Context: As COVID-19 spread across the world, vaccines were developed to fight against the spread of the new disease. Negative attitude and unwillingness to vaccinate when available may be a major hurdle in attaining effective vaccination coverage. Aims: The aim of this study was to assess the attitudes towards the COVID-19 vaccine and identify the predictors of negative attitudes towards the vaccine and identify groups most at risk of uncertainty and unwillingness to receive a COVID-19 vaccine. Settings and Design: General public of Kerala, cross-sectional survey. Methods and Material: The study was conducted in Kerala during the period from 16 January 2021 to 22 February 2021. An online semi-structured questionnaire was sent via google forms with a consent form appended to it. Attitude towards vaccination was measured using a 20-item scale. Statistical Analysis Used: Collected data were analysed using SPSS software version 16. Ordinary least-squares (OLS) regressions were carried out to examine socio-demographic predictors of attitude towards vaccination. Multinomial logistic regression model was fitted to examine associations of socio-demographic with uncertainty and disagree to vaccinate against COVID-19. Results: In this study, 1345 subjects participated. Mean attitude score was 48.68 with SD 13.55. Most of the study subjects were agreeable to take the vaccine once it is available (88.8%). Religion, occupation, and monthly income were found to be the predictors of attitude towards vaccination. Conclusions: The willingness for vaccine uptake was found to be high in our study. However, other aspects such as doubt regarding its safety, effectiveness and duration of protection are considerable and need to be addressed.

Objective: A standard causality assessment tool of an adverse drug reaction (ADR) is essential to compute the risk-benefit assessment of the medication taken by the patient and categorize its relationship likelihood. It should be reproducible and should not differ with the background and experience of the evaluator. Though there are a large number of causality assessment tools, none is unanimously accepted worldwide. So, this study was done to assess the agreement between three frequently used methods of causality assessment, the World Health Organisation-Uppsala Monitoring Centre (WHO-UMC) system, the Naranjo’s algorithm, and the Liverpool algorithm. Methods: 172 ADR forms from the pharmacovigilance unit were randomly selected for the study. Causality assessment was done using three different methods, the WHO-UMC system, Naranjo’s algorithm, and the Liver pool algorithm. Cohen’s Kappa statistics was applied to look for agreement between the causality assessment methods. Results: The agreement between the WHO-UMC criteria and Naranjo’s algorithm was the highest (136), with a Kappa value of 0.511, suggesting a moderate level of agreement. A maximum number of disagreements were noted between the WHO-UMC system and the Liverpool algorithm method (110). Conclusion: A moderate agreement exists between the WHO-UMC system and the Naranjo algorithm. There is poor agreement between the Liverpool algorithm and the other two scales. Therefore, it is recommended that both the WHO-UMC system and the Naranjo algorithm be used for causality assessment of ADRs.

Background: ICU patients are exposed to more number of life saving drugs and face drug related problems like therapeutic failure, drug interactions and frequent adverse drug reactions. The cost of ICU hospitalisation and money spent on medicines is also a huge burden on these patients. A study of prescribing pattern in an ICU set up will serve as a medical audit to monitor and evaluate the prescribing practices to make it more rational and cost effective. Methods: A prospective observational study was carried out in a medical ICU of a tertiary care hospital. All the inpatients admitted in the medical ICU during the study period of 2 months were included in the study. The data obtained from the case sheets were used to assess the prescribing pattern and rationality of drug use. Results: A total of 101 patients were admitted in 2 months. The most common illness for which the patients (22) were admitted was respiratory problems. Average number of drugs per prescription was 6.9. Cardiovascular system (23.9%) drugs were the most frequently prescribed. Pantoprazole (77) was the single most commonly prescribed drug. 40% of the drugs were prescribed from the essential drug list. The average cost of medicines incurred per person in our study was 5126.33 in INR. Conclusions: Polypharmacy and unwanted prescription of proton pump inhibitors can be avoided by prescribing more generics and drugs from essential drug list.