Objectives: This study was aimed to assess the type, prevalence, characteristics of drug interaction and factors associated from admitted patients in medical wards at primary, district and referral hospitals in East Gojjam Zone, Amhara Regional State, Ethiopia.
Methods: A facility-based retrospective cross-sectional study design was conducted among admitted patients in medical wards at different hospitals of East Gojjam Zone from September 2019 to February 2020. Patient-specific data were extracted from patient medical prescription papers using a structured data collection tool. Potential drug-drug interaction was identified using www.drugs.com as drug-drug interaction checker. Data were analyzed using SPSS version 23.0. To identify the explanatory predictors of potential drug-drug interaction, logistic regression analysis was done at a statistical significance level of -value < 0.05.
Results: Of the total 554 prescriptions, 51.1% were prescribed for females with a mean (±standard deviation) age of 40.85 ± 23.09 years. About 46.4% prescriptions of patients had one or more comorbid conditions, and the most frequent identified comorbid conditions were infectious (18.6%) and cardiac problems (6.3%) with 0.46 ± 0.499 average number of comorbid conditions per patient. Totally, 1516 drugs were prescribed with 2.74 ± 0.848 mean number per patient and range of 2-6. Two hundred and forty-two (43.7%) prescriptions had at least one potential drug-drug interaction, and it was found that 292 drug interactions were presented. Almost half of the drug-drug interaction identified was moderate (50%). Overall, the prevalence rate of drug-drug interaction was 43.7%. Older age (adjusted odds ratio = 8.301; 95% confidence interval (5.51-12.4), = 0.000), presence of comorbidities (adjusted odds ratio = 1.72; 95% confidence interval (1.10-2.68), = 0.000) and number of medications greater or equal to 3 (adjusted odds ratio = 2.69; 95% confidence interval (1.42-5.11), = 0.000) were independent predictors for the occurrence of potential drug-drug interaction.
Conclusion: The prevalence of potential drug-drug interaction among admitted patients was relatively high. Pharmacodynamic drug-drug interaction was the common mechanism of drug-drug interaction with moderate degree. Therefore, close follow-up of hospitalized patients is highly recommended.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312158 | PMC |
| http://dx.doi.org/10.1177/20503121211035050 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the formation of amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs) composed of tau aggregates. Research in animal models has generated hypotheses on the underlying mechanisms of the interaction between Aβ and tau pathology. In support of this interaction, results from clinical trials have shown that treatment with anti-Aβ monoclonal antibodies (mAbs) affects tau pathology.
View Article and Find Full Text PDFBackground: The therapeutic management of dementia with Lewy bodies (LBD) is a challenge given the high sensitivity to drugs in this disease. This is particularly sensitive with regard to the management of parkinsonism. In particular, treatment of motor symptoms with levodopa or dopaminergic agonists poses a risk of worsening cognitive and behavioral symptoms.
View Article and Find Full Text PDFBackground: Immunotherapy of Alzheimer's disease (AD) is a promising approach to reducing the accumulation of beta-amyloid, a critical event in the onset of the disease. Targeting the group II metabotropic glutamate receptors, mGluR2 and mGluR3, could be important in controlling Aβ production, although their respective contribution remains unclear due to the lack of selective tools.
Method: 5xFAD mice were chronically treated by a brain penetrant camelid single domain antibody (VHH or nanobody) that is an activator of mGluR2.
Drug Development.
Alzheimers Dement
December 2024
Columbia University Irving Medical Center, New York, NY, USA.
Background: Genetic studies indicate a causal role for microglia, the innate immune cells of the central nervous system (CNS), in Alzheimer's disease (AD). Despite the progress made in identifying genetic risk factors, such as CD33, and underlying molecular changes, there are currently limited treatment options for AD. Based on the immune-inhibitory function of CD33, we hypothesize that inhibition of CD33 activation may reverse microglial suppression and restore their ability to resolve inflammatory processes and mitigate pathogenic amyloid plaques, which may be neuroprotective.
View Article and Find Full Text PDFDrug Development.
Alzheimers Dement
December 2024
The University of Texas Health Science Center at Houston, Houston, TX, USA.
Background: Developing drugs for treating Alzheimer's disease (AD) has been extremely challenging and costly due to limited knowledge on underlying biological mechanisms and therapeutic targets. Repurposing drugs or their combination has shown potential in accelerating drug development due to the reduced drug toxicity while targeting multiple pathologies.
Method: To address the challenge in AD drug development, we developed a multi-task machine learning pipeline to integrate a comprehensive knowledge graph on biological/pharmacological interactions and multi-level evidence on drug efficacy, to identify repurposable drugs and their combination candidates RESULT: Using the drug embedding from the heterogeneous graph representation model, we ranked drug candidates based on evidence from post-treatment transcriptomic patterns, mechanistic efficacy in preclinical models, population-based treatment effect, and Phase 2/3 clinical trials.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!