Awareness about adverse drug reaction monitoring and pharmacovigilance among final year medical students in tertiary care teaching hospital in Andhra Pradesh: a cross sectional study

Background: Adverse drug reaction (ADR) is an unwanted, undesirable effect of a drug that occurs during clinical use. ADRs will occur daily in health care institutions and can unfavourably affect a patient's quality of life, frequently causing considerable morbidity and mortality. Pharmacovigilance is defined as the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem.Methods: It was a non-interventional study was done among hundred final year medical students at Kurnool Medical College, Kurnool, Andhra Pradesh. The study instrument was a predesigned questionnaire was structured by following the precedence, which was set by parallel studies. The participants were given forty-five minutes to answer the questionnaire; the questionnaires were then analyzed by grading the respondents into three categories: poor, unsatisfactory and satisfactory.Results: This study showed satisfactory results about awareness, knowledge and methods of application of pharmacovigilance among final year medical students 55%, 47%, 54% respectively and positive correlation between awareness, knowledge and methods of application of pharmacovigilance among final year medical students significantly (<0.0001) correlated.Conclusions: The present study revealed that the final year medical students were satisfactory in awareness and knowledge and methods of application of pharmacovigilance. The correlations told that the higher the awareness, the more was the knowledge and better were the methods of application. Likewise, the knowledge and practices were significantly and positively related to a correlation

Impact of intraband misregistration on image classification

Remote sensing data acquired from spaceborne platforms in multispectral channels with moderate to high spatial resolution has been extensively used for numerous applications. Registration between images as well as multispectral bands significantly affects the classification accuracy. Data acquired in multiple channels needs accurate intraband registration to minimise classification errors. Availability of very high spatial resolution data such as from SPOT, IRS-P6, IKONOS, and Quickbird demands very accurate intraband registration. Ability to provide accurate intraband registration requires proper knowledge of satellite attitude, Earth rotation correction, sensor geometry etc. While every effort is made to minimise the intraband misregistration at product generation level, it is difficult to remove it all together. In view of this and its significance on remote sensing image classification, an attempt was made to evaluate the impact of intraband misregistration on classification of remote sensing image with high spatial resolution data. Study carried using a prototype image and IRS-P6 LISS-IV image reveals that image data with intraband misregistration greater than 20% significantly reduce image sharpness and leads to misclassification. Though misregistration of NIR band has major impact on classification it was also seen that misregistration among all bands would lead to even greater error in classification and increased edge blurring

What Major Agricultural Cross-Border Trade Products in India Are Influenced by Payments?

This study explores the connection between overall Indian payment statistical indicators and the import-export patterns of around 40 major agricultural products regulated by the Agricultural and Processed Food Products Export Development Authority (APEDA) in India. Using separate regression analyses for import and export transactions from 2013 to 2022, our findings indicate that only a few of these products show a clear impact from payment indicators. In a time when digital payments are becoming increasingly important, the discovery that certain agricultural products are not affected by payment trends has significant implications for the financial landscape. As digital transactions continue to grow, understanding that some agricultural products remain independent of payment trends highlights the need for comprehensive intervention and further research. This study emphasizes the importance of thoroughly investigating these dynamics, providing insights to inform strategic decisions and policies that align with the changing financial ecosystem

Application and Analysis of Machine Learning Algorithms on Pima and Early Diabetes Datasets for Diabetes Prediction

Diabetes is a chronic condition that strike how your body burns food for energy. Much of the food you consume is converted by your body into sugar (glucose), which is then released into your bloodstream. Your pancreas releases insulin when your blood sugar levels rise. Over the years, several scholars have sought to create reliable diabetes prediction models. Due to a lack of adequate data sets and prediction techniques, this discipline still faces many unsolved research issues, which forces researchers to apply big data analytics and ML-based methodology. Four distinct machine learning algorithms are used in the study to analyze healthcare prediction analytics and solve the issues. In this investigation, the Pima and Early detection datasets were employed. We applied the Decision Tree, MLP, Naive Bayes, and Random Forest algorithms to these datasets and evaluated the accuracy and F-Measure. The goal of this research is to develop a system that could more precisely predict a patient's risk of developing diabetes

An analysis of MONTBLEX data on heat and momentum flux at Jodhpur

Parameterization of sensible heat and momentum fluxes as inferred from an analysis of tower observations archived during MONTBLEX-90 at Jodhpur is proposed, both in terms of standard exchange coefficients C H and C D respectively and also according to free convection scaling. Both coefficients increase rapidly at low winds (the latter more strongly) and with increasing instability. All the sensible heat flux data at Jodhpur (wind speed at 10 m ̅U10 &lt; 8 ms−1) also obey free convection scaling, with the flux proportional to the '4/3' power of an appropriate temperature difference such as that between 1 and 30 m. Furthermore, for ̅U10 &lt; 4 ms−1 the momentum flux displays a linear dependence on wind speed

Clinical profile of patients with hypertensive emergencies in a tertiary care hospital

Background: Hypertensive emergency is defined by systolic blood pressure (SBP) ≥180 mmHg and/or diastolic blood pressure (DBP) ≥120 mmHg with acute target organ damage. Hypertensive emergencies can be life threatening and fatal unless timely treated. In the present study we aim to study the clinical profile and outcome of patients admitted with hypertensive emergency in the medical intensive care unit in our hospital. Methods: A cross-sectional observational study of all cases with hypertensive emergency admitted in Medical Intensive care unit (ICU) in Government General Hospital, Srikakulam during the study period was conducted. The clinical profile and outcome of the patients were assessed. Results: Out of the fifty patients in the present study, about 36 (72%) were males and 14 were females (28%) and about one third of the patients (36%) belonged to the age group of 60-69 years. Diabetes mellitus (30%) and dyslipidemia (40%) were the commonly encountered comorbidities in the study population. Most frequent presenting symptoms were neurological deficits (50%) followed by dyspnoea (32%) and chest pain (24%). Intracerebral haemorrhage was the commonest target organ damage found in 30% of the patients. Patients presenting with hypertensive emergencies with neurological target organ damage had statistically significant increased chance of mortality (p=0.007). Conclusions: As hypertension emergencies are consequence of uncontrolled hypertension, it is important to educate and bring awareness among public regarding the screening, early detection, and adherence to prescribed medication for hypertension to avoid adverse clinical outcomes

Formation constants of binary & ternary chelates of Ln(III) with maltol & kojic acid in presence of amino carboxylic acids

174-175The formation constants of binary and ternary systems involving 3-hydroxy-2-methyl-4-pyrone (HMP) (maltol) and 5-hydroxy-2-hydroxymethyl-4-pyrone (HOMP) (kojic acid), with lanthanide metal ions [La(III), Pr(II), Nd(III), Gd(III), Dy(III) and Y(III)] in the presence of iminodiacetic acid (IMDA), hydroxyethyliminodiacetic acid (HIMDA) and nitrilotriacetic acid (NTA) have been determined in aqueous medium at 30°C and μ = 0.1 M (NaClO4). The order of stabilities of ternary systems is: HMP > HOMP and IMDA > HIMDA > NTA. These are explained in the light of the basi-cities of the Iigands and charge neutralisation

ANTIBACTERIAL ACTIVITY OF SOME FOLKLORE MEDICINAL PLANTS FROM SOUTH INDIA

Antibacterial activity and phytochemical tests of eight whole plant methanol extracts belonging to family Euphorbiaceae were evaluated. In agar well diffusion assay the diameter of inhibition zones ranged from 3-13 mm. Phyllanthus emblica showed maximum activity of 13 mm. The MIC and MBC observed were 30-140 mcg/ml and 40-160 mcg/ml, respectively. P. piscatorum and P. emblica showed the lowest MIC (30 mcg/ml), P. emblica the lowest MBC (40 mcg/ml) and thus an effective inhibitor of the tested bacteria. Alkaloids, saponins and tannins were detected in 7 out of 8 tested plants