Asim Shabbir

Introduction Total small bowel length (TSBL) varies substantially and may modify the physiological effect of intestinal bypass in metabolic and bariatric surgery (MBS). Fixed limb lengths do not account for individual variation and may contribute to suboptimal metabolic effect or excessive malabsorption. Methods The APMBSS 2026 TSBL Consensus Panel used a two-round modified Delphi process. Faculty rated 38 statements across seven domains on a 5-point Likert scale. Thirty-five statements reached consensus in Round 1 and were reaffirmed during faculty review at the congress without repeat scoring; only three were revised and revoted. Consensus required a median score of at least 4 and at least 80% of ratings at 4 or 5; strong consensus required at least 90% agreement. Results Forty-one analyzable responses from 15 countries/regions were included in Round 1. Thirty-five statements reached consensus. Three statements were discussed, revised, and revoted; one additional statement reached consensus. Overall, 36 of 38 statements achieved consensus (30 strong, 6 consensus). No final consensus was reached on routine TSBL measurement during standard sleeve gastrectomy or on diminishing metabolic returns beyond a 150-cm biliopancreatic limb in Roux-en-Y gastric bypass. Conclusion The consensus supports standardized measurement and documentation of TSBL and procedure-specific limb lengths in bypass-based procedures. It does not prescribe a universal limb-length formula, but establishes a framework for interpreting bypass physiology, balancing metabolic efficacy and nutritional safety, and evaluating TSBL-adjusted strategies in Asian registries and prospective studies. Key Points • TSBL provides an anatomical denominator for interpreting intestinal bypass. • Standardized TSBL and limb-length documentation was supported by the panel. • No universal TSBL-adjusted limb-length formula was supported. • The panel supported a minimum 300-cm common channel for SADI-S in Asian populations.

Obesity is a multi-faceted health problem impacting many aspects of health-related quality of life (HRQoL). Although the clinical effectiveness of metabolic bariatric surgery (MBS) is well-documented across different settings, qualitative studies on post-MBS HRQoL involving Asian patients remain scarce. This study aimed to qualitatively explore the HRQoL of people with obesity and post-MBS individuals within a Southeast Asian context. In-depth interviews were conducted with people with lived experience with obesity who were visiting a hospital weight management clinic in Singapore, using a semi-structured interview guide. A total of 25 study participants were recruited, including those who had and had not received MBS. Data was analysed using an inductive thematic approach. People with obesity reported substantial symptom burden and impaired physical functioning, issues with appearance and clothing, challenges with romantic relationship or physical intimacy, poor social well-being, and poor psychological and emotional well-being. Post-MBS patients also reported challenges, including loose skin and hair loss affecting appearance, as well as changes in eating habits and reduced food enjoyment. While Southeast Asians with obesity experience HRQoL deficits in similar domains as their counterparts in Western populations, their social well-being, particularly fear of becoming a burden to others, might be more affected. This study highlights the need for culturally sensitive HRQoL measures when assessing the pre- and post-operative outcomes of MBS in Singapore.

Background: Endoscopic assessment for the diagnosis of gastric cancer is limited by interoperator variability and lack of real-time capability. Recently, Raman spectroscopy-based artificial intelligence (AI) has been proposed as a solution to overcome these limitations. Objective: To compare the performance of the AI-enabled Raman spectroscopy with that of high-definition white light endoscopy (HD-WLE) for the risk classification of gastric lesions. Methods: This was a randomized double-arm feasibility proof-of-concept trial in which participants with suspected gastric neoplasia underwent endoscopic assessment using either the Raman spectroscopy-based AI (SPECTRA IMDx™) or HD-WLE performed by expert endoscopists. Identified lesions were classified in real time as having either low or high risk for neoplasia. Diagnostic outcomes were compared between the two groups using histopathology as the reference. Results: A total of 20 patients with 25 lesions were included in the study. SPECTRA, in real-time, performed at a statistically similar level to that of HD-WLE performed by expert endoscopists, achieving an overall sensitivity, specificity, and accuracy of 100%, 80%, and 89.0%, respectively, by patient; and 100%, 80%, and 92%, respectively, by lesion, while expert endoscopists using HD-WLE attained a sensitivity, specificity, and accuracy of 100%, 80%, and 90%, respectively, by patient; and 100%, 83.3%, and 91.7%, respectively, by lesion, in differentiating high-risk from low-risk gastric lesions. Conclusions: The SPECTRA’s comparable performance with that of HD-WLE suggests that it can potentially be a valuable adjunct for less experienced endoscopists to attain accurate and real-time diagnoses of gastric lesions. Larger-scale prospective randomized trials are recommended to validate these promising results further.

Background: Telesurgery has been made increasingly possible with the advancements in robotic surgical platforms and network connectivity. However, long-distance trans-national complex robotic surgeries such as the gastrectomy have yet to be attempted. Methods: Multiple trans-national network connections by Science Innovation Network (SINET), Japan Gigabit Network (JGN) and Arterial Research and Education Network in Asia-Pacific (ARENA-PAC) were established and tested by multiple surgeons in a dry box model. Surgeons’ perceptions of the different networks were recorded. Three robotic radical D2 gastrectomies in live porcine models were performed at a hospital in Toyoake, Japan by a surgical team in a hospital in Singapore approximately 5000km away using the hinotori^TM Surgical Robot System (Medicaroid Corporation, Kobe, Japan). Results: The live porcine robotic gastrectomies were all completed under 205 minutes with no intraoperative complications. From the different networks that were tested, the differences in latency ranged from 107-132ms and did not translate to any significant differences in surgeon timings and perceptions. Conclusions: Trans-national telesurgical radical D2 gastrectomy is feasible in a porcine model. There is no appreciable difference between surgeon performance and perception with network latencies of 107-132ms. Long-range telesurgery as clinical practice may become possible in the future.

Purpose of Review The approval of resmetirom brings great hope to patients with metabolic dysfunction-associated steatohepatitis (MASH). The purpose of this review is to explore its impact on the global health environment. The implementation of multidisciplinary management MASH is proposed. Recent Findings Resmetirom has benefits in the treatment of MASH, and its safety and effectiveness have been studied. The adverse events (AEs) need to be noticed. To improve patient outcomes, a multimodal approach with medication such as resmetirom, combined with metabolic and bariatric surgery (MBS) and lifestyle interventions can be conducted. Summary MASH, a liver disease linked with obesity, is a challenging global healthcare burden compounded by the absence of any approved pharmacotherapy. The recent conditional approval by the Food and Drug Administration (FDA) in the United States of resmetirom, an oral, liver-directed, thyroid hormone receptor beta-selective agonist, marks a significant milestone, offering a treatment option for adults with non-cirrhotic MASH and who have moderate to advanced liver fibrosis. This narrative review discusses the efficacy and safety of resmetirom and its role in the therapeutic landscape of MASH treatment. Despite the promising hepatoprotective effect of resmetirom on histological liver endpoints, its use need further research, particularly regarding ethnic differences, effectiveness and cost-effectiveness, production scalability, social acceptance and accessibility. In addition, integrating resmetirom with other multidisciplinary therapeutic approaches, including lifestyle changes and MBS, might further improve clinical liver-related and cardiometabolic outcomes of individuals with MASH. This review highlights the importance of a comprehensive treatment strategy, supporting continued innovation and collaborative research to refine treatment guidelines and consensus for managing MASH, thereby improving clinical patient outcomes in the growing global epidemic of MASH. Studies done to date have been relatively short and ongoing, the course of the disease is highly variable, the conditions of various patients vary, and given this complex clinical phenotype, it may take many years of clinical trials to show long-term benefits.

[This corrects the article DOI: 10.2196/46036.].

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Background: A plethora of weight management apps are available, but many individuals, especially those living with overweight and obesity, still struggle to achieve adequate weight loss. An emerging area in weight management is the support for one’s self-regulation over momentary eating impulses. Objective: This study aims to examine the feasibility and effectiveness of a novel artificial intelligence–assisted weight management app in improving eating behaviors in a Southeast Asian cohort. Methods: A single-group pretest-posttest study was conducted. Participants completed the 1-week run-in period of a 12-week app-based weight management program called the Eating Trigger-Response Inhibition Program (eTRIP). This self-monitoring system was built upon 3 main components, namely, (1) chatbot-based check-ins on eating lapse triggers, (2) food-based computer vision image recognition (system built based on local food items), and (3) automated time-based nudges and meal stopwatch. At every mealtime, participants were prompted to take a picture of their food items, which were identified by a computer vision image recognition technology, thereby triggering a set of chatbot-initiated questions on eating triggers such as who the users were eating with. Paired 2-sided t tests were used to compare the differences in the psychobehavioral constructs before and after the 7-day program, including overeating habits, snacking habits, consideration of future consequences, self-regulation of eating behaviors, anxiety, depression, and physical activity. Qualitative feedback were analyzed by content analysis according to 4 steps, namely, decontextualization, recontextualization, categorization, and compilation. Results: The mean age, self-reported BMI, and waist circumference of the participants were 31.25 (SD 9.98) years, 28.86 (SD 7.02) kg/m2, and 92.60 (SD 18.24) cm, respectively. There were significant improvements in all the 7 psychobehavioral constructs, except for anxiety. After adjusting for multiple comparisons, statistically significant improvements were found for overeating habits (mean –0.32, SD 1.16; P<.001), snacking habits (mean –0.22, SD 1.12; P<.002), self-regulation of eating behavior (mean 0.08, SD 0.49; P=.007), depression (mean –0.12, SD 0.74; P=.007), and physical activity (mean 1288.60, SD 3055.20 metabolic equivalent task-min/day; P<.001). Forty-one participants reported skipping at least 1 meal (ie, breakfast, lunch, or dinner), summing to 578 (67.1%) of the 862 meals skipped. Of the 230 participants, 80 (34.8%) provided textual feedback that indicated satisfactory user experience with eTRIP. Four themes emerged, namely, (1) becoming more mindful of self-monitoring, (2) personalized reminders with prompts and chatbot, (3) food logging with image recognition, and (4) engaging with a simple, easy, and appealing user interface. The attrition rate was 8.4% (21/251). Conclusions: eTRIP is a feasible and effective weight management program to be tested in a larger population for its effectiveness and sustainability as a personalized weight management program for people with overweight and obesity. Trial Registration: ClinicalTrials.gov NCT04833803; https://classic.clinicaltrials.gov/ct2/show/NCT04833803