Schmidberger Julian, Kloth Christopher, Müller Martin, Kratzer Wolfgang, Klaus Jochen
Department of Internal Medicine I, University Hospital Ulm, Ulm, Baden-Württemberg, Germany.
Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Baden-Württemberg, Germany.
Integr Pharm Res Pract. 2022 Mar 12;11:61-69. doi: 10.2147/IPRP.S351938. eCollection 2022.
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 ( = 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/m 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.
不良药物相互作用频繁发生，危及治疗效果，并导致药物不良反应。本研究旨在对局部限定的随机抽样人群中的潜在药物相互作用进行统计学评估。
在264名正在服药的随机抽样人群中，我们使用药物信息系统AiDKlinik进行分析。使用SAS 9.4版进行统计分析。
82/264（31.1%）名受试者记录到统计学上的潜在药物相互作用，其中男性39/82（47.56%），女性43/82（52.43%）（χ² = 0.081；p = 0.776）。每人检测到的潜在可能相互作用的平均数量为1.60±1.21。包含年龄、体重指数和长期用药数量变量的回归模型显示，长期用药数量与药物相互作用的中度严重和严重反应数量之间存在显著关联（F(3,239) = 28.67，p < 0.0001；(t(239) = 8.28；p < 0.0001)）。经过向后剔除后，回归模型显示与长期用药数量（t (240) = 8.73，p < 0.0001）和体重指数（t (240) = 2.02，p = 0.0442）存在显著交互作用。在描述性分析中，体重指数（BMI）>25 kg/m² 的42/82（51.22%）名受试者和年龄在61 - 70岁的28/82（34.15%）名受试者中，潜在药物相互作用的百分比最高。
在随机人群样本中，长期用药数量、年龄和肥胖可能导致药物 - 药物相互作用增加。
