| چکیده انگلیسی مقاله |
Background and Purpose: Identifying effective symptoms, demographic information, and underlying diseases to predict COVID-19 mortality is essential. We aimed to study the effective clinical and symptomatic characteristics of COVID-19 mortality in hospitalized patients with positive polymerase chain reaction (PCR) test results.
Materials and Methods: For this study, we prospectively collected complete data on 26867 hospitalized individuals who tested PCR positive for COVID-19 from February 20, 2020, to September 12, 2021, in the Khorasan Razavi Province, Iran. We analyzed the data using artificial neural networks (ANN) and logistic regression (LR) models.
Results: The accuracy of the ANN model was higher than the LR (90.27% versus 90.15%). The ten most important predictors that contributed to the prediction of death were decreasing consciousness level, cough, PO2 level, age, chronic kidney disease, fever, headache, smoking status, chronic blood diseases, and diarrhea using the ANN model.
Conclusion: In conclusion, individuals suffering from chronic diseases such as cancer, kidney and blood diseases, as well as immunodeficiency are at a higher risk of mortality. This important finding can help decision-makers and medical professionals in their efforts to consider these conditions and provide effective preventative measures to reduce the risk of death. |
| نویسندگان مقاله |
نسرین تلخی | Nasrin Talkhi
Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
نوشین اکبری شارک | Nooshin Akbari Sharak
Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
راضیه یوسفی | Razieh Yousefi
Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
مریم سالاری | Maryam Salari
Department of Biostatistics, Expert Management and Information Technology, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
سید مسعود ساداتی | Seyed Masoud Sadati
Center of Statistics and Information Technology Management, Imam Reza Hospital, Mashhad University of Medical Sciences, Mashhad, Iran.
محمدتقی شاکری | Mohammad Taghi Shakeri
Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
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