Artificial Intelligence in Surgery: The Future is Now.

Background Clinical Artificial intelligence (AI) has reached a critical inflection point. Advances in algorithmic science and increased understanding of operational considerations in AI deployment are opening the door to widespread clinical pathway transformation. For surgery in particular, the application of machine learning algorithms in fields such as computer vision and operative robotics are poised to radically change how we screen, diagnose, risk-stratify, treat and follow-up patients, in both pre- and post-operative stages, and within operating theatres. Summary In this paper, we summarise the current landscape of existing and emerging integrations within complex surgical care pathways. We investigate effective methods for practical use of AI throughout the patient pathway, from early screening and accurate diagnosis to intraoperative robotics, post-operative monitoring and follow-up. Horizon scanning of AI technologies in surgery is used to identify novel innovations that can enhance surgical practice today, with potential for paradigm shifts across core domains of surgical practice in the future. Any AI-driven future must be built on responsible and ethical usage, reinforced by effective oversight of data governance, and of risks to patient safety in deployment. Implementation is additionally bound to considerations of usability and pathway feasibility, and the need for robust healthcare technology assessment and evidence generation. While these factors are traditionally seen as barriers to translating AI into practice, we discuss how holistic implementation practices can create a solid foundation for scaling AI across pathways. Key Messages The next decade will see rapid translation of experimental development into real-world impact. AI will require evolution of work practices, but will also enhance patient safety, enhance surgical quality outcomes, and provide significant value for surgeons and health systems. Surgical practice has always sat on a bedrock of technological innovation. For those that follow this tradition, the future of AI in surgery starts now.

Weight loss specific to indication, remission of diabetes, and short-term complications after sleeve gastrectomy conversion to Roux-en-Y gastric bypass: a systematic review and meta-analysis.

Laparoscopic sleeve gastrectomy (SG) is the most frequently performed bariatric procedure worldwide. Long-term complications such as insufficient weight loss (IWL) and gastroesophageal reflux disease (GERD) may necessitate SG conversion to Roux-en-Y gastric bypass (RYGB). The aim of this review was to determine the indication-specific weight loss and diabetes remission after SG conversion to RYGB (STOBY). Our objective was to extract all available published data on indication for conversion, weight loss, remission of diabetes, and short-term complications after STOBY. A systematic literature search was conducted to identify studies reporting outcomes following STOBY. A random effects model was used for meta-analysis. The search identified 44 relevant studies. Overall short-term (12-mo) excess weight loss (EWL) was 54.6% (95% confidence interval [CI], 46%-63%) in 23 studies (n = 712) and total weight loss (TWL) was 19.9% (95% CI, 14%-25%) in 21 studies (n = 740). For IWL, short-term (12-mo) pooled weight loss outcomes were 53.9% EWL (95% CI, 48%-59%) in 14 studies (n = 295) and 22.7% TWL (95% CI, 17%-28%) in 12 studies (n = 219), and medium-term (2-5 yr) outcomes were 45.8% EWL (95% CI, 38%-53%) in 7 studies (n = 154) and 20.6% TWL (95% CI, 15%-26%) in 9 studies (n = 206). Overall diabetes remission was 53% (95% CI, 33%-72%), and the perioperative complication rate was 8.2% (95% CI, 7.6%-8.7%). Revisional SG conversion to RYGB for IWL can achieve good weight loss outcomes and diabetes remission.

An Innovative Personalised Management Program for Older Adults with Parkinson's Disease: New Concepts and Future Directions.

INTRODUCTION: Parkinson's disease is a heterogeneous clinical syndrome. Parkinson's disease in older persons presents with a diverse array of clinical manifestations leading to unique care needs. This raises the need for the healthcare community to proactively address the care needs of older persons with Parkinson's disease. Though it is tempting to categorise different phenotypes of Parkinson's disease, a strong evidence based for the same is lacking. There is considerable literature describing the varying clinical manifestations in old age. This article aims to review the literature looking for strategies in personalising the management of an older person with Parkinson's disease.