Background:Obesity is strongly associated with metabolic dysfunction and steatotic liver disease (MASLD). Laparoscopic sleeve gastrectomy (LSG) effectively addresses severe obesity and its metabolic complications. Recent studies suggest that exosomes and their microRNA (miRNA) content mediate systemic metabolic improvements following bariatric surgery. Objective:This study aims to characterize plasma exosomal miRNAs before and after LSG, identify functional candidates linked to MASLD remission, and validate underlying mechanisms in vitro. Methods:Plasma exosomes from control subjects, as well as pre- and post-LSG patients, were isolated via ultracentrifugation, characterized, and subjected to high-throughput miRNA sequencing. Differential expression analysis, weighted gene co-expression network analysis, and random forest modeling were used to identify key miRNAs. Predicted targets, based on multi-database consensus, were integrated with paired liver transcriptomes from GEO (GSE106737, GSE83452). miRNA-target interactions were confirmed through dual-luciferase assays. In a free fatty acid-induced HepG2 MASLD model, miRNA mimics/inhibitors were employed to evaluate lipid accumulation (Oil Red O, intracellular triacylglycerol/total cholesterol) and target expression (qRT-PCR, Western blot). Results:LSG significantly altered circulating exosomal miRNA profiles. Six key miRNAs were identified, with miR-497-5p being the most prominent. Integrative analysis revealed GABARAPL1 as a direct target of miR-497-5p, and its upregulation in post-LSG liver tissues. Luciferase assays confirmed miR-497-5p binding to the GABARAPL1 3'UTR. In HepG2 cells, inhibition of miR-497-5p reduced lipid droplet formation and intracellular triacylglycerol/total cholesterol levels, while overexpression exacerbated steatosis. Inhibition also led to increased GABARAPL1 mRNA and protein levels. Conclusion:LSG induces significant remodeling of the circulating exosomal miRNA profile. Specifically, the downregulation of exosomal miR-497-5p post-LSG appears to alleviate hepatic lipid accumulation by derepressing its target, GABARAPL1, a key regulator of lipophagy. miR-497-5p is thus a potential biomarker and therapeutic target.

Obesity and related metabolic diseases are major global health challenges. Metabolic and bariatric surgery (MBS) is an effective treatment. Yet exploring its molecular mechanisms remains limite due to the challenge of obtaining postoperative tissue samples. While rat models are more convenient in size and operation, mouse models offer unique advantages such as lower breeding costs and easier genetic modification. However, research on mouse MBS models is still limited because of their small size and surgical complexity, highlighting the need for optimized techniques to advance the field. This study aims to establish a high-fat diet-induced (HFD) obesity combined with metabolic dysfunction-associated steatotic liver disease (MASLD) mouse model, and to evaluate the MBS models assisted by microsurgery, so as to provide a reliable tool for mechanism research. Male SPF C57BL/6J mice were randomly assigned to the normal diet (ND) group and the HFD group. The mouse in the HFD group were induced to develop obesity with MASLD through a high-fat diet for 16 weeks. The HFD group was further divided into sham operation group (Sham), sleeve gastrectomy (SG) group, and modified Roux-en-Y gastric bypass (RYGB) group (n = 6). Metabolic efficacy was evaluated by weight, metabolic parameters, and pathological staining analysis at the 4th week post-surgery. Compared with the ND group, the weight of the HFD group increased by 38.25

Background: Video-assisted thoracoscopic (VATS) lobectomy can affect patients’ pulmonary function and quality of life significantly. No optimal protocol combining patient-reported outcome-based symptom management and postdischarge rehabilitation programme has yet been established. This study aimed to assess the efficacy of a novel smartphone app designed for home-based symptom management and rehabilitation. Methods: The app was developed based on three modules: a symptom reporting system with alerts, aerobic and respiratory training exercises, and educational material. Four core symptoms were selected based on a questionnaire survey of 201 patients and three rounds of Delphi voting by 30 experts. The authors screened 265 patients and randomly assigned 136 equally to the app group and usual care group. The primary outcome was pulmonary function recovery at 30 days postoperatively. Secondary outcomes included symptom burden and interference with daily living (both rated using the MD Anderson Symptom Inventory for Lung Cancer), aerobic exercise intensity, emergency department visits, app-related safety, and satisfaction with the app. Findings: Of the 136 participants, 56.6% were women and their mean age was 61 years. The pulmonary function recovery ratio 1 month after surgery in the app group was significantly higher than that in the usual care group (79.32 vs. 75.73%; P=0.040). The app group also recorded significantly lower symptom burden and interference with daily living scores and higher aerobic exercise intensity after surgery than the usual care group. Thirty-two alerts were triggered in the app group. The highest pulmonary function recovery ratio and aerobic exercise intensity were recorded in those patients who triggered alerts in both groups. Interpretation: Using a smartphone app is an effective approach to accelerate home-based rehabilitation after VATS lobectomy. The symptom alert mechanism of this app could optimise recovery outcomes, possibly driven by patients’ increased self-awareness.

BACKGROUND:The triglyceride-glucose index (TyG) has shown comprehensive value in relation to numerous obesity-associated comorbidities, especially cardiovascular diseases. Although their incidence risk and severity are lowered following sleeve gastrectomy (SG), the extent of relief varies. OBJECTIVES:To analyze potential influencing factors of decrease in the TyG index (△TyG) following SG, and establish a predictive model using preoperative data. SETTING:University hospital, China. METHODS:Preoperative and 1-year postoperative data of patients with obesity who underwent SG were collected. After being randomly divided at a proportion of 70%, the patients in the modeling group were further divided into group A (decreased poorly) and group B (decreased satisfactorily) based on the degree of △TyG. After screening the variables with significant differences between the groups, we conducted logistic regression analysis to identify the influencing factors related to △TyG and those with a predictive value. Subsequently, a nomogram was established. Internal, external validations and decision curve analysis (DCA) were performed. Clinical impact curve (CIC) was drawn. RESULTS:The study included 744 patients. Four independent predictors, namely waist-hip ratio (WHR), high-density lipoprotein cholesterol (HDL-c), uric acid (UA), and TyG index were identified. The joint predictor formed by combining these four factors had an area under the curve of .838 (.803-.868) and a significantly better predictive value. The predictive accuracy and clinical net benefit of the nomogram established utilizing the joint predictor were verified. CONCLUSIONS:SG can lead to significant △TyG, with preoperative WHR, HDL-c, UA, and TyG index being independent predictors. The joint predictor can effectively predict the magnitude of the decrease.

This study aimed to investigate the relationship between traditional Chinese Medicine (TCM) body constitution and sleep quality among high-speed railway crew in Beijing, China. Evaluate TCM body constitution and sleep quality by using the constitution in Chinese medicine questionnaire (CCMQ) and the Pittsburgh sleep quality index (PSQI). From March 19, 2022, to November 20, 2023, a total of 799 questionnaires were distributed and returned 742 copies of the CCMQ and PSQI. The univariate analysis results showed significant association between sleep quality and Yang-deficiency constitution, Yin-deficiency constitution, phlegm-dampness constitution, dampness-heat constitution, blood-stasis constitution, Qi-stagnation constitution, Inherited-special constitution, academic degree (P < .05). In the multivariate analysis, Yin-deficiency constitution (OR = 2.492, 95% CI = 1.824-3.405) and Qi-stagnation constitution (OR = 2.097, 95% CI = 1.429-3.076) were associated with the sleep quality (P < .001). This cross-sectional study showed an association between Yin-deficiency and Qi-stagnation constitutions and sleep disorder in Beijing high-speed railway crew. However, the cross-sectional design precludes causal inference, and improving TCM body constitution may not necessarily lead to improved sleep quality. Further longitudinal research is needed to establish causal relationships. Nevertheless, this study provides a case for the potential role of TCM in supporting occupational health.

Obesity is a chronic low-grade inflammatory condition. Laparoscopic sleeve gastrectomy (LSG) is a widely recognized intervention for weight management; however, the percentage of total weight loss (

Background: The global prevalence of non-alcoholic fatty liver disease (NAFLD) is approximately 30%, and the condition can progress to non-alcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma. Metabolic and bariatric surgery (MBS) has been shown to be effective in treating obesity and related disorders, including NAFLD. Objective: In this study, comprehensive machine learning was used to identify biomarkers for precise treatment of NAFLD from the perspective of MBS. Methods: Differential expression and univariate logistic regression analyses were performed on lipid metabolism-related genes in a training dataset (GSE83452) and two validation datasets (GSE106737 and GSE48452) to identify consensus-predicted genes (CPGs). Subsequently, 13 machine learning algorithms were integrated into 99 combinations; among which the optimal combination was selected based on the total score of the area under the curve, accuracy, F-score, and recall in the two validation datasets. Hub genes were selected based on their importance ranking in the algorithms and the frequency of their occurrence. Finally, a mouse model of MBS was established, and the mRNA expression of the hub genes was validated via quantitative PCR. Results: A total of 12 CPGs were identified after intersecting the results of differential expression and logistic regression analyses on a Venn diagram. Four machine learning algorithms with the highest total scores were identified as optimal models. Additionally, PPARA, PLIN2, MED13, INSIG1, CPT1A, and ALOX5AP were identified as hub genes. The mRNA expression patterns of these genes in mice subjected to MBS were consistent with those observed in the three datasets. Conclusion: Altogether, the six hub genes identified in this study are important for the treatment of NAFLD via MBS and hold substantial promise in guiding personalized treatment of NAFLD in clinical settings.

Excessive visceral adipose tissue (VAT) accumulation is strongly associated with numerous metabolic disorders. Laparoscopic sleeve gastrectomy (LSG) reduces VAT, leading to improved metabolic conditions. However, considerable individual variability results in suboptimal metabolic improvements in certain patients post-LSG. Currently, no predictive model for postoperative VAT content exists, and reliance on macroscopic anthropometric or basic metabolic parameters alone fails to accurately predict postoperative metabolic outcomes. This study aims to evaluate the long-term effects of LSG on VAT reduction, identify factors influencing VAT loss, and develop a clinically applicable risk assessment model. This study included 177 patients, randomly divided into a modeling group (132 patients) and a validation group (45 patients). Demographic, metabolic, and imaging data were collected, and patients were categorized based on the median ΔVAT change at 12 months post-LSG. Independent predictors were identified via univariate and multivariate logistic regression, and a nomogram model was developed, followed by external validation. In the modeling group, significant differences in gender, waist-to-hip ratio (WHR), VAT, high-density lipoprotein cholesterol (HDL-c), and hypertension were observed between the high-change and low-change groups. Multivariate logistic regression identified preoperative VAT and HDL-c as independent predictors of weight loss outcomes. The nomogram model demonstrated excellent discriminatory power, with an AUC of 0.7 in the training set and 0.88 in the validation group. The calibration curve confirmed high predictive accuracy, and decision curve analysis (DCA) and clinical impact curve (CIC) analyses underscored the model’s strong clinical applicability. The combination of preoperative HDL-c and VAT serves as an effective predictor of VAT reduction post-LSG, offering a theoretical basis for improving preoperative assessment and facilitating personalized patient management.

Background: Tandem mass tag (TMT) labeling technology in labeled quantitative proteomics has been widely used in studying differentially expressed proteins (DEPs).Objectives: The purpose of the research was to explore DEPs closely associated with optimal initial clinical response.Methods: Optimal initial clinical response was defined as a percentage of excess weight loss (%EWL) >= 50%. Using TMT technology and bioinformatics, we screened DEPs to identify those associated with weight-loss outcomes 1 year after surgery. Key DEPs were validated using western blotting and immunohistochemistry in tissue samples from patients with optimal and suboptimal clinical responses.Results: We enrolled 26 patients, including 13 with optimal initial clinical response and 13 with suboptimal initial clinical response. Of the 267 DEPs screened, only heat shock protein beta 2 (HSP beta 2) best evaluated the weight loss, with an optimal cutoff of 0.8206 (area under the curve, 1.000; 95% confidence interval: 0.868-1.000; sensitivity, 100.00%; specificity, 100.00%). In an external validation cohort, the HSP beta 2 expression was significantly lower in the optimal initial clinical response group than in the suboptimal initial clinical response group.Conclusions: HSP beta 2 is closely associated with the weight-loss outcome of laparoscopic sleeve gastrectomy.

Background:A significant proportion of patients with obesity have comorbid hyperuricemia (HUA). However, the curative effect of sleeve gastrectomy (SG) on HUA remains debated. Objective:To clarify the remission effect of SG on HUA, analyze potential influencing factors, and establish a predictive model using preoperative data. Methods:Pre- and post-operative data from 130 patients with obesity and HUA who underwent SG in our hospital were collected and evaluated for the therapeutic effect on HUA. Binary logistic regression analysis was employed to screen the influencing factors and the ones with predictive value. Predictive model was constructed, then evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) and internal and external validations. Complete remission of HUA was defined as a follow-up SUA level that no longer met the reference value for diagnosing HUA, i.e., an SUA concentration of <428 μmol/L (in males) or <357 μmol/L (in females), according to the reference value in our hospital's laboratory. Results:The mean follow-up duration is 20.4 months. After ≥ one year post SG, the complete remission rate of HUA was 58%. Preoperative hip circumference (HC) and preoperative serum uric acid (SUA) level were found to be predictive variables, the AUC values of which, along with their combination in predicting this outcome, were 0.696, 0.731, 0.738, respectively, p >0.05. The joint predictive model was found to have a sensitivity and specificity of 0.776 and 0.738, respectively, and its reliability was confirmed by internal and external validations. Conclusion:Some patients can achieve HUA complete remission following SG after 1 year. Preoperative SUA concentration and HC can be utilized to predict this outcome in Chinese patients with obesity. The joint predictive model offers potentially better clinical value.

Background:Laparoscopic sleeve gastrectomy (LSG) is associated with sustained and substantial weight loss. However, suboptimal results are observed in certain patients. Objective:Drawing from body composition data at our center, clinically accessible predictive factors for weight loss outcomes were identified, leading to the development and validation of a preoperative predictive model for weight loss following LSG. Methods and Materials:A retrospective analysis was conducted on the general clinical baseline and body composition data of obese patients (body mass index [BMI] ≥ 32.5 kg/m2) who underwent LSG between December 2016 and December 2022. Independent predictors for weight loss outcomes were selected through univariate logistic regression, random forest analysis, and multivariate logistic regression. Subsequently, a nomogram was developed to predict weight loss outcomes and was evaluated for discrimination, accuracy, and clinical utility, with validation performed in a separate cohort. Results:A total of 473 patients with mean BMI were included. The preoperative resting energy expenditure to body weight ratio (REE/BW), fat-free mass index (FFMI), and waist circumference (WC) emerged as independent predictive factors for weight loss outcomes at one year post-LSG. These body composition parameters were incorporated into the construction of an Inbody predictive nomogram, which yielded area under the curve (AUC) values of 0.868 (95% CI: 0.826-0.902) for the modeling cohort and 0.829 (95% CI: 0.756-0.887) for the validation cohort. Calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC) from both groups demonstrated the model's robust discrimination, accuracy, and clinical utility. Conclusion:In obese Chinese patients with a BMI ≥ 32.5 kg/m2, the Inbody-based nomogram integrating REE/BW, FFMI, and WC offers an effective preoperative tool for predicting weight loss outcomes one year after LSG, facilitating surgical planning and postoperative management.

Background: The effect of bariatric surgery on type 2 diabetes mellitus (T2DM) control can be assessed based on predictive models of T2DM remission. Various models have been externally verified internationally. However, long-term validated results after laparoscopic sleeve gastrectomy (LSG) surgery are lacking. The best model for the Chinese population is also unknown. Methods: We retrospectively analyzed Chinese population data 5 years after LSG at Beijing Shijitan Hospital in China between March 2009 and December 2016. The independent t-test, Mann-Whitney U test, and chi-squared test were used to compare characteristics between T2DM remission and non-remission groups. We evaluated the predictive efficacy of each model for long-term T2DM remission after LSG by calculating the area under the curve (AUC), sensitivity, specificity, Youden index, positive predictive value (PPV), negative predictive value (NPV), and predicted-to-observed ratio, and performed calibration using Hosmer-Lemeshow test for 11 prediction models. Results: We enrolled 108 patients, including 44 (40.7%) men, with a mean age of 35.5 years. The mean body mass index was 40.3 +/- 9.1 kg/m(2), the percentage of excess weight loss (%EWL) was (75.9 +/- 30.4)%, and the percentage of total weight loss (%TWL) was (29.1 +/- 10.6)%. The mean glycated hemoglobin A1c (HbA1c) level was (7.3 +/- 1.8)% preoperatively and decreased to (5.9 +/- 1.0)% 5 years after LSG. The 5-year postoperative complete and partial remission rates of T2DM were 50.9% [55/108] and 27.8% [30/108], respectively. Six models, i.e., "ABCD", individualized metabolic surgery (IMS), advanced-DiaRem, DiaBetter, Dixon et al's regression model, and Panunzi et al's regression model, showed a good discrimination ability (all AUC >0.8). The "ABCD" (sensitivity, 74%; specificity, 80%; AUC, 0.82 [95% confidence interval [CI]: 0.74-0.89]), IMS (sensitivity, 78%; specificity, 84%; AUC, 0.82 [95% CI: 0.73-0.89]), and Panunzi et al's regression models (sensitivity, 78%; specificity, 91%; AUC, 0.86 [95% CI: 0.78-0.92]) showed good discernibility. In the Hosmer-Lemeshow goodness-of-fit test, except for DiaRem (P <0.01), DiaBetter (P <0.01), Hayes et al (P = 0.03), Park et al (P = 0.02), and Ramos-Levi et al's (P <0.01) models, all models had a satifactory fit results (P >0.05). The P values of calibration results of the "ABCD" and IMS were 0.07 and 0.14, respectively. The predicted-to-observed ratios of the "ABCD" and IMS were 0.87 and 0.89, respectively. Conclusion: The prediction model IMS was recommended for clinical use because of excellent predictive performance, good statistical test results, and simple and practical design features.

Lipoma is a common type of benign soft tissue tumor that can occur in the shoulders, neck and back, in addition to other body parts. The Retzius space is a small anatomical space between the pubic symphysis and the bladder located extraperitoneally and filled with loose fatty connective tissue. Giant lipomas are rare in the Retzius space. A 61-year-old Chinese male arrived at Beijing Yanhua Hospital (Beijing, China) due to frequent urination, and CT scan images of the lower abdomen observed a large pelvic mass and left inguinal hernia. Preoperative clinical manifestations and auxiliary examination suggested that the tumor originated from the urinary bladder wall. The maximum tumor diameter was ~25 cm and abdominal pressure was increased. Therefore, laparoscopic pelvic tumor resection combined with inguinal hernia repair was attempted. Intraoperatively, the tumor was found to originate from the Retzius space and the postoperative pathological diagnosis was lipoma. The present case report may serve as a reference for minimally invasive treatment of this type of rare disease in future.

Following laparoscopic gastrectomy (LG), one of the critical complications that can arise is a pancreatic fistula (PF). The inability to promptly prevent, diagnose, and manage this condition can lead to severe complications and potentially be life-threatening for the patient. The incidence of PF post-LG in gastric cancer treatment is related to factors such as surgical approach, surgical instruments, characteristics of the pancreas itself, tumor stage, and the surgeon's experience. Currently, the diagnosis of postoperative PF is mainly based on the definition and diagnostic criteria consensus established by the International Study Group of Pancreatic Surgery. Gastrointestinal surgeons should be aware of the risk factors for PF, perform LG for gastric cancer with great care and precision, avoid pancreatic injury, and actively work to reduce the risk of postoperative PF.

Purpose:Gastroesophageal reflux disease (GERD) is a common complication after laparoscopic sleeve gastrectomy (LSG); This study aimed to construct a model that can predict the incidence of GERD after LSG by exploring the correlation between the results of high-resolution esophageal manometry (HREM) and the incidence of GERD after LSG. Patients and Methods:We collected the clinical data of patients who had undergone HREM before bariatric surgery from September 2013 to September 2019 at the bariatric center of our hospital. The Gerd-Q scores during the postoperative follow-up were collected to determine the incidence of GERD. A logistic regression analysis was performed to explore the correlation of the HREM results and general clinical data with the incidence of GERD after LSG. Results:The percentage of synchronous contractions, lower esophageal sphincter (LES) resting pressure, and history of smoking were correlated with the development of GERD after LSG, with the history of smoking and percentage of synchronous contractions as risk factors and LES resting pressure as a protective factor. The training set showed an area under the ROC curve (AUC) of the nomogram model of 0.847. The validation set showed an AUC of 0.761. The decision and clinical impact curves showed a high clinical value for the prediction model. Conclusion:The HREM results correlated with the development of GERD after LSG, with the percentage of synchronous contractions and LES resting pressure showing predictive value. Combined with the history of smoking, the predictive model showed a high confidence and clinical value.

Background and Aims: An imbalance in lipid metabolism is the main cause of NAFLD. While the pathogenesis of lipid accumulation mediated by extrahepatic regulators has been extensively studied, the intrahepatic regulators modulating lipid homeostasis remain unclear. Previous studies have shown that systemic administration of IL-22 protects against NAFLD; however, the role of IL-22/IL22RA1 signaling in modulating hepatic lipid metabolism remains uncertain. Approach and Results: This study shows that hepatic IL22RA1 is vital in hepatic lipid regulation. IL22RA1 is downregulated in palmitic acid-treated mouse primary hepatocytes, as well as in the livers of NAFLD model mice and patients. Hepatocyte-specific Il22ra1 knockout mice display diet-induced hepatic steatosis, insulin resistance, impaired glucose tolerance, increased inflammation, and fibrosis compared with flox/flox mice. This is attributed to increased lipogenesis mediated by the accumulation of hepatic oxysterols, particularly 3 beta-hydroxy-5-cholestenoic acid (3β HCA). Mechanistically, hepatic IL22RA1 deficiency facilitates 3β HCA deposition through the activating transcription factor 3/oxysterol 7 alpha-hydroxylase axis. Notably, 3β HCA facilitates lipogenesis in mouse primary hepatocytes and human liver organoids by activating liver X receptor-alpha signaling, but IL-22 treatment attenuates this effect. Additionally, restoring oxysterol 7 alpha-hydroxylase or silencing hepatic activating transcription factor 3 reduces both hepatic 3β HCA and lipid contents in hepatocyte-specific Il22ra1 knockout mice. Conclusions: These findings indicate that IL22RA1 plays a crucial role in maintaining hepatic lipid homeostasis in an activating transcription factor 3/oxysterol 7 alpha-hydroxylase-dependent manner and establish a link between 3β HCA and hepatic lipid homeostasis.

This study aimed to examine the correlation between preoperative body mass index (BMI) and adequate percentage of total weight loss (TWL

Non-alcoholic fatty liver disease (NAFLD) is a hepatic metabolic syndrome arising from lipid metabolic imbalance, with its prevalence increasing globally. In this study, we observed a significant up-regulation of interferon regulatory factor 8 (IRF8) in the liver of NAFLD model mice and patients. Overexpression of IRF8 induced lipid accumulation in the mouse primary hepatocytes. Mice with adeno-associated virus-mediated IRF8 overexpression exhibited hepatic steatosis due to up-regulated peroxisome proliferator-activated receptor γ (PPARγ) expression and increased fatty acid uptake and lipogenesis. In vitro, small interfering RNA-mediated IRF8 knockdown attenuated triglyceride accumulation by dampening PPARγ expression through transcriptional inhibition of brain and muscle ARNT-like 1. The PPARγ-specific antagonist GW9662 abolished the effect of IRF8 overexpression. Furthermore, adeno-associated virus-mediated IRF8 knockdown in the mouse liver markedly alleviated hepatic steatosis and obesity-related metabolic syndrome. These findings indicate that IRF8 plays a vital role in modulating hepatic lipid metabolism in a PPARγ-dependent manner and provide a previously unknown insight into NAFLD therapeutic strategies.

BACKGROUND:Bariatric surgery is an effective treatment for morbid obesity. However, a subset of individuals seeking bariatric surgery may exhibit a metabolically healthy obesity (MHO) phenotype, suggesting that they may not experience metabolic complications despite being overweight.OBJECTIVE:This study aimed to determine the prevalence and metabolic features of MHO in a population undergoing bariatric surgery.METHODS:A representative sample of 665 participants aged 14 or older who underwent bariatric surgery at our center from January 1, 2010 to January 1, 2020 was included in this cohort study. MHO was defined based on specific criteria, including blood pressure, waist-to-hip ratio, and absence of diabetes.RESULTS:Among the 665 participants, 80 individuals (12.0%) met the criteria for MHO. Female gender (P = .021) and younger age (P < .001) were associated with a higher likelihood of MHO. Smaller weight and BMI were observed in individuals with MHO. However, a considerable proportion of those with MHO exhibited other metabolic abnormalities, such as fatty liver (68.6%), hyperuricemia (55.3%), elevated lipid levels (58.7%), and abnormal lipoprotein levels (88%).CONCLUSION:Approximately 1 in 8 individuals referred for bariatric surgery displayed the phenotype of MHO. Despite being metabolically healthy based on certain criteria, a significant proportion of individuals with MHO still exhibited metabolic abnormalities, such as fatty liver, hyperuricemia, elevated lipid levels, and abnormal lipoprotein levels, highlighting the importance of thorough metabolic evaluation in this population.