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، جلد ۱۴، شماره ۳، صفحات ۱-۱
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Development and Validation of a Risk Score Model for Predicting the Progression of COVID-19 Among Iranian Patients |
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| چکیده انگلیسی مقاله |
Background: The recent novel coronavirus disease 2019 (COVID-19) pandemic has underlined the importance of risk score models in public health emergencies. This study aimed to develop a risk prediction score to identify high-risk hospitalized patients for disease progression on admission.
Methods: This prospective cohort study included 171 COVID-19 patients, identified through the reverse transcription polymerase chain reaction test, admitted to Bohlol Hospital in Gonabad City, Iran, between April 4 and June 5, 2021. The patients' demographic, clinical, and laboratory data were collected upon admission, and clinical outcomes were monitored until the end of the study. The discovery dataset (80% of the data) was used to develop the risk score model based on clinical and laboratory features and patient characteristics to predict COVID-19 progression. An additive risk score model was developed based on the regression coefficients of the significant variables in a multiple logistic regression model. The performance of the risk score model was evaluated on the validation dataset (20% of the data) using the receiver operating characteristic (ROC) curve. Statistical analyses were performed with SPSS (version 21.0).
Results: The mean age of participants was 59.54 (SD=20.52) years, and 48.6% were male. Most patients (82.5%) fully recovered or showed improvement, while 5.2% experienced disease progression and 12.3% died. Three variables, interleukin-6, neutrophil-to-lymphocyte ratio, and lung involvement, were found to be significant in predicting risk, with a good discriminatory ability, having an area under the ROC curve of 0.970 (95% CI, 0.935 - 1.00) in the discovery set and 0.973 (95% CI, 0.923 -1.00) in the validation set.
Conclusion: The developed risk score model in this study can be used as a clinical diagnostic tool to identify COVID-19 patients at higher risk of disease progression and aid in informed decision-making and resource utilization in similar situations, such as respiratory disease outbreaks in the post-corona era. |
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| کلیدواژه‌های انگلیسی مقاله |
Coronavirus, COVID-19, Risk score, Prediction, Disease progression, Iran |
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| نویسندگان مقاله |
| Fatemeh Mohammadzadeh
Department of Epidemiology & Biostatistics, School of Health, Social Development & Health Promotion Research Center, Gonabad University of Medical Sciences, Gonabad, Iran.
| Ali Delshad Noughabi
Social Development and Health Promotion Research Center, Gonabad University of Medical Sciences, Gonabad, Iran.
| Sina Sabeti Bilondi
Islamic Azad University of Gonabad, Clinical Reasearch Development Unit, Bohlool Hospital, Gonabad University of Medical Sciences, Gonabad, Iran.
| Mitra Tavakolizadeh
Clinical Reasearch Development Unit, Bohlool Hospital, Gonabad University of Medical Sciences, Gonabad, Iran.
| Jafar Hajavi
Department of Microbiology, School of Medicine, Infectious Disease Research Center, Gonabad University of Medical Sciences, Gonabad, Iran.
| Hosein Aalami
Clinical Reasearch Development Unit, Gonabad University of Medical Sciences, Gonabad, Iran.
| Mohsen Sahebanmaleki
Bohlool Hospital, Health Promotion Research Center, Gonabad University of Medical Sciences, Gonabad, Iran.
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| نشانی اینترنتی |
http://jrh.gmu.ac.ir/browse.php?a_code=A-10-646-1&slc_lang=en&sid=1 |
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| کد مقاله (doi) |
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| زبان مقاله منتشر شده |
en |
| موضوعات مقاله منتشر شده |
● Disease Control |
| نوع مقاله منتشر شده |
مقاله اصیل پژوهشی |
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