Objectives: Reducing adverse drug events, including those resulting from drug-drug interactions, will be a health safety issue of increasing importance for dental practitioners in the coming decades as greater numbers of older adults seek oral health care. The purpose of this study was to identify prescription drugs with the potential for serious interactions and estimate prevalent use among older adults visiting the dentist.
Study Design: The Medicare Current Beneficiary Survey is an ongoing series of nationally representative surveys of Medicare beneficiaries. Potentially serious drug interactions were selected with the use of published work by Partnership to Prevent Drug-Drug Interactions. Drug interactions were identified and prevalence estimates made for community-dwelling older adults visiting the dentist. Analyses were completed to test associations between sociodemographic and health-related variables and the use of prescription drugs with the potential for serious interactions.
Results: Overall, 3.4% of those visiting the dentist were estimated to have been prescribed drugs with the potential for a serious drug interaction. Drugs commonly prescribed in dentistry with the potential for serious interactions include the benzodiazepines, macrolide antibiotics, and nonsteroidal antiinflammatory analgesics.
Conclusions: Understanding potentially harmful drug combinations, their clinical consequences, and the frequency with which implicated drugs are being prescribed will assist practitioners in clinically managing patients and avoiding inappropriate prescribing.
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http://dx.doi.org/10.1016/j.tripleo.2011.03.048 | DOI Listing |
Virol J
January 2025
Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, 130122, People's Republic of China.
Monkeypox virus (MPXV) is an important zoonotic pathogenic virus, which poses serious threats to public health. MPXV infection can be prevented by immunization against the variola virus. Because of the safety risks and side effects of vaccination with live vaccinia virus (VACV) strain Tian Tan (VTT), we constructed two gene-deleted VTT recombinants (TTVAC7 and TTVC5).
View Article and Find Full Text PDFAnal Chim Acta
February 2025
Food Inspection and Quarantine Technology Center of Shenzhen Customs, Shenzhen Academy of Inspection and Quarantine, Shenzhen, 518045, PR China.
Background: Ochratoxin A (OTA) is toxic secondary metabolites produced by fungi and can pose a serious threat to food safety and human health. Due to the high stability and toxicity, OTA contamination in agricultural products is of great concern. Therefore, the development of a highly sensitive and reliable OTA detection method is crucial to ensure food safety.
View Article and Find Full Text PDFAnal Chim Acta
February 2025
Institute for Advanced Study (IAS), College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, Guangdong, 518060, China. Electronic address:
Background: Alzheimer's disease (AD) is a neurodegenerative disorder with a very long duration, posing a serious threat to people's life and health. To date, no medicine that can cure or reverse the disease has been developed or reported, so early diagnosis and timely intervention are essential. The concentration of Phosphorylated tau181 (P-tau181) in blood has been approved by FDA as a standard for assisting clinical diagnosis of AD.
View Article and Find Full Text PDFLancet Neurol
February 2025
Department of Neurology, International University of Health and Welfare, Narita, Japan.
Background: Evidence from preclinical studies suggests that IL-6 signalling has the potential to modulate immunopathogenic mechanisms upstream of autoantibody effector mechanisms in patients with generalised myasthenia gravis. We aimed to assess the safety and efficacy of satralizumab, a humanised monoclonal antibody targeting the IL-6 receptor, in patients with generalised myasthenia gravis.
Methods: LUMINESCE was a randomised, double-blind, placebo-controlled, multicentre, phase 3 study at 105 sites, including hospitals and clinics, globally.
Mar Pollut Bull
January 2025
JK Laxmipat University, Jaipur, Rajasthan, India.
Marine pollution due to oil spills presents major risks to coastal areas and aquatic life, leading to serious environmental health concerns. Oil Spill detection using SAR data has transitioned from traditional segmentation to a variety of machine learning & deep learning models like UNET proving its efficiency for the task. This research paper proposes a GSCAT-UNET model for efficient oil spill detection and discrimination from lookalikes.
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