Efficacy, safety and cost effectiveness of oral Doxofylline and Theophylline for mild to moderate persistent bronchial asthma: A randomized prospective open labeled comparative study.

AIM : To compare the efficacy, safety and cost effectiveness of oral Doxofylline and Theophylline for mild to moderate persistent bronchial asthma patients. MATERIALS AND METHODS: A Randomized prospective, open labeled comparative study of 1 year (Jul 2014-Jun 2015) duration was conducted in 186 patients who were attending the thoracic medicine outpatient department of Chengalpattu Medical College satisfying the inclusion and exclusion criteria after obtaining ethical clearance. METHODOLOGY: The study subjects were randomly allocated into two groups. Group 1 patients were treated with Doxofylline 400mg once daily and group 2 patients were treated with Theophylline twice daily. Demographic data, history, clinical examination and details of drug prescription by the treating physician were recorded in the study proforma. Relevant lab investigations were done at the beginning and at the end of the study. The patients were followed up for 12 weeks. The schedule of patient visit is as follows Visit 1 for initial or baseline assessment and follow-up at 4, 8 & 12 weeks. STATISTICAL ANALYSIS: The data collected were analyzed using Student t test (two tailed, independent) to find the significance of study parameters on continuous scale between two groups. Chi-square/ Fisher Exact test was used to find the significance of study parameters on categorical scale between two or more groups. RESULT: Doxofylline was better than deriphylline in subjective parameters of asthma control test questionnaire and subjective rating of asthma control. Doxofylline had equal efficacy as that of deriphylline in spirometric parameters (p ≤ 0.001). Doxofylline was significantly safe compared to deriphylline as inferred from lesser incidence of adverse drug reactions. Adverse reactions are encountered in 10% of doxofylline and 22% of deriphylline group. Deriphylline was the cheaper and cost effective methylxanthene for the treatment of bronchial asthma in developing countries at population level. Doxofylline even though costlier had better safety profile with less adverse reactions compared to deriphylline. It can be used as an individual based approach in asthma management. CONCLUSION: Doxofylline is a newer methylxanthine with few adverse effects and equal efficacy as compared with deriphylline. It is a better alternative in the management of bronchial asthma

Analysis of cutaneous adverse drug reactions in a tertiary care teaching hospital

Background: Cutaneous Adverse Drug Reaction (CADR) is considered as one of the reasons for discontinuation of drug as well as medication non-adherence. This study analyses the common drugs causing CADR, clinical spectrum of different types of CADR, causality and drugs causing severe CADR.Methods: This was a retrospective cross-sectional observational study conducted by the Department of Pharmacology, Coimbatore Medical College, Coimbatore, Tamil Nadu, India. The study was conducted using data collected in CDSCO’s ADR reporting forms with CADR from June 2015 to July 2017. Patient’s information, details related to adverse drug reaction, suspected medication details, concomitant medication history, causality and seriousness were recorded.Results: A total of 102 CADR were evaluated in this study. The mean age of sample was 37.21±20.33 years. Maximum number of cases was in the age group of 40-49 years. Male to female ratio was 0.96:1. The commonly incriminated drugs causing CADR were antimicrobial agents. Ciprofloxacin (21.57%), phenytoin (9.8%), diclofenac sodium (6.86%), anti-snake venom (6.86%) and vancomycin (3.92%) were the common drugs implicated in CADR. Maculopapular rash and itching were the most common CADR. Anticonvulsants especially phenytoin was commonly associated with severe CADR.Conclusions: The present study has made an impact on all departments of this institution and awareness has been created about spontaneous reporting of all adverse drug reactions in CDSCO ADR reporting forms to the pharmacovigilance centres. Thus, sound knowledge about the adverse drug reactions may decrease the occurrence of drug induced morbidity and mortality.

Game theory based Ad-hoc On Demand Distance Vector Routing Protocol to Extend the Wireless Sensor Networks Life Time

This paper proposes a solution to increase the energy life time of wireless sensor networks (WSNs) via a concept of game theory enabled ad-hoc on demand distance vector (AODV) routing algorithm. Game theory is an optimal promising candidate for decision making in a wireless networking scenario to find the optimal path for data packets transfer between source node and destination node, where combination with the AODV routing algorithm, a procedure of game theory enabled AODV (GTEAODV) is developed and proposed in this research paper. The developed and proposed methodology is validated through simulation in NS2 environment and the results show an improvement in energy life time of the order of 30-35% in comparison to the existing routing methodology which uses co-operative routing techniques among the nodes in WSN. Further, the throughput of game theory enabled adhoc on demand routing is also highly improved in comparison to existing traditional approaches though obtained results. Though, game theory approach is an existing approach concatenation of it with AODV can provide increased network performance which is significant as portrayed in research results shown in the paper. Hence, by virtue of providing enhanced energy life time and data security through the nature of the algorithm, the proposed GTEAODV algorithm can be employed in defence applications for secure data transmission and reception for forthcoming deployment of 5G systems which are blossoming in world wide scenario

Detection of fetal brain abnormalities using data augmentation and convolutional neural network in internet of things

The all-embracing morphological changes in fetal brain development in the whole time pregnancy are visually seen in acquisition of Magnetic Resonance Imaging (MRI) techniques. In the way of exploring fetal brain development, Convolutional Neural Network (CNN) technique brings out automatic segmentation and classification. Monitoring fetal brain development is crucial to prevent brain abnormality. With the automation and resource optimization provided by IOT technology in healthcare applications, the national healthcare industries can improve the quality of care while lowering costs. The remarkable progresses in image recognition tasks are undergone via CNN to recognize complex patterns in image data. It faces the standstill challenges in observing the fetal brain development inclusive of 16–39 weeks gestation images and explores the optimized performance evaluation for quantitative assessment. The goal of this research is to improve access to brain development information by utilizing modern medical detection method as well as embedding IoT (internet of things). The brain malformations are considered as a problem in recent days, to overcome this problem the Detection of Fetal Brain Abnormalities (DFBA) using Data Augmentation is proposed in this paper and the IOT technology is helps to identify the detection in easy way. The proposed DFBA perform in three stages image pre-processing, model build and performance evaluation. The input dataset comprises 875 MRI scan images taken from the Harvard medical school with the training set as 80%, testing set as 10%, and validation set as 10%. Once the data is retrieved, the preprocessing techniques are carried out using Normalization and Reshaping for better progress and result. In sequence to pre-processing, Data augmentation is applied to increase the size of the dataset for CNN to be processed for classification. The efficiency of the proposed DFBA approach has been determined using the evaluation metrics such as Recall, F1-score, Accuracy, Precision, Confusion matrix and Support. The proposed method peculiarly tests set accuracy as 83% are obtained which is better than the existing classifiers

Abstracts of the International Conference on Recent Trends in Mathematics and Computer Science 2023

This book presents the abstracts of the selected contributions to the International Conference on Recent Trends in Mathematics and Computer Science 2023 (ICRTMCS-2023), held on 19-21 October 2023 by the Auxilium College of Arts and Science for Women, Regunathapuram, Tamil Nadu, India. ICRTMCS-2023 was a multidisciplinary conference organized with the objective of bringing together eminent academicians, research scholars, and students to exchange ideas, communicate, to discuss research findings and new advances on recent and emerging trends in the field of Mathematics and Computer Science. Moreover, the conference would also enable the participants to explore new fields and gain immense knowledge. Conference Title: International Conference on Recent Trends in Mathematics and Computer Science 2023Conference Acronym: ICRTMCS-2023Conference Date: 19-21 October 2023Conference Venue: Hybrid (Online and Auxilium College of Arts and Science for Women, Regunathapuram, India)Conference Organizer: Departments of Mathematics and Computer Science, Auxilium College of Arts and Science for Women, Regunathapuram, Tamil Nadu, Indi

TEQIP - III Sponsored First International Conference on Innovations and Challenges in Computing, Analytics and Security

This book contains abstracts of the various research papers of the academic & research community presented at the International Conference on Innovations and Challenges in Computing, Analytics and Security (ICICCAS-2020). ICICCAS-2020 has served as a platform for researchers, professionals to meet and exchange ideas on computing, data analytics, and security. The conference has invited papers in seven main tracks of Data Science, Networking Technologies, Sequential, Parallel, Distributed and Cloud Computing, Advances in Software Engineering, Multimedia, Image Processing, and Embedded Systems, Security and Privacy, Special Track (IoT, Smart Technologies and Green Engineering). The Technical and Advisory Committee Members were from various countries that have rich Research and Academic experience. Conference Title: TEQIP - III Sponsored First International Conference on Innovations and Challenges in Computing, Analytics and SecurityConference Acronym: ICICCAS-2020Conference Date: 29-30 July 2020Conference Location: Pondicherry Engineering College, Puducherry – 605014, India (Virtual Mode)Conference Organizer: Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, India.Conference Sponsor: TEQIP-III NPIU (A Unit of the Ministry of Human Resource Development, India)