A case report of life threatening Dapsone Hypersensitivity Syndrome

Dapsone is widely used for a variety of infections, immune and hypersensitivity disorders. However, the use of Dapsone may be associated with a plethora of adverse effects, the most serious being Dapsone Hypersensitivity Syndrome (DHS) wherein the patient typically presents with a triad of fever, skin eruption and internal organ involvement, that occurs during first 2 to 8 weeks of initiating the treatment. The incidence of DHS ranges from 0.5% to 3%.  Here we report a case of severe life threatening Dapsone induced hypersensitivity reaction in a 21year old female who presented with high grade fever, generalized lymphadenopathy, skin rash and hepato-splenomegaly. This condition is best approached with immediate discontinuation of offending drug and prompt administration of oral or IV glucocorticoids. The case is being reported to emphasize the need for timely diagnosis and prompt treatment for successful outcome as it can cause irreversible organ damage or death if untreated early

Drug utilization study in dengue infection in a tertiary care hospital

Background: Dengue fever (DF) is a serious public health problem, gaining global attention because of its morbidity and mortality. Less studies on Drug utilization pattern of DF in India. The present study was undertaken to analyze Drug utilization pattern of dengue infection in a tertiary care hospital.Methods: A prospective cross-sectional study was conducted for a period of 2 months in a tertiary care hospital and the data was analyzed by using various drug use indicators.Results: A total of 52 prescriptions were analyzed. Male and female were (46.16%, 53.84%), A total of 330 drugs were prescribed. 86 (26.06%) antibiotics, 70 (21.21%) antipyretics, 51 (15.46%) antacids, 19 (5.76%) multivitamins, 52 (15.76%) anti-emetics and 52 (15.76%) papaya leaf extract was prescribed. 84 (25.46%) oral and 246 (74.54%) injectable drugs. IV-fluids given to all patients. 10 (19.24%) were given blood transfusion. 6.17 drugs per prescription. 96% drugs were prescribed by brand names. High DDD for drugs like diclofenac (184), doxycycline (115), metronidazole (2.5), pantoprazole (161.5), rabeprazole (34.6), ondansetron (200) was observed.Conclusions: Most commonly used drugs are antipyretics, antibiotics, antacids, antiemetic, papaya leaf extract. As the incidence of DF is increasing with epidemics, demand for specific treatment guidelines is in great need. Early recognition of the disease, with a rational approach in case management leads good clinical outcome

Evaluation of hepatoprotective activity of Boerhaavia diffusa against carbon tetrachloride induced liver toxicity in albino rats

Background: Modern allopathic medicine has very little to offer for the treatment of liver disorders in spite of consistent effort for new drug discovery. Hence, this study was conducted to elucidate the hepatoprotective activity of aqueous extract of traditional medicinal plant Boerhaavia diffusa against carbon tetrachloride (CCl4) induced toxicity in male albino rats.Methods: The hepatoprotective effect of the aqueous extracts of B. diffusa was evaluated by biochemical parameters such as serum alanine transferases (ALT), serum asparate transferases (AST), alkaline phosphatase (ALP), total serum bilirubin, and serum protein, and confirmed by histopathology of liver. The toxicant CCl4 was used to induce hepatotoxicity and silymarin were used as control drug. The aqueous extracts of B. diffusa were administered at the doses of 250 mg/kg/day and 500 mg/kg/day orally for 4 days. One-way analysis of variance was used for the statistical analysis of data. A probability value of p<0.05 was considered as significant.Results: Administration of B. diffusa at doses 250 and 500 mg/kg orally demonstrated hepatoprotective activity by preventing the increase of ALT, AST, ALP, and serum bilirubin and also confirmed by histopathology of the liver. The results were comparable to that of silymarin®.Conclusion: The results of this study confirmed the hepatoprotective activity of aqueous extracts of B. diffusa at doses of 250 mg/kg/and 500 mg/kg/against CCl4 induced hepatotoxicity in rats. However, the dose adjustments may be necessary to optimize the similar hepatoprotective efficacy in clinical settings

Prospective observational study of drug utilization in neonatal seizure at a tertiary care hospital with Pharmacoeconomics

Background: Seizures are the most common indicator of significant neurologic dysfunction in neonatal period with incidence of 11.7/1000 live births. Phenobarbitone is used as first line of treatment since 1900s. Newer anti-epileptic drugs (AED) available are Levetiracetam, Topiramate etc. Present study focused on utilization pattern of AED, treatment outcomes and to study economic burden of disease.Methods: An observational study was done on 100 neonates admitted to Neonatal Intensive Care Unit in Basaveshwara hospital, Kalaburagi (June 2016-May 2017). Prescription data was entered into specially designed proforma, WHO core indicators were determined. The data was analyzed using descriptive statistics and presented as means and percentages.Results: Majority of neonates were male (58%) and 63% were diagnosed with subtle seizure. Out of 458 drugs prescribed, 201 were antiepileptics. 41% cases were successfully managed by monotherapy. Most commonly used drug was phenobarbitone (82%) and phenytoin (31%). Leviteracetam, newer AED was used in 3 refractory cases. The major combination of drugs used was Phenobarbitone-Phenytoin (24%). AED were rationally prescribed, but antibiotic was over-utilized(68%). 31% cases had adverse drug reaction. On average per prescription, number of drugs used were 4.6 and drug cost was Rs.3803/-. The total cost of illness per patient was Rs.16363/-.Conclusions: AED utilization in neonatal seizures was in accordance to guidelines, with phenobarbitone being extensively used despite its potential neurotoxicity. The utilization of newer AED would increase if clinicians are supported with the safety and efficacy data. Although monotherapy was preferred with respect to AED, antibiotics were highly prescribed; hence awareness is needed to curb this practice

Pharmacovigilance study in medicine department in a tertiary care hospital

Background: Adverse drug reactions (ADRs) are major worldwide public health problem. Proper reporting of an ADR is very important as it reduces number of deaths due to ADR and extra financial burden on patients. The aim of the study was to assess the pattern of ADR reporting in outpatients and inpatients of medicine department and to assess their causality, severity and preventability.Methods: This was a prospective observational study done from April 2013 to June 2014 or in 100 consecutive study subjects (which ever happen first) with ADRs in department of medicine. The clinical pattern, spectrum of ADRs reported and assessment of ADRs in terms of causality, severity and preventability .The causality, severity and preventability assessment was done on the basis of applying various scales for each of them.Results: A total of 153 suspected ADRs were reported and evaluated from 100 patients. Dermatological system (28%) was most commonly involved. Drug class most commonly associated was Antimicrobials (51%). 68% ADRs were classified as “Probable” in view of causality, while 68% were found to be “Moderate” in case of severity. In 65% of the cases the ADRs was “Probably Preventable”. In majority of the cases the suspected drug was withdrawn and alternate therapy was instituted. Most patients recovered from the ADR.70% of these ADR was Type A.Conclusions: Awareness about ADR reporting is still poor amongst healthcare professionals in India. Conducting regular training programmes can improve the number of ADR reporting

Deep Learning-based SNR Estimation for Multistage Spectrum Sensing in Cognitive Radio Networks, Journal of Telecommunications and Information Technology, 2022, nr 4

Vacant frequency bands are used in cognitive radio (CR) by incorporating the spectrum sensing (SS) technique. Spectrum sharing plays a central role in ensuring the effectiveness of CR applications. Therefore, a new multi-stage detector for robust signal and spectrum sensing applications is introduced here. Initially, the sampled signal is subjected to SNR estimation by using a convolutional neural network (CNN). Next, the detection strategy is selected in accordance with the predicted SNR levels of the received signal. Energy detector (ED) and singular value-based detector (SVD) are the solutions utilized in the event of high SNR, whilst refined non-negative matrix factorization (MNMF) is employed in the case of low SNR. CNN weights are chosen via the Levy updated sea lion optimization (LU-SLNO) algorithm inspired by the traditional sea lion optimization (SLNO) approach. Finally, the outcomes of the selected detectors are added, offering a precise decision on spectrum tenancy and existence of the signal

“A Review of Fractal Antenna Design and its Applicationsâ€

Antenna is a very important component for the wireless communication systems using radio frequency and microwaves. By definition, an antenna is a device used to transform an RF signal, travelling on a conductor, into an electromagnetic wave in free space. The IEEE Standard Definitions of Terms for Antennas (IEEE Std 145 - 1983) defines the antenna or aerial as “a means for radiating or receiving radio wavesâ€. In other words it is a transitional structure between free space and a guiding device that is made to efficiently radiate and receive radiated electromagnetic waves. Antennas are commonly used in radio, television broadcasting, cell phones, radar and other systems involving the use of electromagnetic waves. Antennas demonstrate a property known as reciprocity, which means that an antenna will maintain the same characteristics regardless if it is transmitting or receiving. Operators a re looking for antennas that can perform over several frequency bands or are reconfigurable as the demands on the system changes

Deep Learning-based SNR Estimation for Multistage Spectrum Sensing in Cognitive Radio Networks

Vacant frequency bands are used in cognitive radio (CR) by incorporating the spectrum sensing (SS) technique. Spectrum sharing plays a central role in ensuring the effectiveness of CR applications. Therefore, a new multi-stage detector for robust signal and spectrum sensing applications is introduced here. Initially, the sampled signal is subjected to SNR estimation by using a convolutional neural network (CNN). Next, the detection strategy is selected in accordance with the predicted SNR levels of the received signal. Energy detector (ED) and singular value-based detector (SVD) are the solutions utilized in the event of high SNR, whilst refined non-negative matrix factorization (MNMF) is employed in the case of low SNR. CNN weights are chosen via the Levy updated sea lion optimization (LU-SLNO) algorithm inspired by the traditional sea lion optimization (SLNO) approach. Finally, the outcomes of the selected detectors are added, offering a precise decision on spectrum tenancy and existence of the signal

Pharmacovigilance study in medicine department in a tertiary care hospital

Background: Adverse drug reactions (ADRs) are major worldwide public health problem. Proper reporting of an ADR is very important as it reduces number of deaths due to ADR and extra financial burden on patients. The aim of the study was to assess the pattern of ADR reporting in outpatients and inpatients of medicine department and to assess their causality, severity and preventability.Methods: This was a prospective observational study done from April 2013 to June 2014 or in 100 consecutive study subjects (which ever happen first) with ADRs in department of medicine. The clinical pattern, spectrum of ADRs reported and assessment of ADRs in terms of causality, severity and preventability .The causality, severity and preventability assessment was done on the basis of applying various scales for each of them.Results: A total of 153 suspected ADRs were reported and evaluated from 100 patients. Dermatological system (28%) was most commonly involved. Drug class most commonly associated was Antimicrobials (51%). 68% ADRs were classified as “Probable” in view of causality, while 68% were found to be “Moderate” in case of severity. In 65% of the cases the ADRs was “Probably Preventable”. In majority of the cases the suspected drug was withdrawn and alternate therapy was instituted. Most patients recovered from the ADR.70% of these ADR was Type A.Conclusions: Awareness about ADR reporting is still poor amongst healthcare professionals in India. Conducting regular training programmes can improve the number of ADR reporting