Payavard Salamat

Use of Gabapentin in Management of Acute Pain After Surgery: Review of Literature

Amir Hossein Eskandari

Background and goals: Breast surgery is one of the most common surgical operations performed worldwide as well as in Iran. Acute postoperative pain is managed by different therapeutic modalities in these procedures, and opioid are the most frequently used option; however their adverse consequences imposes restriction of use. The goal of this article is to review the effects of gabapentin on postoperative pain and opioid use in breast surgeries.
Materials and Method: PubMed, Ovid Medline, and Scopus databases from 2000 to 2019; as well as Google scholar, first 350 results, were searched for all clinical trials and review articles about the subject, using various related keywords. Sixty-two articles were reviewed by 2 researchers and finally data from 22 papers were gathered and assessed.
Results: This review demonstrates that gabapentin is effective in reducing acute postoperative pain after operations of the breast. Also, rate of opioid consumption, an important objective in the period after surgery, is reduced by use of opioids.
Conclusion: This study prompts the effectiveness of gabapentin in controlling postoperative pain in breast operations; since this drug is very seldom used for this purpose in our country, we propose that medical staff consider it as a powerful option after breast procedures.

Identifying Important Factors of Arthroplasty in Patients with Degenerative Knee Osteoarthritis Based on Association Rule Mining Approach

Seyed Mohammad Javad Mortazavi

Background and Aim: Total Knee Arthroplasty (TKA) aims to reduce the pain and improve the quality of life of patients with progressive osteoarthritis. When the indication of patients' disease is established, this type of surgery should be performed as soon as possible because patients' late attendance increases surgical complications. Therefore, identification of factors influencing the choice of this type of treatment approach is of great importance. The purpose of this study is to identify the factors that influence the choice of this treatment approach in patients using the Apriori algorithm in the form of Association Rules.
Materials and Methods: This study is performed on 233 patients referring to Imam Khomeini Hospital in Tehran for a knee replacement surgery; the needed data have been registered at Bone and Joint Reconstruction Research Center. In this study, after the preprocessing stage, the important factors in decision making of knee replacement surgery have been identified by using the Apriori algorithm and by its implementation in the software environment of RStudio. After being extracted, these factors and the relationship among them are given to orthopedic practitioners for confirmation.
Results: In this study, flexion contracture above 20 degrees, deformity (varous-valgus) above 15 degrees, final flexion between 51-75 degrees, and medial cartilage destruction were, respectively, the most important factors in selecting patients for knee replacement therapy.
Conclusion: The results showed that data-mining Algorithms could be used to identify effective factors to select patients for this treatment approach.

Survey on the Contamination Rate of Stagnant Water and Soil to Vermamoeba vermiformis in Arak Parks, Iran, 2017-2018

Sima Rasti

Background and Aim: Vermamoeba vermiformis is an opportunistic free living amoeba(FLA) that is ubiquitous in different environmental sources. This Amoeba can cause Amoebic Keratitis(AK) and Granulomatous Amoebic Encephlitis (GAE) in immunocompromised patients. This study was conducted to determine the rate of Vermamoeba vermiformis in stagnant water and soil in Arak.
Materials and Methods: In this Cross-Sectional study, stagnant water(60) and soil samples(36) were collected from Arak parks. The samples were filtered in 0.45µm nitrocellulose paper and cultured on to 1.5% NNA for the presence of free living amoeba(FLA). After DNA extraction, Vermamoeba vermiformis was identified by Polymerase Chain Reaction(PCR) using primers NA1 and NA2. Eight isolates of Vermamoeba vermiformis were sequenced blasted and after confirmation, recorded in the Gene Bank. The data were recorded in SPSS.16 and analyzed using X² and Fischer Exact test.
Results: Out of 96 environmental sources, 29.2% were positive for free living amoeba. The rate of FLA pollution in stagnant water and soil were 28.3 and 30.6% respectively(P<0.001). The contamination rate of stagnant water and soil with Vermamoeba vermiformis were 10% and 16.7%, respectively(P<0.001).
Conclusion: The results of the present study revealed ,that stagnant water and soil resources were contaminated to FLA and Vermamoeba. Due to the Pathogenic ability of this amoeba and the possibility of endosymbian pathogens in it, health education is recommended for controlling and preventing the disease, especially in susceptible patients, including those who use contact lenses.

The Relationship between the Use of Social Networks and the Health Literacy of Ilam Public Library Users in 2018

Saleh Rahimi

Background and Aim: Due to the impact of health literacy on how people decide about their health, such literacy is considered as one of the important issues in improving community health. The purpose of this study was to determine the relationship between the use of social networks and the health literacy of Ilam public library users.
Materials and Methods: The present study is a practical research conducted based on descriptive-survey method in 2018. Sample size was selected by stratified random sampling. Besides, a three-part questionnaire was applied for data collection. Moreover, SPSS software was used for data analysis: Aanalysis of the mean, standard deviation and correlation coefficient.
Results: According to the average scores, public library users have had good results in health literacy components, with the aim of understanding, assessment, reading, decision making, and access to health information. Also, there was a significant relationship between the use of social networks and users' health literacy; in other words, if there was an increase in the use of social networks, health literacy level would increase.
Conclusion: Since social networks have been instrumental in enhancing the health literacy of public library users as a source of health and sanitary information, appropriate social networking can be provided to share experiences and increase the level of users' health literacy by taking into account the security of users' information and the accuracy of the given information, thereby providing new opportunities and conditions for users, doctors, patients, and planners of this domain.

The Impact of Organizational Climate of College and Hospital Libraries of Medical Sciences Universities on Librarians' Job Burnout

Fatemeh Sheikhshoaei

Background and Aim: Considering the effect of organizational climate on work motivation, not using the librarians who have a satisfactory feeling about their job can cause irreversible damages to the library. Therefore, the aim of this study is to determine the effect of organizational climate of college and hospital libraries on the burnout of librarians working there.
Materials and Methods: This is an applied research and a descriptive-analytical survey. One hundred seventy-seven librarians from faculties and hospital libraries affiliated to Tehran, Iran and Shahid Beheshti Universities of Medical Sciences were surveyed by census method in 2019. Data collection instruments were Halpin and Croft's organizational climate and Maslach and Jackson job burnout questionnaires. The validity was confirmed by 3 experts and the reliability by Cronbach's alpha coefficient. For data analysis, SPSS software, and descriptive and analytical statistics were used.
Results: The findings showed that the mean of organizational climate was at a desirable level (3.4) and the average of job burnout was 1.7; therefore, the job burnout status of librarians is desirable because it is a negative variable. Also, the components of organizational climate predict 41% of job burnout variable. Among demographic characteristics, job burnout variable varies only in terms of field of study, and organizational climate only in terms of the type of library.
Conclusion: In general, the organizational climate status and job burnout status of the studied libraries are desirable; also, organizational climate components affect job burnout.

Study of Association between Factor XI Polymorphism and Recurrent Miscarriage in Iran Helal Infertility Center (Rouyesh) Patients

Hamid Choobineh

Background and Aim: Recurrent pregnancy loss(RPL) is known as two or three pregnancy losses before 20^th week of pregnancy. RPL accounts for 5% of abortions in women and has a devastating effect on the marital status of families. One of the reasons for RPL is hemostatic complications; thus, we studied the correlation between factor XI polymorphism and RPL in patients who referred to Helal Infertility Center(Rouyesh).
Material and Methods: In this case-control study, 144 patients with a history of miscarriages(at least two) and 150 healthy female with a minimum of one successful birth and no abortion were enrolled. DNA extraction was taken from leukocytes of whole blood. To investigate the polymorphisms, polymerase chain reaction was run, and the presence of polymorphism was analyzed using RFLP method.
Results: Regarding FXI polymorphism, TT, CT, and CC genotype frequencies were 59.7%, 36.1%, and 4.2%, respectively. In healthy control group, the TT, CT, and CC frequencies were 45.3%, 49.4%, and 5.3%, respectively.
Conclusion: TT homozygote genotype could be an RPL risk factor(p<0.05); however, in its CT heterozygote form, C allele could have a protective role against RPL.

The Analysis of Physicians' Acquittal according to Current Iranian Laws

Ahmadreza Khazaei

Background and Aim: Because of its direct connection with human life, medicine is a sacred profession that has been considered by infallible imams (pbuh) and stories have been told about it from the beginning of Islam. With the increasing progress of technology, the study of the relationship between a patient and his/her doctor and of patients' familiarity with their rights has expanded. However, what has been the focus of legislators' attention more than ever is the compensation of damages caused by medical acts.
Materials and Methods: First, using library resources and validated research articles, we conducted a comparison method. Then, the collected documents were studied with descriptive and analytical method. In addition to books, articles, and the writings of law and jurisprudence sites, the researcher benefited from the opinions of jurists, lawyers, physicians, and the losers of medical affairs to explain the purpose of this research.
Results: With certain rules, the legislator has removed the causes of physician's commitment and responsibility; obtaining the consent of the patient or his/her guardian before treatment is among them.
Conclusion: This article considers full support for the physicians' acts in curing patients. However, it is necessary to highlight the responsibilities of the medical team; in fact, non-compliance with medical regulations as well as technical standards and regulations will have legal consequences.

Diagnosis of Breast Cancer Using Decision Tree, Artificial Neural Network and Naive Bayes to Provide a Native Model for Fars Province

Ali Asghar Safaei

Background and Aim: Breast cancer is the most common type of cancer and the main cause of death from cancer in women worldwide. Technologies such as data mining, have enabled experts in this area to improve decision making in the early diagnosis of the disease. Therefore, the purpose of this research is to develop an automatic diagnostic model for breast cancer by employing data mining methods and selecting the model with the highest accuracy of diagnosis.
Materials and Methods: In this study, 654 available patient records of Motahari breast cancer Clinic in Shiraz" were used as the sample. The number of records was reduced to 621 after the pre-processing operation. These samples had 22 features that ultimately used ten were used as effective features in the design of the model. Three types of Decision tree, Naive Bayes and Artificial neural network were used for diagnosis of breast cancer and 10-fold cross-validation method for constructing and evaluating the model on the collected data set.
Results: The results of the three techniques mentioned all three models showed promising results in detecting breast cancer. Finally, the artificial neural network accounted for the highest accuracy of 94/49%(sensitivity 96/19%, specificity 86/36%) in the diagnosis of breast cancer.
Conclusion: Based on the results of the decision tree, the risk factors such as age, weight, Age of menstruation, menopause, OCP of records duration, and the age of the first pregnancy were among the factors affecting the incidence of breast cancer in women.