Intuitive Surgical (United States)

Surgical staplers are essential tools in minimally invasive surgery (MIS), enabling tissue division, hemostasis, and secure anastomoses. With the growth of robotic-assisted surgery, robotic staplers such as SureForm have recently become available. These staplers offer precise articulation and real-time tissue compression monitoring. However, the clinical advantages of robotic staplers over bedside staplers remain uncertain. Studies show mixed results across specialties, mainly due to small sample sizes, outdated data, and data heterogeneity. This study protocol proposes a series of future analyses that will evaluate the clinical outcomes and resource utilization of robotic versus bedside staplers in robotic-assisted surgeries across multiple specialties using recent real-world data. This retrospective cohort study will use data from the Premier Healthcare Database (PHD), a large hospital-based database covering patients with varied payers across the United States. Adult patients (≥18 years) who underwent elective, fully robotic-assisted lung, colorectal, gastric, or bariatric surgeries from 2019 to 2023 will be included. Each surgical specialty will be analyzed in a separate paper. Patients will be categorized into two groups based on the type of surgical stapler used: robotic staplers (SureForm) and bedside staplers (manual or powered). The primary outcome will be postoperative leak (air leak for lung resection; anastomotic leak for colorectal, gastrectomy, and bariatric). Key secondary outcomes are other complications, conversion to open surgery, operative time, transfusion requirements, length of stay (LOS), and cost. Overlap weighting will be applied to minimize bias. Results will be disseminated through peer-reviewed surgical journals and presentations at relevant surgical meetings.

Abstract Our research project aimed to advance the design and performance optimization of composite-material drones through a multifaceted analysis integrating computational fluid dynamics (CFD), rigid-body dynamics, and structural evaluations. Focusing on a quadcopter equipped with a novel 3-axis rotating mechanism—previously conceptualized for dynamic thrust vectoring—the design has been validated with its aerodynamic feasibility and operational efficiency. The mechanism enables independent propeller rotation around three axes, enhancing maneuverability by dynamically adjusting thrust vectors during flight. Using ANSYS Fluent, steady-state CFD simulations were conducted with the Moving Reference Frame (MRF) method to model an eight-inch composite propeller (carbon fiber-reinforced polymer matrix) under varying angles of attack (AoA: 0°–15°) and rotational speeds (RPM: 5000–15,000). The MRF approach simplified the interaction between the rotating domain and the stationary fluid domain, striking a balance between computational efficiency and accuracy for preliminary design validation. Aerodynamic performance metrics were analyzed to identify optimal operating conditions, including lift coefficient (Cl) and drag coefficient (Cd). At 5° AoA, the propeller achieved Cl = 4.7 and Cd = 0.3, striking an optimal balance between thrust generation and energy efficiency. This configuration minimized flow separation and vortex shedding, which are critical for maintaining stability in multi-axis rotations. RPM-dependent simulations revealed a nonlinear relationship between thrust and rotational speed: while thrust increased with RPM, drag forces grew disproportionately beyond 12,000 RPM due to turbulent skin friction and tip-vortex interactions, corroborating prior studies on propeller energy losses. Our research findings indicate a minimum center-to-center propeller spacing of 400 mm to eliminate aerodynamic interference and prevent wake turbulence from one rotor from disrupting adjacent propellers. Our research provides actionable insights for designing multi-axis thrust-vectoring drones, emphasizing the interplay between composite material properties, aerodynamic efficiency, and geometric configuration. The validated 3-axis mechanism demonstrates the potential for applications in agile UAVs operating in constrained or turbulent environments [13]. Future work will integrate transient simulations and experimental prototyping to refine dynamic performance under real-world conditions.

Abstract Objective To evaluate 2-year cost to insured patients treated with Roux-en-Y gastric bypass (RYGB) or glucagon-like peptide-1 receptor agonists (GLP-1 RAs) for type 2 diabetes (T2D) and obesity. Methods Using the 2017 to 2023 Merative™ claims database, we identified adult patients with severe obesity and T2D who were treated with a RYGB or GLP-1 RAs. Patients with RYGB had no treatment with GLP-1 RAs, and those who received GLP-1 RA therapy with tirzepatide or semaglutide for ≥ 2 years had no metabolic and bariatric surgery (MBS) procedures. The study cohorts were matched on demographics including obesity, associated medical problems, and baseline direct or out-of-pocket (OOP) costs to patients in the year prior to treatment initiation. Direct costs included those from outpatient services, inpatient admissions, and outpatient prescription filled that were paid directly by patients. We compared this cost up to two years after treatment initiation using paired t-tests. Results 1012 matched RYGB and GLP-1 RA patients were analyzed, including 35% male. At 1-year after treatment initiation, healthcare costs paid directly by patients were similar for the RYGB ($2,301) and GLP-1 RA ($2,179) (delta = $122, p = 0.15) cohorts. From one to two years after index treatment date, OOP costs were significantly lower in the RYGB treatment group ($1,277 vs. $2,104, p < 0.01). Two years after treatment initiation, RYGB patients spent $704 less in OOP costs than similar patients treated with GLP-1 RA medications (p < 0.01). Conclusions Direct OOP healthcare costs were lower for RYGB compared to GLP-1 RA use patients 2-years after treatment initiation.

Background: There is limited clinical evidence from India comparing robotic-assisted surgery (RAS), laparoscopic surgery (LPS), and open laparotomy (OL) approaches for managing stage 1 endometrial cancer (EC). This multicenter study aimed to evaluate and compare the perioperative and short-term outcomes of these techniques across high-volume Indian institutions.Methodology: This multicenter, retrospective, non-randomized comparative study reviewed medical records of consecutive patients who underwent OL, LPS, or RAS for stage 1 EC between January 2010 and December 2023.Results: A total of 2,090 patient records were analyzed, including 1,223 in the RAS group, 451 in the LPS group, and 416 in the OL group. The average age was 59.66 ± 9.31 years, with no significant differences between groups. The overall mean operative time was 220.51 ± 93.73 minutes, with the RAS group demonstrating a significantly shorter duration than both OL and LPS groups (P < 0.001). The mean estimated blood loss was 128.87 ± 226.75 mL, with the RAS group resulting in the least blood loss, followed by the LPS and OL groups (P < 0.001). The need for intraoperative blood transfusion was also lowest in the RAS group. Intraoperative complications were more frequent in the OL group, while conversion to open surgery was higher in the LPS group (P < 0.001). Hospital stay was shortest in the RAS group (2.71 days), followed by the LPS (3.77 days) and OL (5.95 days) groups (P < 0.001). Postoperative complications were significantly fewer in the RAS and LPS groups than in the OL group. Positive margins were lowest in the RAS group (P < 0.001). Sentinel lymph node sampling was highest in the RAS group (P < 0.001). Patients in the RAS group started adjuvant treatment sooner than the LPS (P < 0.001) and OL (P = 0.004) groups.Conclusions: This study reports the first multicentric evidence for RAS in Indian settings, compared to conventional approaches, and offers encouraging outcomes.

Precise intraoperative delineation of tumor margin is critical for maximizing resection completeness and minimizing recurrence in head and neck cancers (HNC). Label-free Fluorescence Lifetime Imaging (FLIm), which captures the fluorescence decay characteristics of endogenous molecules, offers a real-time method for differentiating malignant from healthy tissue during surgery without the need of contrast agents. Here, we present a data-centric artificial intelligence (AI) framework to enhance the robustness and accuracy of FLIm-based classification models for HNC. FLIm data were collected in vivo from 92 patients undergoing both transoral robotic surgery (TORS) and non-TORS procedures for HNC using a multispectral FLIm device with 355 nm excitation. To improve model performance, a data-centric approach leveraging confident learning was implemented to identify and exclude instances with low quality. An interpretability framework was further integrated to quantify feature contributions and elucidate FLIm-derived sources of contrast. Under a leave-one-patient-out cross-validation scheme, the model demonstrated a strong discriminative ability with an area under the receiver operating characteristic curve of 0.94 in differentiating healthy versus cancerous tissue. In tumor boundary regions, borderline predictions revealed transitional tissue properties, with strong correlations observed between model predictions and FLIm parameters in spectral channels corresponding to NADH and FAD—key metabolic cofactors indicative of cellular metabolic shifts at tumor margins. The impact of tumor anatomical site (base of tongue, palatine tonsil, oral tongue) and p16+ (HPV) status on classification performance was also assessed. These findings underscore the potential of label-free FLIm to provide accurate, real-time guidance for intraoperative margin assessment and dysplasia grading, advancing surgical precision in head and neck surgical oncology.

Accurate and efficient surgical robotic tool pose estimation is of fundamental significance to downstream applications such as augmented reality (AR) in surgical training and learning-based autonomous manipulation. While significant advancements have been made in pose estimation for humans and animals, it is still a challenge in surgical robotics due to the scarcity of published data. The relatively large absolute error of the da Vinci end effector kinematics and arduous calibration procedure make calibrated kinematics data collection expensive. Driven by this limitation, we collected a dataset, dubbed SurgPose, providing instance-aware semantic keypoints for visual surgical tool pose estimation and tracking. By marking keypoints using ultraviolet (UV) reactive paint, which is invisible under white light and fluorescent under UV light, we execute the same trajectory under different lighting conditions to collect raw videos and keypoint annotations, respectively. The SurgPose dataset consists of approximately 120 K surgical instrument instances of 6 categories as shown in Fig. 1. Since the videos are collected in stereo pairs, the 2D pose can be lifted to 3D based on stereo-matching depth. In addition to releasing the dataset, we tested a few baseline approaches to surgical instrument tracking to demonstrate the utility of SurgPose. More details can be found at surgpose.github.io.

Objective:This study aimed to characterize SureForm stapler usage trends in robotic sleeve gastrectomy (RSG) and compare associated outcomes, accounting for staple height used.Background:The proportion of sleeve gastrectomy cases done robotically is increasing, but uncertainty remains about optimal stapler choice, reload height and reinforcement, and the impact of these choices on perioperative outcomes.Methods:Elective laparoscopic and robotic SG performed from January 1, 2019, to February 28, 2023, were identified in the PINC AI Healthcare Database. Patients who underwent RSG were included. RSG with no stapler type/height information was excluded. The incidences of complications such as bleeding, leak, and sepsis in the perioperative period were evaluated using International Classification of Diseases/Current Procedure Terminology codes. Hospital resource utilization data such as length of stay, operative time, intensive care unit utilization, and readmission were also analyzed. Propensity score matching (PSM) analysis was used to compare outcomes.Results:A total of 35,795 RSG were analyzed with 23,904 documenting use of SureForm stapler. Use of at least one SureForm white reload increased from 19.2% to 52.7% in the study period; use of 3 or more white reloads per case increased from 6% to 71%. PSM analysis compared 5795 RSG with any white reload versus 5795 RSG with non-white reloads, showing equivalent complication rates, marginally shorter length of stay, and longer operative time with white reloads.Conclusions:There is a trend toward downsizing to white stapler reloads in RSG without significant changes in perioperative outcomes and minor differences in hospital resource utilization. These findings suggest that white stapler reload use is safe in RSG.

This study aims to provide the first comparative real-world evidence of laparoscopic and robotic-assisted ventral hernia repairs performed in India, regardless of defect size or technique used. The primary objective was to compare postoperative pain, analgesic use, and quality of life (QOL) between the two groups. Additionally, data on length of hospital stay, operating time, incidence of intra- and postoperative complications, re-admission rates, and use of tacks were collected and analyzed. The study included 290 cases: 111 (38.28%) in the robotic group and 179 (61.72%) in the laparoscopic group. Incisional hernias were more common in the robotic group (65 patients, 58.56%), while primary ventral hernias were more prevalent in the laparoscopic group (113 patients, 63.13%). The most common robotic repair approach was extended totally extraperitoneal Rives-Stoppa (eTEP-RS) withor without transversus abdominis release (TAR), performed in 75 (67.56%) cases. In the laparoscopic group, intraperitoneal onlay mesh (IPOM) plus was the most frequently performed procedure, used in 115 (64.25%) cases. The robotic group reported significantly lower pain levels after 6 hours, 24 hours, and 14 days following surgery. The numberand duration of analgesic use were significantly reducedin the robotic group. Additionally, the robotic group had significantly better health perception scores. Compared to the laparoscopic group, the robotic group experienced significantly fewer postoperative complications (2 vs. 16; p = 0.013). Notably, the robotic group did not use tacks for mesh fixation, while tacks were employed in roughly 116 (64.8%) of the laparoscopic cases. In real-world Indian settings, this study demonstrates the feasibility of robotic-assisted ventral hernia repairs, regardless of defect size or technique used.