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Endodontic emergency patients' profile and treatment outcome - a prospective cohort study.
BMC Oral Health
December 2024
Department of Clinical Dentistry Section of Endodontics, The Faculty of Medicine, University of Bergen, Bergen, Norway.
Background: Toothache is a debilitating condition, often with mild to excruciating pain, swelling, eating difficulties and insomnia. This study aims to delineate the profiles of patients seeking emergency dental care, focusing on the diagnosis, treatment, and outcomes following non-surgical root canal treatment.
Methods: This prospective cohort study was conducted from 2012 to 2021 at the Section for Endodontics, Department of Clinical Dentistry, University of Bergen, Norway.
QCL Infrared Spectroscopy Combined with Machine Learning as a Useful Tool for Classifying Acetaminophen Tablets by Brand.
Molecules
July 2024
Área Básicas Exactas, Universidad del Sinú, Seccional Cartagena, Cartagena 130015, Colombia.
The development of new methods of identification of active pharmaceutical ingredients (API) is a subject of paramount importance for research centers, the pharmaceutical industry, and law enforcement agencies. Here, a system for identifying and classifying pharmaceutical tablets containing acetaminophen (AAP) by brand has been developed. In total, 15 tablets of 11 brands for a total of 165 samples were analyzed.
View Article and Find Full Text PDFPredicting delirium and the effects of medications in hospitalized COVID-19 patients using machine learning: A retrospective study within the Korean Multidisciplinary Cohort for Delirium Prevention (KoMCoDe).
Digit Health
January 2024
Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea.
Objective: Delirium is commonly reported from the inpatients with Coronavirus disease 2019 (COVID-19) infection. As delirium is closely associated with adverse clinical outcomes, prediction and prevention of delirium is critical. We developed a machine learning (ML) model to predict delirium in hospitalized patients with COVID-19 and to identify modifiable factors to prevent delirium.
View Article and Find Full Text PDFThe Effectiveness of Paracetamol to Reduce the Post-Vaccination SARS-CoV-2 Adverse Effects in an Italian Vaccination Center.
Vaccines (Basel)
September 2023
Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy.
The arrival of specific vaccines was crucial for the eradication of COVID-19. Despite the security of the vaccination, the administration of COVID-19 mRNA vaccines often causes systemic side effects for a short time after the injection, such as headache, fatigue, fever, muscle pain and nausea. These side effects can limit the adherence to COVID-19 vaccines administration, especially in healthcare workers.
View Article and Find Full Text PDFThe Skeletal Oncology Research Group Machine Learning Algorithm (SORG-MLA) for predicting prolonged postoperative opioid prescription after total knee arthroplasty: an international validation study using 3,495 patients from a Taiwanese cohort.
BMC Musculoskelet Disord
July 2023
Department of Orthopaedic Surgery, National Taiwan University Hospital, No.7 Chung-Shan South Road, Taipei, 10002, Taiwan.
Background: Preoperative prediction of prolonged postoperative opioid use (PPOU) after total knee arthroplasty (TKA) could identify high-risk patients for increased surveillance. The Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) has been tested internally while lacking external support to assess its generalizability. The aims of this study were to externally validate this algorithm in an Asian cohort and to identify other potential independent factors for PPOU.
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