Background: Since the 1970s, studies have examined potential risk factors associated with adverse drug reactions (ADRs) in a variety of settings. However, no pharmacoepidemiological study exists that incorporates clinical and laboratory parameters in a multiple regression model in order to consider predictors for ADRs.
Objectives: To characterize risk factors associated with ADRs in patients admitted to university hospital departments of internal medicine.
Design and setting: Intensive pharmacovigilance was carried out in departments of internal medicine of two university hospitals. All admissions were followed prospectively for the occurrence of ADRs by members of a pharmacoepidemiological team consisting of physicians, pharmacologists and pharmacists. To identify patients at high risk for experiencing ADRs, patient histories and several clinical and laboratory data, determined at the time of admission, were taken into consideration. In addition to the drug prescribed, 40 parameters defined vital status at admission. These included temperature, heart rate, blood pressure (systolic-diastolic), body mass index, nicotine and alcohol use, and first laboratory test results after admission on nutrition status, inflammation, liver, kidney, pancreas or thyroid status, electrolytes, blood count and coagulation.
Results: 907 patients were observed during the study period. The mean age of the study population was 60 +/- 16 years. The median number of different drugs administered per patient during hospitalization was 9.6 +/- 7.7. In 345 patients, 592 ADRs were evaluated: 33.4% possible, 61.5% probable and 4.7% highly probable. Two ADR-related deaths were observed during the study period. Analysing ADR predictors, 17 of 40 parameters reached significance in univariate analysis, but only five in a multivariate binary regression model: raised temperature (odds ratio [OR] 1.609; 95% CI 1.133, 2.285), low erythrocyte levels (OR 0.386; 95% CI 0.194, 0.768), low thrombocyte levels (OR 0.788, 95% CI 0.627, 0.989), high number of drugs (OR 1.117; 95% CI 1.076, 1.159) and female sex (OR 1.562; 95% CI 0.785, 2.013) were independent predictors for ADRs.
Conclusion: For the patients investigated, of the large number of clinical data available only five independent factors predict ADR occurrence. Taking these results into account, physicians will be able to focus early on patients at risk for ADRs. To minimize ADR occurrence, ADR predictors should be integrated into the clinical pathway.