Perioperative and extended outcomes of patients undergoing parastomal hernia repair following cystectomy and ileal conduit.

Purpose: To report perioperative and long-term postoperative outcomes of cystectomy patients with ileal conduit (IC) urinary diversion undergoing parastomal hernia (PSH) repair.

Method: We reviewed patients who underwent cystectomy and IC diversion between 2003 and 2022 in our center. Baseline variables, including surgical approach of PSH repair and repair technique, were captured.

Competency in Robotic Surgery: Standard Setting for Robotic Suturing Using Objective Assessment and Expert Evaluation.

Objective: Surgical skill assessment tools such as the End-to-End Assessment of Suturing Expertise (EASE) can differentiate a surgeon's experience level. In this simulation-based study, we define a competency benchmark for intraoperative robotic suturing using EASE as a validated measure of performance.

Design: Participants conducted a dry-lab vesicourethral anastomosis (VUA) exercise.

Artificial Intelligence-Based Video Feedback to Improve Novice Performance on Robotic Suturing Skills: A Pilot Study.

Automated skills assessment can provide surgical trainees with objective, personalized feedback during training. Here, we measure the efficacy of artificial intelligence (AI)-based feedback on a robotic suturing task. Forty-two participants with no robotic surgical experience were randomized to a control or feedback group and video-recorded while completing two rounds (R1 and R2) of suturing tasks on a da Vinci surgical robot.

A vision transformer for decoding surgeon activity from surgical videos.

The intraoperative activity of a surgeon has substantial impact on postoperative outcomes. However, for most surgical procedures, the details of intraoperative surgical actions, which can vary widely, are not well understood. Here we report a machine learning system leveraging a vision transformer and supervised contrastive learning for the decoding of elements of intraoperative surgical activity from videos commonly collected during robotic surgeries.

Human visual explanations mitigate bias in AI-based assessment of surgeon skills.

Artificial intelligence (AI) systems can now reliably assess surgeon skills through videos of intraoperative surgical activity. With such systems informing future high-stakes decisions such as whether to credential surgeons and grant them the privilege to operate on patients, it is critical that they treat all surgeons fairly. However, it remains an open question whether surgical AI systems exhibit bias against surgeon sub-cohorts, and, if so, whether such bias can be mitigated.

A multi-institutional study using artificial intelligence to provide reliable and fair feedback to surgeons.

Background: Surgeons who receive reliable feedback on their performance quickly master the skills necessary for surgery. Such performance-based feedback can be provided by a recently-developed artificial intelligence (AI) system that assesses a surgeon's skills based on a surgical video while simultaneously highlighting aspects of the video most pertinent to the assessment. However, it remains an open question whether these highlights, or explanations, are equally reliable for all surgeons.

An Assessment Tool to Provide Targeted Feedback to Robotic Surgical Trainees: Development and Validation of the End-To-End Assessment of Suturing Expertise (EASE).

Purpose: To create a suturing skills assessment tool that comprehensively defines criteria around relevant sub-skills of suturing and to confirm its validity.

Materials And Methods: 5 expert surgeons and an educational psychologist participated in a cognitive task analysis (CTA) to deconstruct robotic suturing into an exhaustive list of technical skill domains and sub-skill descriptions. Using the Delphi methodology, each CTA element was systematically reviewed by a multi-institutional panel of 16 surgical educators and implemented in the final product when content validity index (CVI) reached ≥0.

Tranexamic Acid and Prothrombotic Complications Following Total Hip and Total Knee Arthroplasty: A Population-Wide Safety Analysis Accounting for Surgeon Selection Bias.

Background: Tranexamic acid (TXA) utilization during total joint arthroplasty (TJA) has become ubiquitous. However, concerns remain regarding the risk of thrombotic complications. The goal of this study was to examine the risk of prothrombotic complications in patients who received TXA during total knee (TKA) and total hip arthroplasty (THA).

Association of Suturing Technical Skill Assessment Scores Between Virtual Reality Simulation and Live Surgery.

Robotic surgical performance, in particular suturing, has been linked to postoperative clinical outcomes. Before attempting live surgery, virtual reality (VR) simulators afford opportunities for training surgeons to learn fundamental technical skills. Herein, we evaluate the association of suturing technical skill assessments between VR simulation and live surgery, and functional clinical outcomes.

Tailored Feedback Based on Clinically Relevant Performance Metrics Expedites the Acquisition of Robotic Suturing Skills-An Unblinded Pilot Randomized Controlled Trial.

Purpose: Previously, we identified 8 objective suturing performance metrics highly predictive of urinary continence recovery after robotic-assisted radical prostatectomy. Here, we aimed to test the feasibility of providing tailored feedback based upon these clinically relevant metrics and explore the impact on the acquisition of robotic suturing skills.

Materials And Methods: Training surgeons were recruited and randomized to a feedback group or a control group.

Technical Skill Impacts the Success of Sequential Robotic Suturing Substeps.

Robotic surgical performance, in particular suturing, has been associated with postoperative clinical outcomes. Suturing can be deconstructed into components (, , , and ) allowing for the provision of more specific feedback while teaching suturing and more precision when evaluating suturing technical skill and prediction of clinical outcomes. This study evaluates if the technical skill required for particular substeps of the suturing process is associated with the execution of subsequent substeps in terms of technical skill, accuracy, and efficiency.