Comparison of effectiveness of 7.5% Povidone-iodine with 1% Clotrimazole ear drops and lignocaine in Otomycosis

Objectives: Our study is comparing the effectiveness of 7.5% Povidone-iodine with 1% Clotrimazole ear drops and lignocaine in the management of Otomycosis to highlight the importance of replacing conventional antifungals in routine practice. Setting: Department of ENT and Head and Neck Surgery, Holy Family Hospital, Rawalpindi, Pakistan. Study design: A prospective randomized control trial Methodology: This study was conducted for 12 months in our institute from July 2014 to June 2015. A total number of 148 patients with clinically diagnosed Otomycosis between the age group 15 to 55 years were studied. All patients with a clinical diagnosis of Otomycosis presenting with all four features of earache, itching, ear-blockage, and ear discharge in ENT OPD were included. Ear swabs were taken and sent for fungal culture. Patients were divided into A and B groups each comprising of 74 patients. Group A received 1% Clotrimazole ear drops and lignocaine and group B received 7.5% Povidone-iodine for 14 days after the results of cultures were received. At the end of 14 days, patients of both groups were compared based on the resolution of symptoms and signs. Results: At the end of 14 days, 32 out of 74 patients (43%) in group A receiving 1% Clotrimazole ear drops and lignocaine reported resolution of all symptoms, and 52 out of 74 patients(70%) showed complete resolution of all signs, while in group B,68 out of 74 patients(91%) showed complete resolution of symptoms and 69 out of 74 patients (93%) showed complete resolution of signs. Our study showed significant improvement in signs and symptoms of Otomycosis achieved by treatment with 7.5% Povidone-iodine compared to that achieved by 1% Clotrimazole ear drops and lignocaine. Conclusion: 7.5% Povidone-iodine is a more effective antifungal agent in the treatment of Otomycosis as compared to 1% Clotrimazole ear drops and lignocaine

Dexamethasone Versus Ondansetron in Preventing Postoperative Nausea and Vomiting In Laparoscopic Surgery

Objective: To compare the efficacy of dexamethasone 8mg versus ondansetron 4mg in preventing postoperative nausea and vomiting (PONV) in patients undergoing laparoscopic cholecystectomy Methodology: This quasi-experimental study was conducted at the Department of Anaesthesia and Intensive Care, Holy Family Hospital from 29th July 2018 to 28th January 2019.  Anesthesia was induced with propofol (2mg/kg IV) and Atracurium (0.5 mg/kg IV) was given to facilitate tracheal intubation. Nalbuphine (0.2mg/kg) was used as analgesic.Patients were randomly divided into two groups. Patients in Group A received 4mg ondansetron at end of surgery and Group B received 8mg dexamethasone at induction. Results: A total of 90 patients were included according to the inclusion criteria of the study. The mean age (years) in the study was 37.11+10.60 years. Frequency and percentage of nausea (up to 24 hours) among both the groups was 28 (62.2) and 28 (62.2) respectively (p-value = 1.0) while the frequency and percentage of vomiting (within 24 hours after extubation) was 28 (62.2) and 27 (60.0) respectively (p-value = 0.829) Conclusion: The study concluded that there was no significant difference dexamethasone and ondansetron in preventing postoperative nausea and vomiting

ESBL determination and antibacterial drug resistance pattern of Klebsiella Pneumoniae amongst patients at PIMS Islamabad

Background: A number of life threatening infections due to various bacterial pathogens are major cause  of death in Pakistan. In a situation like the other developing countries, there is a general increase in the  drug resistance due to the irrational use of the antibiotics. The present study was carried out to evaluate the prevalence and development of resistance in Klebsiella pneumoniae against commonly used antibiotics.Methods and Materials: A total of 200 samples from different wards of the hospitals were received by the pathology laboratory of Pakistan Institute of Medical Sciences, Islamabad, which comprised of urine  65, blood 50 and other miscellaneous samples from various sources. Klebsiella pneumoniae was isolated and characterized using morphological, cultural, and biochemical methods and were further confirmed by using commercially available API 20E kit. The isolates were subjected to culture sensitivity test using  Kirby Bauer disc diffusion method.Results: The organism was found to be the most prevalent Gram-negative bacilli. K. pneumoniae showed  highest resistance against coamoxiclav and cephalosporins.Conclusion: The study revealed that ESBL producing strains were resistant to most of the beta-lactam antibiotics. This trend therefore has become a significant problem and can be controlled with continued surveillance or monitoring for rationally improved antibiotics usage, in order to prevent the drug resistance and re-emergence of infection.Key words: Klebsiella pneumoniae, ESBL (Extended-spectrum beta-lactamase), API (Analytical Profile Index

ESBL DETERMINATION AND ANTIBACTERIAL DRUG RESISTANCE PATTERN OF KLEBSIELLA PNEUMONIAE AMONGST PATIENTS AT PIMS ISLAMABAD

Background: A number of life threatening infections due to various bacterial pathogens are major cause of death in Pakistan. In a situation like the other developing countries, there is a general increase in the drug resistance due to the irrational use of the antibiotics. The present study was carried out to evaluate the prevalence and development of resistance in Klebsiella pneumoniae against commonly used antibiotics. Methods and Materials: A total of 200 samples from different wards of the hospitals were received by the pathology laboratory of Pakistan Institute of Medical Sciences, Islamabad, which comprised of urine 65, blood 50 and other miscellaneous samples from various sources. Klebsiella pneumoniae was isolated and characterized using morphological, cultural, and biochemical methods and were further confirmed by using commercially available API 20E kit. The isolates were subjected to culture sensitivity test using Kirby Bauer disc diffusion method. Results: The organism was found to be the most prevalent Gram-negative bacilli. K. pneumoniae showed highest resistance against coamoxiclav and cephalosporins. Conclusion: The study revealed that ESBL producing strains were resistant to most of the beta-lactam antibiotics. This trend therefore has become a significant problem and can be controlled with continued surveillance or monitoring for rationally improved antibiotics usage, in order to prevent the drug resistance and re-emergence of infection

Bayesian Analysis of two Censored Shifted Gompertz Mixture Distributions using Informative and Noninformative Priors

This study deals with Bayesian analysis of shifted Gompertz mixture model under type-I censored samples assuming both informative and noninformative priors. We have discussed the Bayesian estimation of parameters of shifted Gompertz mixture model under the uniform, and gamma priors assuming three loss functions. Further, some properties of the model with some graphs of the mixture density are discussed. These properties include Bayes estimators, posterior risks and reliability function under simulation scheme. Bayes estimates are obtained considering two cases: (a) when the shape parameter is known and (b) when all parameters are unknown. We analyzed some simulated sets in order to investigate the effect of prior belief, loss functions, and performance of the proposed set of estimators of the mixture model parameters

Optimization of Bioconvective Magnetized Walter’s B Nanofluid Flow towards a Cylindrical Disk with Artificial Neural Networks

Nanotechnology is a fundamental component of modern technology. Researchers have concentrated their efforts in recent years on inventing various algorithms to increase heat transmission rates. Using nanoparticles in host fluids to dramatically improve the thermal properties of ordinary fluids is one way to address this problem. The article deals with the bio-convective Walter’s B nanofluid with thermophoresis and Brownian diffusion through a cylindrical disk under artificial neural networks (ANNs). In addition, the thermal conductivity, radiation, and motile density of microorganisms are taken into consideration. The Buongiorno model is utilized to investigate the properties of nanofluids in motile microorganisms. By using appropriate similarity variables, a dimensionless system of a differential system is attained. The non-linear simplified system of equations has been numerically calculated via the Runge–Kutta fourth-order shooting process. The consequences of flow parameters on the velocity field, temperature distribution, species volumetric concentration, and microorganism fields are all addressed. Two distinct artificial neural network models were produced using numerical data, and their prediction performance was thoroughly examined. It is noted that according to the error histograms, the ANN model’s training phase has very little error. Furthermore, mean square error values calculated for local Nusselt number, local Sherwood number, and local motile density number, parameters were obtained as 3.58×10−3, 1.24×10−3, and 3.55×10−5, respectively. Both artificial neural network models can predict with high accuracy, according to the findings of the calculated performance parameters

Optimization of Bioconvective Magnetized Walter’s B Nanofluid Flow towards a Cylindrical Disk with Artificial Neural Networks

Nanotechnology is a fundamental component of modern technology. Researchers have concentrated their efforts in recent years on inventing various algorithms to increase heat transmission rates. Using nanoparticles in host fluids to dramatically improve the thermal properties of ordinary fluids is one way to address this problem. The article deals with the bio-convective Walter’s B nanofluid with thermophoresis and Brownian diffusion through a cylindrical disk under artificial neural networks (ANNs). In addition, the thermal conductivity, radiation, and motile density of microorganisms are taken into consideration. The Buongiorno model is utilized to investigate the properties of nanofluids in motile microorganisms. By using appropriate similarity variables, a dimensionless system of a differential system is attained. The non-linear simplified system of equations has been numerically calculated via the Runge–Kutta fourth-order shooting process. The consequences of flow parameters on the velocity field, temperature distribution, species volumetric concentration, and microorganism fields are all addressed. Two distinct artificial neural network models were produced using numerical data, and their prediction performance was thoroughly examined. It is noted that according to the error histograms, the ANN model’s training phase has very little error. Furthermore, mean square error values calculated for local Nusselt number, local Sherwood number, and local motile density number, parameters were obtained as 3.58×10−3, 1.24×10−3, and 3.55×10−5, respectively. Both artificial neural network models can predict with high accuracy, according to the findings of the calculated performance parameters

Bayesian Inference of Mixture of two Rayleigh Distributions: A New Look

There are several papers which discuss the Bayesian analysis of the mixture models under type I singly censored samples. This paper considers a new methodology for Bayesian analysis of mixture models under doubly censored samples. We have discussed the Bayesian estimation of parameters of the two-component mixture of Rayleigh distribution under square root gamma, Maxwell and half normal priors using two loss functions. Further, we analyzed some simulated and real data sets in order to investigate the performance of the estimators for the parameters of the proposed mixture model.&nbsp