The nutritional status of hospitalised patients is often at risk or compromised and predisposed to further deterioration after discharge, leading to poor clinical outcomes, high healthcare costs, and poor quality of life. This paper aims to provide evidence-based best-practice recommendations to address this, supported by a national survey of healthcare professionals in Singapore and reviewed by a multidisciplinary expert panel under the Sarcopenia Interest Group of Society of Parenteral and Enteral Nutrition Singapore (SingSPEN). We advocate screening all patients with a validated tool which includes a disease activity/burden component, an easily accessible dietitian referral pathway for patients at risk of malnutrition, and an individualised nutrition care plan formulated and delivered using a multidisciplinary team approach for patients at risk or with malnutrition. A comprehensive team would include not only dietitians but also physicians, nurses, physiotherapists, speech therapists, and medical social workers working together towards a common goal. Information on why nutrition is important for good health and how it can be achieved should also be provided to all patients and their caregivers before and after hospital discharge. With the above recommendations, we seek to improve upon the current nutrition care processes at discharge for healthcare institutions in Singapore.

Background: Multimodal prehabilitation programs, which may incorporate nutritional supplementation and exercise, have been developed to combat sarcopenia in surgical patients to enhance post-operative outcomes. However, the optimal regime remains unknown. The use of beta-hydroxy beta-methylbutyrate (HMB) has beneficial effects on muscle mass and strength. However, its effect on muscle quality in the perioperative setting has yet to be established. This study aims to explore the impact of a multimodal prehabilitation program using a bundle of care that includes high-protein oral nutritional supplementation (HP ONS) with HMB and resistance exercise on muscle quality and functional outcomes in sarcopenic surgical patients. Methods: Sarcopenic adult patients undergoing elective major gastrointestinal surgeries were recruited for this pilot interventional cohort study. They were enrolled in a 2–4-week multimodal prehabilitation program comprising resistance exercise, nutritional supplementation, vitamin supplementation, comorbid optimization and smoking cessation. Participants were provided three units of HP ONS with HMB per day pre-operatively. The primary outcome was changes in intramuscular adipose tissue (IMAT) as a proxy of muscle quality, assessed using Artificial Intelligence (AI)-aided ultrasonography. Secondary outcomes include changes in anthropometric measurements and functional characteristics. Outcomes were measured before prehabilitation, after prehabilitation and 1 month post-operatively. Results: A total of 36 sarcopenic patients, with a median age of 71.5 years, were included in this study. There was an increase in the IMAT index after two weeks of prehabilitation (p = 0.032) to 1 month after surgery (p = 0.028). Among functional parameters, improvement was observed in gait speed (p = 0.01) after two weeks of prehabilitation, which returned to baseline post-operatively. The median length of hospital stay was 7 (range: 2–75) days. Conclusions: The increase in the IMAT index in a sarcopenic surgical cohort undergoing prehabilitation may be due to altered muscle metabolism in elderly sarcopenic patients. A prehabilitation regime in sarcopenic patients incorporating HP ONS with HMB and resistance exercise is feasible and is associated with increased gait speed.

The development of deep learning systems in artificial intelligence (AI) has enabled advances in endoscopy, and AI-aided colonoscopy has recently been ushered into clinical practice as a clinical decision-support tool. This has enabled real-time AI-aided detection of polyps with a higher sensitivity than the average endoscopist, and evidence to support its use has been promising thus far. This review article provides a summary of currently published data relating to AI-aided colonoscopy, discusses current clinical applications, and introduces ongoing research directions. We also explore endoscopists’ perceptions and attitudes toward the use of this technology, and discuss factors influencing its uptake in clinical practice.