Background And Objective: Adherence is essential in antiviral therapy for chronic hepatitis C. We investigated the effect of real-time medication monitoring on adherence to ribavirin.
Methods: In this randomized controlled trial, patients in the intervention group received a medication dispenser that monitored ribavirin intake real-time during 24 weeks PEG-interferon/ribavirin±boceprevir or telaprevir. Patients in the control group received standard-of-care. Adherence was also measured by pill count.
Results: Seventy-two patients were assigned to either intervention (n=35) or control groups (n=37). Median adherence by pill count was 96% (range: 43%-100%) with 30 (94%) of patients exhibiting≥80% adherence. Perfect adherence (i.e. 100%) was similar in intervention and control groups: 22 (85%) vs. 15 (75%) (P=0.47). Adherences by real-time medication monitoring and by pill count did not correlate (R=0.19, P=0.36). No predictors of poor adherence could be identified. Ribavirin trough levels after 8 weeks (median: 2.4 vs. 2.7mg/L, P=0.30) and 24 weeks (median: 3.0 vs. 3.0mg/L, P=0.69), and virological responses did not differ between intervention and control groups.
Conclusions: Adherence to ribavirin during PEG-interferon containing therapy in chronic hepatitis C is high. Real-time medication monitoring did not influence adherence to ribavirin, plasma ribavirin levels or virological responses.
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http://dx.doi.org/10.1016/j.clinre.2015.12.014 | DOI Listing |
Mol Neurobiol
January 2025
Department of Anesthesiology, Yijishan Hospital, First Affiliated Hospital of Wannan Medical College, Wuhu, 241004, China.
Stroke is the second-leading global cause of death. The damage attributed to the immune storm triggered by ischemia-reperfusion injury (IRI) post-stroke is substantial. However, data on the transcriptomic dynamics of pyroptosis in IRI are limited.
View Article and Find Full Text PDFJACC Clin Electrophysiol
December 2024
Physiology, Amsterdam Cardiovascular Sciences, Heart Failure, and Arrhythmias, Amsterdam University Medical Center, location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. Electronic address:
Background: Atrial fibrillation (AF) persistence is associated with molecular remodeling that fuels electrical conduction abnormalities in atrial tissue. Previous research revealed DNA damage as a molecular driver of AF.
Objectives: This study sought to explore the diagnostic value of DNA damage in atrial tissue and blood samples as an indicator of the prevalence of electrical conduction abnormalities and stage of AF.
J Wound Care
January 2025
Division of Plastic Surgery, Integrated Burn & Wound Care Center, Department of Surgery, Shuang-Ho Hospital, New Taipei City, Taiwan.
Objective: Deep sternal wound infection (DSWI) is a rare but devastating complication that is estimated to occur in 1-2% of patients after median sternotomy. Current standard of care (SoC) comprises antibiotics, debridement and negative pressure wound therapy (NPWT). Hyperbaric oxygen therapy (HBOT) appears to be an effective adjuvant therapy for osteomyelitis.
View Article and Find Full Text PDFBMJ Open Diabetes Res Care
December 2024
The Australian Centre for Behavioural Research in Diabetes, Diabetes Victoria, Carlton, Victoria, Australia.
Introduction: This analysis aimed to investigate diabetes-specific psychological outcomes among adults with type 1 diabetes (T1D) using hybrid closed-loop (HCL) versus standard therapy.
Research Design And Methods: In this multicenter, open-label, randomized, controlled, parallel-group clinical trial, adults with T1D were allocated to 26 weeks of HCL (MiniMed™ 670G) or standard therapy (insulin pump or multiple daily injections without real-time continuous glucose monitoring). Psychological outcomes (awareness and fear of hypoglycemia; and diabetes-specific positive well-being, diabetes distress, diabetes treatment satisfaction, and diabetes-specific quality of life (QoL)) were measured at enrollment, mid-trial and end-trial.
Sensors (Basel)
January 2025
Industrial Systems Institute, Athena Research and Innovation Center, 26504 Patras, Greece.
Object detection is a pivotal research domain within computer vision, with applications spanning from autonomous vehicles to medical diagnostics. This comprehensive survey presents an in-depth analysis of the evolution and significant advancements in object detection, emphasizing the critical role of machine learning (ML) and deep learning (DL) techniques. We explore a wide spectrum of methodologies, ranging from traditional approaches to the latest DL models, thoroughly evaluating their performance, strengths, and limitations.
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