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Showing 4 results for Fathi
Response of Lipoprotein a, Blood Coagulation and Fibrinolysis Factors to Aerobic Exercise in Overweight Women
Roghayeh Shad, Nahid Bijeh, Mehrdad Fathi,
Volume 12, Issue 6 (Feb & Mar 2019)
Abstract
Background and Aim: Despite the significant progress in the field of health, Cardiovascular diseases are the leading cause of death among people. For this purpose, the present study was conducted to evaluate the effect of eight weeks of aerobic exercise on lipoprotein a, blood coagulation and fibrinolysis factors in overweight women.
Materials and Methods: In this semi experimental study with pre and post-test design, 21 overweight women subjects aged between 20 and 30 were randomly selected from experimental (10 people) and control (11 people). The aerobic exercise protocol consisted of five sessions per week for 30 minutes and with an intensity of 55%-75% heart rate reserve (HRR). Blood samples were collected from subjects in two stages to evaluate the considered variables. Measurement of levels of Lipoprotein a, Fibrinogen, PT, PTT, Platelet counts and Hemoglobin. For data analysis, repeated measures of variance analysis at a significant level of 5 hundredths were used by employing SPSS software.
Results: The mean values of Lipoprotein a, Fibrinogen, PT and Platelet counts in the control group showed no significant change after eight weeks of training (P>0.05). While PTT changes in the both groups was significant in the post-test compared to the pre-test (P=0.006). The inter-group difference, in any of the variables between the experimental and control groups, was not significant (P>0.05).
Conclusion: Eight weeks of aerobic training had no effect on Lipoprotein a and blood coagulation and fibrinolysis factors, however, this training program can take effective steps in improving health promotion in overweight women.

Determining the Information Requirements of Electronic Prescribing and Medication Administration System for Cardiovascular Patients
Reza Safdari, Farnoosh Larti, Kamyar Fathi Salari, Saman Mohammadpour,
Volume 14, Issue 3 (Aug & Sep 2020)
Abstract
Background and Aim: Cardiovascular diseases and medication errors are among the leading causes of morbidity and mortality around the world. Electronic prescribing and Medication Administration(ePMA) systems can prevent medication errors to some extent. This study aimed to determine the information requirements of ePMA systems.
Materials and Methods: This descriptive study was conducted in Imam Khomeini Hospital of Tehran and School of Allied Medical Sciences affiliated to Tehran University of Medical Sciences (TUMS) in the summer of 2019 in two phases: literature review and survey-based questionnaire. Information items obtained from reviewing the texts of 100 articles were organized in three questionnaires. In the survey phase, questionnaires were distributed among physicians, nurses, and the experts of health information management(HIM) and medical informatics, using census sampling method. The reliability of the questionnaires was measured using Cronbach's coefficient alpha. Statistical analysis was done using SPSS.
Results: The findings showed that based on specialists’ point of view, patients' demographic information items and unique identifiers gained the highest average, above 4.7. Physicians agreed most with clinical information, including medication history and generic names. From the nurses’ point of view, the information items of the patients’ problems and the procedures performed and the types of drug doses obtained a complete average of 5.
Conclusion: The need for information items varies among different users of ePMA systems, but there may be items that are common for them. Future studies should further investigate financial and pharmaceutical information requirements based on the perspectives of other hospital pharmacy and accounting staff.

The Effects of Implementing Clinical Decision Support Systems on the Diagnosis, Treatment and Management of Cancers: A Systematic Review
Saman Mohammadpour, Reza Rabiei, Elham Shabahrami, Kamyar Fathisalari, Maryam Khakzad, Mostafa Langarizadeh,
Volume 16, Issue 2 (Jun 2022)
Abstract
Background and Aim: Cancer is the second leading cause of death in the world, which leads to the death of more than 10 million people in the world every year. Its early diagnosis, management and proper treatment play an important role in reducing complications and mortality. One of the support tools in early diagnosis, treatment and management of this disease are Clinical Decision Support System (CDSS), which are divided into two groups, rule-based and non-rule-based. Rule-based decision support systems are created based on clinical guidelines, while non-rule-based decision support systems use machine learning. In this research, the effects of decision support systems, rule-based and non-rule-based, on cancer diagnosis, treatment and management were measured.
Materials and Methods: The present study was conducted using a systematic review method, which was conducted by searching the Web of Science, Scopus, IEEE and PubMED databases until 12/31/2021. After removing duplicates and evaluating the characteristics of the inclusion and exclusion criteria, studies related to the goal were selected. The selection of articles was based on the title, abstract and full text The data collection tool was the data extraction form, which included year of study, type of study, system of body, organ of body, the service provided by the decision support system, type of decision support system, effect, effect index and the score of effect index. Narrative synthesis were used for data analysis.
Results: Out of 768 articles, 16 articles related to the objectives of the study were identified. Studies were presented in two categories of clinical decision-support systems: Rule-based and non-Rule based. The effects evaluated in the clinical decision support systems were Rule-based, dose adjustment, symptoms, adherence to treatment guidelines, care time, smoking, need for chemotherapy and pain management, all of which except pain management were significant and positive. The effects evaluated were in the category of non-Rule based clinical decision support systems, diagnostic and therapeutic decisions, controlling neutropenia, all of which were significant and positive except controlling neutropenia.
Conclusion: The results obtained for the effectiveness of both Rule-based and non-Rule-based decision support systems indicated different benefits of these two categories. Therefore, using their combination in the field of cancer can bring very useful results.

Identifying the Role Players of the Gestational Diabetes Self-Management Network on Mobile Health (Based on the Social Network Analysis)
Mohammad Mehdi Sepehri, Minoo Fathi, Nasrin Taherkhani, Roghaye Khasha,
Volume 19, Issue 1 (4-2025)
Abstract
Background and Aim: The development of self-management application for gestational Diabetes based on mobile health, can increase the quality of life of pregnant mothers and reduce the cost of health care and treatment. In order to develop such an application, it is necessary to identify the key players of this system and examine the relationships between them. Then a gestational Diabetes self-management network based on mobile health tools can be presented.
Materials and Methods: The study was conducted in four phases. In the first phase, key players and roles were identified through literature review. In the second phase, interviews with experts were conducted to assess the identified players and their roles. The third phase involved identifying the relationships between players and their roles, accomplished by designing and completing questionnaires that explored the existence or absence of connections between them. In the final phase, the most critical roles and players were determined using social network analysis, employing three centrality indices: degree centrality, betweenness centrality, and closeness centrality.
Results: A total of 22 role players and 17 roles were identified. Based on the results, the Ministry of Health, with a degree centrality index of 41.12, was found to be the most influential and powerful role player in this network. The endocrinologist, nutritionist and obstetrician, with degree centrality indices of 38.52, 36.79, and 31.60. were ranked next. This indicates that the acceptance of this network by the medical community plays a critical role. Additionally, all three centrality indices showed that the role of patient education had the highest values, followed by roles such as education for specialists and healthcare staff, supporting patients in self-care behaviors, and ensuring patient safety and privacy, which were identified as the key roles.
Conclusion: This study aimed to identify various aspects of network design and the influential roles impacting the self-management of gestational Diabetes through mobile health. The Ministry of Health and the National Prevention Committee exhibited the most connections with each other in fulfilling their shared roles. Therefore, the Ministry of Health can fully delegate some roles to the National Prevention. Additionally, recognizing key roles underscores the necessity of prioritizing education and resource allocation for these roles.

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