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ChatGPT vs Expert-Guided Care Pathways for Postesophagectomy Symptom Management.
Ann Thorac Surg Short Rep
December 2024
Department of Surgery, Baylor College of Medicine, Houston, Texas.
Background: The objective of this study was to compare generative artificial intelligence-initiated care pathways, using ChatGPT, with expert-guided consensus-initiated care pathways from AskMayoExpert (AME) for symptom management of esophageal cancer patients after esophagectomy.
Methods: A formal protocol for development of 9 AME care pathways was followed for specific patient-identified domains after esophagectomy for esophageal cancer. Domain scores were measured and assessed through the Upper Digestive Disease tool.
Presenting Symptoms Define Time to Diagnosis in Degenerative Cervical Myelopathy: Process Mapping From a Musculoskeletal Triage Unit in the UK.
Musculoskeletal Care
March 2025
Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Study Design: Retrospective cohort study.
Objective: Tackling delayed diagnosis in degenerative cervical myelopathy (DCM) is a global research priority. On average, it takes 2-5 years, leading to worse outcomes from surgery and greater disability.
A data management system for precision medicine.
PLOS Digit Health
January 2025
Clinical Care & Research, ORTEC B.V., Zoetermeer, The Netherlands.
Precision, or personalised medicine has advanced requirements for medical data management systems (MedDMSs). MedDMS for precision medicine should be able to process hundreds of parameters from multiple sites, be adaptable while remaining in sync at multiple locations, real-time syncing to analytics and be compliant with international privacy legislation. This paper describes the LogiqSuite software solution, aimed to support a precision medicine solution at the patient care (LogiqCare), research (LogiqScience) and data science (LogiqAnalytics) level.
View Article and Find Full Text PDFMulti-modal prediction of extracorporeal support-a resource intensive therapy, utilizing a large national database.
JAMIA Open
February 2025
Artificial Intelligence (AI) for Health Institute (AIHealth), Washington University in St Louis, St Louis, MO 63130, United States.
Objective: Extracorporeal membrane oxygenation (ECMO) is among the most resource-intensive therapies in critical care. The COVID-19 pandemic highlighted the lack of ECMO resource allocation tools. We aimed to develop a continuous ECMO risk prediction model to enhance patient triage and resource allocation.
View Article and Find Full Text PDFDelays in getting injured patients to hospital in a timely manner can increase avoidable death and disability. Like many low- or middle-income countries (LMICs), Rwanda experiences delays related to lack of efficient prehospital communication and formal guidelines to triage patients for hospital care. This paper describes the protocol to develop, roll out, and evaluate the effectiveness of a Destination Decision Support Algorithm (DDSA) integrated in an electronic communication platform, '912Rwanda'.
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