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- Gero, Daniel, et al.
(author)
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Defining Global Benchmarks in Bariatric Surgery A Retrospective Multicenter Analysis of Minimally Invasive Roux-en-Y Gastric Bypass and Sleeve Gastrectomy
- 2019
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In: Annals of Surgery. - : Lippincott Williams & Wilkins. - 0003-4932 .- 1528-1140. ; 270:5, s. 859-867
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Journal article (peer-reviewed)abstract
- Objective: To define “best possible” outcomes for bariatric surgery (BS)(Roux-en-Y gastric bypass [RYGB] and sleeve gastrectomy [SG]).Background: Reference values for optimal surgical outcomes in well-defined low-risk bariatric patients have not been established so far. Consequently, outcome comparison across centers and over time is impeded by heterogeneity in case-mix.Methods: Out of 39,424 elective BS performed in 19 high-volume academic centers from 3 continents between June 2012 and May 2017, we identified 4120 RYGB and 1457 SG low-risk cases defined by absence of previous abdominal surgery, concomitant procedures, diabetes mellitus, sleep apnea, cardiopathy, renal insufficiency, inflammatory bowel disease, immunosuppression, anticoagulation, BMI>50 kg/m2 and age>65 years. We chose clinically relevant endpoints covering the intra- and postoperative course. Complications were graded by severity using the comprehensive complication index. Benchmark values were defined as the 75th percentile of the participating centers’ median values for respective quality indicators.Results: Patients were mainly females (78%), aged 38±11 years, with a baseline BMI 40.8 ± 5.8 kg/m2. Over 90 days, 7.2% of RYGB and 6.2% of SG patients presented at least 1 complication and no patients died (mortality in nonbenchmark cases: 0.06%). The most frequent reasons for readmission after 90-days following both procedures were symptomatic cholelithiasis and abdominal pain of unknown origin. Benchmark values for both RYGB and SG at 90-days postoperatively were 5.5% Clavien-Dindo grade ≥IIIa complication rate, 5.5% readmission rate, and comprehensive complication index ≤33.73 in the subgroup of patients presenting at least 1 grade ≥II complication.Conclusion: Benchmark cutoffs targeting perioperative outcomes in BS offer a new tool in surgical quality-metrics and may be implemented in quality-improvement cycle.ClinicalTrials.gov Identifier NCT03440138
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| 2. |
- Saux, Patrick, et al.
(author)
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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.
- 2023
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In: The Lancet. Digital health. - 2589-7500. ; 5:10
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Journal article (peer-reviewed)abstract
- 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.In this multinational retrospective observational study we enrolled adult participants (aged ≥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 follow-up 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.10231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30602 patient-years. Among participants in all 12 cohorts, 7701 (75·3%) were female, 2530 (24·7%) 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 2·8 kg/m2 (95% CI 2·6-3·0) and mean RMSE BMI was 4·7 kg/m2 (4·4-5·0), and the mean difference between predicted and observed BMI was -0·3 kg/m2 (SD 4·7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery.We developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions.SOPHIA Innovative Medicines Initiative 2 Joint Undertaking, supported by the EU's Horizon 2020 research and innovation programme, the European Federation of Pharmaceutical Industries and Associations, Type 1 Diabetes Exchange, and the Juvenile Diabetes Research Foundation and Obesity Action Coalition; Métropole Européenne de Lille; Agence Nationale de la Recherche; Institut national de recherche en sciences et technologies du numérique through the Artificial Intelligence chair Apprenf; Université de Lille Nord Europe's I-SITE EXPAND as part of the Bandits For Health project; Laboratoire d'excellence European Genomic Institute for Diabetes; Soutien aux Travaux Interdisciplinaires, Multi-établissements et Exploratoires programme by Conseil Régional Hauts-de-France (volet partenarial phase 2, project PERSO-SURG).
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| 3. |
- Stenberg, Erik, 1979-
(author)
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Preventing complications in bariatric surgery
- 2016
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Doctoral thesis (other academic/artistic)abstract
- Obesity is a major public health problem. Bariatric surgery is currently the only available treatment that offers sufficient weight-loss and metabolic benefits over time. Although bariatric surgery is considered safe now, serious complications still occur. The aim of this thesis was to identify factors associated with an increased risk for postoperative complication after laparoscopic gastric bypass surgery.Study I included patients operated with laparoscopic gastric bypass surgery in Sweden from May 2007 until September 2012. The risk for serious complication was low (3.4%). Suffering an intraoperative adverse event or conversion of the operation to open surgery were the strongest risk factors for postoperative complication. The annual operative volume and experience of the procedure at the institution were also important risk factors. Patient-specific risk factors appeared to be less important although age was associated with an increased risk. In Study II, a raised glycated haemoglobin A1c (HbA1c) was evaluated as a risk factor for serious postoperative complications in non-diabetics. A higher incidence of serious postoperative complications was seen with elevated HbA1c values, even at levels classified as ‘‘pre-diabetic’’.Study III was a multicentre, randomised clinical trial (RCT). 2507 patients planned for laparoscopic gastric bypass surgery were randomised to either mesenteric defects closure or non-closure. Closure of the mesenteric defects reduced the rate of reoperation for small bowel obstruction from 10.2% to 5.5% at 3 years after surgery. A small increase in the rate of serious postoperative complication within the first 30 days was seen with mesenteric defects closure. This relatively small increase in risk was however outweighed by the marked reduction of later reoperations for small bowel obstruction.Study IV was a comparison between study III and an observational study on the same population under the same period of time. Although the observational study reached the same conlusion as the RCT, the efficacy of mesenteric defects closure was less pronounced. Observational studies may thus be an alternative to RCTs under situations when RCTs are not feasible. The efficacy may however be underestimated.
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