Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Development and validation of an EHR-based risk prediction model for geriatric patients undergoing urgent and emergency surgery.
BMC Anesthesiol
January 2025
Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA, 94612, USA.
Background: Clinical determination of patients at high risk of poor surgical outcomes is complex and may be supported by clinical tools to summarize the patient's own personalized electronic health record (EHR) history and vitals data through predictive risk models. Since prior models were not readily available for EHR-integration, our objective was to develop and validate a risk stratification tool, named the Assessment of Geriatric Emergency Surgery (AGES) score, predicting risk of 30-day major postoperative complications in geriatric patients under consideration for urgent and emergency surgery using pre-surgical existing electronic health record (EHR) data.
Methods: Patients 65-years and older undergoing urgent or emergency non-cardiac surgery within 21 hospitals 2017-2021 were used to develop the model (randomly split: 80% training, 20% test).
Triglyceride-glucose index in predicting the risk of new-onset diabetes in the general population aged 45 years and older: a national prospective cohort study.
BMC Endocr Disord
January 2025
Department of Endocrinology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110033, China.
Objective: Insulin resistance (IR) is often present in diabetes, which imposes a heavy burden on the prevention and treatment of diabetes. Triglyceride glucose index (TyG) is simple, reliable and reproducible in detecting IR, and has great advantages in predicting the risk of diabetes. The aim of this study was to analyze the potential association between TyG and the risk of diabetes in Chinese middle-aged and older adults using a prospective cohort study design.
View Article and Find Full Text PDFRationale and design of the multicenter, national, randomized, open labeled phase III trial: allogeneic stem cell transplantation as a potential curative treatment for patients with relapsed or progressed multiple myeloma (AlloRelapseMM Study).
BMC Cancer
January 2025
Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Background: Even though major improvements have been made in the treatment of myeloma, the majority of patients eventually relapse or progress. Patients with multiple myeloma who relapse after initial high-dose chemotherapy with autologous stem cells have a median progression free survival up to 2-3 years, depending on risk factors such as previous remission duration. In recent years, growing evidence has suggested that allogeneic stem cell transplantation could be a promising treatment option for patients with relapsed or progressed multiple myeloma.
View Article and Find Full Text PDFInfluence of two different printing methods on the accuracy of full-guided implant insertion - a laboratory study in undergraduate dental students.
BDJ Open
January 2025
Department of Oral and Maxillofacial Surgery (Head: Prof. Dr. Dr. Bernd Lethaus), University Hospital Tübingen, Eberhard Karls Universität Tübingen, Osianderstr. 2-8, D-72076, Tübingen, Germany.
Objectives: The aim of the present study was to compare the accuracy of fully guided implant insertion in vitro achieved by two fabrication methods in a cohort of undergraduates. We hypothesized that both methods achieve a comparable accuracy.
Methods: Surface scans and cone beam computed tomography images of 48 mandibular models were matched.
Accuracy of Current Large Language Models and The Retrieval Augmented Generation Model in Determining Dietary Principles in Chronic Kidney Disease.
J Ren Nutr
January 2025
Assistant professor, Department of Electrical and Electronics Engineering, Faculty of Engineering and Architecture, Burdur Mehmet Akif Ersoy University, Burdur, Türkiye.
Objective: Large Language Models (LLMs) have emerged as powerful tools with significant potential for quickly accessing information in the nutrition and health, as in many fields. Retrieval augmented generation (RAG) has been included among artificial intelligence (AI) powered chatbot structures as a framework developed to increase the accuracy and ability of LLMs. This study aimed to evaluate the accuracy of LLMs (GPT4, Gemini, and Llama) and RAG in determining dietary principles in chronic kidney disease.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!