Long-term follow-up after GBP for morbid obesity showed better scores in most aspects of HRQoL compared to obese controls but did not achieve the levels of the general population. Patients with better medical outcome after gastric bypass operation had better HRQoL.
No significant differences were observed in objectively measured changes in PA or time spent sedentary from 3 months pre-surgery to 9 months postsurgery among women undergoing RYGB. However, women with higher pre-surgery PA decreased their PA postsurgery while women with lower pre-surgery PA increased their PA.
LRYGB is an efficient method for sustained long-term body weight loss. There is, however, a concomitant decrease in BMD and S-calcium, and an increase in fP-PTH.
Severe obesity has been associated with numerous comorbidities and reduced health-related quality of life (HRQoL). Although many studies have reported changes in HRQoL after bariatric surgery, few were long-term prospective studies. We examined the performance of the convolution neural network (CNN) for predicting 5-year HRQoL after bariatric surgery based on the available preoperative information from the Scandinavian Obesity Surgery Registry (SOReg). CNN was used to predict the 5-year HRQoL after bariatric surgery in a training dataset and evaluated in a test dataset. In general, performance of the CNN model (measured as mean squared error, MSE) increased with more convolution layer filters, computation units, and epochs, and decreased with a larger batch size. The CNN model showed an overwhelming advantage in predicting all the HRQoL measures. The MSEs of the CNN model for training data were 8% to 80% smaller than those of the linear regression model. When the models were evaluated using the test data, the CNN model performed better than the linear regression model. However, the issue of overfitting was apparent in the CNN model. We concluded that the performance of the CNN is better than the traditional multivariate linear regression model in predicting long-term HRQoL after bariatric surgery; however, the overfitting issue needs to be mitigated using more features or more patients to train the model.
Previously published literature has identified a few predictors of health-related quality of life (HRQoL) after bariatric surgery. However, performance of the predictive models was not evaluated rigorously using real world data. To find better methods for predicting prognosis in patients after bariatric surgery, we examined performance of the Bayesian networks (BN) method in predicting long-term postoperative HRQoL and compared it with the convolution neural network (CNN) and multivariable logistic regression (MLR). The patients registered in the Scandinavian Obesity Surgery Registry (SOReg) were used for the current study. In total, 6542 patients registered in the SOReg between 2008 and 2012 with complete demographic and preoperative comorbidity information, and preoperative and postoperative 5-year HROoL scores and comorbidities were included in the study. HRQoL was measured using the RAND-SF-36 and the obesity-related problems scale. Thirty-five variables were used for analyses, including 19 predictors and 16 outcome variables. The Gaussian BN (GBN), CNN, and a traditional linear regression model were used for predicting 5-year HRQoL scores, and multinomial discrete BN (DBN) and MLR were used for 5-year comorbidities. Eighty percent of the patients were randomly selected as a training dataset and 20% as a validation dataset. The GBN presented a better performance than the CNN and the linear regression model; it had smaller mean squared errors (MSEs) than those from the CNN and the linear regression model. The MSE of the summary physical scale was only 0.0196 for GBN compared to the 0.0333 seen in the CNN. The DBN showed excellent predictive ability for 5-year type 2 diabetes and dyslipidemia (area under curve (AUC) = 0.942 and 0.917, respectively), good ability for 5-year hypertension and sleep apnea syndrome (AUC = 0.891 and 0.834, respectively), and fair ability for 5-year depression (AUC = 0.750). Bayesian networks provide useful tools for predicting long-term HRQoL and comorbidities in patients after bariatric surgery. The hybrid network that may involve variables from different probability distribution families deserves investigation in the future.
Overweight/obese male partners of RYGB patients also lose weight during the first 9 months post-operatively. However, symptoms of body dissatisfaction, anxiety, and depression remain unchanged, as does self-reported sleep quality.
Introduction
Alcohol overconsumption remains one of the adverse effects associated with bariatric surgery. Many previous studies have used subjective methods to evaluate the prevalence of alcohol overconsumption. In 2018, Örebro University Hospital started to use phosphatidylethanol 16:0/18:1 (PEth) as a screening tool pre- and postbariatric surgery. Research exploring alcohol use after bariatric surgery assessed with PEth is scarce.
Aim
The aim of this study is to evaluate the prevalence of alcohol overconsumption in bariatric surgery patients measured 2 years postoperatively with PEth and to identify possible risk factors associated with alcohol overconsumption.
Methods
This was a register-based retrospective, observational cohort study with PEth results collected from medical records at Örebro University Hospital. Patients who underwent bariatric surgery between January 2016 and June 2019 and who were registered in the Scandinavian Obesity Surgery Registry (SOReg) were included.
Results
PEth results from 410 bariatric surgery patients were identified. PEth values significantly increased from baseline to the postoperative follow-up (from 3.0% before surgery to 8.3% at the 2-year follow-up). In a univariate logistic regression analysis, the associated risk factors were found to be male sex (odds ratio, OR 2.14), older age (OR 1.06), and hypertension (OR 3.32).
Conclusion
The prevalence of alcohol overconsumption measured with PEth 2 years after bariatric surgery was 8.3% and was associated with male sex, older age, and hypertension. More studies are needed to validate the results of this study because it is not known whether PEth values are affected by bariatric surgery.
Graphical abstract
During spontaneous breathing, the LES pressure was the lowest during end-expiration but there were no differences in BrP and IGP. LES, BrP and IGP decreased during anesthesia but BrP remained positive in all patients. During the application of PEEP, esophageal pressures increased and this may have a protective effect against regurgitation.
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