Publications by authors named "Donald L Van Der Peet"

Background: Artificial intelligence (AI) models have been applied in various medical imaging modalities and surgical disciplines, however the current status and progress of ultrasound-based AI models within hepatopancreatobiliary surgery have not been evaluated in literature. Therefore, this review aimed to provide an overview of ultrasound-based AI models used for hepatopancreatobiliary surgery, evaluating current advancements, validation, and predictive accuracies.

Method: Databases PubMed, EMBASE, Cochrane, and Web of Science were searched for studies using AI models on ultrasound for patients undergoing hepatopancreatobiliary surgery.

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Introduction: The variety of robotic surgery systems, training modalities, and assessment tools within robotic surgery training is extensive. This systematic review aimed to comprehensively overview different training modalities and assessment methods for teaching and assessing surgical skills in robotic surgery, with a specific focus on comparing objective and subjective assessment methods.

Methods: A systematic review was conducted following the PRISMA guidelines.

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Background: Clinical decision-making in gastrointestinal surgery is complex due to the unpredictability of tumoral behavior and postoperative complications. Artificial intelligence (AI) could aid in clinical decision-making by predicting these surgical outcomes. The current status of AI-based clinical decision-making within gastrointestinal surgery is unknown in recent literature.

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Background: Unnecessary D2-gastrectomy and associated costs can be prevented after detecting non-curable gastric cancer, but impact of staging on treatment costs is unclear. This study determined the cost impact of F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) and staging laparoscopy (SL) in gastric cancer staging.

Materials And Methods: In this cost analysis, four staging strategies were modeled in a decision tree: (1) FDG-PET/CT first, then SL, (2) SL only, (3) FDG-PET/CT only, and (4) neither SL nor FDG-PET/CT.

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ChatGPT has brought about a new era of digital health, as this model has become prominent and been rapidly developing since its release. ChatGPT may be able to facilitate improvements in surgery as well; however, the influence of ChatGPT on surgery is largely unknown at present. Therefore, the present study reports on the current applications of ChatGPT in the field of surgery, evaluating its workflow, practical implementations, limitations, and future perspectives.

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Background: Glycemic control is an important goal of bariatric surgery in patients with type 2 diabetes mellitus (T2DM) and obesity. The laparoscopic one-anastomosis gastric bypass (OAGB) has potential metabolic benefits over the laparoscopic Roux-en-Y gastric bypass (RYGB). Aim of this study is to examine whether RYGB or OAGB grants better glycemic control 12 months post-surgery.

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Introduction: Minimally invasive techniques have shown better short term and similar oncological outcomes compared to open techniques in the treatment of gastric cancer in Asian countries. It remains unknown whether these outcomes can be extrapolated to Western countries, where patients often present with advanced gastric cancer.

Materials And Methods: A pooled analysis of two Western randomized controlled trials (STOMACH and LOGICA trial) comparing minimally invasive gastrectomy (MIG) and open gastrectomy (OG) in advanced gastric cancer was performed.

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Objective: To examine the influence of the LOGICA RCT (randomized controlled trial) upon the practice and outcomes of laparoscopic gastrectomy within the Netherlands.

Background: Following RCTs the dissemination of complex interventions has been poorly studied. The LOGICA RCT included 10 Dutch centers and compared laparoscopic to open gastrectomy.

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Background: Abdominal pain after bariatric surgery (BS) is frequently observed. Despite numerous diagnostic tests, the cause of abdominal pain is not always found.

Objectives: To quantify type and number of diagnostic tests performed in patients with abdominal pain after BS and evaluate the burden and their yield in the diagnostic process.

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The operating room nowadays is a data-rich environment to which Artificial Intelligence (AI) can respond. Current AI applications mainly focus on supporting perioperative decision-making and on improving surgical skills and safety. Specific steps need to be taken to advance the implementation of AI.

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Purpose: Long-term follow-up after bariatric surgery (BS) reveals high numbers of patients with abdominal pain that often remains unexplained. The aim of this prospective study was to give an overview of diagnoses for abdominal pain, percentage of unexplained complaints, number and yield of follow-up visits, and time to establish a diagnosis.

Materials And Methods: Patients who visited the Spaarne Gasthuis Hospital, The Netherlands, between December 2020 and December 2021 for abdominal pain after BS, were eligible and followed throughout the entire episode of abdominal pain.

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Background: Adequate lymphadenectomy is an important step in gastrectomy for cancer, with a modified D2 lymphadenectomy being recommended for advanced gastric cancers. When assessing a novel technique for the treatment of gastric cancer, lymphadenectomy should be non-inferior. The aim of this study was to assess completeness of lymphadenectomy and distribution patterns between open total gastrectomy (OTG) and minimally invasive total gastrectomy (MITG) in the era of peri-operative chemotherapy.

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Background: Laparoscopic gastrectomy could reduce pain and opioid consumption, compared to open gastrectomy. However, it is difficult to judge the clinical relevance of this reduction, since these outcomes are reported in few randomized trials and in limited detail.

Methods: This secondary analysis of a multicenter randomized trial compared laparoscopic versus open gastrectomy for resectable gastric adenocarcinoma (cT1-4aN0-3bM0).

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Background: Neoadjuvant chemoradiotherapy (nCRTx) reduces the incidence of recurrence, while anastomotic leakage has shown increase the risk of recurrence. The primary objective of this retrospective study was to investigate the incidence and pattern of recurrence and secondary median recurrence-free interval and post-recurrence survival in patients with and without anastomotic leakage after multimodal therapy for esophageal adenocarcinoma.

Methods: Patients with recurrence after multimodal therapy between 2010 and 2018 were included.

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Introduction: Robot-assisted surgery is often performed by experienced laparoscopic surgeons. However, this technique requires a different set of technical skills and surgeons are expected to alternate between these approaches. The aim of this study is to investigate the crossover effects when switching between laparoscopic and robot-assisted surgery.

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Background: Male patients are underrepresented in bariatric surgery (BS) despite a relatively equal proportion of men and women experiencing obesity.

Objectives: Differences in frequency and severity of obesity-associated medical problems (OAMPs) between men and women undergoing BS or in a control group (HELIUS [HEalthy Life In an Urban Setting]) were evaluated. The hypothesis was that men undergoing BS are less healthy than women.

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The purpose of this study was to investigate hospital variation in the placement, surgical techniques, and safety of feeding jejunostomies (FJ) during minimally invasive esophagectomy (MIE) in the Netherlands. This nationwide cohort study analyzed patients registered in the Dutch Upper Gastrointestinal Cancer Audit (DUCA) that underwent MIE for cancer. Hospital variation in FJ placement rates were investigated using case-mix corrected funnel plots.

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Importance: Laparoscopic gastrectomy is rapidly being adopted worldwide as an alternative to open gastrectomy to treat gastric cancer. However, laparoscopic gastrectomy might be more expensive as a result of longer operating times and more expensive surgical materials. To date, the cost-effectiveness of both procedures has not been prospectively evaluated in a randomized clinical trial.

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Background: Machine learning (ML) has been introduced in various fields of healthcare. In colorectal surgery, the role of ML has yet to be reported. In this systematic review, an overview of machine learning models predicting surgical outcomes after colorectal surgery is provided.

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Background: Machine learning (ML) has seen an increase in application, and is an important element of a digital evolution. The role of ML within upper gastrointestinal surgery for malignancies has not been evaluated properly in the literature. Therefore, this systematic review aims to provide a comprehensive overview of ML applications within upper gastrointestinal surgery for malignancies.

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Objective: This study investigated the patterns, predictors, and survival of recurrent disease following esophageal cancer surgery.

Background: Survival of recurrent esophageal cancer is usually poor, with limited prospects of remission.

Methods: This nationwide cohort study included patients with distal esophageal and gastroesophageal junction adenocarcinoma and squamous cell carcinoma after curatively intended esophagectomy in 2007 to 2016 (follow-up until January 2020).

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