RISK FACTORS FOR POTENTIAL DRUG-DRUG INTERACTIONS OF ANALGESICS IN HOSPITALIZED UROLOGICAL PATIENTS - Milovanović, Ivan; Pejčić, Ana; Kovačević, Zoran; Janićijević, Katarina (Sanamed, 2026)
Objective: To evaluate potential drug–drug interactions (pDDIs) involving analgesics in hospitalized urological patients and identify risk factors influencing their number. Methods: This study involved a post hoc analysis based on data obtained from a retrospective observational cohort clinical study conducted at the Clinic of Urology, University Clinical Centre Kragujevac, Serbia. Of the original 220 patients, 191 who received analgesics were included. Daily pharmacotherapy data, along with demographic and clinical characteristics, were collected, while pDDIs were identified and classified using the Lexicomp Interaction Checker. Descriptive statistics were used to summarize the data. Multiple linear regression with backward elimination was used to identify independent predictors of the number of pDDIs. Results: Analgesic-related pDDIs were detected in 175 patients (91.6%). Non-steroidal anti-inflammatory drugs (NSAIDs) were prescribed to 173 patients (90.6%), opioids to 53 (27.7%), and paracetamol to 54 (28.3%). The mean number of pDDIs per patient was 5.5 ± 5.5 (range 0–30). Category X interactions most frequently included NSAID combinations (diclofenac + ketorolac, ketorolac + metamizole), while category D interactions frequently involved enoxaparin + ketorolac and opioid–benzodiazepine pairs. Category C interactions were dominated by NSAID + potassium chloride and tramadol + ondansetron or atropine combinations. Multiple regression analysis identified diabetes, a higher number of prescribed drugs, and the use of NSAIDs or opioids as positive predictors of the number of pDDIs, whereas a cancer diagnosis was associated with a lower number. Conclusion: Analgesic-related pDDIs affect the majority of hospitalized urological patients. Avoiding high-risk combinations, close monitoring, and multidisciplinary medication review in patients with risk factors may help reduce preventable harm.