Current training on the basics of robotic surgery in the Netherlands: Time for a multidisciplinary approach?

Introduction: The following research questions were answered: (1) What are the training pathways followed by the current robot professionals? (2) Are there any differences between the surgical specialties in robot training and robot use? (3) What is their opinion about multidisciplinary basic skills training? Methods: An online questionnaire was sent to 91 robot professionals in The Netherlands. The questionnaire contained 21 multiple-choice questions focusing on demographics, received robot training, and their opinion on basic skills training in robotic surgery. Results: The response rate was 62 % (n = 56): 13 general surgeons, 16 gynecologists, and 27 urologists. The urologists performed significantly more robotic procedures than surgeons and gynecologists. The kind of training of all professionals varied from a training program by Intuitive Surgical, master-apprenticeship with or without duo console, fellowship, and self-designed training programs. The training did neither differ significantly among the different specialties nor the year of starting robotic surgery. Majority of respondents favor an obliged training program including an examination for the basics of robot skills training. Conclusion: Training of the current robot professionals is mostly dependent on local circumstances and the manufacturer of the robot system. Training is independent of the year of start with robotic surgery and speciality. To guarantee the quality of future training of residents and fellows in robot-assisted surgery, clear training goals should be formulated and implemented. Since this study shows that current training of different specialities does not differ, training in robotic surgery could be started by a multidisciplinary basic skills training and assessment

A multicenter study on Leigh syndrome: Disease course and predictors of survival

Background: Leigh syndrome is a progressive neurodegenerative disorder, associated with primary or secondary dysfunction of the mitochondrial oxidative phosphorylation. Despite the fact that Leigh syndrome is the most common phenotype of mitochondrial disorders in children, longitudinal natural history data is missing. This study was undertaken to assess the phenotypic and genotypic spectrum of patients with Leigh syndrome, characterise the clinical course and identify predictors of survival in a large cohort of patients. Methods. This is a retrospective study of patients with Leigh syndrome that have been followed at eight centers specialising in mitochondrial diseases in Europe; Gothenburg, Rotterdam, Helsinki, Copenhagen, Stockholm, Brussels, Bergen and Oulu. Results: A total of 130 patients were included (78 males; 52 females), of whom 77 patients had identified pathogenic mutations. The median age of disease onset was 7 months, w

A clinician’s guide for developing a prediction model: a case study using real-world data of patients with castration-resistant prostate cancer

Purpose: With the increasing interest in treatment decision-making based on risk prediction models, it is essential for clinicians to understand the steps in developing and interpreting such models. Methods: A retrospective registry of 20 Dutch hospitals with data on patients treated for castration-resistant prostate cancer was used to guide clinicians through the steps of developing a prediction model. The model of choice was the Cox proportional hazard model. Results: Using the exemplary dataset several essential steps in prediction modelling are discussed including: coding of predictors, missing values, interaction, model specification and performance. An advanced method for appropriate selection of main effects, e.g. Least Absolute Shrinkage and Selection Operator (LASSO) regression, is described. Furthermore, the assumptions of Cox proportional hazard model are discussed, and how to handle violations of the proportional hazard assumption using time-varying coefficients. Conclusion: This study provides a comprehensive detailed guide to bridge the gap between the statistician and clinician, based on a large dataset of real-world patients treated for castration-resistant prostate cancer