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Background: There is a paucity of data comparing 30-day morbidity and mortality of sleeve gastrectomy (SG), Roux-en-Y gastric bypass (RYGB), and one anastomosis gastric bypass (OAGB). This study aimed to compare the 30-day safety of SG, RYGB, and OAGB in propensity score-matched cohorts. Materials and methods: This analysis utilised data collected from the GENEVA study which was a multicentre observational cohort study of bariatric and metabolic surgery (BMS) in 185 centres across 42 countries between 01/05/2022 and 31/10/2020 during the Coronavirus Disease-2019 (COVID-19) pandemic. 30-day complications were categorised according to the Clavien–Dindo classification. Patients receiving SG, RYGB, or OAGB were propensity-matched according to baseline characteristics and 30-day complications were compared between groups. Results: In total, 6770 patients (SG 3983; OAGB 702; RYGB 2085) were included in this analysis. Prior to matching, RYGB was associated with highest 30-day complication rate (SG 5.8%; OAGB 7.5%; RYGB 8.0% (p = 0.006)). On multivariate regression modelling, Insulin-dependent type 2 diabetes mellitus and hypercholesterolaemia were associated with increased 30-day complications. Being a non-smoker was associated with reduced complication rates. When compared to SG as a reference category, RYGB, but not OAGB, was associated with an increased rate of 30-day complications. A total of 702 pairs of SG and OAGB were propensity score-matched. The complication rate in the SG group was 7.3% (n = 51) as compared to 7.5% (n = 53) in the OAGB group (p = 0.68). Similarly, 2085 pairs of SG and RYGB were propensity score-matched. The complication rate in the SG group was 6.1% (n = 127) as compared to 7.9% (n = 166) in the RYGB group (p = 0.09). And, 702 pairs of OAGB and RYGB were matched. The complication rate in both groups was the same at 7.5 % (n = 53; p = 0.07). Conclusions: This global study found no significant difference in the 30-day morbidity and mortality of SG, RYGB, and OAGB in propensity score-matched cohorts.
30-day morbidity and mortality of sleeve gastrectomy, Roux-en-Y gastric bypass and one anastomosis gastric bypass: a propensity score-matched analysis of the GENEVA data
Singhal R.;Cardoso V. R.;Wiggins T.;Super J.;Ludwig C.;Gkoutos G. V.;Mahawar K.;Pedziwiatr M.;Major P.;Zarzycki P.;Pantelis A.;Lapatsanis D. P.;Stravodimos G.;Matthys C.;Focquet M.;Vleeschouwers W.;Spaventa A. G.;Zerrweck C.;Vitiello A.;Berardi G.;Musella M.;Sanchez-Meza A.;Cantu F. J.;Mora F.;Cantu M. A.;Katakwar A.;Reddy D. N.;Elmaleh H.;Hassan M.;Elghandour A.;Elbanna M.;Osman A.;Khan A.;layani L.;Kiran N.;Velikorechin A.;Solovyeva M.;Melali H.;Shahabi S.;Agrawal A.;Shrivastava A.;Sharma A.;Narwaria B.;Narwaria M.;Raziel A.;Sakran N.;Susmallian S.;Karagoz L.;Akbaba M.;Piskin S. Z.;Balta A. Z.;Senol Z.;Manno E.;Iovino M. G.;Osman A.;Qassem M.;Arana-Garza S.;Povoas H. P.;Vilas-Boas M. L.;Naumann D.;Li A.;Ammori B. J.;Balamoun H.;Salman M.;Nasta A. M.;Goel R.;Sanchez-Aguilar H.;Herrera M. F.;Abou-mrad A.;Cloix L.;Mazzini G. S.;Kristem L.;Lazaro A.;Campos J.;Bernardo J.;Gonzalez J.;Trindade C.;Viveiros O.;Ribeiro R.;Goitein D.;Hazzan D.;Segev L.;Beck T.;Reyes H.;Monterrubio J.;Garcia P.;Benois M.;Kassir R.;Contine A.;Elshafei M.;Aktas S.;Weiner S.;Heidsieck T.;Level L.;Pinango S.;Ortega P. M.;Moncada R.;Valenti V.;Vlahovic I.;Boras Z.;Liagre A.;Martini F.;Juglard G.;Motwani M.;Saggu S. S.;Momani H. A.;Lopez L. A. A.;Cortez M. A. C.;Zavala R. A.;D'Haese RN C.;Kempeneers I.;Himpens J.;Lazzati A.;Paolino L.;Bathaei S.;Bedirli A.;Yavuz A.;Buyukkasap C.;Ozaydin S.;Kwiatkowski A.;Bartosiak K.;Waledziak M.;Santonicola A.;Angrisani L.;Iovino P.;Palma R.;Iossa A.;Boru C. E.;De Angelis F.;Silecchia G.;Hussain A.;Balchandra S.;Coltell I. B.;Perez J. L.;Bohra A.;Awan A. K.;Madhok B.;Leeder P. C.;Awad S.;Al-Khyatt W.;Shoma A.;Elghadban H.;Ghareeb S.;Mathews B.;Kurian M.;Larentzakis A.;Vrakopoulou G. Z.;Albanopoulos K.;Bozdag A.;Lale A.;Kirkil C.;Dincer M.;Bashir A.;Haddad A.;Hijleh L. A.;Zilberstein B.;de Marchi D. D.;Souza W. P.;Broden C. M.;Gislason H.;Shah K.;Ambrosi A.;Pavone G.;Tartaglia N.;Kona S. L. K.;Kalyan K.;Perez C. E. G.;Botero M. A. F.;Covic A.;Timofte D.;Maxim M.;Faraj D.;Tseng L.;Liem R.;Oren G.;Dilektasli E.;Yalcin I.;AlMukhtar H.;Hadad M. A.;Mohan R.;Arora N.;Bedi D.;Rives-Lange C.;Chevallier J. -M.;Poghosyan T.;Sebbag H.;Zinai L.;Khaldi S.;Mauchien C.;Mazza D.;Dinescu G.;Rea B.;Perez-Galaz F.;Zavala L.;Besa A.;Curell A.;Balibrea J. M.;Vaz C.;Galindo L.;Silva N.;Caballero J. L. E.;Sebastian S. O.;Marchesini J. C. D.;da Fonseca Pereira R. A.;Sobottka W. H.;Fiolo F. E.;Turchi M.;Coelho A. C. J.;Zacaron A. L.;Barbosa A.;Quinino R.;Menaldi G.;Paleari N.;Martinez-Duartez P.;de Esparza G. M. A. R.;Esteban V. S.;Torres A.;Garcia-Galocha J. L.;Josa M.;Pacheco-Garcia J. M.;Mayo-Ossorio M. A.;Chowbey P.;Soni V.;de Vasconcelos Cunha H. A.;Castilho M. V.;Ferreira R. M. A.;Barreiro T. A.;Charalabopoulos A.;Sdralis E.;Davakis S.;Bomans B.;Dapri G.;Van Belle K.;Takieddine M.;Vaneukem P.;Karaca E. S. A.;Karaca F. C.;Sumer A.;Peksen C.;Savas O. A.;Chousleb E.;Elmokayed F.;Fakhereldin I.;Aboshanab H. M.;Swelium T.;Gudal A.;Gamloo L.;Ugale A.;Ugale S.;Boeker C.;Reetz C.;Hakami I. A.;Mall J.;Alexandrou A.;Baili E.;Bodnar Z.;Maleckas A.;Gudaityte R.;Guldogan C. E.;Gundogdu E.;Ozmen M. M.;Thakkar D.;Dukkipati N.;Shah P. S.;Shah S. S.;Shah S. S.;Adil M. T.;Jambulingam P.;Mamidanna R.;Whitelaw D.;Adil M. T.;Jain V.;Veetil D. K.;Wadhawan R.;Torres A.;Torres M.;Tinoco T.;Leclercq W.;Romeijn M.;van de Pas K.;Alkhazraji A. K.;Taha S. A.;Ustun M.;Yigit T.;Inam A.;Burhanulhaq M.;Pazouki A.;Eghbali F.;Kermansaravi M.;Jazi A. H. D.;Mahmoudieh M.;Mogharehabed N.;Tsiotos G.;Stamou K.;Rodriguez F. J. B.;Navarro M. A. R.;Torres O. M.;Martinez S. L.;Tamez E. R. M.;Cornejo G. A. M.;Flores J. E. G.;Mohammed D. A.;Elfawal M. H.;Shabbir A.;Guowei K.;So J. B.;Kaplan E. T.;Kaplan M.;Kaplan T.;Pham D. T.;Rana G.;Kappus M.;Gadani R.;Kahitan M.;Pokharel K.;Osborne A.;Pournaras D.;Hewes J.;Napolitano E.;Chiappetta S.;Bottino V.;Dorado E.;Schoettler A.;Gaertner D.;Fedtke K.;Aguilar-Espinosa F.;Aceves-Lozano S.;Balani A.;Nagliati C.;Pennisi D.;Rizzi A.;Frattini F.;Foschi D.;Benuzzi L.;Parikh C.;Shah H.;Pinotti E.;Montuori M.;Borrelli V.;Dargent J.;Copaescu C. A.;Hutopila I.;Smeu B.;Witteman B.;Hazebroek E.;Deden L.;Heusschen L.;Okkema S.;Aufenacker T.;den Hengst W.;Vening W.;van der Burgh Y.;Ghazal A.;Ibrahim H.;Niazi M.;Alkhaffaf B.;Altarawni M.;Cesana G. C.;Anselmino M.;Uccelli M.;Olmi S.;Stier C.;Akmanlar T.;Sonnenberg T.;Schieferbein U.;Marcolini A.;Awruch D.;Vicentin M.;de Souza Bastos E. L.;Gregorio S. A.;Ahuja A.;Mittal T.;Bolckmans R.;Wiggins T.;Baratte C.;Wisnewsky J. A.;Genser L.;Chong L.;Taylor L.;Ward S.;Hi M. W.;Heneghan H.;Fearon N.;Plamper A.;Rheinwalt K.;Heneghan H.;Geoghegan J.;Ng K. C.;Fearon N.;Kaseja K.;Kotowski M.;Samarkandy T. A.;Leyva-Alvizo A.;Corzo-Culebro L.;Wang C.;Yang W.;Dong Z.;Riera M.;Jain R.;Hamed H.;Said M.;Zarzar K.;Garcia M.;Turkcapar A. G.;Sen O.;Baldini E.;Conti L.;Wietzycoski C.;Lopes E.;Pintar T.;Salobir J.;Aydin C.;Atici S. D.;Ergin A.;Ciyiltepe H.;Bozkurt M. A.;Kizilkaya M. C.;Onalan N. B. D.;Zuber M. N. B. A.;Wong W. J.;Garcia A.;Vidal L.;Beisani M.;Pasquier J.;Vilallonga R.;Sharma S.;Parmar C.;Lee L.;Sufi P.;Sinan H.;Saydam M.
2022-01-01
Abstract
Background: There is a paucity of data comparing 30-day morbidity and mortality of sleeve gastrectomy (SG), Roux-en-Y gastric bypass (RYGB), and one anastomosis gastric bypass (OAGB). This study aimed to compare the 30-day safety of SG, RYGB, and OAGB in propensity score-matched cohorts. Materials and methods: This analysis utilised data collected from the GENEVA study which was a multicentre observational cohort study of bariatric and metabolic surgery (BMS) in 185 centres across 42 countries between 01/05/2022 and 31/10/2020 during the Coronavirus Disease-2019 (COVID-19) pandemic. 30-day complications were categorised according to the Clavien–Dindo classification. Patients receiving SG, RYGB, or OAGB were propensity-matched according to baseline characteristics and 30-day complications were compared between groups. Results: In total, 6770 patients (SG 3983; OAGB 702; RYGB 2085) were included in this analysis. Prior to matching, RYGB was associated with highest 30-day complication rate (SG 5.8%; OAGB 7.5%; RYGB 8.0% (p = 0.006)). On multivariate regression modelling, Insulin-dependent type 2 diabetes mellitus and hypercholesterolaemia were associated with increased 30-day complications. Being a non-smoker was associated with reduced complication rates. When compared to SG as a reference category, RYGB, but not OAGB, was associated with an increased rate of 30-day complications. A total of 702 pairs of SG and OAGB were propensity score-matched. The complication rate in the SG group was 7.3% (n = 51) as compared to 7.5% (n = 53) in the OAGB group (p = 0.68). Similarly, 2085 pairs of SG and RYGB were propensity score-matched. The complication rate in the SG group was 6.1% (n = 127) as compared to 7.9% (n = 166) in the RYGB group (p = 0.09). And, 702 pairs of OAGB and RYGB were matched. The complication rate in both groups was the same at 7.5 % (n = 53; p = 0.07). Conclusions: This global study found no significant difference in the 30-day morbidity and mortality of SG, RYGB, and OAGB in propensity score-matched cohorts.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/125285
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.
