| 1. |
- Backman, Olof, et al.
(författare)
-
Gastric Bypass Surgery Reduces De Novo Cases of Type 2 Diabetes to Population Levels : A Nationwide Cohort Study From Sweden
- 2019
-
Ingår i: Annals of Surgery. - : Lippincott Williams & Wilkins. - 0003-4932 .- 1528-1140. ; 269:5, s. 895-902
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: The aim of this study was to determine long-term changes in pharmacological treatment of type 2 diabetes after primary Roux-en-Y gastric bypass (RYGB) surgery, in patients with and without pharmacological treatment of diabetes preoperatively.SUMMARY OF BACKGROUND DATA: Several studies have shown that gastric bypass has good effect on diabetes, at least in the short-term. This study is a nationwide cohort study using Swedish registers, with basically no patients lost to follow-up during up to 7 years after surgery.METHODS: The effect of RYGB on type 2 diabetes drug treatment was evaluated in this nationwide matched cohort study. Participants were 22,047 adults with BMI ≥30 identified in the nationwide Scandinavian Surgical Obesity Registry, who underwent primary RYGB between 2007 and 2012. For each individual, up to 10 general population comparators were matched on birth year, sex, and place of residence. Prescription data were retrieved from the nationwide Swedish Prescribed Drug Register through September 2015. Incident use of pharmacological treatment was analyzed using Cox regression.RESULTS: Sixty-seven percent of patients with pharmacological treatment of type 2 diabetes before surgery were not using diabetes drugs 2 years after surgery and 61% of patients were not pharmacologically treated up to 7 years after surgery. In patients not using diabetes drugs at baseline, there were 189 new cases of pharmacological treatment of type 2 diabetes in the surgery group and 2319 in the matched general population comparators during a median follow-up of 4.6 years (incidence: 21.4 vs 27.9 per 10,000 person-years; adjusted hazard ratio 0.77, 95% confidence interval 0.67-0.89; P < 0.001).CONCLUSIONS: Gastric bypass surgery not only induces remission of pharmacological treatment of type 2 diabetes but also protects from new onset of pharmacological diabetes treatment. The effect seems to persist in most, but not all, patients over 7 years of follow-up.
|
|
| 2. |
- Cao, Yang, Associate Professor, 1972-, et al.
(författare)
-
A Comparative Study of Machine Learning Algorithms in Predicting Severe Complications after Bariatric Surgery
- 2019
-
Ingår i: Journal of Clinical Medicine. - : MDPI. - 2077-0383. ; 8:5
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Severe obesity is a global public health threat of growing proportions. Accurate models to predict severe postoperative complications could be of value in the preoperative assessment of potential candidates for bariatric surgery. So far, traditional statistical methods have failed to produce high accuracy. We aimed to find a useful machine learning (ML) algorithm to predict the risk for severe complication after bariatric surgery.Methods: We trained and compared 29 supervised ML algorithms using information from 37,811 patients that operated with a bariatric surgical procedure between 2010 and 2014 in Sweden. The algorithms were then tested on 6250 patients operated in 2015. We performed the synthetic minority oversampling technique tackling the issue that only 3% of patients experienced severe complications.Results: Most of the ML algorithms showed high accuracy (>90%) and specificity (>90%) in both the training and test data. However, none of the algorithms achieved an acceptable sensitivity in the test data. We also tried to tune the hyperparameters of the algorithms to maximize sensitivity, but did not yet identify one with a high enough sensitivity that can be used in clinical praxis in bariatric surgery. However, a minor, but perceptible, improvement in deep neural network (NN) ML was found.Conclusion: In predicting the severe postoperative complication among the bariatric surgery patients, ensemble algorithms outperform base algorithms. When compared to other ML algorithms, deep NN has the potential to improve the accuracy and it deserves further investigation. The oversampling technique should be considered in the context of imbalanced data where the number of the interested outcome is relatively small.
|
|
| 3. |
- Cao, Yang, Associate Professor, 1972-, et al.
(författare)
-
Deep Learning Neural Networks to Predict Serious Complications After Bariatric Surgery : Analysis of Scandinavian Obesity Surgery Registry Data
- 2020
-
Ingår i: JMIR Medical Informatics. - : JMIR Publications. - 2291-9694. ; 8:5
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Obesity is one of today's most visible public health problems worldwide. Although modern bariatric surgery is ostensibly considered safe, serious complications and mortality still occur in some patients.OBJECTIVE: This study aimed to explore whether serious postoperative complications of bariatric surgery recorded in a national quality registry can be predicted preoperatively using deep learning methods.METHODS: Patients who were registered in the Scandinavian Obesity Surgery Registry (SOReg) between 2010 and 2015 were included in this study. The patients who underwent a bariatric procedure between 2010 and 2014 were used as training data, and those who underwent a bariatric procedure in 2015 were used as test data. Postoperative complications were graded according to the Clavien-Dindo classification, and complications requiring intervention under general anesthesia or resulting in organ failure or death were considered serious. Three supervised deep learning neural networks were applied and compared in our study: multilayer perceptron (MLP), convolutional neural network (CNN), and recurrent neural network (RNN). The synthetic minority oversampling technique (SMOTE) was used to artificially augment the patients with serious complications. The performances of the neural networks were evaluated using accuracy, sensitivity, specificity, Matthews correlation coefficient, and area under the receiver operating characteristic curve.RESULTS: In total, 37,811 and 6250 patients were used as the training data and test data, with incidence rates of serious complication of 3.2% (1220/37,811) and 3.0% (188/6250), respectively. When trained using the SMOTE data, the MLP appeared to have a desirable performance, with an area under curve (AUC) of 0.84 (95% CI 0.83-0.85). However, its performance was low for the test data, with an AUC of 0.54 (95% CI 0.53-0.55). The performance of CNN was similar to that of MLP. It generated AUCs of 0.79 (95% CI 0.78-0.80) and 0.57 (95% CI 0.59-0.61) for the SMOTE data and test data, respectively. Compared with the MLP and CNN, the RNN showed worse performance, with AUCs of 0.65 (95% CI 0.64-0.66) and 0.55 (95% CI 0.53-0.57) for the SMOTE data and test data, respectively.CONCLUSIONS: MLP and CNN showed improved, but limited, ability for predicting the postoperative serious complications after bariatric surgery in the Scandinavian Obesity Surgery Registry data. However, the overfitting issue is still apparent and needs to be overcome by incorporating intra- and perioperative information.
|
|
| 4. |
- Cao, Yang, Associate Professor, 1972-, et al.
(författare)
-
Using a Convolutional Neural Network to Predict Remission of Diabetes After Gastric Bypass Surgery : Machine Learning Study From the Scandinavian Obesity Surgery Register
- 2021
-
Ingår i: JMIR Medical Informatics. - : JMIR Publications. - 2291-9694. ; 9:8
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Prediction of diabetes remission is an important topic in the evaluation of patients with type 2 diabetes (T2D) before bariatric surgery. Several high-quality predictive indices are available, but artificial intelligence algorithms offer the potential for higher predictive capability.OBJECTIVE: This study aimed to construct and validate an artificial intelligence prediction model for diabetes remission after Roux-en-Y gastric bypass surgery.METHODS: Patients who underwent surgery from 2007 to 2017 were included in the study, with collection of individual data from the Scandinavian Obesity Surgery Registry (SOReg), the Swedish National Patients Register, the Swedish Prescribed Drugs Register, and Statistics Sweden. A 7-layer convolution neural network (CNN) model was developed using 80% (6446/8057) of patients randomly selected from SOReg and 20% (1611/8057) of patients for external testing. The predictive capability of the CNN model and currently used scores (DiaRem, Ad-DiaRem, DiaBetter, and individualized metabolic surgery) were compared.RESULTS: In total, 8057 patients with T2D were included in the study. At 2 years after surgery, 77.09% achieved pharmacological remission (n=6211), while 63.07% (4004/6348) achieved complete remission. The CNN model showed high accuracy for cessation of antidiabetic drugs and complete remission of T2D after gastric bypass surgery. The area under the receiver operating characteristic curve (AUC) for the CNN model for pharmacological remission was 0.85 (95% CI 0.83-0.86) during validation and 0.83 for the final test, which was 9%-12% better than the traditional predictive indices. The AUC for complete remission was 0.83 (95% CI 0.81-0.85) during validation and 0.82 for the final test, which was 9%-11% better than the traditional predictive indices.CONCLUSIONS: The CNN method had better predictive capability compared to traditional indices for diabetes remission. However, further validation is needed in other countries to evaluate its external generalizability.
|
|
| 5. |
- Jans, Anders, et al.
(författare)
-
Duration of type 2 diabetes and remission rates after bariatric surgery in Sweden 2007-2015 : A registry-based cohort study
- 2019
-
Ingår i: PLoS Medicine. - : Public Library of Science. - 1549-1277 .- 1549-1676. ; 16:11
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Although bariatric surgery is an effective treatment for type 2 diabetes (T2D) in patients with morbid obesity, further studies are needed to evaluate factors influencing the chance of achieving diabetes remission. The objective of the present study was to investigate the association between T2D duration and the chance of achieving remission of T2D after bariatric surgery.METHODS AND FINDINGS: We conducted a nationwide register-based cohort study including all adult patients with T2D and BMI ≥ 35 kg/m2 who received primary bariatric surgery in Sweden between 2007 and 2015 identified through the Scandinavian Obesity Surgery Registry. The main outcome was remission of T2D, defined as being free from diabetes medication or as complete remission (HbA1c < 42 mmol/mol without medication). In all, 8,546 patients with T2D were included. Mean age was 47.8 ± 10.1 years, mean BMI was 42.2 ± 5.8 kg/m2, 5,277 (61.7%) were women, and mean HbA1c was 58.9 ± 17.4 mmol/mol. The proportion of patients free from diabetes medication 2 years after surgery was 76.6% (n = 6,499), and 69.9% at 5 years (n = 3,765). The chance of being free from T2D medication was less in patients with longer preoperative duration of diabetes both at 2 years (odds ratio [OR] 0.80/year, 95% CI 0.79-0.81, p < 0.001) and 5 years after surgery (OR 0.76/year, 95% CI 0.75-0.78, p < 0.001). Complete remission of T2D was achieved in 58.2% (n = 2,090) at 2 years, and 46.6% at 5 years (n = 681). The chance of achieving complete remission correlated negatively with the duration of diabetes (adjusted OR 0.87/year, 95% CI 0.85-0.89, p < 0.001), insulin treatment (adjusted OR 0.25, 95% CI 0.20-0.31, p < 0.001), age (adjusted OR 0.94/year, 95% CI 0.93-0.95, p < 0.001), and HbA1c at baseline (adjusted OR 0.98/mmol/mol, 95% CI 0.97-0.98, p < 0.001), but was greater among males (adjusted OR 1.57, 95% CI 1.29-1.90, p < 0.001) and patients with higher BMI at baseline (adjusted OR 1.07/kg/m2, 95% CI 1.05-1.09, p < 0.001). The main limitations of the study lie in its retrospective nature and the low availability of HbA1c values at long-term follow-up.CONCLUSIONS: In this study, we found that remission of T2D after bariatric surgery was inversely associated with duration of diabetes and was highest among patients with recent onset and those without insulin treatment.
|
|
| 6. |
- Jans, Anders, 1981-, et al.
(författare)
-
Factors affecting relapse of type 2 diabetes after bariatric surgery in Sweden 2007-2015 : a registry-based cohort study
- 2022
-
Ingår i: Surgery for Obesity and Related Diseases. - : Elsevier. - 1550-7289 .- 1878-7533. ; 18:3, s. 305-312
-
Forskningsöversikt (refereegranskat)abstract
- BACKGROUND: Although a large proportion of patients with type 2 diabetes (T2DM) who have undergone metabolic surgery experience initial remission some patients later suffer from relapse. While several factors associated with T2D remission are known, less is known about factors that may influence relapse.OBJECTIVES: To identify possible risk factors for T2D relapse in patients who initially experienced remission.SETTING: Nationwide, registry-based study.METHODS: We conducted a nationwide registry-based retrospective cohort study including all adult patients with T2D and body mass index ≥35 kg/m2 who received primary metabolic surgery with Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) in Sweden between 2007 and 2015. Patients who achieved complete diabetes remission 2 years after surgery was identified and analyzed. Main outcome measure was postoperative relapse of T2D, defined as reintroduction of diabetes medication.RESULTS: In total, 2090 patients in complete remission at 2 years after surgery were followed for a median of 5.9 years (interquartile range [IQR] 4.3-7.2 years) after surgery. The cumulative T2D relapse rate was 20.1%. Duration of diabetes (hazard ratio [HR], 1.09; 95% confidence interval [CI], 1.05-1.14; P < .001), preoperative glycosylated hemoglobin A1C (HbA1C) level (HR, 1.01; 95% CI, 1.00-1.02; P = .013), and preoperative insulin treatment (HR, 2.67; 95% CI, 1.84-3.90; P < .001) were associated with higher rates for relapse, while postoperative weight loss (HR, .93; 95% CI, .91-.96; P < .001), and male sex (HR, .65; 95% CI, .46-.91; P = .012) were associated with lower rates.CONCLUSION: Longer duration of T2D, higher preoperative HbA1C level, less postoperative weight loss, female sex, and insulin treatment prior to surgery are risk factors for T2D relapse after initial remission.
|
|
| 7. |
- Josefsson, Emma, et al.
(författare)
-
The effect of routine division of the greater omentum on small bowel obstruction after Roux-en-Y gastric bypass
- 2023
-
Ingår i: Surgery for Obesity and Related Diseases. - : Elsevier. - 1550-7289 .- 1878-7533. ; 19:3, s. 178-183
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: It remains unknown whether routine division of the greater omentum during laparoscopic Roux-en-Y gastric bypass (LRYGB) influences the risk for small bowel obstruction (SBO) after RYGB.OBJECTIVE: To evaluate the effect of omental division on SBO after LRYGB stratified by handling of the mesenteric defects.SETTING: Nationwide, registry-based.METHODS: In this registry-based cohort study, 40,517 patients who underwent LRYGB in Sweden within the period from January 1, 2007, to December 31, 2019, with data from the Scandinavian Obesity Surgery Registry (SOReg) were included. The study was based on combined data from the SOReg, the National Patient Register, the Swedish Prescribed Drugs Register, and the Total Population Registry. The main outcome was reoperation for SBO.RESULTS: During a follow-up period of 5.9 ± 2.6 years, the cumulative incidence of SBO was 11.2% in the nondivision group compared with 9.7% among patients with divided omentum (hazard ratio [HR] = .83, 95% confidence interval [CI]: .77-.89, P < .001). The association was seen in patients without mesenteric defects closure (HR = .69, 95% CI: .61-.78, P < .001) as well as patients with closed mesenteric defects (HR = .80, 95% CI: .74-.87, P < .001).CONCLUSION: Division of the greater omentum is associated with reduced risk for SBO after antecolic, antegastric LRYGB and should be considered as a complement to mesenteric defects closure to further reduce the risk for SBO after LRYGB.
|
|
| 8. |
- le Roux, Carel W., et al.
(författare)
-
Bariatric Surgery : There Is a Room for Improvement to Reduce Mortality in Patients with Type 2 Diabetes
- 2021
-
Ingår i: Obesity Surgery. - : Springer. - 0960-8923 .- 1708-0428.
-
Tidskriftsartikel (refereegranskat)abstract
- The new Scandinavian Obesity Surgery Registry (SOReg) report may influence current guidelines. Patients without type 2 diabetes (T2DM) prior to bariatric surgery had lower mortality over 6.3 years compared to those with T2DM. Moreover, patients with T2DM who achieved remission within 1 year after surgery had lower mortality than those who did not remit. Finally, there was no threshold at 10 years, but rather a linear relationship between duration of T2DM and glycemic remission. The SOReg report challenges existing recommendations and clinical practice. A case may also be made for patients with T2DM who did not achieve glycemic remission after 1 year to have a combination approach of surgery with medicines rather than surgery alone. Ultimately, the impact of T2DM duration on glycemic remission again suggest that patients with T2DM should have bariatric surgery earlier.
|
|
| 9. |
- Näslund, Erik, et al.
(författare)
-
Association of Metabolic Surgery With Major Adverse Cardiovascular Outcomes in Patients With Previous Myocardial Infarction and Severe Obesity A Nationwide Cohort Study
- 2021
-
Ingår i: Circulation. - : Lippincott Williams & Wilkins. - 0009-7322 .- 1524-4539. ; 143:15, s. 1458-1467
-
Tidskriftsartikel (refereegranskat)abstract
- Background: The number of patients with myocardial infarction and severe obesity is increasing and there is a lack of evidence how these patients should be treated. The aim of this study was to investigate the association between metabolic surgery (Roux-en-Y gastric bypass and sleeve gastrectomy) and major adverse cardiovascular events in patients with previous myocardial infarction (MI) and severe obesity.Methods: Of 566 patients with previous MI registered in the SWEDEHEART registry (Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) undergoing metabolic surgery and registered in the nationwide Scandinavian Obesity Surgery Registry, 509 patients (Roux-en-Y gastric bypass n=465; sleeve gastrectomy n=44) could be matched 1:1 to a control with MI from SWEDEHEART, but no subsequent metabolic surgery regarding sex, age (+/- 3 years), year of MI (+/- 3 years), and body mass index (+/- 3). The 2 groups were well matched, except for a lower proportion of reduced ejection fraction after MI (7% versus 12%), previous heart failure (10% versus 19%), atrial fibrillation (6% versus 10%), and chronic obstructive pulmonary disease (4% versus 7%) in patients undergoing metabolic surgery.Results: The median (interquartile range) follow-up time was 4.6 (2.7-7.1) years. The 8-year cumulative probability of major adverse cardiovascular events was lower in patients undergoing metabolic surgery (18.7% [95% CI, 15.9-21.5%] versus 36.2% [33.2-39.3%], adjusted hazard ratio, 0.44 [95% CI, 0.32-0.61]). Patients undergoing metabolic surgery had also a lower risk of death (adjusted HR, 0.45 [95% CI, 0.29-0.70]; MI, 0.24 [0.14-0.41]) and new onset heart failure, but there were no significant differences regarding stroke (0.91 [0.38-2.20]) and new onset atrial fibrillation (0.56 [0.31-1.01]).Conclusions: In severely obese patients with previous MI, metabolic surgery is associated with a low risk for serious complications, lower risk of major adverse cardiovascular events, death, new MI, and new onset heart failure. These findings need to be confirmed in a randomized, controlled trial.
|
|
| 10. |
- Stenberg, Erik, 1979-, et al.
(författare)
-
Early complications after laparoscopic gastric bypass surgery : results from the Scandinavian Obesity Surgery Registry
- 2014
-
Ingår i: Annals of Surgery. - : Lippincott Williams & Wilkins. - 0003-4932 .- 1528-1140. ; 260:6, s. 1040-1047
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To identify risk factors for serious and specific early complications of laparoscopic gastric bypass surgery using a large national cohort of patients.BACKGROUND: Bariatric procedures are among the most common surgical procedures today. There is, however, still a need to identify preoperative and intraoperative risk factors for serious complications.METHODS: From the Scandinavian Obesity Surgery Registry database, we identified 26,173 patients undergoing primary laparoscopic gastric bypass operation for morbid obesity between May 1, 2007, and September 30, 2012. Follow-up on day 30 was 95.7%. Preoperative data and data from the operation were analyzed against serious postoperative complications and specific complications.RESULTS: The overall risk of serious postoperative complications was 3.4%. Age (adjusted P = 0.028), other additional operation [odds ratio (OR) = 1.50; confidence interval (CI): 1.04-2.18], intraoperative adverse event (OR = 2.63; 1.89-3.66), and conversion to open surgery (OR = 4.12; CI: 2.47-6.89) were all risk factors for serious postoperative complications. Annual hospital volume affected the rate of serious postoperative complications. If the hospital was in a learning curve at the time of the operation, the risk for serious postoperative complications was higher (OR = 1.45; CI: 1.22-1.71). The 90-day mortality rate was 0.04%.CONCLUSIONS: Intraoperative adverse events and conversion to open surgery are the strongest risk factors for serious complications after laparoscopic gastric bypass surgery. Annual operative volume and total institutional experience are important for the outcome. Patient related factors, in particular age, also increased the risk but to a lesser extent.
|
|
