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Ethics code: IR.MEDILAM.REC.1399.247
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taghinezhad F, Kafashian M, Kalvandi G, Shafiei E. Use of artificial neural networks to predict Epidemiological and Clinical risk factors for COVID-19 patient mortality in Ilam, Iran: a retrospective cohort study. Journal title 2022; 5 (1)
URL: http://newresearch.medilam.ac.ir/article-1-1087-en.html
URL: http://newresearch.medilam.ac.ir/article-1-1087-en.html
Psychosocial Injuries Research Center, Ilam University of Medical sciences, Ilam, Iran
Abstract: (1103 Views)
Since December 2019, coinciding with the outbreak of COIVD-19 in China and its spread to all countries, the greatest post-World War II health crisis and human society challenge has severely affected health systems, the global economy, and governments. [1] As previous priorities and routine activities in most areas have ceased and extensive efforts and investments have been made to prevent, diagnose and treat the disease, reduce the incidence rate, reduce the number of critically ill patients in need of intensive care and finally reduce the mortality rate [2]. Despite this unprecedented effort, various diagnostic and therapeutic aspects of the proposed and in use have been accompanied by many challenges and doubts so far [3]. Therefore, reducing the limitations and gaps in existing knowledge is the main priority and focus of studies in the field of medical sciences according to the encouragement of the World Health Organization. [4] According to studies, many factors can affect the prognosis of coronary heart disease and mortality. Most of the information on the epidemiological and laboratory factors of COVID-19 is insufficient and questionable, and there is insufficient evidence and evidence for its use. Recognizing the importance of each of the indicators related to mortality from disease, using efficient output models can in the process of treatment and better care, management of scarce resources during the peak of the disease, including prioritization of special beds and hospital beds, human resource management due to limitations Professional human resources, increasing the reliability of patients at lower risk for home care, appropriate planning for drug allocation and possible vaccines if used in the future. Therefore, the aim of this study was to explain the role of epidemiological and laboratory risk factors on the mortality of coronary patients using the artificial neural network model.
Methods: The present study is a retrospective cohort study in which the demographic and laboratory characteristics of patients who referred from the onset of coronary heart disease (March 1) to July 1 with a definitive diagnosis of COVID-19 and improved or died were studied. they enter. Demographic, clinical and laboratory variables are then analyzed using the artificial network model to identify risk factors associated with patient mortality.
After approving the plan and getting the code of ethics, information is collected from the files or the registry system. After completing the information through previous data, reviewing the files if necessary and contacting patients and their families, analysis and analysis using MATLAB software and effective factors in mortality, mediating variables, and the share of each The factor will be identified in explaining the variance of the dependent variable to determine the importance of each factor and ...... and the results will be presented in the form of analysis, table and graph.
Methods: The present study is a retrospective cohort study in which the demographic and laboratory characteristics of patients who referred from the onset of coronary heart disease (March 1) to July 1 with a definitive diagnosis of COVID-19 and improved or died were studied. they enter. Demographic, clinical and laboratory variables are then analyzed using the artificial network model to identify risk factors associated with patient mortality.
After approving the plan and getting the code of ethics, information is collected from the files or the registry system. After completing the information through previous data, reviewing the files if necessary and contacting patients and their families, analysis and analysis using MATLAB software and effective factors in mortality, mediating variables, and the share of each The factor will be identified in explaining the variance of the dependent variable to determine the importance of each factor and ...... and the results will be presented in the form of analysis, table and graph.
Received: 2020/06/28 | Accepted: 2022/06/19 | Published: 2022/08/20
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