Purpose: Multi-dose drug dispensing (MDD) is a dosing aid that provides patients with disposable bags containing all drugs intended for 1 dosing moment. MDD is believed to increase medication adherence, but studies are based on self-reported data, and results may depend on socially desirable answers. Therefore, our purpose was to determine the effect of MDD on medication adherence in non-adherent patients taking vitamin K antagonists (VKAs), and to compare with instructing patients on medication use.
Methods: We conducted a before-after study in non-adherent patients where MDD was the exposure and change in adherence after MDD initiation was the outcome (within patient comparison). Time in therapeutic range (TTR) was selected as a measure for adherence, as this reflects stability of VKA treatment. To analyze whether MDD improved adherence as compared with standard care (ie, letters or calls from nurses of the anticoagulation clinic), non-adherent patients without MDD were also followed to estimate their TTR change over time (between patient comparison).
Results: Eighty-three non-adherent VKA patients started using MDD. The median TTR was 63% before MDD and 73% 6 months after MDD. The within patient TTR increased on average by 13% (95%CI 6% to 21%) within 1 month after starting MDD and remained stable during the next 5 months. The TTR of MDD-patients increased 10% (95%CI 2% to 19%) higher as compared with non-MDD patients within 1 month but was similar after 4 months (TTR difference 3%, 95%CI -2% to 9%).
Conclusions: Adherence improved after initiation of MDD. Compared with instructing patients, MDD was associated with better adherence within 1 month but was associated with similar improvement after 4 months.
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http://dx.doi.org/10.1002/pds.4346 | DOI Listing |
Appl Neuropsychol Adult
January 2025
Faculty Xavier Institute of Engineering, Mahim, India.
In the fields of engineering, science, technology, and medicine, artificial intelligence (AI) has made significant advancements. In particular, the application of AI techniques in medicine, such as machine learning (ML) and deep learning (DL), is rapidly growing and offers great potential for aiding physicians in the early diagnosis of illnesses. Depression, one of the most prevalent and debilitating mental illnesses, is projected to become the leading cause of disability worldwide by 2040.
View Article and Find Full Text PDFNaunyn Schmiedebergs Arch Pharmacol
January 2025
Graduate School of PLA Medical College, Chinese PLA General Hospital and PLA Medical College, 28 Fu Xing Road, Beijing, 100083, China.
Extensive researches illuminate a potential interplay between immune traits and psychiatric disorders. However, whether there is the causal relationship between the two remains an unresolved question. We conducted a two-sample bidirectional mendelian randomization by utilizing summary data of 731 immune cell traits from genome-wide association studies (GCST90001391-GCST90002121)) and 11 psychiatric disorders including attention deficit/hyperactivity disorder (ADHD), anxiety disorder, autism spectrum disorder (ASD), bipolar disorder (BIP), anorexia nervosa (AN), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), Tourette syndrome (TS), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), and substance use disorders (cannabis) (SUD) from the Psychiatric Genomics Consortium (PGC).
View Article and Find Full Text PDFBrain Behav Immun Health
February 2025
Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases-IRCAD, University of Eastern Piedmont, 28100, Novara, Italy.
Major Depressive Disorder (MDD) is a widespread psychiatric condition impacting social and occupational functioning, making it a leading cause of disability. The diagnosis of MDD remains clinical, based on the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 criteria, as biomarkers have not yet been validated for diagnostic purposes or as predictors of treatment response. Traditional treatment strategies often follow a one-size-fits-all approach obtaining suboptimal outcomes for many patients who fail to experience response or recovery.
View Article and Find Full Text PDFNiger Med J
January 2025
Department of Physiology, RUHS College of Medical Sciences, India.
Background: Previous research has shown that Major Depressive Disorder (MDD) is accompanied by severe impairments in cognitive and autonomic processes, which may linger even when mood symptoms recover. This study aimed to analyse the relationship between depression severity, as measured by the Hamilton Depression Rating Scale (HAM-D), and how it affects heart rate variability (HRV) and cognitive function in patients with Major Depressive Disorder (MDD).
Methodology: The cross-sectional study was conducted at RUHS College of Medical Sciences and Associated Hospitals, Jaipur, from July 2022 to January 2023 on 90 subjects having major depressive disorder (MDD) of either sex in the 20-40 age group using the Hamilton score for depression (HAM D), Heart Rate Variability (HRV) measurements, and a battery of cognitive tests.
Ann Gen Psychiatry
January 2025
National Directorate-General for Hospitals, Budapest, Hungary.
Objective: This study examined mental health literacy and predictors of disorder recognition among primary care providers (PCPs) in Hungary.
Methods: 208 PCPs in Hungary completed a survey assessing demographics, mental health stigma, and exposure to mental health (i.e.
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