Radiofrequency ablation (RFA) in unresectable pancreatic adenocarcinoma: meta-analysis & systematic review.

Background: Pancreatic adenocarcinoma remains a challenging malignancy with a poor prognosis. Radiofrequency ablation (RFA) has emerged as a potential treatment for unresectable pancreatic adenocarcinoma (UPAC) aimed at improving survival and quality of life. This meta-analysis and systematic review evaluates the outcomes of RFA in UPAC.

A rare case of perianal alveolar rhabdomyosarcoma.

Perianal alveolar rhabdomyosarcoma is a rare sarcoma that requires a high index of suspicion along with tissue biopsy for accurate diagnosis. Successful treatment, even in the setting of recurrence, requires a multidisciplinary approach.

Adherence to enhanced recovery after surgery (ERAS) in older adults following colorectal resection.

Introduction: Enhanced recovery after surgery (ERAS) is an established pathway to improve short-term outcomes in colorectal surgery. It is unclear whether the efficacy, feasibility, and safety of the ERAS protocol are similar in older and younger patients. The study examined adherence to the ERAS protocol and identified factors leading to deviations in older patients.

Safety and effectivity of Kono-S anastomosis in Crohn's patients: a systematic review and Meta-analysis.

Purpose: Kono-S anastomosis, an antimesenteric, functional, end-to-end handsewn anastomosis, was introduced in 2011. The aim of this meta-analysis is to evaluate the safety and effectivity of the Kono-S technique.

Methods: A comprehensive search of MEDLINE (PubMed), Embase (Elsevier), Scopus (Elsevier), and Cochrane Central (Ovid) from inception to August 24th, 2023, was conducted.

Risk Factors of Asymptomatic Kidney Stone Passage in Adults with Recurrent Kidney Stones.

Key Points: Asymptomatic stone passage was common in patients with recurrent calcium-containing kidney stones. Higher the number of stones at presentation, more likely it was that a kidney stone would spontaneously pass over time without causing any symptoms.

Background: Kidney stones are a common health problem and are characterized by a high risk of recurrence.

Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study.

Background: Anastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study evaluates the feasibility of predicting AL using machine learning (ML) algorithms based on preoperative data.

Methods: We retrospectively analyzed data including 21 predictors from patients undergoing colorectal surgery with bowel anastomosis at four Swiss hospitals.

An analysis of virtual reality in abdominal surgery-A scoping review.

Background: The integration of virtual reality (VR) in surgery has gained prominence as VR applications have increased in popularity.

Methods: A scoping review was undertaken, gathering the most relevant sources, utilising a detailed literature search of medical and academic databases including EMBASE, PubMed, Cochrane, IEEE, Google Scholar, and the Google search engine.

Results: Of the 18 articles included, 7 focused on VR in colon surgery, 5 addressed VR in pancreas surgery, and the remaining 6 concentrated on VR in liver surgery.

Analysis of artificial intelligence in thyroid diagnostics and surgery: A scoping review.

Background: Artificial Intelligence provides numerous applications in the healthcare sector. The main aim of this study is to evaluate the extent of the current application of artificial intelligence in thyroid diagnostics.

Methods: Our protocol was based on the Scoping Reviews extension of the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA-ScR).

Development and validation of a predictive model of the hospital cost associated with bariatric surgery.

Hospitals are facing difficulties in predicting, evaluating, and managing cost-affecting parameters in patient treatments. Inaccurate cost prediction leads to a deficit in operational revenue. This study aims to determine the ability of Machine Learning (ML) algorithms to predict the cost of care in bariatric and metabolic surgery and develop a predictive tool for improved cost analysis.

Second Primary Cancer Among Patients With Papillary Thyroid Carcinoma Following the Chernobyl Disaster.

Importance: To our knowledge, there are no complete population-based studies of the risks of developing second malignant tumors after papillary thyroid carcinoma (PTC) in patients following the Chernobyl nuclear accident.

Objective: To study the risk of second primary cancers in patients with PTC after the Chernobyl disaster.

Design, Setting, And Participants: This was a retrospective cohort study conducted in the Republic of Belarus over a 31-year time frame evaluating patients with primary PTC and second malignant tumors.

Safety and efficacy of LA-ERCP procedure following Roux-en-Y gastric bypass: a systematic review and meta-analysis.

Introduction: Rapid weight loss following Roux-en-Y gastric bypass surgery (RYGB) translates to an increased need for endoscopic retrograde cholangiopancreatography (ERCP) intervention. Laparoscopically Assisted Transgastric ERCP (LA-ERCP) has emerged to address the issue of accessing the excluded stomach. This study aims to evaluate the safety and efficacy of LA-ERCP procedure following RYGB.

Machine learning in pancreas surgery, what is new? literature review.

Background: Machine learning (ML) is an inquiry domain that aims to establish methodologies that leverage information to enhance performance of various applications. In the healthcare domain, the ML concept has gained prominence over the years. As a result, the adoption of ML algorithms has become expansive.

Corrigendum: The development of machine learning in bariatric surgery.

[This corrects the article DOI: 10.3389/fsurg.2023.

Gastrointestinal Stromal Tumor (GIST): A Remarkable Case Report and Literature Review.

Gastrointestinal stromal tumor (GIST) makes up less than 1% of all gastrointestinal tumors, but it is the most common mesenchymal tumor of the digestive system. It is commonly found in the stomach and the small intestine and rarely seen in the colon and the esophagus. Additionally, sigmoid GIST is quite rare since colorectal GIST often occurs in the rectum.

The development of machine learning in bariatric surgery.

Background: Machine learning (ML), is an approach to data analysis that makes the process of analytical model building automatic. The significance of ML stems from its potential to evaluate big data and achieve quicker and more accurate outcomes. ML has recently witnessed increased adoption in the medical domain.

Developing and validating a multivariable prediction model for predicting the cost of colon surgery.

Hospitals are burdened with predicting, calculating, and managing various cost-affecting parameters regarding patients and their treatments. Accuracy in cost prediction is further affected when a patient suffers from other health issues that hinder the traditional prognosis. This can lead to an unavoidable deficit in the final revenue of medical centers.

Cost and Quality Comparison of Hernia Surgery in Stationary, Day-Patient and Outpatient Care.

Background: Medical progress is increasingly enabling more and more stationary treatment to be provided in the outpatient sector. This development should be welcomed, as healthcare costs have been rising for years. The design of efficient processes and a needs-based infrastructure enable further savings.

Haemophilus influenzae drug resistance in France from 2017 to 2021: consideration for treatment of otitis media.

Objectives: Haemophilus influenzae is a prevalent agent of respiratory infections, including acute otitis media (AOM), that lead to high antibiotic prescription and may contribute to the development of bacterial resistance to antibiotics. The objective of this work was to describe and analyse antibiotic resistance of H. influenzae from 2017 to 2021 in France.

The development of machine learning in lung surgery: A narrative review.

Background: Machine learning reflects an artificial intelligence that allows applications to improve their accuracy to predict outcomes, eliminating the need to conduct explicit programming on them. The medical field has increased its focus on establishing tools for integrating machine learning algorithms in laboratory and clinical settings. Despite their importance, their incorporation is minimal in the medical sector yet.

Suprapubic Cholecystectomy Improves Cosmetic Outcome Compared to Classic Cholecystectomy.

Currently, cholecystectomy is performed laparoscopically. While the conventional approach (CA) with four access ports persists, other methods seek to reduce trauma or to optimize cosmetic results. In this study, the safety and cosmetic outcome of a suprapubic approach (SA) were evaluated.

The Effects of Anastomotic Leaks on the Net Revenue from Colon Surgery.

Background: Complications in colon surgery can have severe health consequences, while at the same time, they are associated with increased costs. An anastomotic leak (AL) is associated with significantly increased costs compared to cases without. The aim of our analysis was to evaluate, which individual processes and patient-unrelated factors influencing the treatment process of colon surgery are responsible for the financial burden in patients with AL.

The Development of Artificial Intelligence in Hernia Surgery: A Scoping Review.

Background: Artificial intelligence simulates human intelligence in machines that have undergone programming to make them think like human beings and imitate their activities. Artificial intelligence has dominated the medical sector to perform various patient diagnosis activities and improve communication between professionals and patients. The main goal of this study is to perform a scoping review to evaluate the development of artificial intelligence in all forms of hernia surgery except the diaphragm and upside-down hernia.