Krueger, Alexander

BACKGROUND: The creation of operative reports is a tedious documentation task that increases administrative burden, which is a potential driver of burnout. Additionally, operative reports are inherently subjective and may contain inaccuracies and incomplete information. Recent advances in artificial intelligence (AI) technology have enabled computer vision systems to accurately detect operative steps on surgical video. We aim to develop a platform for the automated creation of video-based AI surgical operative reports in robotic-assisted radical prostatectomy. STUDY DESIGN: An AI computer vision algorithm was used to automatically detect surgical steps. Each step detected on video was mapped to prespecified text, which was then compiled into a narrative AI operative report. The accuracy of the AI operative reports was compared with operative reports written by surgeons, using expert review of raw surgical video footage as the ground truth. RESULTS: A total of 158 cases from a tertiary referral center were included. In surgeon operative reports, 84 cases (53.2%) had at least 1 discrepancy between the operative report and surgical video. Of these, 43 cases (27.2%) had a clinically significant discrepancy based on expert video review. In AI operative reports, 46 cases (29.1%) had at least 1 discrepancy between the operative report and surgical video. Of these, 20 cases (12.7%) had a clinically significant discrepancy. Overall accuracy was higher for AI operative reports compared with surgeon operative reports (87.3% vs 72.8%, p = 0.001). CONCLUSIONS: Operative reports created by AI achieved higher accuracy than those written by surgeons. To our knowledge, this is the first report of automated video-based AI surgical documentation. Future studies are warranted to explore the potential for this novel tool to reduce documentation burden, improve operative report accuracy, promote surgical transparency, and decrease subjectivity in surgical documentation.

Metabolic syndrome (MetS) is associated with low-grade inflammation, which can be exacerbated by renal artery stenosis (RAS) and renovascular hypertension, potentially worsening outcomes through pro-inflammatory cytokines. This study investigated whether mesenchymal stem/stromal cells (MSCs) could reduce fat inflammation in pigs with MetS and RAS. Twenty-four pigs were divided into Lean (control), MetS, MetS + RAS, and MetS + RAS + MSCs. In the MSC-treated group, autologous adipose-derived MSCs (107 cells) were injected into the renal artery six weeks after RAS induction. After four weeks, fat volumes and inflammatory markers were assessed. MSC treatment reduced levels of pro-inflammatory cytokines (MCP-1, TNF-a, IL-6) in the renal vein blood and in perirenal fat. The MSCs also decreased fat fibrosis, restored adipocyte size, and altered adipogenesis-related gene expression, particularly in the perirenal fat. These effects were less pronounced in subcutaneous fat. The MSC therapy attenuated fat inflammation and improved metabolic outcomes in pigs with MetS + RAS, suggesting that adipose-derived MSCs may offer a promising therapeutic approach for metabolic disorders.