A retrospective cross-sectional study to evaluate the adverse drug reactions reported in the tertiary care health center in Northern India

Background: In terms of morbidity and death, adverse drug reactions (ADR) have been highlighted as a worldwide burden. Determining the origin of ADRs remains a tough issue and no one approach for determining causation has been adopted as the gold standard throughout the world. Aim and Objectives: The objectives of the present study were (1) to evaluate the causality of ADRs using World Health Organization-Uppsala Monitoring Center (WHO-UMC) and Naranjo Algorithm ADRs causality assessment tools and (2) to evaluate the agreement and correlation between two universally used approaches for causality assessment of ADRs viz. WHO-UMC system and Naranjo algorithm. The secondary objective was to assess the reported ADRs in a tertiary care hospital in Northern India. Materials and Methods: The present study was a retrospective cross-sectional study. A total of 180 patients of ADRs from different departments of tertiary care hospital which were reported by Pharmacovigilance unit over a period of April 2018 to May 2019 were assessed. The causality assessment for these reported ADRs were done by WHO-UMC system and Naranjo algorithm. The agreement between these two methods calculated by Cohen’s kappa (?) statistics and Spearman’s correlation was used to evaluate the correlation between these two methods. Results: According to WHO-UMC criteria, 55.5% of adverse event instances were of the probable type, 34.4% were possible, 9.4% of cases were improbable, and 0.5% of cases were definite. According to the Naranjo methodology, 80.5% of adverse outcomes were likely, while 19.4% were feasible. The WHO and Naranjo causality comparisons had a positive and fair agreement (= 0.29), according to Cohen’s kappa test. Between the WHO-UMC scale and the Naranjo algorithm, the Spearman’s correlation coefficient was determined to be 0.409. Conclusion: “Probable” was the most common causality category observed by the WHO-UMC scale and the Naranjo algorithm. The WHO-UMC scale and the Naranjo algorithm have a good and reasonable agreement.