Machine Learning Risk Prediction Model of 90-day Mortality After Gastrectomy for Cancer.

Objective: To develop and validate a risk prediction model of 90-day mortality (90DM) using machine learning in a large multicenter cohort of patients undergoing gastric cancer resection with curative intent.

Background: The 90DM rate after gastrectomy for cancer is a quality of care indicator in surgical oncology. There is a lack of well-validated instruments for personalized prognosis of gastric cancer.

Textbook outcome and survival after gastric cancer resection with curative intent: A population-based analysis.

Background: The concept of textbook outcome (TO) has been proposed for analyzing quality of surgical care. This study assessed the incidence of TO among patients undergoing curative gastric cancer resection, predictors for TO achievement, and the association of TO with survival.

Method: All patients with gastric and gastroesophageal junction cancers undergoing curative gastrectomy between January 2014-December 2017 were identified from a population-based database (Spanish EURECCA Registry).

Evaluation of data quality in the Spanish EURECCA Esophagogastric Cancer Registry.

Background: Although the number of nationwide clinical registries in upper gastrointestinal cancer is increasing, few of them perform regular clinical audits. The Spanish EURECCA Esophagogastric Cancer Registry (SEEGCR) was launched in 2013. The aim of this study was to assess the reliability of the data in terms of completeness and accuracy.

Mechanical intestinal obstruction secondary to congenital diaphragmatic hernia in an adult. Report of a case.

We present a case of congenital diaphragmatic hernia diagnosed in an adult. It is a kind of exceptional pathology outside the pediatric age with few cases reported in the literature. Its presentation is unusual, especially in the form of mechanical intestinal obstruction, requiring surgical treatment.