Abstract: Background: The incidence of adverse reactions to iodinated contrast media has risen. The dearth of reports on reactions to the administration of iso- and low-osmolar contrast media should be addressed. We, therefore, studied the profile of adverse reactions to iodinated contrast media; viz., (a) the body systems affected (b) causality, (c) severity, and (d) preventability. Objective: To study adverse reactions (causes and severity) to iodinated contrast media at Srinagarind Hospital. Method: Between March and July, 2015, 1,101 patients from the Department of Radiology were observed and interviewed for the occurrence of adverse reactions. The patients were classified per Naranjo’s algorithm and through use of an adverse reactions questionnaire. Results: A total of 105 cases (9.5%) reported adverse reactions (57% male; 43% female); among whom 2% were iso-osmolar vs. 98% low-osmolar. Diagnoses included hepatoma and cholangiocarcinoma (24.8%), colorectal cancer (9.5%), breast cancer (5.7%), cervical cancer (3.8%), lung cancer (2.9%), bone cancer (1.9%), and others (51.5%). Underlying diseases included hypertension and diabetes mellitus type 2. Mild, moderate, and severe adverse reactions accounted for 92, 5 and 3%, respectively. The respective groups of escalating symptoms included (a) mild urticaria, itching, rash, nausea, vomiting, dizziness, and headache; (b) moderate hypertension, hypotension, dyspnea, tachycardia and bronchospasm; and (c) severe laryngeal edema, profound hypotension, and convulsions. All reactions could be anticipated per Naranjo’s algorithm. Conclusion: Mild to moderate adverse reactions to low-osmolar contrast media were most common and these occurred immediately after administration. For patient safety and better outcomes, improving the identification of patients likely to have an adverse reaction is essential.
Abstract: In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.
As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.
Abstract: Upper gastrointestinal endoscopy is a commonly performed diagnostic and therapeutic procedure and has many adverse effects like cardiopulmonary complications, complications related to sedation, infectious complications, bleeding and perforation. So this study was undertaken to evaluate important variables like patient’s age, gender and stage of the procedure in relation to the cardiopulmonary changes during diagnostic upper gastrointestinal endoscopy by monitoring oxygen saturation, blood pressure, heart rate and electrocardiogram. This is a prospective longitudinal hospital based study involving a total of 140 consecutive patients, at Sri. B. M. Patil Medical College, Hospital and Research Centre. Cardiopulmonary changes during upper gastrointestinal endoscopy are more common in the age groups of 51-60 years, with equal frequency in both male and female. Oxygen saturation levels decreased by about 4% in both sexes during introduction of endoscopy. Mild to moderate hypoxia was found in 32% of the study group. Severe hypoxia was found in 5% of the patients, mostly in those patients who are above 50 years of age. Tachycardia was noted in 88% of the study group patients. Blood pressure increased to hypertension levels in 22 patients (15.7%) which returned to normal within few minutes after the procedure. S-T depression was noticed in 4% of patients and T wave inversion in 8% of patients during upper gastrointestinal endoscopy. All these changes disappeared after 10 minutes after the endoscopy. Cardiopulmonary changes are common during upper gastrointestinal endoscopy. Maximum changes in oxygen saturation, heart rate and blood pressure occurred immediately after the introduction of endoscope. The cardiopulmonary changes did not manifest into any identifiable clinical symptoms. The rate of recovery was faster in younger age groups and women.
Abstract: Anxiety is a common disorder that attacks many people in society and often accompanied by physiological sensations such as tachycardia, chest pain, shortness of breath, insensitivity and etc. The purpose of this study is to characterize the putative anxiolytic-like effects of DEV (dichloromethane extracts of valerian) using the elevated plus maze (EPM) in rats. DEV was dissolved in DMSO and orally administered at different doses to adult male wistar rats, 0.5, 1.5 and 3 hours before behavioral evaluation in an EPM respectively. Control rats were treated with an equal volume of DMSO. Single treatment of DEV (at 0.1,0.2. 0.3, and 0.4 g/kg) significantly increased time-spent and arm entries into open arms of EPM versus control groups (p
Abstract: The technological concepts such as wireless hospital
and portable cardiac telemetry system require the development of
physiological signal acquisition devices to be easily integrated into
the hospital database. In this paper we present the low cost, portable
wireless ECG acquisition hardware that transmits ECG signals to a
dedicated computer.The front end of the system obtains and
processes incoming signals, which are then transmitted via a
microcontroller and wireless Bluetooth module. A monitoring
purpose Bluetooth based end user application integrated with patient
database management module is developed for the computers. The
system will act as a continuous event recorder, which can be used to
follow up patients who have been resuscitatedfrom cardiac arrest,
ventricular tachycardia but also for diagnostic purposes for patients
with arrhythmia symptoms. In addition, cardiac information can be
saved into the patient-s database of the hospital.
Abstract: An electrocardiogram (ECG) feature extraction system
based on the calculation of the complex resonance frequency
employing Prony-s method is developed. Prony-s method is applied
on five different classes of ECG signals- arrhythmia as a finite sum
of exponentials depending on the signal-s poles and the resonant
complex frequencies. Those poles and resonance frequencies of the
ECG signals- arrhythmia are evaluated for a large number of each
arrhythmia. The ECG signals of lead II (ML II) were taken from
MIT-BIH database for five different types. These are the ventricular
couplet (VC), ventricular tachycardia (VT), ventricular bigeminy
(VB), and ventricular fibrillation (VF) and the normal (NR). This
novel method can be extended to any number of arrhythmias.
Different classification techniques were tried using neural networks
(NN), K nearest neighbor (KNN), linear discriminant analysis (LDA)
and multi-class support vector machine (MC-SVM).
Abstract: The application of Neural Network for disease
diagnosis has made great progress and is widely used by physicians.
An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which
was the great motivation towards our study. In our work, tachycardia
features obtained are used for the training and testing of a Neural
Network. In this study we are using Fuzzy Probabilistic Neural
Networks as an automatic technique for ECG signal analysis. As
every real signal recorded by the equipment can have different
artifacts, we needed to do some preprocessing steps before feeding it
to our system. Wavelet transform is used for extracting the
morphological parameters of the ECG signal. The outcome of the
approach for the variety of arrhythmias shows the represented
approach is superior than prior presented algorithms with an average
accuracy of about %95 for more than 7 tachy arrhythmias.