsenreich, Daniel Moritz, Iannelli, Antonio, and Parmar, Chetan

Subjects
WEIGHT loss, BARIATRIC surgery, BODY mass index, MEDICATION therapy management, INTRAOPERATIVE awareness
Abstract

Background: The prevalence of obesity is already a worldwide health concern. The development of straightforward guidelines regarding the whole available armamentarium (i.e., medical, endoscopic, and surgical interventions in conjunction with a guidance program) is paramount to offering the best multimodal approach to patients with obesity. Methods: The International Federation for Surgery of Obesity and Metabolic Disorders-European Chapter (IFSO-EC) identified a panel of experts to develop the present guidelines. The panel formulated a series of clinical questions (based on the patient, intervention, comparison, and outcome conceptual framework), which have been voted on and approved. A GRADE methodology will be applied to assess the quality of evidence and formulate recommendations employed to minimize selection and information biases. This approach aims to enhance the reliability and validity of recommendations, promoting greater adherence to the best available evidence. Results: These guidelines are intended for adult patients with a body mass index (BMI) ≥ 30 kg/m2 who are candidates for metabolic bariatric surgery (MBS). The expert panel responsible for developing these guidelines comprised 25 panelists (92% were bariatric surgeons) and 3 evidence reviewers, with an average age of 50.1 ± 10.2 years. The panel focused on 3 key questions regarding the combined use of structured lifestyle interventions, approved obesity management medications, and endoscopic weight loss procedures with MBS. Conclusions: The complexity of obesity as a chronic disease requires a comprehensive knowledge of all the available and feasible therapeutic options. The IFSO-EC society felt the urgent need to develop methodologically valid guidelines to give a full picture and awareness of the possible surgical and non-surgical therapeutic strategies employed with a multimodal approach. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Three-Year Outcomes of Oral Antibiotics vs Intravenous and Oral Antibiotics for Uncomplicated Acute Appendicitis

Author

Selänne, Liisa, primary, Haijanen, Jussi, additional, Sippola, Suvi, additional, Hurme, Saija, additional, Rautio, Tero, additional, Nordström, Pia, additional, Rantanen, Tuomo, additional, Pinta, Tarja, additional, Ilves, Imre, additional, Mattila, Anne, additional, Rintala, Jukka, additional, Marttila, Harri, additional, Meriläinen, Sanna, additional, Laukkarinen, Johanna, additional, Sävelä, Eeva-Liisa, additional, Paajanen, Hannu, additional, Grönroos, Juha, additional, and Salminen, Paulina, additional

Published
2024
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22. Current recommendations for procedure selection in class I and II obesity developed by an expert modified Delphi consensus

Author

Kermansaravi, Mohammad, primary, Chiappetta, Sonja, additional, Parmar, Chetan, additional, Shikora, Scott A., additional, Prager, Gerhard, additional, LaMasters, Teresa, additional, Ponce, Jaime, additional, Kow, Lilian, additional, Nimeri, Abdelrahman, additional, Kothari, Shanu N., additional, Aarts, Edo, additional, Abbas, Syed Imran, additional, Aly, Ahmad, additional, Aminian, Ali, additional, Bashir, Ahmad, additional, Behrens, Estuardo, additional, Billy, Helmuth, additional, Carbajo, Miguel A., additional, Clapp, Benjamin, additional, Chevallier, Jean-Marc, additional, Cohen, Ricardo V., additional, Dargent, Jerome, additional, Dillemans, Bruno, additional, Faria, Silvia L., additional, Neto, Manoel Galvao, additional, Garneau, Pierre Y., additional, Gawdat, Khaled, additional, Haddad, Ashraf, additional, ElFawal, Mohamad Hayssam, additional, Higa, Kelvin, additional, Himpens, Jaques, additional, Husain, Farah, additional, Hutter, Matthew M., additional, Kasama, Kazunori, additional, Kassir, Radwan, additional, Khan, Amir, additional, Khoursheed, Mousa, additional, Kroh, Matthew, additional, Kurian, Marina S., additional, Lee, Wei-Jei, additional, Loi, Ken, additional, Mahawar, Kamal, additional, McBride, Corrigan L., additional, Almomani, Hazem, additional, Melissas, John, additional, Miller, Karl, additional, Misra, Monali, additional, Musella, Mario, additional, Northup, C. Joe, additional, O’Kane, Mary, additional, Papasavas, Pavlos K., additional, Palermo, Mariano, additional, Peterson, Richard M., additional, Peterli, Ralph, additional, Poggi, Luis, additional, Pratt, Janey S. A., additional, Alqahtani, Aayad, additional, Ramos, Almino C., additional, Rheinwalt, Karl, additional, Ribeiro, Rui, additional, Rogers, Ann M., additional, Safadi, Bassem, additional, Salminen, Paulina, additional, Santoro, Sergio, additional, Sann, Nathaniel, additional, Scott, John D., additional, Shabbir, Asim, additional, Sogg, Stephanie, additional, Stenberg, Erik, additional, Suter, Michel, additional, Torres, Antonio, additional, Ugale, Surendra, additional, Vilallonga, Ramon, additional, Wang, Cunchuan, additional, Weiner, Rudolf, additional, Zundel, Natan, additional, Angrisani, Luigi, additional, and De Luca, Maurizio, additional

Published
2024
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23. The First Modified Delphi Consensus Statement for Resuming Bariatric and Metabolic Surgery in the COVID-19 Times

Author

Pouwels, Sjaak, Omar, Islam, Aggarwal, Sandeep, Aminian, Ali, Angrisani, Luigi, Balibrea, Jose María, Bhandari, Mohit, Biter, L. Ulas, Blackstone, Robin P., Carbajo, Miguel A., Copaescu, Catalin A., Dargent, Jerome, Elfawal, Mohamed Hayssam, Fobi, Mathias A., Greve, Jan-Willem, Hazebroek, Eric J., Herrera, Miguel F., Himpens, Jacques M., Hussain, Farah A., Kassir, Radwan, Kerrigan, David, Khaitan, Manish, Kow, Lilian, Kristinsson, Jon, Kurian, Marina, Lutfi, Rami Edward, Moore, Rachel L., Noel, Patrick, Ozmen, Mahir M., Ponce, Jaime, Prager, Gerhard, Purkayastha, Sanjay, Rafols, Juan Pujol, Ramos, Almino C., Ribeiro, Rui J. S., Sakran, Nasser, Salminen, Paulina, Shabbir, Asim, Shikora, Scott A., Singhal, Rishi, Small, Peter K., Taylor, Craig J., Torres, Antonio J., Vaz, Carlos, Yashkov, Yury, and Mahawar, Kamal

Published
2021
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27. Renal Cortical Glucose Uptake Is Decreased in Insulin Resistance and Correlates Inversely With Serum Free-fatty Acids.

Author

Rebelos, Eleni, Mari, Andrea, Honka, Miikka-Juhani, Pekkarinen, Laura, Latva-Rasku, Aino, Laurila, Sanna, Rajander, Johan, Salminen, Paulina, Iida, Hidehiro, Ferrannini, Ele, and Nuutila, Pirjo

Abstract

Context Studies on human renal metabolism are scanty. Nowadays, functional imaging allows the characterization of renal metabolism in a noninvasive manner. We have recently demonstrated that fluorodeoxyglucose F18 (18F FDG) positron emission tomography can be used to analyze renal glucose uptake (GU) rates, and that the renal cortex is an insulin-sensitive tissue. Objective To confirm that renal GU is decreased in people with obesity and to test whether circulating metabolites are related to renal GU. Design, Setting and Participants Eighteen people with obesity and 18 nonobese controls were studied with [18F]FDG positron emission tomography during insulin clamp. Renal scans were obtained ∼60 minutes after [18F]FDG injection. Renal GU was measured using fractional uptake rate and after correcting for residual intratubular [18F]FDG. Circulating metabolites were measured using high-throughput proton nuclear magnetic resonance metabolomics. Results Cortical GU was higher in healthy nonobese controls compared with people with obesity (4.7 [3.4-5.6] vs 3.1 [2.2-4.3], P =.004, respectively), and it associated positively with the degree of insulin sensitivity (M value) (r = 0.42, P =.01). Moreover, cortical GU was inversely associated with circulating β-OH-butyrate (r = -0.58, P =.009), acetoacetate (r = -0.48, P =.008), citrate (r = −0.44, P =.01), and free fatty acids (r = −0.68, P <.0001), even when accounting for the M value. On the contrary, medullary GU was not associated with any clinical parameters. Conclusion These data confirm differences in renal cortical GU between people with obesity and healthy nonobese controls. Moreover, the negative correlations between renal cortex GU and free fatty acids, ketone bodies, and citrate are suggestive of substrate competition in the renal cortex. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Cohort study on incidence of new-onset type 2 diabetes in patients after bariatric surgery and matched controls.

Author

Vahtera, Viiko, Pajarinen, Jukka, Kivimäki, Mika, Ervasti, Jenni, Pentti, Jaana, Stenholm, Sari, Vahtera, Jussi, and Salminen, Paulina

Subjects
TYPE 2 diabetes, BARIATRIC surgery, PEOPLE with diabetes, GASTRIC banding, GASTRIC bypass, TYPE 2 diabetes diagnosis, COHORT analysis
Abstract

Background: Metabolic bariatric surgery the reduces risk of new-onset type 2 diabetes in individuals with obesity, but it is unclear whether the benefit varies by sex, age, or socioeconomic status. The aim was to assess the risk of new-onset type 2 diabetes after metabolic bariatric surgery in these subgroups. Methods: The Finnish Public Sector study, a follow-up study with matched controls nested in a large employee cohort, included patients without type 2 diabetes and with a diagnosis of obesity or self-reported BMI of at least 35 kg/m2. For each patient who had laparoscopic metabolic bariatric surgery (2008–2016), two propensity-score matched controls were selected. New-onset type 2 diabetes was ascertained from linked records from national health registries. Results: The study included a total of 917 patients and 1811 matched controls with obesity. New-onset type 2 diabetes was diagnosed in 15 of the patients who had metabolic bariatric surgery (4.1 per 1000 person-years) and 164 controls (20.2 per 1000 person-years). The corresponding rate ratio (RR) was 0.20 (95% c.i. 0.12 to 0.35) and the rate difference (RD) was −16.1 (−19.8 to −12.3) per 1000 person-years. The risk reduction was more marked in individuals of low socioeconomic status (RR 0.10 (0.04 to 0.26) and RD −20.6 (−25.6 to −15.5) per 1000 person-years) than in those with higher socioeconomic status (RR 0.35 (0.18 to 0.66) and RD −11.5 (−16.9 to −6.0) per 1000 person-years) (Pinteraction = 0.017). No differences were observed between sexes or age groups. Conclusion: Metabolic bariatric surgery was associated with a reduced risk of new-onset type 2 diabetes in men and women and in all age groups. The greatest benefit was observed in individuals of low socioeconomic status. The impact of metabolic bariatric surgery on the risk of new-onset type 2 diabetes was investigated in individuals with obesity. The findings indicate that metabolic bariatric surgery significantly reduces the risk of type 2 diabetes across sexes and age groups, with the most substantial benefit observed in individuals of low socioeconomic status. Lay Summary: Metabolic bariatric surgery reduces the risk of new-onset type 2 diabetes in individuals with obesity or severe obesity. The risk of new-onset type 2 diabetes after metabolic bariatric surgery varies between socioeconomic status subgroups. In this prospective study, new-onset type 2 diabetes occurred in 1.6% of 917 patients who underwent metabolic bariatric surgery and 9.1% of 1811 propensity score-matched controls. Risk reduction was more marked in individuals of low socioeconomic status. There were no differences between sex or age groups. The reduced risk of new-onset type 2 diabetes after metabolic bariatric surgery emphasizes the need to increase access to treatment in patients with severe obesity. As the preventive effect was most pronounced in individuals of low socioeconomic status associated with both greater burden of disease and worse access to healthcare, the findings need to be taken into account in health policies to reduce health inequalities. [ABSTRACT FROM AUTHOR]

Published
2024
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29. A core outcome set for appendicitis: A consensus approach utilizing modified Delphi methodology.

Author

Butts, Christopher A., Byerly, Saskya, Nahmias, Jeffry, Gelbard, Rondi, Ziesmann, Markus, Bruns, Brandon, Davidson, Giana H., Di Saverio, Salomone, Esposito, Thomas J., Fischkoff, Katherine, Joseph, Bellal, Kaafarani, Haytham, Mentula, Panu, Podda, Mauro, Sakran, Joseph V., Salminen, Paulina, Sammalkorpi, Henna, Sawyer, Robert G., Skeete, Dionne, and Tesoriero, Ronald

Published
2024
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32. Insulin-stimulated brain glucose uptake correlates with brain metabolites in severe obesity: A combined neuroimaging study

Author

Rebelos, Eleni, primary, Latva-Rasku, Aino, additional, Koskensalo, Kalle, additional, Pekkarinen, Laura, additional, Saukko, Ekaterina, additional, Ihalainen, Jukka, additional, Honka, Miikka-Juhani, additional, Tuisku, Jouni, additional, Bucci, Marco, additional, Laurila, Sanna, additional, Rajander, Johan, additional, Salminen, Paulina, additional, Nummenmaa, Lauri, additional, Jansen, Jacobus FA, additional, Ferrannini, Ele, additional, and Nuutila, Pirjo, additional

Published
2023
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34. Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study

Author

Saux, Patrick, primary, Bauvin, Pierre, additional, Raverdy, Violeta, additional, Teigny, Julien, additional, Verkindt, Hélène, additional, Soumphonphakdy, Tomy, additional, Debert, Maxence, additional, Jacobs, Anne, additional, Jacobs, Daan, additional, Monpellier, Valerie, additional, Lee, Phong Ching, additional, Lim, Chin Hong, additional, Andersson-Assarsson, Johanna C, additional, Carlsson, Lena, additional, Svensson, Per-Arne, additional, Galtier, Florence, additional, Dezfoulian, Guelareh, additional, Moldovanu, Mihaela, additional, Andrieux, Severine, additional, Couster, Julien, additional, Lepage, Marie, additional, Lembo, Erminia, additional, Verrastro, Ornella, additional, Robert, Maud, additional, Salminen, Paulina, additional, Mingrone, Geltrude, additional, Peterli, Ralph, additional, Cohen, Ricardo V, additional, Zerrweck, Carlos, additional, Nocca, David, additional, Le Roux, Carel W, additional, Caiazzo, Robert, additional, Preux, Philippe, additional, and Pattou, François, additional

Published
2023
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35. A core outcome set for appendicitis: A consensus approach utilizing modified Delphi methodology

Author

Butts, Christopher A., primary, Byerly, Saskya, additional, Nahmias, Jeffry, additional, Gelbard, Rondi, additional, Ziesmann, Markus, additional, Bruns, Brandon, additional, Davidson, Giana H., additional, Di Saverio, Salomone, additional, Esposito, Thomas J., additional, Fischkoff, Katherine, additional, Joseph, Bellal, additional, Kaafarani, Haytham, additional, Mentula, Panu, additional, Podda, Mauro, additional, Sakran, Joseph V., additional, Salminen, Paulina, additional, Sammalkorpi, Henna, additional, Sawyer, Robert G., additional, Skeete, Dionne, additional, Tesoriero, Ronald, additional, and Yeh, D. Dante, additional

Published
2023
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