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Showing 3 results for Eclampsia
Detecting Of Preeclampsia By Expert System: A Case Study In Tehran University Of Medical Sciences Hospitals
Raheleh Salari, Mostafa Langarizadeh, Kambiz Bahaaddin Beigi, Ali Akramizadeh, Maryam Kashanian,
Volume 9, Issue 6 (3-2016)
Abstract

Background and Aim: Diagnosis of preeclampsia has an essential role in applying appropriate treatment plan for the patients. The aim of this study was to design an expert system in order to diagnos preeclampsia in order to assist the clinicians.

Materials and Methods: This was a cross-sectional study which resulted in developing a new system. The study population consisted of all patients admitted to three Maternity hospitals affliated to Tehran University of Medical Sciences (TUMS). Sample size included 215 medical records which were randomly selected. The results obtained were compared with the diagnosis from experts by kappa test using SPSS software.

Results: First of all, input parameters fuzzificated and entered into inference engine. Outputs were categorized in two groups as patients and healthy, with the final diagnosis and clinical explanation. The results obtained from system evaluation showed that accuracy, specificity and sensitivity of the system were 98.2 percent, 100 percent and 96.4 percent respectively.

Conclusion: Based on evaluation results, it could be concluded that fuzzy logic is an efficient method for designing of expert systems in the field of obstetrics and gynecology. Also, due to the similarity of the logic used in the proposed system with workflow and medical decision making, it will be accepted by the physicians.


Identification of Information Elements for Preeclampsia Android-Based Self-Management Application
Reza Safdari, Mozhgan Rahmanian, Shahrbanoo Pahlevany Nejad ,
Volume 12, Issue 6 (3-2019)
Abstract
Background and Aim: Preeclampsia is one of the most prominent cases of pregnancy related diseases that threatens health at global level, especially in developing countries. In Iran, with 14% of outbreak, it is the second most common cause of maternal mortality. The main goal of this study was to identify the information requirements of the Android-based preeclampsia self-Management application.
Materials & Methods: This was a descriptive study that was done in 2018 in Amir_Almomenin Hospital affiliated to Semnan University of Medical Sciences in two stages of reviewing the sources and the need for data elements. In the review phase, after studying the articles and study, the data requirements and factors which affecting the prevalence of preeclampsia were identified and a survey of qualified physicians was done by designing a researcher-made questionnaire.
Results: This research results indicate that 63.9% of the respondents assigned to the elements mentioned in the demographic findings. 75.9% of them identified health information elements as very important. Also, 77.85% of the research community considered the elements in the lifestyle sector to be of the highest importance. All participants recognized that reminder in the program was necessary. Approximately 33.33% of them reconsidered sport education to be at the lowest level, while 45.24% rated it as being of the highest importance.
Conclusion: The information requirements of this program were determined in 6 groups of health history, educational tips, lifestyle, alarms, referral, and reporting. These programs can help pregnant mothers with preeclampsia to control their disease to minimize complications by observing proper nutrition and principles of treatment.

Conceptual Model Design and Evaluation of a Preeclampsia Self-Management Application; Android based
Shahrbanoo Pahlevanynejad, Reza Safdari, Mojgan Rahmanian, Mohammad Saleh Safari,
Volume 16, Issue 1 (3-2022)
Abstract
Background and Aim: Preeclampsia is one of the most serious cases of high-risk pregnancies that endanger women’s health worldwide, especially in developing countries. Preeclampsia is a specific pregnancy syndrome with a prevalence of about 7-14%, which is one of the three leading causes of death in pregnant women. Preeclampsia is the second most common cause of maternal mortality in Iran and accounts for 14% of maternal mortality. The present study was conducted to design, create and evaluate mobile-based preeclampsia self-care application.
Materials and Methods: This study was conducted in four stages to assess the needs of information elements, design, create and evaluate preeclampsia self-care application. In needs assessment step, 42 specialists, assistants and personnel related to the subject working in the Amir Al-Momenin (AS) Educational, Research and Treatment Center affiliated to Semnan University of Medical Sciences participated. The program was then initially evaluated by 7 physicians, and finally the suggestions provided by users in the design of the program were applied and the final version of the program was completed. The application was designed in the Android Studio environment and then its usability was evaluated using the opinions of 20 mothers and the QUIS tool.
Results: The information elements and functional capabilities required by the program were determined. In addition, the program established communication between the patient and the provider, also created the possibility of care management and control of the disease process. The performance of the program was evaluated by physicians and experts and then evaluated by pregnant mothers in terms of usability. The findings showed that users were satisfied with the application.
Conclusion: The use of mobile-based applications is a useful way to increase knowledge and promote the health of pregnant mothers and facilitate their access to medical information and acquire the necessary skills in their disease. This program helps pregnant mothers with preeclampsia to control their disease by observing proper nutrition and treatment principles to minimize the complications of their disease.

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