Objective: To detect the frequency of potential drug-drug interactions (DDIs) in an outpatient group of elderly people in 6 European countries, as well as to describe differences among countries.
Data Sources And Methods: Drug use data were collected from 1601 elderly persons living in 6 European countries. The study population participated in a controlled intervention study over 18 months investigating the impact of pharmaceutical care. Potential DDIs were studied using a computerized detection program.
Results: The elderly population used on average 7.0 drugs per person; 46% had at least 1 drug combination possibly leading to a DDI. On average, there were 0.83 potential DDIs per person. Almost 10% of the potential DDIs were classified to be avoided according to the Swedish interaction classification system, but nearly one-third of them were to be avoided only for predisposed patients. The risk of subtherapeutic effect as a result of a potential DDI was as common as the risk of adverse reactions. Furthermore, we found differences in the frequency and type of potential DDIs among the countries.
Conclusions: Potential DDIs are common in elderly people using many drugs and are part of a normal drug regimen. Some combinations are likely to have negative effects; more attention must be focused on detecting and monitoring patients using such combinations. As differences in potential DDIs among countries were found, the reasons for this variability need to be explored in further studies.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1345/aph.1A484 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Drug-Drug Interactions Between HIV Antivirals and Concomitant Drugs in HIV Patients: What We Know and What We Need to Know.
Pharmaceutics
December 2024
Clinical Pharmacology Unit, San Giovanni di Dio e Ruggi d'Aragona University Hospital, 84131 Salerno, Italy.
Highly active antiretroviral therapy has led to a significant increase in the life expectancy of people living with HIV. The trade-off is that HIV-infected patients often suffer from comorbidities that require additional treatment, increasing the risk of Drug-Drug Interactions (DDIs), the clinical relevance of which has often not been determined during registration trials of the drugs involved. Therefore, it is important to identify potential clinically relevant DDIs in order to establish the most appropriate therapeutic approaches.
View Article and Find Full Text PDFHow Often Is Rifampin Therapy Initiated and Completed in Patients With Periprosthetic Joint Infections?
Clin Orthop Relat Res
January 2025
Department of Medicine, Duke University, Durham, NC, USA.
Background: Rifampin therapy is indicated for the treatment of staphylococcal periprosthetic joint infection (PJI) in patients who have undergone debridement, antibiotics, and implant retention (DAIR) or one-stage revision as per the Infectious Diseases Society of America (IDSA) guideline. Given the well-established effectiveness of rifampin as adjunctive therapy in staphylococcal PJI, it is crucial to evaluate its utilization in practice and identify factors that contribute to its underuse or incomplete administration, as these deviations may undermine treatment efficacy and patient outcomes.
Questions/purposes: Among patients who met clear indications for rifampin use having undergone DAIR or one-stage revision for staphylococcal PJI, (1) what proportion of patients did not receive it? (2) What proportion of patients started it but did not complete the planned course? (3) Where documented in the medical record, what were the common reasons for not using it or prematurely discontinuing it, and in what percentage of the patients' charts was no reason given? (4) What proportion of patients were taking a medication that put them at risk for a drug-drug interaction (DDI)?
Methods: Using an institutional database, patients who underwent DAIR or revision arthroplasty for PJI from January 2013 to April 2023 were identified (n = 935).
Drug interactions in a sample of inpatients diagnosed with cannabis use disorder.
J Neural Transm (Vienna)
January 2025
Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
The majority of patients with cannabis use disorder (CUD) regularly take medication. Cannabinoids influence metabolism of some commonly prescribed drugs. However, little is known about the characteristics and frequency of potential cannabis-drug (CDIs) and drug-drug interactions (DDIs) in patients with CUD.
View Article and Find Full Text PDFA retrospective study on potential drug‒drug interactions in patients with severe asthma receiving biological therapy: a single-center experience.
BMC Pulm Med
January 2025
Clinic for Lung Diseases Jordanovac, University Hospital Centre Zagreb, Zagreb, Croatia.
Background: Prevalence of potential drug-drug interactions (pDDIs) in adult patients with severe asthma on biological therapy and their clinical significance have not been fully addressed, thus the aim of this study was to investigate them.
Methods: In this retrospective observational study, patients who were diagnosed with severe asthma and to whom biological therapy was prescribed between September 2015 and December 2020, were enrolled. The study was conducted at the Department of Allergic and Obstructive Pulmonary Diseases, Clinic for Lung Diseases Jordanovac, Clinical Hospital Center Zagreb.
A Multi-Source drug combination and Omnidirectional feature fusion approach for predicting Drug-Drug interaction events.
J Biomed Inform
January 2025
Northwest Normal University, College of Computer Science and Engineering, Lanzhou, China. Electronic address:
Background: In the medical context where polypharmacy is increasingly common, accurately predicting drug-drug interactions (DDIs) is necessary for enhancing clinical medication safety and personalized treatment. Despite progress in identifying potential DDIs, a deep understanding of the underlying mechanisms of DDIs remains limited, constraining the rapid development and clinical application of new drugs.
Methods: This study introduces a novel multimodal drug-drug interaction (MMDDI) model based on multi-source drug data and comprehensive feature fusion techniques, aiming to improve the accuracy and depth of DDI prediction.
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!