ABSTRACT
Background: Cutaneous adverse drug reactions (CADRs) range from mild-to-severe types and occasionally can become fatal. Hence, these incur additional financial burden both to patients and community. Aim and Objective: The aim of the study was to describe the characteristics of CADRs reported to ADR monitoring center (AMC) of a tertiary care center. Materials and Methods: CADRs reported to the AMC over a period of 2 ½ years were retrospectively studied. This study mainly focused on affected age group, gender, various pattern of CADRs, the group and name of drugs causing CADRs, and severity and causality assessment. Results: CADRs contributed 31.6% of the total ADRs reported to the AMC. Among these, 51.7% were females and 40% were of 51–60 years age group. About 37.9% of CADRs were pruritus. Antibacterial drugs were the most common cause of CADRs and beta-lactam antibiotics were responsible for 30% of CADRs. Stevens Johnson syndrome (SJS) constituted 4.9% of CADRs and 20% of this was due to Paracetamol. Drugs were withdrawn in 89% of cases and 85% cases recovered. On causality assessment, 94% were of probable category. Conclusion: Pruritus was the most commonly observed CADR and antibacterial drugs were the most common cause. Beta lactam antibiotic was the most frequent antibacterial drug to cause CADRs. The most common serious CADR was SJS and Paracetamol was the most frequent culprit drug.
ABSTRACT
Background: P drugs are preferred or priority or personal choice drugs of the prescriber for a disease which should be prepared by the doctor. Aims and Objectives: This study was done to describe the process of P drug selection done in the task-based learning (TBL) group. Materials and Methods: This was a descriptive study done in the Department of Pharmacology of a Government Medical College in Central Kerala for a period of 2 months (June 1, 2018, to July 31, 2018) after receiving clearance from the Institutional Review Board. Participants who performed task-based learning of P drug concept were assessed for the proper completion of various steps in P drug selection. Results: All the participants could write the proper diagnosis and therapeutic objectives in the task sheet for case scenario related to absence seizure, angina, Type 2 diabetes mellitus, grand mal epilepsy, and pregnancy-induced hypertension. The weights assigned for efficacy, safety, cost, and suitability varied with each student, however, the most common weights were 0.4, 0.4, 0.1, and 0.1. The weights assigned amongst the eight clinical scenarios were found to differ with P < 0.001 for efficacy, safety, cost, and suitability on doing Kruskal–Wallis test. On doing one-way analysis of variance for group score F = 21.02 and drug score F = 20.91, both were found to differ significantly across the conditions with P < 0.001. The selected P drug was improperly prescribed across the clinical conditions except for that of bronchial asthma. Conclusion: TBL using multi-attributive analysis for P drug selection ensured considering various factors during its selection process for P drug selection.