Identification of Clinical Features Associated with Mortality in COVID-19 Patients

Rahimeh Eskandarian, Roohallah Alizadehsani (), Mohaddeseh Behjati, Mehrdad Zahmatkesh, Zahra Alizadeh Sani, Azadeh Haddadi, Kourosh Kakhi, Mohamad Roshanzamir, Afshin Shoeibi, Sadiq Hussain, Fahime Khozeimeh, Mohammad Tayarani Darbandy, Javad Hassannataj Joloudari, Reza Lashgari, Abbas Khosravi, Saeid Nahavandi and Sheikh Mohammed Shariful Islam
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Rahimeh Eskandarian: Semnan University of Medical Sciences
Roohallah Alizadehsani: Deakin University
Mohaddeseh Behjati: Iran University of Medical Sciences
Mehrdad Zahmatkesh: Semnan University of Medical Sciences
Zahra Alizadeh Sani: Iran University of Medical Sciences
Azadeh Haddadi: Islamic Azad University
Kourosh Kakhi: Deakin University
Mohamad Roshanzamir: Fasa University
Afshin Shoeibi: University of Granada
Sadiq Hussain: Dibrugarh University
Fahime Khozeimeh: Deakin University
Mohammad Tayarani Darbandy: Islamic Azad University Taft
Javad Hassannataj Joloudari: University of Birjand
Reza Lashgari: Shahid Beheshti University
Abbas Khosravi: Deakin University
Saeid Nahavandi: Deakin University
Sheikh Mohammed Shariful Islam: Deakin University

SN Operations Research Forum, 2023, vol. 4, issue 1, 1-20

Abstract: Abstract Understanding clinical features and risk factors associated with COVID-19 mortality is needed to early identify critically ill patients, initiate treatments and prevent mortality. A retrospective study on COVID-19 patients referred to a tertiary hospital in Iran between March and November 2020 was conducted. COVID-19-related mortality and its association with clinical features including headache, chest pain, symptoms on computerized tomography (CT), hospitalization, time to infection, history of neurological disorders, having a single or multiple risk factors, fever, myalgia, dizziness, seizure, abdominal pain, nausea, vomiting, diarrhoea and anorexia were investigated. Based on the investigation outcome, decision tree and dimension reduction algorithms were used to identify the aforementioned risk factors. Of the 3008 patients (mean age 59.3 ± 18.7 years, 44% women) with COVID-19, 373 died. There was a significant association between COVID-19 mortality and old age, headache, chest pain, low respiratory rate, oxygen saturation

Keywords: COVID‐19; Mortality; Risk factors; Symptoms; Machine learning (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s43069-022-00191-3

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