Objective: To report our initial experience in the treatment of prostate cancer with robotic-assisted laparoscopic radical prostatectomy (RALP), evaluating our results in terms of learning curve, postoperative outcomes and positive surgical margins.
Material And Methods: From April 2005 to February 2006, a single surgeon performed 41 RALP using the da Vinci robot (Intuitive Surgical, Inc., Sunnyvale, Calif., USA). Clinical and pathological data were collected prospectively and analyzed by a researcher from outside our clinic. The main perioperative parameters assessed were the following: operative time, blood loss, transfusion rate, conversion rate, intra- and postoperative complications, hospitalization time, catheterization time, and positive surgical margin rate. To evaluate the learning curve, patients were stratified into three groups: from case 1 to 10 (group 1), from case 11 to 20 (group 2), and from case 21 to 41 (group C).
Results: Median operative time was 210 min. Mean blood loss was 400 ml, with 9.8% of the patients receiving blood transfusions. Conversion to open surgery occurred in 2 cases (4.9%), while 4 postoperative complications (9.7%) were reported. Median times of hospitalization and catheterization were 7 days. Positive surgical margins were detected in 26.8% of the cases (6.9% among pT2 patients). Operative time (p < 0.001), blood loss (p = 0.02), transfusion rate (p = 0.006), and postoperative complication rates (p = 0.03) reduced along the learning curve.
Conclusion: RALP is a feasible and reproducible technique, with a short learning curve and low perioperative complication rate. Even during the initial phase of the learning curve, good results were obtained with regard to postoperative complications and oncological outcome.
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http://dx.doi.org/10.1159/000127333 | DOI Listing |
Sci Rep
January 2025
Cardiovascular Research Center, Rajaie Cardiovascular, Medical, and Research Center, University of Medical Sciences, Tehran, Iran.
Assessing myocardial viability is crucial for managing ischemic heart disease. While late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is the gold standard for viability evaluation, it has limitations, including contraindications in patients with renal dysfunction and lengthy scan times. This study investigates the potential of non-contrast CMR techniques-feature tracking strain analysis and T1/T2 mapping-combined with machine learning (ML) models, as an alternative to LGE-CMR for myocardial viability assessment.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Rheumatology and Immunology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Developing a new diagnostic prediction model for osteoarthritis (OA) to assess the likelihood of individuals developing OA is crucial for the timely identification of potential populations of OA. This allows for further diagnosis and intervention, which is significant for improving patient prognosis. Based on the NHANES for the periods of 2011-2012, 2013-2014, and 2015-2016, the study involved 11,366 participants, of whom 1,434 reported a diagnosis of OA.
View Article and Find Full Text PDFBMC Musculoskelet Disord
January 2025
Division of Orthopaedic Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada.
Background: To summarize the statistical performance of machine learning in predicting revision, secondary knee injury, or reoperations following anterior cruciate ligament reconstruction (ACLR), and to provide a general overview of the statistical performance of these models.
Methods: Three online databases (PubMed, MEDLINE, EMBASE) were searched from database inception to February 6, 2024, to identify literature on the use of machine learning to predict revision, secondary knee injury (e.g.
World Neurosurg
January 2025
Department of Neurology, The First People's Hospital of Jingzhou, The First Affiliated Hospital of Yangtze University, Jingzhou 434000, China. Electronic address:
Objective: This study was to explore the factors associated with prolonged hospital length of stay (LOS) in patients with intracranial aneurysms (IAs) undergoing endovascular interventional embolization and construct prediction model machine learning algorithms.
Methods: Employing a retrospective cohort study design, this study collected patients with ruptured IA who received endovascular treatment at Jingzhou First People's Hospital during the inclusion period from September 2022 to December 2023. The entire dataset was randomly split into training and testing dataset with a 7:3 ratio.
J Clin Neurosci
January 2025
Division of Neurosurgery, Department of Surgery, National University Hospital, National University Health System, Singapore.
Ventriculoperitoneal shunt (VPS) insertion is a neurosurgical procedure done routinely for managing hydrocephalus. However, the technique of shunt insertion remains controversial. In this study, we retrospectively compared the accuracy of shunt placement using ultrasound (US) guidance to freehand insertion.
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