Background And Aims: Poor adherence to medications is a major health concern especially among older subjects. To plan future studies to improve adherence, an epidemiological study, called "Fiesole Misurata", was conducted. The aim of the present paper was to verify the representativeness of the database in evaluating the AntiHyperTensives (AHTs)-taking behaviour.
Methods: Demographic records of all subjects aged ≥65 years (n = 2,228) living in the community of Fiesole (Florence, Italy) was retrieved from the Registry Office of Fiesole Municipality. The corresponding healthcare records were obtained from administrative archives of the Local Health Authority (claim dataset). Moreover, a cohort of subjects aged ≥65 years (n = 385) living in the community was screened by means of a multidimensional geriatric evaluation (cross-sectional dataset).
Results: In claim dataset, biyearly prevalences of hospitalization for ischemic cardiomyopathy, heart failure, and stroke were 3.7, 3.0, and 3.2%, respectively. In the cross-sectional dataset, prevalences were 11.2, 6.7, and 7.1%, respectively. The most used drugs were angiotensin-converting enzyme inhibitors (43.6% in the claim dataset, 45.3% in the cross-sectional dataset) and diuretics (35.6% and 47.0%, respectively). Among the incident users of AHTs, 63.5% was highly adherent (≥80%) over the first 6 months of follow-up, while 14.3 and 22.2% were intermediate (40-79%) and low (<40%) adherent. The percentage of high adherers decreased with time and reached 31.2% at the 24th month.
Conclusions: These findings indicate that "Fiesole Misurata" study database can be used to develop future strategies aimed at improving the adherence to AHTs in older individuals.
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Sci Data
January 2025
Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Large language models (LLMs) have the potential to enhance the verification of health claims. However, issues with hallucination and comprehension of logical statements require these models to be closely scrutinized in healthcare applications. We introduce CliniFact, a scientific claim dataset created from hypothesis testing results in clinical research, covering 992 unique interventions for 22 disease categories.
View Article and Find Full Text PDFBMJ Open
December 2024
PMV Research Group, Medical Faculty and University Hospital Cologne, University of Cologne, Koln, Germany
Introduction: In Germany, there has been no population-level pharmacoepidemiological study on the safety of the COVID-19 vaccines. One factor preventing such a study so far relates to challenges combining the different relevant data bodies on vaccination with suitable outcome data, specifically statutory health insurance claims data. Individual identifiers used across these data bodies are of unknown quality and reliability for data linkage.
View Article and Find Full Text PDFJ Affect Disord
January 2025
Division of Molecular Epidemiology, Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8573, Japan; Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8573, Japan; Department of Pharmaceutical Sciences, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan. Electronic address:
Background: As multiple Japanese academic societies have recently issued treatment guidelines for perinatal antidepressant treatments, it is considered worthwhile to evaluate the latest trends and continuation of antidepressant medication during pregnancy to optimize antenatal prescriptions.
Methods: The prevalence, trend, and continuation of antidepressant use during pregnancy in Japan from 2012 to 2023 were evaluated, using a large administrative claims database, in women whose pregnancies ended in live births. Annual changes were evaluated using a multivariate logistic regression model adjusted for maternal age at delivery.
Diabetes Ther
January 2025
Eli Lilly and Company, Indianapolis, IN, USA.
Introduction: The study objective was to describe characteristics and utilization patterns of tirzepatide users with type 2 diabetes (T2D) using the Healthcare Integrated Research Database in the USA.
Methods: Adults (≥18 years) included had T2D diagnosis; ≥1 tirzepatide claim (May 2022-January 2023; first claim date = index date); and continuous medical and pharmacy enrollment during the 6-month baseline and follow-up periods from the index date. Baseline demographics, clinical characteristics, and 6-month follow-up dosing and treatment patterns were summarized descriptively.
Neuroinformatics
January 2025
Institute of Biophotonics, National Yang Ming Chiao Tung University, 155, Sec. 2, Li-Nong St. Beitou Dist, Taipei, 112304, Taiwan.
Background: Meningioma, the most common primary brain tumor, presents significant challenges in MRI-based diagnosis and treatment planning due to its diverse manifestations. Convolutional Neural Networks (CNNs) have shown promise in improving the accuracy and efficiency of meningioma segmentation from MRI scans. This systematic review and meta-analysis assess the effectiveness of CNN models in segmenting meningioma using MRI.
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