Quantitative (Non-qualitative) Changes of IgG Anti-Mumps After Freeze-‎Thaw Cycles

Object. The result of freeze-thaw (FT) tested sera is always doubtful, and is a matter of question which is accompanied by false negative results. Aim: To determine the effect of repeated FT cycles, on the assay results of mumps IgG antibody. Material and Methods. This prospective laboratory study includes 25 volunteers. 25 sera underwent tests for first Mumps IgG antibody, and then were frozen at -20 degrees centigrade. One week later, they were thawed and stored again at 4 degrees centigrade for one more week when the second assays, were performed. The results for mumps IgG ELISA as an effect of two FT cycles and storage temperature were reported. The results were recorded by first and second Immune Serum Ratio (ISR) value (for first and second assay) and the percentage change of ISR. A linear regression model applied for analyzing ISR change percentage. Results. There were three kinds of ISR value change as: 1-The stable ISR value (44%). 2-The decreasing change of ISR value (32%) mainly among males, older in age (14-19 years) and the first ISR more than the value of four. 3-The increasing change of ISR value (24%) which occurred in males 10-12 years with the first ISR value of 1-2 (lowest concentration). Based on regression model, level of the first ISR and group of test were significant factor for change percentage of ISR, but neither gender nor age, were significant. Discussions. Mumps IgG antibody , as a function of two FT cycles, was affected by quantitative but not qualitative alteration. If the first ISR has value of 3-4, most probably it wills no any significant changes due to at least two FT cycles

Effect of valerian capsules in patients with migraine attacks treated with sodium valproate: a randomized clinical trial

Background and aims: Nowadays so many preventive drugs for migraine with different effects are used all around the world. One of the plants that are used traditionally in the treatment of migraine is Valeriana officinalis. The present study was aimed to evaluate the effect of valerian capsule (350 mg, three times daily) on frequency, duration and intensity of migraine attacks. Method: The present study is a Randomized, single-blind clinical trial that is carried out on 84 female patients suffering from migraine headaches. The patients were randomly allocated to case (n=42) and control groups (n=42) and treated during three consecutive phases of 45 days. In the first phase, both groups received sodium valproate tablet, (200 mg, twice daily) and indomethacin capsule (25 mg, in attacks). In the second phase, valerian capsule (350 mg, three times daily) was added to other drugs of case group. Control group received placebo instead of valerian. Finally, in the third phase, both groups were treated the same as the first phase. And then the data obtained from the drug influence on pain intensity were analyzed based on Mann-Whitney and K2. Results: All 84 patients cooperated to the end of study. The results indicated that valerian capsule significantly reduced the frequency, duration and intensity of migraine attacks in a way that the mean of migraine attacks reduced from 6.2±2.3 to 2.2±1.2, the duration reduced from 17.0± 9.2 to 5.7±3.7 hours and intensity from 8.7±1.2 to 3.0±1.3. Conclusion: According to the remarkable effect of valerian capsule on the prevention of migraine attacks, it seems that it can be a potential alternative to common migraine medications

Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach

Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables "number of blood donation" and "number of blood deferral": as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models. © 2016 Tayeb Mohammadi et al

A correlated frailty model for analysing risk factors in bilateral corneal graft rejection for Keratoconus: a Bayesian approach

There are many unknown causes that increase the rate of corneal graft rejection. In bilateral cases, some of these unknown causes are common, and some are individual factors. In this paper, we use a correlated frailty model to analyse risk factors for bilateral corneal graft in Keratoconus. Applying the piecewise constant baseline hazard model, we have performed a Bayesian analysis of the correlated frailty model using the Markov chain Monte Carlo method. The correlated frailty model and the shared frailty model are compared by deviance information criterion. The results show more accurate and better fit for the correlated frailty model. Copyright (C) 2005 John Wiley & Sons, Ltd

Artificial Neural Network to Modeling Zero-inflated Count Data: Application to Predicting Number of Return to Blood Donation.

BACKGROUND Traditional statistical models often are based on certain presuppositions and limitations that may not presence in actual data and lead to turbulence in estimation or prediction. In these situations, artificial neural networks (ANNs) could be suitable alternative rather than classical statistical methods. STUDY DESIGN  A prospective cohort study. METHODS The study was conducted in Shahrekord Blood Transfusion Center, Shahrekord, central Iran, on blood donors from 2008-2009. The accuracy of the proposed model to prediction of number of return to blood donations was compared with classical statistical models. A number of 864 donors who had a first-time successful donation were followed for five years. Number of return for blood donation was considered as response variable. Poisson regression (PR), negative binomial regression (NBR), zero-inflated Poisson regression (ZIPR) and zero-inflated negative binomial regression (ZINBR) as well as ANN model were fitted to data. MSE criterion was used to compare models. To fitting the models, STATISTICA 10 and, R 3.2.2 was used RESULTS: The MSE of PR, NBR, ZIPR, ZINBR and ANN models was obtained 2.71, 1.01, 1.54, 0.094 and 0.056 for the training and 4.05, 9.89, 3.99, 2.53 and 0.27 for the test data, respectively. CONCLUSIONS The ANN model had the least MSE in both training, and test data set and has a better performance than classic models. ANN could be a suitable alternative for modeling such data because of fewer restrictions

The effect of teaching using, problem base learning and lecture on behavior, attitude and learning of nursing (BSc) students

Background and aim: Problem base learning results in the clarification of the words and concepts, the definition of the concepts, problem analysis, providing a systematic method to describe the situation during analysis process, the determination of learning objectives, getting more knowledge according to learning requirements and merging of the new knowledge with solutions. Regarding the progress of nursing science across the world and the importance of promotion in nursing education using new educational methods, the aim of this research was to determine the effect of teaching using both problem base learning and lecture on behavior, attitude and learning of nursing (BSc) students at Shahre-Kord university of medical science. Methods: This research was a semi-experimental study involved 40 of nursing (at 4th semester) students at Shahre-Kord university of medical sciences who were learning the internal course (surgery 2). They were selected using conventional sampling method and divided into two equal groups of case and control, using random sampling method. The problem base learning and lecture methods were used to teach individuals of case and control groups, respectively. At the end of the course, using a questionnaire, behavior, attitude, and learning of the students were assessed. Using T and Manvitni tests, the data was analyzed. Results: The students were 95% female and single. The mean of age in both groups was 22/04±1 years. There was no significant difference between the two groups in terms of the three former semester average scores, using t-test. The mean of learning in the case and control was 68.24±6.8 and 44.98±9.8, respectively. The mean of attitude in the case and control was 123.3±21 and 96.8±8 and the mean of behavior in the two groups was 69.5±2.5 and 63±3.1, respectively (p<0.001). There was significant statistical difference (p<0.05) in the two categories of evaluation and application between the two groups studied (p<0.05). There was also slight difference in the level of understanding between these two groups. Conclusion: Based on the results, teaching by problem base learning is more useful than lecture in modification and improvement of learning and attitude of the students studied. The results of this research is offered and recommended to the educational officials to substitute this method for the traditional ones

A hybrid ANN-GA model to prediction of bivariate binary responses: Application to joint prediction of occurrence of heart block and death in patients with myocardial infarction

Background: In medical studies, when the joint prediction about occurrence of two events should be anticipated, a statistical bivariate model is used. Due to the limitations of usual statistical models, other methods such as Artificial Neural Network (ANN) and hybrid models could be used. In this paper, we propose a hybrid Artificial Neural Network-Genetic Algorithm (ANN-GA) model to prediction the occurrence of heart block and death in myocardial infarction (MI) patients simultaneously. Methods: For fitting and comparing the models, 263 new patients with definite diagnosis of MI hospitalized in Cardiology Ward of Hajar Hospital, Shahrekord, Iran, from March, 2014 to March, 2016 were enrolled. Occurrence of heart block and death were employed as bivariate binary outcomes. Bivariate Logistic Regression (BLR), ANN and hybrid ANN-GA models were fitted to data. Prediction accuracy was used to compare the models. The codes were written in Matlab 2013a and Zelig package in R3.2.2. Results: The prediction accuracy of BLR, ANN and hybrid ANN-GA models was obtained 77.7%, 83.69% and 93.85% for the training and 78.48%, 84.81% and 96.2% for the test data, respectively. In both training and test data set, hybrid ANN-GA model had better accuracy. Conclusions: ANN model could be a suitable alternative for modeling and predicting bivariate binary responses when the presuppositions of statistical models are not met in actual data. In addition, using optimization methods, such as hybrid ANN-GA model, could improve precision of ANN model. © 2016, Health Hamadan University of Medical Sciences. All rights reserved

Influential factors on growth parameters in infants using quantile regression analysis

زمینه و هدف: یکی از مسایل مهمی که بر سلامت جامعه تأثیر می گذارد، سلامت رشد کودک می باشد. بر این اساس شناخت عوامل موثر بر رشد جسمی کودکان و نیز شناخت اقدامات لازم برای حفظ و ارتقای سلامت آن ها بسیار مهم است. هدف از مطالعه حاضر تعیین عوامل مؤثر بر شاخص های رشد شیرخواران شامل قد، وزن و دور سر در شیرخواران با استفاده از تحلیل رگرسیون چندک می باشد. روش بررسی: در این مطالعه توصیفی- تحلیلی از اطلاعات مطالعه کوهورت انجام شده، در گروه تحقیقات طب اسلامی دانشگاه علوم پزشکی شهرکرد، از ماه مبارک رمضان سال 1385 تا 1388، استفاده شده است. 92 نوزاد سالم که دارای شرایط ورود به مطالعه بودند، مورد بررسی قرار گرفتند. اثرات عوامل موثر برروی شاخص های رشد، وزن، قد و دور سر، در چندک ‌های مختلف با استفاده از مدل رگرسیون چندک مقایسه شد. یافته ها: بر اساس نتایج، شاخص های رشد با وزن ابتدای تولد رابطه مستقیم دارد. تأثیر مستقیم سن مادر نیز تا 6 ماه برای وزن و دور سر کاملاً مشهود بود. رتبه تولد روی شاخص های رشد اثری معکوس داشت. مصرف آهن در چندک های 20 و 40 قد و مصرف شیر مادر در دهک دوم دور سر معنی دار بود (05/0>P). نتیجه گیری: نتایج به دست آمده از روش رگرسیون چندک به خاطر برازش خطوط رگرسیونی مختلف جامع تر از روش رگرسیون خطی بود و اثرگذاری متغیرهای تحصیلات پدر، رتبه تولد، شاخص توده بدنی مادر، تعداد اعضای خانواده، مصرف آهن، ویتامین و شیر مادر توسط رگرسیون خطی یافت نشد. در ضمن توجه بیشتری نسبت به شاخص های رشد دختران خصوصاً تا بعد از 6 ماه باید صورت گیرد

FREE INTERACTOR MATRIX METHOD FOR CONTROL PERFORMANCE ASSESSMENT OF MULTI-VARIATE SYSTEMS

In this paper, an alternative method for the assessment of multi-vitiate control loop performance with consider twocircumstances. First, known time delays between each pair of inputs and outputs, and second, without relying on any a priori knowledge about the process model or timedelays. The performance of the control loop is calculated from data driven autoregressive moving average (ARMA) and prediction error model. It is clear that the limited data in scalar measure used for performance assessment results tends to steady-state as time tends to infinity, but large number of samples gives risen in scalar measures and tends to infinity as time samples tends to infinity and therefore it becomes difficult to calculate the performance index. In this paper, the later problem is solved by considering initial part of scalar measures with steady value for next-to-next time samples to calculate the control-loop performance index which would be utilized to decide healthy working of the control loop. Simulation example is included to show the performance index of multi-variate control loop