Potential drug-drug interactions associated with clinical and laboratory findings at hospital admission.
Milena KovačevićSandra Vezmar KovačevićSlavica RadovanovićPredrag StevanovićBranislava MiljkovićPublished in: International journal of clinical pharmacy (2019)
Background Drug-drug interactions represent one of the causes of adverse therapy outcomes through deteriorated efficacy or safety. However, the true extent of harm related to drug-drug interactions is not well established due to a lack of recognition and understanding. Objective The aim of this study was to investigate the association of potential drug-drug interactions with patients variables recorded at admission. Setting A cross-sectional correlation study was performed on the Cardiology ward of the University Clinical Hospital Center in Belgrade, Serbia. Method Data were retrospectively obtained from medical records and LexiInteract was used as the screening tool for potential drug-drug interactions. Main outcome measure Clinical and laboratory parameters recorded at the patients admission. Results A total of 351 patient records entered the analysis, with the mean age of 70 ± 10 years. The prevalence of potentially relevant drug-drug interactions was 61% (N = 213). After controlling for patient characteristics, nine potential drug-drug interactions were significantly associated with laboratory values outside the range and five potential drug-drug interactions with inadequate clinical parameter values. Potential drug-drug interactions were associated with abnormalities in blood count, metabolic parameters, electrolyte imbalance and renal function parameters. Association with inadequate control of systolic, diastolic blood pressure, as well as heart rhythm was also shown. Conclusion Drug-drug interactions were associated with patients clinical and laboratory findings. Our findings may assist in the identification of patients with increased likelihood of suboptimal therapy outcomes. Generating evidence through post-marketing drug-drug interactions research would lead to improvement in clinical decision-support systems, increased effectiveness and utilization in everyday clinical practice.
Keyphrases
- blood pressure
- adverse drug
- end stage renal disease
- ejection fraction
- chronic kidney disease
- healthcare
- heart failure
- randomized controlled trial
- drug induced
- clinical decision support
- systematic review
- stem cells
- heart rate
- mesenchymal stem cells
- electronic health record
- case report
- acute kidney injury
- risk assessment
- deep learning
- climate change