Implementation of a Comprehensive Protocol for Enhanced Recovery After Surgery (ERAS) in Kidney Transplant Recipients Improves Patient and Graft Outcomes.

Background: Enhanced recovery after surgery (ERAS) protocols have gained widespread acceptance as a means to enhance surgical outcomes. However, the intricate care required for kidney transplant recipients has not yet led to the establishment of a universally recognized and dependable ERAS protocol for kidney transplantation.

Objective: We devised a customized ERAS protocol to determine its effectiveness in improving surgical and postoperative outcomes among kidney transplant recipients.

Chronic Scrotal Content Pain: a Review of the Literature and Management Schemes.

Purpose Of Review: Chronic scrotal content pain (CSCP) is a complex condition with multiple etiologies that requires a thorough understanding of its pathophysiology, workup, and treatment options. We performed a comprehensive and contemporary review to augment our current understanding of CSCP.

Recent Findings: We discuss new advances in CSCP-specific pain questionnaires, modern studies of microscopic spermatic cord denervation and its variations, and novel techniques including electric nerve stimulation and cryoablation in addition to randomized control trials with significant negative findings.

A deep-learning model using automated performance metrics and clinical features to predict urinary continence recovery after robot-assisted radical prostatectomy.

Objectives: To predict urinary continence recovery after robot-assisted radical prostatectomy (RARP) using a deep learning (DL) model, which was then used to evaluate surgeon's historical patient outcomes.

Subjects And Methods: Robotic surgical automated performance metrics (APMs) during RARP, and patient clinicopathological and continence data were captured prospectively from 100 contemporary RARPs. We used a DL model (DeepSurv) to predict postoperative urinary continence.

Experts vs super-experts: differences in automated performance metrics and clinical outcomes for robot-assisted radical prostatectomy.

Objectives: To evaluate automated performance metrics (APMs) and clinical data of experts and super-experts for four cardinal steps of robot-assisted radical prostatectomy (RARP): bladder neck dissection; pedicle dissection; prostate apex dissection; and vesico-urethral anastomosis.

Subjects And Methods: We captured APMs (motion tracking and system events data) and synchronized surgical video during RARP. APMs were compared between two experience levels: experts (100-750 cases) and super-experts (2100-3500 cases).

Use of Automated Performance Metrics to Measure Surgeon Performance during Robotic Vesicourethral Anastomosis and Methodical Development of a Training Tutorial.

Purpose: We sought to develop and validate automated performance metrics to measure surgeon performance of vesicourethral anastomosis during robotic assisted radical prostatectomy. Furthermore, we sought to methodically develop a standardized training tutorial for robotic vesicourethral anastomosis.

Materials And Methods: We captured automated performance metrics for motion tracking and system events data, and synchronized surgical video during robotic assisted radical prostatectomy.

Crowdsourced versus expert evaluations of the vesico-urethral anastomosis in the robotic radical prostatectomy: is one superior at discriminating differences in automated performance metrics?

Crowdsourcing from the general population is an efficient, inexpensive method of surgical performance evaluation. In this study, we compared the discriminatory ability of experts and crowdsourced evaluators (the Crowd) to detect differences in robotic automated performance metrics (APMs). APMs (instrument motion tracking and events data directly from the robot system) of anterior vesico-urethral anastomoses (VUAs) of robotic radical prostatectomies were captured by the dVLogger (Intuitive Surgical).

Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes.

Purpose: Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP).

Materials And Methods: We trained three ML algorithms utilizing APMs directly from robot system data (training material) and hospital length of stay (LOS; training label) (≤2 days and >2 days) from 78 RARP cases, and selected the algorithm with the best performance.

Outpatient Laparoscopic Appendectomy: Feasible in a Public County Hospital?

Background: Outpatient laparoscopic appendectomy is being used increasingly as a treatment option for acute, uncomplicated appendicitis. This was a prospective validation study in a large, urban, public safety-net hospital.

Study Design: From 2014 to 2016, all patients undergoing laparoscopic appendectomy for acute, uncomplicated appendicitis were enrolled in a prospective observational trial.