Evaluation of Potential Drug Interactions with AiDKlinik^® in a Random Population Sample

Undesirable drug interactions are frequent, they endanger the success of therapy, and they lead to adverse drug reactions. The present study aimed to evaluate statistically potentially drug interactions in a locally circumscribed, random sample population.

In a random sample population of 264 patients taking medications, we performed analyses with the drug information system AiDKlinik^®. Statistical analysis was performed using SAS version 9.4.

Statistically potentially drug interactions were recorded in 82/264 (31.1%) subjects, including 39/82 (47.56%) men, and 43/82 (52.43%) women (χ ²= 0.081; p = 0.776). The average number of potential possible interactions detected per person was 1.60 ± 1.21. The regression model with the variables age, body-mass-index and number of long-term-medications shows a significant association between the number of long-term medications taken and the number of moderately severe and severe reactions to drug interactions (F(3.239) = 28.67, p < 0.0001; (t(239) 8.28; p < 0.0001)). After backward elimination, the regression model showed a significant interaction with the number of long-term medications (t (240) = 8.73, p < 0.0001) and body-mass-index (t (240) = 2.02, p = 0.0442). In descriptive analysis, the highest percentages of potential drug interactions occurred in 42/82 (51.22%) subjects with body mass indices (BMIs) >25 kg/m² and in 28/82 (34.15%) subjects aged 61-70 years.

Number of long-term medications use, age, and obesity may lead to increased drug-drug interactions in a random population sample.