Survival Analysis Using Surgeon Skill Metrics and Patient Factors to Predict Urinary Continence Recovery After Robot-assisted Radical Prostatectomy.

BACKGROUND: It has been shown that metrics recorded for instrument kinematics during robotic surgery can predict urinary continence outcomes. OBJECTIVE: To evaluate the contributions of patient and treatment factors, surgeon efficiency metrics, and surgeon technical skill scores, especially for vesicourethral anastomosis (VUA), to models predicting urinary continence recovery following robot-assisted radical prostatectomy (RARP). DESIGN, SETTING, AND PARTICIPANTS: Automated performance metrics (APMs; instrument kinematics and system events) and patient data were collected for RARPs performed from July 2016 to December 2017. Robotic Anastomosis Competency Evaluation (RACE) scores during VUA were manually evaluated. Training datasets included: (1) patient factors; (2) summarized APMs (reported over RARP steps); (3) detailed APMs (reported over suturing phases of VUA); and (4) technical skills (RACE). Feature selection was used to compress the dimensionality of the inputs. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The study outcome was urinary continence recovery, defined as use of 0 or 1 safety pads per day. Two predictive models (Cox proportional hazards [CoxPH] and deep learning survival analysis [DeepSurv]) were used. RESULTS AND LIMITATIONS: Of 115 patients undergoing RARP, 89 (77.4%) recovered their urinary continence and the median recovery time was 166 d (interquartile range [IQR] 82-337). VUAs were performed by 23 surgeons. The median RACE score was 28/30 (IQR 27-29). Among the individual datasets, technical skills (RACE) produced the best models (C index: CoxPH 0.695, DeepSurv: 0.708). Among summary APMs, posterior/anterior VUA yielded superior model performance over other RARP steps (C index 0.543-0.592). Among detailed APMs, metrics for needle driving yielded top-performing models (C index 0.614-0.655) over other suturing phases. DeepSurv models consistently outperformed CoxPH; both approaches performed best when provided with all the datasets. Limitations include feature selection, which may have excluded relevant information but prevented overfitting. CONCLUSIONS: Technical skills and "needle driving" APMs during VUA were most contributory. The best-performing model used synergistic data from all datasets. PATIENT SUMMARY: One of the steps in robot-assisted surgical removal of the prostate involves joining the bladder to the urethra. Detailed information on surgeon performance for this step improved the accuracy of predicting recovery of urinary continence among men undergoing this operation for prostate cancer.

Safety and feasibility of urological procedures in Jehovah's Witness patients.

OBJECTIVES: To describe the safety and feasibility of urological transfusion-free surgeries in Jehovah's Witness patients. METHODS: An institutional review board-approved, retrospective review of Jehovah's Witness patients who underwent urological transfusion-free surgeries between 2003 and 2019 was carried out. Surgeries were stratified into low, intermediate and high risk based on complexity, invasiveness and bleeding potential. Patient demographics, perioperative data and clinical outcomes are reported. RESULTS: A total of 161 Jehovah's Witness patients (median age 63.4 years) underwent 171 transfusion-free surgeries, including 57 (33.3%) in low-, 82 (47.9%) in intermediate- and 32 (18.8%) in high-risk categories. The mean estimated blood loss increased with risk category at 48 mL (range 10-50 mL), 150 mL (range 50-200 mL) and 388 mL (range 137-500 mL), respectively (P < 0.001). Implementing blood augmentation and conservation techniques increased with each risk category (3.5% vs 29% vs 69%, respectively; P < 0.001). Average length of stay increased concordantly at 1.6 days (range 0-12 days), 2.9 days (range 1-13 days) and 5.6 days (range 2-12 days), respectively (P ≤ 0.001). However, there was no increase in complication rates and readmission rates attributed to bleeding among the risk categories at 30 days (P = 0.9 and 0.4, respectively) and 90 days (P = 0.7 and 0.7, respectively). CONCLUSIONS: Transfusion free urological surgery can be safely carried out on Jehovah's Witness patients using contemporary perioperative optimization. Additionally, these techniques can be expanded for use in the general patient population to avoid short- and long-term consequences of perioperative blood transfusion.

Virtual Reality vs Dry Laboratory Models: Comparing Automated Performance Metrics and Cognitive Workload During Robotic Simulation Training.

Background: This study compares surgical performance during analogous vesico-urethral anastomosis (VUA) tasks in two robotic training environments, virtual reality (VR) and dry laboratory (DL), to investigate transferability of skill assessment across the two platforms. Utilizing computer-generated performance metrics and pupillary data, we evaluated the two environments to distinguish surgical expertise and ultimately whether performance in the VR simulation correlates with performance in live robotic surgery in the DL. Materials and Methods: Experts (≥300 cases) and trainees (<300 cases) performed analogous VUAs during VR and DL sessions on a da Vinci robotic console following an Institutional Review Board (IRB) approved protocol (HS-16-00318). Twenty-two metrics were generated in each environment (kinematic metrics, tissue metrics, and biometrics). The DL included 18 previously validated automated performance metrics (APMs) (kinematics and event metrics) captured by an Intuitive system data recorder. In both settings, Tobii Pro Glasses 2 recorded the task-evoked pupillary response (reported as Index of Cognitive Activity [ICA]) to indicate cognitive workload, analyzed by EyeTracking cognitive workload software. Pearson correlation, Mann-Whitney, and independent t-tests were used for the comparative analyses. Results: Our study included six experts (median caseload 1300 [interquartile range 400-3000]) and 11 trainees (25 [0-250]). A total of 8/9 metrics directly comparable between VR and DL showed significant positive correlation (r ≥ 0.554, p ≤ 0.032); 5/22 VR metrics distinguished expertise, including task time (p = 0.031), clutch usage (p = 0.040), unnecessary needle piercing (p = 0.026), and suspected injury to the endopelvic fascia (p = 0.040). This contrasts with 14/22 APMs in DL (p ≤ 0.038), including linear velocities of all three instruments (p ≤ 0.038) and dominant-hand instrument wrist articulation (p = 0.013). Trainees experienced higher cognitive workload (ICA) in both environments when compared with experts (p < 0.036). Conclusions: Most performance metrics between VR and DL exhibited moderate to strong correlations, showing transferability of skills across the platforms. Comparing training environments, APMs during DL tasks are better able to distinguish expertise than VR-generated metrics.