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Adverse events following pediatric immunization in an Indian city
Varun Paramkusham,Prashanth Palakurthy,Navya sri Gurram,Varun Talla,Hunsur Nagendra Vishwas,Venkateshwar Rao Jupally,Satyanarayan Pattnaik 대한백신학회 2021 Clinical and Experimental Vaccine Research Vol.10 No.3
Purpose: Adverse effects are noticeable immediately after vaccination, especially when vaccinated to healthy people at the time of vaccination. The vaccine may cause adverse events which are very rare but adverse event following immunization surveillance becomes correspondingly more important in a less studied population like India. Hence, there is a need for carrying out a study pertaining to vaccine safety in the pediatric population of age 0–12 years and assessing the events occurring post-vaccination. Materials and Methods: A prospective observational study was conducted in three primary healthcare centers and two tertiary care hospitals for 6 months from April 2016 to September 2016 with a total of 826 children enrolled. Detected adverse events for suspected vaccines were analyzed for causality by the World Health Organization causality assessment instrument. Sex-specific differences in incidences of adverse events were assessed. Results: The cumulative adverse events were found highest in pentavalent vaccines (510 incidences, 62.04%) followed by the bacillus Calmette-Guérin vaccine (189 incidences, 22.99%). The study didn’t reveal any significant association in incidences of adverse events following immunization and sex of the children. Conclusion: Vaccine safety surveillance studies are need of the hour in developing countries to maintain public trust in vaccines, the ultimate objective being to have vaccines with the most favorable benefit-risk profile. The present study discussed the various adverse events following immunization and suggested the absence of any sex-specific difference in incidences of adverse events in children.
Varun Thakur,Sanjay Kumar Nayak,Kodihalli Keeriti Nagaraja,Sonnada Math Shivaprasad 대한금속·재료학회 2015 ELECTRONIC MATERIALS LETTERS Vol.11 No.3
Surface nitridation of the c-sapphire substrate is used to improve the optical and structural quality of a GaN nanowall network film grown by plasma assisted molecular beam epitaxy. The nitridation results in the formation of a thin AlN layer on the sapphire surface. Several in-situ and ex-situ characterization are complementarily used to probe the changes in epitaxial growth, band edge emission and strain in the films. The GaN nanowall network layer formed on the pre-nitrided substrate shows a two order higher intensity of band edge luminescence than that of a GaN epilayer, demonstrating its potential for light-emission applications.
Varun Arvind,Jun S. Kim,Eric K. Oermann,Deepak Kaji,Samuel K. Cho 대한척추신경외과학회 2018 Neurospine Vol.15 No.4
Objective: Machine learning algorithms excel at leveraging big data to identify complex patterns that can be used to aid in clinical decision-making. The objective of this study is to demonstrate the performance of machine learning models in predicting postoperative complications following anterior cervical discectomy and fusion (ACDF). Methods: Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), and random forest decision tree (RF) models were trained on a multicenter data set of patients undergoing ACDF to predict surgical complications based on readily available patient data. Following training, these models were compared to the predictive capability of American Society of Anesthesiologists (ASA) physical status classification. Results: A total of 20,879 patients were identified as having undergone ACDF. Following exclusion criteria, patients were divided into 14,615 patients for training and 6,264 for testing data sets. ANN and LR consistently outperformed ASA physical status classification in predicting every complication (p<0.05). The ANN outperformed LR in predicting venous thromboembolism, wound complication, and mortality (p<0.05). The SVM and RF models were no better than random chance at predicting any of the postoperative complications (p<0.05). Conclusion: ANN and LR algorithms outperform ASA physical status classification for predicting individual postoperative complications. Additionally, neural networks have greater sensitivity than LR when predicting mortality and wound complications. With the growing size of medical data, the training of machine learning on these large datasets promises to improve risk prognostication, with the ability of continuously learning making them excellent tools in complex clinical scenarios.
Dimension reduction and classification in ECG signal interpretation using FA & PCA: A comparison
VARUN GUPTA,MONIKA MITTAL 장전수학회 2018 Proceedings of the Jangjeon mathematical society Vol.21 No.4
Electrocardiogram (ECG) is the electrical activity of the heart. It consists of P-wave, QRS complex and T-wave. Each beat shows electrical impulse propagation in the heart of the body. Due to higher dimension of ECG signal, its analysis needs dimension reduction tech- niques for pre-processing of the data. In this paper, authors proposed Factor Analysis (FA) and Principal Component Analysis (PCA) for re- ducing dimension of the ECG signal. The choice of its usage depends on problem which is clearly known and specied. Physionet ECG data- base (MIT-BIH long term ECG database, Ventricular Tachyarrhythmia, AHA(American Heart Association) Database) and real time ECG data- base has been used in this paper for checking detector performance using FA and PCA. PCA gave better results than FA. SNR (Signal to Noise Ratio) is also checked and calculated that is 93.25 dB and 91.25 dB for PCA and FA respectively. Dierent work proposed by dierent authors on ECG signal classification has been compared.
Varun Bajaj,Ram Bilas Pachori 대한의용생체공학회 2013 Biomedical Engineering Letters (BMEL) Vol.3 No.1
Purpose Epileptic seizure is generated by abnormal synchronization of neurons of the cerebral cortex of the patients,which is commonly detected by electroencephalograph (EEG)signals. In this paper, the intracranial EEG signals have been used to detect focal temporal lobe epilepsy. Methods This paper presents a new method based on empirical mode decomposition (EMD) of EEG signals for detection of epileptic seizures. The proposed method uses the Hilbert transformation of intrinsic mode functions (IMFs),obtained by EMD process that provides analytic signal representation of IMFs. The instantaneous area measured from the trace of the windowed analytic IMFs of EEG signals provides rules-based detection of focal temporal lobe epilepsy. Results The experiment results on intracranial EEG signals are included to show the effectiveness of the proposed method for detection of focal temporal lobe epilepsy. The performance evaluation of the proposed method for epileptic seizure detection has performed by computing the sensitivity (SEN),specificity (SPE), positive predictive value (PPV), negative predictive value (NPV) and error rate detection (ERD). Conclusions The proposed method has been compared to the existing methods for detecting focal temporal lobe epilepsy from intracranial EEG signals. The proposed method has provided detection of focal temporal lobe epilepsy with increased accuracy.
Varun Arya,Vijay Laxmy Malhotra,JK Dayashankara Rao,Shruti Kirti,Siddharth Malhotra,Radhey Shyam Sharma 대한구강악안면외과학회 2019 대한구강악안면외과학회지 Vol.45 No.5
Objectives: This study examined the effects of plasma-rich growth factors (PRGF) on accelerating bone regeneration/repair in fresh extraction sock-ets, and determined the quality and quantity of bone by assessing the bone density using cone-beam computed tomography (CBCT). Materials and Methods: Twenty patients, who had undergone bilateral extractions, were included in this study. In one extraction socket, PRGF was used and covered with an autologous fibrin plug. Nothing was used in the opposite side extraction socket. Thirteen weeks post extraction, the level of bone regeneration was evaluated on both sides with CBCT. Results: At the end of the study, the mean bone density according to the Hounsfield units (HU) in the control group and PRGF group was 500.05 HU (type III bone type) and 647.95 HU (type II bone type), respectively. Conclusion: This study recommends the use of PRGF in post extraction sites to accelerate the rate of bone regeneration and improve the quality of regenerated bone. The technique to process PRGF was simple compared to previously mentioned techniques used for platelet-rich plasma (PRP) preparation. PRP preparation requires a two-cycle centrifugation procedure, leading to a longer processing time.