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

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, 202

Collaborative Prescribing Practice in Managing Patients Post-Bariatric Surgery in a Tertiary Centre in Singapore

Background: A collaborative prescribing (CP) practice model, established by the endocrinologists, pharmacists, and advanced practice nurses, aims to provide for the postoperative monitoring and medical and nutritional management of stable patients after bariatric surgery. Method: Under the CP agreement, endocrinologists refer patients who have undergone bariatric surgery with stable medical conditions to CP practitioners, comprising senior pharmacists and advanced practice nurses. CP practitioners review the patient’s weight loss progress, blood test results and vitals, the sufficiency of micronutrient repletion, adherence to supplements and medications, and chronic disease control. CP practitioners can prescribe and adjust the medications and supplements, in accordance with a clinical evaluation and standard guidance. Patients who require immediate attention due to complications or red flags are referred to the primary endocrinologist for further management. Results: From 5 May 2020 to 30 September 2023, CP practitioners provided 672 consultations. At least 68% and 80% of patients achieved appropriate weight loss post-surgery during the acute and maintenance phases, respectively. Less than 10% of the patients presented with anaemia and iron deficiency, and vitamin B12, folate and vitamin D deficiency. More than 80% of patients achieved a HbA1c of less than 7%. Conclusions: The CP practice framework provides a sustainable and viable model to facilitate optimal outcomes after bariatric surgery

Examining spousal and family support as predictors of long-term weight loss and remission of type 2 diabetes following bariatric surgery in Singapore: a retrospective cohort study

Objectives Postoperative outcomes vary considerably across bariatric patients and may be related to psychosocial factors. In this study, we examined whether a patient’s family support predicts postsurgical weight loss and the remission of type 2 diabetes mellitus (T2DM).Design Retrospective cohort study in Singapore.Setting Participants were recruited from a public hospital in Singapore.Participants Between 2008 and 2018, 359 patients completed a presurgical questionnaire before undergoing gastric bypass or sleeve gastrectomy.Outcome measures As part of the questionnaire, patients described their family support in terms of structure (marital status, number of family members in the household) and function (marriage satisfaction, family emotional support, family practical support). Linear mixed-effects and Cox proportional-hazard models were used to examine whether these family support variables predicted percent total weight loss or T2DM remission up to 5 years postsurgery. T2DM remission was defined as glycated haemoglobin (HbA1c) <6.0% without medications.Results Participants had a mean preoperative body mass index of 42.6±7.7 kg/m2 and HbA1c (%) of 6.82±1.67. Marital satisfaction was found to be a significant predictor of postsurgical weight trajectories. Namely, patients who reported higher marital satisfaction were more likely to sustain weight loss than patients who reported lower marital satisfaction (β=0.92, SE=0.37, p=0.02). Family support did not significantly predict T2DM remission.Conclusions Given the link between marital support and long-term weight outcomes, providers could consider asking patients about their spousal relationships during presurgical counselling.Trial registration number NCT04303611

Multiparametric Magnetic Resonance Imaging and Magnetic Resonance Elastography to Evaluate the Early Effects of Bariatric Surgery on Nonalcoholic Fatty Liver Disease

Background. Bariatric surgery is the most effective treatment for morbid obesity and reduces the severity of nonalcoholic fatty liver disease (NAFLD) in the long term. Less is known about the effects of bariatric surgery on liver fat, inflammation, and fibrosis during the early stages following bariatric surgery. Aims. This exploratory study utilises advanced imaging methods to investigate NAFLD and fibrosis changes during the early metabolic transitional period following bariatric surgery. Methods. Nine participants with morbid obesity underwent sleeve gastrectomy. Multiparametric MRI (mpMRI) and magnetic resonance elastography (MRE) were performed at baseline, during the immediate (1 month), and late (6 months) postsurgery period. Liver fat was measured using proton density fat fraction (PDFF), disease activity using iron-correct T1 (cT1), and liver stiffness using MRE. Repeated measured ANOVA was used to assess longitudinal changes and Dunnett’s method for multiple comparisons. Results. All participants (Age 45.1±9.0 years, BMI 39.7±5.3 kg/m2) had elevated hepatic steatosis at baseline (PDFF >5%). In the immediate postsurgery period, PDFF decreased significantly from 14.1±7.4% to 8.9±4.4% (p=0.016) and cT1 from 826.9±80.6 ms to 768.4±50.9 ms (p=0.047). These improvements continued to the later postsurgery period. Bariatric surgery did not reduce liver stiffness measurements. Conclusion. Our findings support using MRI as a noninvasive tool to monitor NAFLD in patient with morbid obesity during the early stages following bariatric surgery

Discovery of super-insecticide-resistant dengue mosquitoes in Asia: threats of concomitant knockdown resistance mutations

Aedes aegypti (Linnaeus, 1762) is the main mosquito vector for dengue and other arboviral infectious diseases. Control of this important vector highly relies on the use of insecticides, especially pyrethroids. The high frequency (>78%) of the L982W substitution was detected at the target site of the pyrethroid insecticide, the voltage-gated sodium channel (Vgsc) of A. aegypti collected from Vietnam and Cambodia. Alleles having concomitant mutations L982W + F1534C and V1016G + F1534C were also confirmed in both countries, and their frequency was high (>90%) in Phnom Penh, Cambodia. Strains having these alleles exhibited substantially higher levels of pyrethroid resistance than any other field population ever reported. The L982W substitution has never been detected in any country of the Indochina Peninsula except Vietnam and Cambodia, but it may be spreading to other areas of Asia, which can cause an unprecedentedly serious threat to the control of dengue fever as well as other Aedes-borne infectious diseases.Published versionThis study was supported by the Japan Agency for Medical Research and Development (AMED) JP17fm0108018, JP20fk0108067, JP20wm0225007, JP21wm0125006, JP21wm0225007, and JP21fk0108613