Cognitive load in tele-robotic surgery: a comparison of eye tracker designs.

PURPOSE: Eye gaze tracking and pupillometry are evolving areas within the field of tele-robotic surgery, particularly in the context of estimating cognitive load (CL). However, this is a recent field, and current solutions for gaze and pupil tracking in robotic surgery require assessment. Considering the necessity of stable pupillometry signals for reliable cognitive load estimation, we compare the accuracy of three eye trackers, including head and console-mounted designs. METHODS: We conducted a user study with the da Vinci Research Kit (dVRK), to compare the three designs. We collected eye tracking and dVRK video data while participants observed nine markers distributed over the dVRK screen. We compute and analyze pupil detection stability and gaze prediction accuracy for the three designs. RESULTS: Head-worn devices present better stability and accuracy of gaze prediction and pupil detection compared to console-mounted systems. Tracking stability along the field of view varies between trackers, with gaze predictions detected at invalid zones of the image with high confidence. CONCLUSION: While head-worn solutions show benefits in confidence and stability, our results demonstrate the need to improve eye tacker performance regarding pupil detection, stability, and gaze accuracy in tele-robotic scenarios.

Cognitive effort detection for tele-robotic surgery via personalized pupil response modeling.

PURPOSE: Gaze tracking and pupillometry are established proxies for cognitive load, giving insights into a user's mental effort. In tele-robotic surgery, knowing a user's cognitive load can inspire novel human-machine interaction designs, fostering contextual surgical assistance systems and personalized training programs. While pupillometry-based methods for estimating cognitive effort have been proposed, their application in surgery is limited by the pupil's sensitivity to brightness changes, which can mask pupil's response to cognitive load. Thus, methods considering pupil and brightness conditions are essential for detecting cognitive effort in unconstrained scenarios. METHODS: To contend with this challenge, we introduce a personalized pupil response model integrating pupil and brightness-based features. Discrepancies between predicted and measured pupil diameter indicate dilations due to non-brightness-related sources, i.e., cognitive effort. Combined with gaze entropy, it can detect cognitive load using a random forest classifier. To test our model, we perform a user study with the da Vinci Research Kit, where 17 users perform pick-and-place tasks in addition to auditory tasks known to generate cognitive effort responses. RESULTS: We compare our method to two baselines (BCPD and CPD), demonstrating favorable performance in varying brightness conditions. Our method achieves an average true positive rate of 0.78, outperforming the baselines (0.57 and 0.64). CONCLUSION: We present a personalized brightness-aware model for cognitive effort detection able to operate under unconstrained brightness conditions, comparing favorably to competing approaches, contributing to the advancement of cognitive effort detection in tele-robotic surgery. Future work will consider alternative learning strategies, handling the difficult positive-unlabeled scenario in user studies, where only some positive and no negative events are reliably known.

Towards navigation in endoscopic kidney surgery based on preoperative imaging.

Endoscopic renal surgeries have high re-operation rates, particularly for lower volume surgeons. Due to the limited field and depth of view of current endoscopes, mentally mapping preoperative computed tomography (CT) images of patient anatomy to the surgical field is challenging. The inability to completely navigate the intrarenal collecting system leads to missed kidney stones and tumors, subsequently raising recurrence rates. A guidance system is proposed to estimate the endoscope positions within the CT to reduce re-operation rates. A Structure from Motion algorithm is used to reconstruct the kidney collecting system from the endoscope videos. In addition, the kidney collecting system is segmented from CT scans using 3D U-Net to create a 3D model. The two collecting system representations can then be registered to provide information on the relative endoscope position. Correct reconstruction and localization of intrarenal anatomy and endoscope position is demonstrated. Furthermore, a 3D map is created supported by the RGB endoscope images to reduce the burden of mental mapping during surgery. The proposed reconstruction pipeline has been validated for guidance. It can reduce the mental burden for surgeons and is a step towards the long-term goal of reducing re-operation rates in kidney stone surgery.

ASSIST-U: A system for segmentation and image style transfer for ureteroscopy.

Kidney stones require surgical removal when they grow too large to be broken up externally or to pass on their own. Upper tract urothelial carcinoma is also sometimes treated endoscopically in a similar procedure. These surgeries are difficult, particularly for trainees who often miss tumours, stones or stone fragments, requiring re-operation. Furthermore, there are no patient-specific simulators to facilitate training or standardized visualization tools for ureteroscopy despite its high prevalence. Here a system ASSIST-U is proposed to create realistic ureteroscopy images and videos solely using preoperative computerized tomography (CT) images to address these unmet needs. A 3D UNet model is trained to automatically segment CT images and construct 3D surfaces. These surfaces are then skeletonized for rendering. Finally, a style transfer model is trained using contrastive unpaired translation (CUT) to synthesize realistic ureteroscopy images. Cross validation on the CT segmentation model achieved a Dice score of 0.853 ± 0.084. CUT style transfer produced visually plausible images; the kernel inception distance to real ureteroscopy images was reduced from 0.198 (rendered) to 0.089 (synthesized). The entire pipeline from CT to synthesized ureteroscopy is also qualitatively demonstrated. The proposed ASSIST-U system shows promise for aiding surgeons in the visualization of kidney ureteroscopy.

Intraoperative gaze guidance with mixed reality.

Efficient communication and collaboration are essential in the operating room for successful and safe surgery. While many technologies are improving various aspects of surgery, communication between attending surgeons, residents, and surgical teams is still limited to verbal interactions that are prone to misunderstandings. Novel modes of communication can increase speed and accuracy, and transform operating rooms. A mixed reality (MR) based gaze sharing application on Microsoft HoloLens 2 headset that can help expert surgeons indicate specific regions, communicate with decreased verbal effort, and guide novices throughout an operation is presented. The utility of the application is tested with a user study of endoscopic kidney stone localization completed by urology experts and novice surgeons. Improvement is observed in the NASA task load index surveys (up to 25.23%), in the success rate of the task (6.98% increase in localized stone percentage), and in gaze analyses (up to 31.99%). The proposed application shows promise in both operating room applications and surgical training tasks.

Development of an augmented reality guidance system for head and neck cancer resection.

The use of head-mounted augmented reality (AR) for surgeries has grown rapidly in recent years. AR aids in intraoperative surgical navigation through overlaying three-dimensional (3D) holographic reconstructions of medical data. However, performing AR surgeries on complex areas such as the head and neck region poses challenges in terms of accuracy and speed. This study explores the feasibility of an AR guidance system for resections of positive tumour margins in a cadaveric specimen. The authors present an intraoperative solution that enables surgeons to upload and visualize holographic reconstructions of resected cadaver tissues. The solution involves using a 3D scanner to capture detailed scans of the resected tissue, which are subsequently uploaded into our software. The software converts the scans of resected tissues into specimen holograms that are viewable through a head-mounted AR display. By re-aligning these holograms with cadavers with gestures or voice commands, surgeons can navigate the head and neck tumour site. This workflow can run concurrently with frozen section analysis. On average, the authors achieve an uploading time of 2.98 min, visualization time of 1.05 min, and re-alignment time of 4.39 min, compared to the 20 to 30 min typical for frozen section analysis. The authors achieve a mean re-alignment error of 3.1 mm. The authors' software provides a foundation for new research and product development for using AR to navigate complex 3D anatomy in surgery.

Eye gaze metrics for skill assessment and feedback in kidney stone surgery.

PURPOSE: Surgical skill assessment is essential for safe operations. In endoscopic kidney stone surgery, surgeons must perform a highly skill-dependent mental mapping from the pre-operative scan to the intraoperative endoscope image. Poor mental mapping can lead to incomplete exploration of the kidney and high reoperation rates. Yet there are few objective ways to evaluate competency. We propose to use unobtrusive eye-gaze measurements in the task space to evaluate skill and provide feedback. METHODS: We capture the surgeons' eye gaze on the surgical monitor with the Microsoft Hololens 2. To enable stable and accurate gaze detection, we develop a calibration algorithm to refine the eye tracking of the Hololens. In addition, we use a QR code to locate the eye gaze on the surgical monitor. We then run a user study with three expert and three novice surgeons. Each surgeon is tasked to locate three needles representing kidney stones in three different kidney phantoms. RESULTS: We find that experts have more focused gaze patterns. They complete the task faster, have smaller total gaze area, and the gaze fewer times outside the area of interest. While fixation to non-fixation ratio did not show significant difference in our findings, tracking the ratio over time shows different patterns between novices and experts. CONCLUSION: We show that a non-negligible difference holds between novice and expert surgeons' gaze metrics in kidney stone identification in phantoms. Expert surgeons demonstrate more targeted gaze throughout a trial, indicating their higher level of proficiency. To improve the skill acquisition process for novice surgeons, we suggest providing sub-task specific feedback. This approach presents an objective and non-invasive method to assess surgical competence.

Augmented-Reality Surgery to Guide Head and Neck Cancer Re-resection: A Feasibility and Accuracy Study.

BACKGROUND: Given the complex three-dimensional (3D) anatomy of head and neck cancer specimens, head and neck surgeons often have difficulty relocating the site of an initial positive margin to perform re-resection. This cadaveric study aimed to determine the feasibility and accuracy of augmented reality surgery to guide head and neck cancer re-resections. METHODS: This study investigated three cadaveric specimens. The head and neck resection specimen was 3D scanned and exported to the HoloLens augmented reality environment. The surgeon manually aligned the 3D specimen hologram into the resection bed. Accuracy of manual alignment and time intervals throughout the protocol were recorded. RESULTS: The 20 head and neck cancer resections performed in this study included 13 cutaneous and 7 oral cavity resections. The mean relocation error was 4 mm (range, 1-15 mm) with a standard deviation of 3.9 mm. The mean overall protocol time, from the start of 3D scanning to alignment into the resection bed, was 25.3 ± 8.9 min (range, 13.2-43.2 min). Relocation error did not differ significantly when stratified by greatest dimension of the specimen. The mean relocation error of complex oral cavity composite specimens (maxillectomy and mandibulectomy) differed significantly from that of all the other specimen types (10.7 vs 2.8; p < 0.01). CONCLUSIONS: This cadaveric study demonstrated the feasibility and accuracy of augmented reality to guide re-resection of initial positive margins in head and neck cancer surgery.

Rethinking causality-driven robot tool segmentation with temporal constraints.

PURPOSE: Vision-based robot tool segmentation plays a fundamental role in surgical robots perception and downstream tasks. CaRTS, based on a complementary causal model, has shown promising performance in unseen counterfactual surgical environments in the presence of smoke, blood, etc. However, CaRTS requires over 30 iterations of optimization to converge for a single image due to limited observability. METHOD: To address the above limitations, we take temporal relation into consideration and propose a temporal causal model for robot tool segmentation on video sequences. We design an architecture named Temporally Constrained CaRTS (TC-CaRTS). TC-CaRTS has three novel modules to complement CaRTS-temporal optimization pipeline, kinematics correction network, and spatial-temporal regularization. RESULTS: Experiment results show that TC-CaRTS requires fewer iterations to achieve the same or better performance as CaRTS on different domains. All three modules are proven to be effective. CONCLUSION: We propose TC-CaRTS, which takes advantage of temporal constraints as additional observability. We show that TC-CaRTS outperforms prior work in the robot tool segmentation task with improved convergence speed on test datasets from different domains.

Coexpression of TLR9 and VEGF-C is associated with lymphatic metastasis in prostate cancer.

Prostate cancer (PCa) is one of the most frequent cancers in men, and its biomolecular targets have been extensively studied. This study aimed to analyze the expression of toll-like receptor 9 (TLR9) and vascular endothelial growth factor C (VEGF-C) and the clinical value of the coexpression of TLR9 and VEGF-C in PCa. We retrospectively evaluated 55 patients with clinically localized, intermediate-risk, or high-risk PCa who underwent laparoscopic radical prostatectomy (LRP) and extended pelvic lymph node dissection (ePLND) without neoadjuvant hormonal therapy at a single institution from June 2013 to December 2016. In all 55 patients, the median number of lymph nodes (LNs) resected was 23 (range: 18-31), and a total of 1269 LNs were removed, of which 78 LNs were positive. Seventeen patients had positive LNs, with a positive rate of 30.9%. In addition, the immunohistochemical results in the above patients revealed that high TLR9 expression was correlated with higher Gleason score (GS) (P = 0.049), increased LN metastasis (P = 0.004), and more perineural invasion (PNI) (P = 0.033). Moreover, VEGF-C expression was associated with GS (P = 0.040), pathological stage (pT stage) (P = 0.022), LN metastasis (P = 0.003), and PNI (P = 0.001). Furthermore, a significant positive correlation between TLR9 and VEGF-C was found (P < 0.001), and the TLR9/VEGF-C phenotype was associated with LN metastasis (P = 0.047). Collectively, we propose that TLR9 stimulation may promote LN metastasis in PCa cells through the upregulation of VEGF-C expression, thereby affecting the prognosis of PCa patients. Therefore, these markers may serve as valuable targets for the treatment of PCa.

Comparing intravenous peramivir with oral oseltamivir for patients with influenza: a meta-analysis of randomized controlled trials.

BACKGROUND: The study was to compare the efficacy between IV peramivir and oral oseltamivir treatments in patients with influenza. METHODS: The PubMed, EMBASE, Scopus, ClinicalTrials.gov, and Cochrane Library databases were searched for studies published before January 2020. RESULTS: The meta-analysis was conducted to calculate the pooled effect size by using a random-effects model. Seven randomized controlled trials (RCTs) including 1,138 patients were reviewed. The incidence of total complications revealed no significant difference between 600 mg IV peramivir (P600) and 75 mg oral oseltamivir (O75) treatments (2.8% vs. 4.1%; risk ratio [RR] = 0.70; 95% confidence interval [CI]: 0.36-1.38). The incidence of pneumonia was not significantly different between the P600 and O75 treatment groups (2.2% vs. 2.7%; RR = 0.74; 95% CI: 0.37-1.51). Regarding the time to the alleviation of symptoms, no difference was found in P600 and O75 treatment (MD = -3.00; 95% CI: -11.07 to 5.06). The rate of fever clearance in 24 h and the time to fever resolution were not statistically different between the IV peramivir and oral oseltamivir treatments (at different dosages) groups. CONCLUSIONS: The treatment of influenza with IV peramivir or oral oseltamivir had similar clinical efficacy.

Cross-modal self-supervised representation learning for gesture and skill recognition in robotic surgery.

PURPOSE: Multi- and cross-modal learning consolidates information from multiple data sources which may offer a holistic representation of complex scenarios. Cross-modal learning is particularly interesting, because synchronized data streams are immediately useful as self-supervisory signals. The prospect of achieving self-supervised continual learning in surgical robotics is exciting as it may enable lifelong learning that adapts to different surgeons and cases, ultimately leading to a more general machine understanding of surgical processes. METHODS: We present a learning paradigm using synchronous video and kinematics from robot-mediated surgery. Our approach relies on an encoder-decoder network that maps optical flow to the corresponding kinematics sequence. Clustering on the latent representations reveals meaningful groupings for surgeon gesture and skill level. We demonstrate the generalizability of the representations on the JIGSAWS dataset by classifying skill and gestures on tasks not used for training. RESULTS: For tasks seen in training, we report a 59 to 70% accuracy in surgical gestures classification. On tasks beyond the training setup, we note a 45 to 65% accuracy. Qualitatively, we find that unseen gestures form clusters in the latent space of novice actions, which may enable the automatic identification of novel interactions in a lifelong learning scenario. CONCLUSION: From predicting the synchronous kinematics sequence, optical flow representations of surgical scenes emerge that separate well even for new tasks that the model had not seen before. While the representations are useful immediately for a variety of tasks, the self-supervised learning paradigm may enable research in lifelong and user-specific learning.

An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma.

Pelvic ring disruptions result from blunt injury mechanisms and are often found in patients with multi-system trauma. To grade pelvic fracture severity in trauma victims based on whole-body CT, the Tile AO/OTA classification is frequently used. Due to the high volume of whole-body trauma CTs generated in busy trauma centers, an automated approach to Tile classification would provide substantial value, e. g., to prioritize the reading queue of the attending trauma radiologist. In such scenario, an automated method should perform grading based on a transparent process and based on interpretable features to enable interaction with human readers and lower their workload by offering insights from a first automated read of the scan. This paper introduces an automated yet interpretable pelvic trauma decision support system to assist radiologists in fracture detection and Tile grade classification. The method operates similarly to human interpretation of CT scans and first detects distinct pelvic fractures on CT with high specificity using a Faster-RCNN model that are then interpreted using a structural causal model based on clinical best practices to infer an initial Tile grade. The Bayesian causal model and finally, the object detector are then queried for likely co-occurring fractures that may have been rejected initially due to the highly specific operating point of the detector, resulting in an updated list of detected fractures and corresponding final Tile grade. Our method is transparent in that it provides finding location and type using the object detector, as well as information on important counterfactuals that would invalidate the system's recommendation and achieves an AUC of 83.3%/85.1% for translational/rotational instability. Despite being designed for human-machine teaming, our approach does not compromise on performance compared to previous black-box approaches.

Identification of Ovarian Cancer Patients Most Likely to Achieve Chemotherapy Response Score 3 Following Neoadjuvant Chemotherapy: Development of a Predictive Nomogram.

Background: The chemotherapy response score (CRS) system is a reproducible prognostic tool for patients receiving neoadjuvant chemotherapy (NACT) for tubo-ovarian high-grade serous carcinoma (HGSC). Achieving CRS 3 following NACT can be used as a surrogate for progression-free survival (PFS) and overall survival (OS). This study aimed to identify predictors of CRS 3 and develop a predictive nomogram. Methods: Data were extracted from 106 HGSC patients receiving NACT. Logistic regression was used to identify independent predictors for CRS 3. A nomogram was established based on the multivariate regression model. Results: All patients received three cycles of NACT, and CRS 3 was observed in 24 (22.6%) patients. Compared with patients in the CRS 1-2 group, patients in the CRS 3 groups had significantly improved PFS (log-rank test P < 0.0001). The multivariate regression analysis identified post-NACT CA125, percent decrease in CA125, post-NACT human epididymis protein 4 (HE4), and post-NACT hemoglobin level as independent predictors of CRS 3. The Hosmer-Lemeshow test showed goodness-of-fit of this regression model (P = 0.272). The nomogram including these factors presented good discrimination (area under the curve = 0.82), good calibration (mean absolute error = 0.039), and a net benefit within the threshold probabilities of CRS 3 > 5%. Conclusions: We validated the prognostic role of the CRS system and developed a nomogram that predicts the possibility of CRS 3 following NACT. The nomogram helps to identify patients who would benefit the most from NACT. More studies are warranted to validate this model.

Leveraging vision and kinematics data to improve realism of biomechanic soft tissue simulation for robotic surgery.

PURPOSE: Surgical simulations play an increasingly important role in surgeon education and developing algorithms that enable robots to perform surgical subtasks. To model anatomy, finite element method (FEM) simulations have been held as the gold standard for calculating accurate soft tissue deformation. Unfortunately, their accuracy is highly dependent on the simulation parameters, which can be difficult to obtain. METHODS: In this work, we investigate how live data acquired during any robotic endoscopic surgical procedure may be used to correct for inaccurate FEM simulation results. Since FEMs are calculated from initial parameters and cannot directly incorporate observations, we propose to add a correction factor that accounts for the discrepancy between simulation and observations. We train a network to predict this correction factor. RESULTS: To evaluate our method, we use an open-source da Vinci Surgical System to probe a soft tissue phantom and replay the interaction in simulation. We train the network to correct for the difference between the predicted mesh position and the measured point cloud. This results in 15-30% improvement in the mean distance, demonstrating the effectiveness of our approach across a large range of simulation parameters. CONCLUSION: We show a first step towards a framework that synergistically combines the benefits of model-based simulation and real-time observations. It corrects discrepancies between simulation and the scene that results from inaccurate modeling parameters. This can provide a more accurate simulation environment for surgeons and better data with which to train algorithms.

Impact of Poor Preoperative Glycemic Control on Outcomes among Patients with Cervical Cancer Undergoing a Radical Hysterectomy.

BACKGROUND: The impact of preoperative glycemic control on the survival outcomes of patients undergoing a radical hysterectomy (RH) for cervical cancer has not been investigated. PATIENTS AND METHODS: We reviewed patients who underwent a type III RH for cervical cancer between January 2004 and June 2011 in our institution. RESULTS: A total of 431 patients were included and 83 (19.3%) were diagnosed with diabetes mellitus (DM). Poorly controlled DM (preoperative hemoglobin A1c [HbA1c] ≥7.0%) was observed in 49 (59.0%) diabetic patients. Compared to patients without DM and diabetic patients with good glycemic control (preoperative HbA1c <7.0%), diabetic patients with poor glycemic control had significantly higher risks of tumor recurrence, cervical cancer-specific death, and overall death. In multivariate analysis, DM with poor glycemic control independently predicted recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). We excluded patients without DM and performed a sensitivity analysis. When HbA1c levels were treated as a dichotomous variable, preoperative HbA1c ≥7.0% was independently associated with RFS, CSS, and OS. When HbA1c level was treated as a continuous variable, it remained an independent predictor of RFS, CSS, and OS. CONCLUSION: DM with poor glycemic control prior to RH was significantly associated with an increased risk of recurrence and mortality in cervical cancer patients. These results underscore the importance of intensive glycemic control and close follow-up for diabetic patients.

The added value of fasting blood glucose to serum squamous cell carcinoma antigen for predicting oncological outcomes in cervical cancer patients receiving neoadjuvant chemotherapy followed by radical hysterectomy.

OBJECTIVE: To determine the combination of fasting blood glucose (FBG) with squamous cell carcinoma antigen (SCCA) assessments in the prediction of tumor responses to chemotherapy and pretreatment prognostication among patients receiving neoadjuvant chemotherapy (NACT) for locally advanced cervical cancer (LACC). METHODS: Data of 347 LACC patients were retrospectively reviewed. Receiver operating characteristic (ROC) curves were constructed, and areas under the curves (AUCs) were compared to evaluate the ability to predict complete response (CR) following NACT. Patients were stratified into groups with low and high levels of SCCA and FBG and combined into low- or high-SCCA and low- or high-FBG groups. Cox regression analysis was performed to identify determinants of recurrence-free survival (RFS) and overall survival (OS). RESULTS: The AUCs were 0.70, 0.68, and 0.66 for SCCA, FBG, and a combination of SCCA and FBG for predicting CR following NACT, respectively; however, the differences among AUCs were not significant (P = .496). Pretreatment SCCA and FBG levels were identified as independent predictors of RFS and OS. The high-SCCA/high-FBG group showed significantly worse prognosis than the low-SCCA/low-FBG group. After adjusting for other variables, high-SCCA/high-FBG remained independently associated with an increased risk of tumor recurrence and death. CONCLUSION: SCCA, FBG, and a combination of SCCA and FBG could acceptably predict CR following NACT. Pretreatment SCCA and FBG levels were independent prognostic factors. The combination of SCCA and FBG levels refined the prognostic stratification of LACC patients, which allowed the group of patients with the highest risk of recurrence and death to be identified.

Efficacy and Safety of Lesinurad in Patients with Hyperuricemia Associated with Gout: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

OBJECTIVE: To evaluate the efficacy and safety of lesinurad for the treatment of hyperuricemia in patients with gout. DESIGN: Systematic review and meta-analysis of randomized controlled trials (RCTs). PATIENTS OR PARTICIPANTS: Five RCTs, which included 1959 patients, compared the efficacy and safety of lesinurad in patients with hyperuricemia associated with gout. MEASUREMENTS AND RESULTS: Relevant studies were identified from PubMed, EMBASE, Cochrane Library databases, and the ClinicalTrials.gov registry. Two reviewers independently assessed the studies. Individual effect sizes were standardized, and a meta-analysis was conducted to calculate the pooled effect size by using a random-effect model. The primary outcomes were the proportion of patients achieving target serum uric acid (sUA) levels by month 6 and the mean sUA levels at month 6 and month 12. Gout-related outcomes were also assessed. The secondary outcome was the number of treatment-emergent adverse events (TEAEs). Compared with xanthine oxidase inhibitor (XOI) monotherapy, lesinurad 200 mg or 400 mg in combination with allopurinol or febuxostat exhibited a higher proportion of patients achieving target sUA levels of < 6.0 mg/dl or < 5.0 mg/dl, respectively, by month 6. Lesinurad-plus-XOI groups also significantly sustained lower mean sUA levels at month 6 and month 12 compared to XOI alone group. In gout-related outcomes, no significant treatment group differences favored lesinurad. The number of TEAEs was comparable between the lesinurad 200 mg-plus-XOI group and the XOI-monotherapy group. Although lesinurad 400 mg monotherapy demonstrated superior efficacy compared with placebo, significantly more TEAEs occurred. CONCLUSIONS: Although the combination of lesinurad 200 mg and XOI is effective and well tolerated for treating patients with gout who have not achieved an adequate response to XOI monotherapy, clinical gout-related outcomes were not improved. Therefore, additional studies investigating the long-term clinical implication of lesinurad are warranted.