Robotic-assisted minimally invasive esophagectomy (RAMIE) is increasingly used as an alternative to conventional minimally invasive esophagectomy (CMIE). However, many prior comparisons include mixed patient populations and variable neoadjuvant treatment strategies. Because neoadjuvant chemoradiotherapy (nCRT) can make esophagectomy technically more difficult, the relative performance of RAMIE in this specific setting remains uncertain. We performed a systematic review and meta-analysis using Nested Knowledge AutoLit to compare RAMIE and CMIE among patients undergoing esophagectomy after predominantly nCRT-based treatment. Eligible studies directly compared the two operative approaches and reported perioperative, surgical, or oncologic outcomes. Effect estimates were pooled with random-effects models. Odds ratios (ORs) were used for dichotomous outcomes, and mean differences (MDs) were used for continuous outcomes. Analyses were performed in R version 4.5.2 using the meta package. Risk of bias was assessed with ROBINS-I. Seven studies including 2,395 patients were analyzed; 609 patients underwent RAMIE and 1,786 underwent CMIE. Compared with CMIE, RAMIE was associated with lower estimated blood loss (MD −26.44 mL, 95
Postoperative pancreatic fistula (POPF) is the most serious complication of pancreaticoduodenectomy (PD); established risk tools require intraoperative variables. We assessed the diagnostic accuracy of preoperative endoscopic ultrasound (EUS) strain elastography for intraoperative pancreatic texture and, exploratorily, predictors of clinically relevant POPF (CR-POPF). Prospective single-centre study of 100 consecutive patients undergoing elective PD. The index test was preoperative EUS strain ratio (SR), threshold ≤ 2.5 prespecified before enrolment; the reference standard was intraoperative texture recorded independently by two blinded surgeons, with neck-margin fibrosis grade as secondary reference. CR-POPF (ISGPS 2016 Grade B/C) was adjudicated blind to EUS. Accuracy is reported with Wilson 95
Artificial intelligence systems for intraoperative surgical guidance are approaching clinical deployment, yet no study has quantified automation bias (defined as the tendency to over-rely on automated recommendations) in the context of surgical decision-making. As these systems enter operative workflows, the surgeon’s ability to recognize and override incorrect AI guidance becomes a critical safety requirement. To measure the extent to which surgeons modify incision plans after exposure to AI-labeled visual guidance and to determine the rate at which incorrect AI suggestions are accepted. A two-phase controlled experiment was conducted among 19 surgeons (10 residents, 2 fellows, 7 attendings). Participants drew incision lines on 20 static frames from robotic cholecystectomy videos, first without guidance (Phase 01) and then with a mock AI overlay (Phase 02). Overlays were either correct (derived from expert consensus) or deliberately incorrect (shifted toward unsafe anatomy) at an approximately 70:30 ratio. No actual AI model was used. The primary outcome was mean perpendicular distance (MPD) between Phase 01 and Phase 02 lines. Secondary outcomes included AI-corridor adherence, over-reliance and under-reliance rates, behavioral accuracy, and confidence shift. Across 231 paired observations, MPD did not differ significantly between correct (75.5 pixels; SD, 33.4) and incorrect (71.1 pixels; SD, 31.7) overlay conditions (P = .35). Directional analysis revealed that surgeons accepted incorrect AI suggestions in 60.6
Although appendectomy is widely accepted as the standard of treatment in children with complex appendicitis without appendiceal mass and/or abscess, discussion remains on the optimal surgical approach. In this group, we aimed to compare outcomes of laparoscopic appendectomy (LA) with open appendectomy (OA). A multicentre, prospective cohort study was conducted in children (< 18 years old) with preoperative suspicion of complex appendicitis without appendiceal mass and/or abscess. The primary outcome was the proportion of participants experiencing postoperative complications within 3 months. Secondary outcomes included hospitalization, unscheduled healthcare visits, disability days, parental work absence, health-related quality of life (Hr-QoL), patient satisfaction, and healthcare costs. Propensity analysis was performed to adjust for baseline differences and selection bias. In total, 1308 children were enrolled across 38 Dutch hospitals, nine were excluded from analysis leaving a total of 1299. Of these, 989 (76.1
Robotic-assisted surgery (RAS) has transformed modern surgical practice and introduced unique challenges to teamwork and communication. While prior research has examined human factors integration, barriers, and interventions in RAS, we explore operating room (OR) professionals’ experiences of teamwork across all operative phases. This study aims to give voice to OR professionals actively performing RAS and to understand what they perceive as effective and ineffective teamwork in their experiences. Using an interpretivist paradigm, we conducted critical incident-based, semi-structured interviews with 21 OR professionals across multiple roles and specialties at two teaching hospitals using a closed-console RAS system. We analyzed the data using reflexive thematic analysis and employing an inductive, semantic coding strategy in which the content of the data was coded as explicitly described by the participants. We organized the results across three operative phases. In the pre-operative phase, deliberate planning, including team briefings, equipment checks, procedural steps, and patient and robot positioning, was reported as more important for teamwork in RAS. During the intraoperative phase, effective and ineffective teamwork was, respectively, described as the presence or absence of explicit verbal communication (closed-loop communication, real-time narration, anticipation in tandem with verbal prompts), team reflexivity, centralized coordination through a bedside assistant, psychological safety, and shared mental models. In the post-operative phase, participants linked teamwork quality to patient safety and operative efficiency in a cascading effect. Teamwork in RAS requires a more deliberate, structured team approach than in open or laparoscopic surgery. We provide best practices for effective teamwork and pitfalls to avoid in RAS. Targeted training emphasizing teamwork and communication may enhance team effectiveness and patient safety in robotic surgical environments.
