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Predicting lack of clinical improvement following varicose vein ablation using machine learning.
J Vasc Surg Venous Lymphat Disord
December 2024
Department of Surgery, University of Toronto, Canada; Division of Vascular Surgery, St. Michael's Hospital, Unity Health Toronto, Canada; Institute of Medical Science, University of Toronto, Canada; Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM), University of Toronto, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Canada; Department of Surgery, King Faisal Specialist Hospital and Research Center, Saudi Arabia. Electronic address:
Objective: Varicose vein ablation is generally indicated in patients with active/healed venous ulcers. However, patient selection for intervention in individuals without venous ulcers is less clear. Tools that predict lack of clinical improvement (LCI) following vein ablation may help guide clinical decision-making but remain limited.
View Article and Find Full Text PDFConstruction and validation of a predictive model for the risk of rebleeding in patients with esophageal and gastric varices hemorrhage.
BMC Gastroenterol
December 2024
Department of Gastroenterology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning Province, 116011, China.
Background And Purpose: Esophageal and gastric varices hemorrhage (EGVH) is a life-threatening condition with the 6-week mortality rate of 15-25%. Up to 60% of patients with EGVH may experience rebleeding with a mortality rate of 33%. The existing scoring systems, such as RS scoring system (Rockall score, RS) and GBS scoring system (Glasgow-Blatchford score, GBS), have limitations in predicting the risk of rebleeding.
View Article and Find Full Text PDFApplication of machine learning methods for predicting esophageal variceal bleeding in patients with cirrhosis.
Eur Radiol
December 2024
Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Objective: To develop and compare machine learning models based on CT morphology features, serum biomarkers, and basic physical conditions to predict esophageal variceal bleeding.
Materials And Methods: Two hundred twenty-four cirrhotic patients with esophageal variceal bleeding and non-bleeding were included in the retrospective study. Clinical and serum biomarkers were used in our study.
Analysis of risk factors and establishment of prediction model for lower extremity deep vein thrombosis after lumbar fusion surgery.
BMC Surg
December 2024
Department of Orthopedics, Qilu Hospital of Shandong University, Jinan, 250012, PR, China.
Background: Lower extremity deep vein thrombosis (LEDVT) is a common complication after orthopedic surgery. Currently, a reliable assessment tool is lacking to evaluate the risk of postoperative LEDVT in patients undergoing lumbar fusion surgery. This study aims to explore the risk factors for LEDVT formation after lumbar fusion surgery and establish a predictive model for it.
View Article and Find Full Text PDFABC score is a better predictor for 30-day mortality in upper gastrointestinal bleeding: A prospective single-center study.
Indian J Gastroenterol
December 2024
Department of Gastroenterology and Hepatology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, 576 104, India.
Background: Acute upper gastrointestinal bleeding (UGIB) still has a mortality rate of about 10%. Several pre-endoscopy scoring systems have been developed to predict the outcome, but none accurately predict mortality. The present study was aimed at comparing the new ABC score (age, blood tests and comorbidities) with other pre-existing scoring systems to predict mortality.
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