Objectives: Minimally invasive apical sacropexies (MI-APSC) can be performed using robotics or laparoscopy. We hypothesized that operative characteristics of MI-APSC, laparoscopic (LSC) and robotic (RSC), were similar. The objective of our study was to compare operative characteristics, objective prolapse outcomes, and robotic learning curve.
Methods: Ninety-two women planning MI-APSC for treatment of apical pelvic organ prolapse from 2006 to 2010 were included in the study. The primary outcome was operative time. The secondary outcomes included estimated blood loss, rate of conversion, intraoperative complications, hospital stay, and objective prolapse outcome. We also analyzed the robotic learning curve. Statistical analysis included independent samples t test, Wilcoxon rank sum test, χ, and multiple logistic regressions; significance was set at P < 0.05. Learning curve was graphed with moving average and analyzed with moving block technique.
Results: Forty-eight RSCs and 43 LSCs were analyzed. Mean operative times were LSC, 238 ± 59 minutes; and RSC, 242 ± 54 minutes. Robotic MI-APSC setup was longer (P = 0.02). Complications, conversions, estimated blood loss and hospital stay were low and similar between groups. Patients' characteristics were similar. Concomitant procedures produced longer operative times.
Conclusions: Operating room experiences with laparoscopic- and robotic-assisted approaches to MI-APSC were similar, but setup time is longer for the robotic-assisted approach. The robotic learning curve is short for surgeons who have experience with LSC.
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http://dx.doi.org/10.1097/SPV.0b013e31824a3995 | DOI Listing |
Adv Radiat Oncol
February 2025
Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, the Netherlands.
Purpose: Ultrahypofractionation presents challenges for a subset of high-risk prostate cancer patients due to the large planning target volume (PTV) margin required for the seminal vesicles. Online adaptive radiation therapy could potentially reduce this margin. This paper focuses on the development, preclinical validation, and clinical testing of online adaptive robotic stereotactic body radiation therapy for this patient group.
View Article and Find Full Text PDFMethodsX
June 2025
Universidad de Virginia, Charlottesville, United States.
The research aims to evaluate the effect of a robotics-based computational thinking program on executive functions and visuospatial skills in preschool children. Additionally, the study will explore the relationship between these three variables and early experiences with toys. The study will be a cluster-randomized controlled trial with pre- and post-intervention measures.
View Article and Find Full Text PDFNanoscale
January 2025
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
Liquid biopsies are expected to advance cancer management, and particularly physical cues are gaining attention for indicating tumorigenesis and metastasis. Atomic force microscopy (AFM) has become a standard and important tool for detecting the mechanical properties of single living cells, but studies of developing AFM-based methods to efficiently measure the mechanical properties of circulating tumor cells (CTCs) in liquid biopsy for clinical utility are still scarce. Herein, we present a proof-of-concept study based on the complementary combination of AFM and microfluidics, which allows label-free sorting of individual CTCs and subsequent automated AFM measurements of the mechanical properties of CTCs.
View Article and Find Full Text PDFSurg Innov
January 2025
Division of General, Minimally Invasive, and Robotic Surgery, Department of Surgery, University of Illinois at Chicago, Chicago, IL, USA.
Background: Transabdominal pre-peritoneal inguinal hernia repair using the da Vinci Single-Port robot (SP-TAPP) is currently performed in few centers. We aimed to define the learning curve for SP-TAPP by analyzing operative times.
Methods: The operative times of 122 SP-TAPP performed between 2019 and 2024 were retrospectively analyzed.
Biosci Trends
January 2025
Department of Rehabilitation, Beijing Rehabilitation Hospital Capital Medical University, Beijing, China.
In human-computer interaction, gesture recognition based on physiological signals offers advantages such as a more natural and fast interaction mode and less constrained by the environment than visual-based. Surface electromyography-based gesture recognition has significantly progressed. However, since individuals have physical differences, researchers must collect data multiple times from each user to train the deep learning model.
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