Survey of polypharmacy prescription in a tertiary care hospital, belagavi

  Polypharmacy is the use of four or more medications in one prescription or implies the prescription of too many medications for an individual. Concerns about polypharmacy include increase adverse drug reactions, drug interactions, prescribing cascade and higher cost. Objectives: To conduct a prescription survey of polypharmacy in tertiary care hospital at Belagavi. Methodology: The study was conducted in the Medicine outpatient department of a tertiary care hospital, Belagavi, after obtaining approval and clearance from the Institutional Ethics Committee. Total 83 patients were selected by Simple Random Sampling and the data were collected prospectively by direct observation in specially designed proforma containing relevant patient details like registration number, age, gender and diagnosis, disease data and drug data. Results: Out of the total sample population (N=83), 56.62% had prescriptions falling under major polypharmacy (>6 drugs), 43.37% had prescriptions categorized as minor polypharmacy (3-5 drugs). The most common age group of patients receiving prescriptions with polypharmacy was between 41 to 60 years accounting for 38.55%. Majority of the patients receiving prescriptions with polypharmacy in our study were females (59.03%) as compared to males (40.96%). Major polypharmacy is more prevalent in patients receiving treatment for Hypertension (60.24%) followed by patients with diabetes (23.67%). Conclusion: Our prescription survey portrays polypharmacy to be widely prevalent in a tertiary care setting. Specific treatment goals with certainty are the essential need for curing diseases rather than polypharmacy, which could be a possible threat of more harm than good

Dynamic Defense Mechanism for DoS Attacks in Wireless Environments Using Hybrid Intrusion Detection System and Statistical Approaches

Security in wireless frameworks is a significant and difficult task because of the open environment. The Denial of Service (DoS) is as yet significant endeavour to make an online assistance inaccessible. The objective of this attack is to keep the authentic nodes from getting to the administrations. Intrusion detection systems assume an essential job in identifying DoS attacks that improve the performance of the system. However massive information from the system presents huge difficulties to the discovery of DoS attack, as the identification framework needs adaptable techniques for gathering, storing and processing a lot of information. In order to defeat these difficulties, this paper proposes Hybrid Intrusion Detection System (HIDS) framework dependent on different MLP strategies. In this article HIDS utilizes Naive Bayes (NB), irregular random forest (RF), decision tree (DT), multilayer perceptron (MLP), K-nearest neighbours (K-NN) and support vector machine (SVM) for better outcomes. The NSL-KDD dataset and UNSW-NB15 dataset are taken to examine the detection accuracy. The experiment results show that the proposed defence system is accomplished with high accuracy, high detection rate and low false alarm rate in both the datasets