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Clinical and imaging features predict mortality in COVID-19 infection in Iran.
Homayounieh, Fatemeh; Zhang, Eric W; Babaei, Rosa; Karimi Mobin, Hadi; Sharifian, Maedeh; Mohseni, Iman; Kuo, Anderson; Arru, Chiara; Kalra, Mannudeep K; Digumarthy, Subba R.
  • Homayounieh F; Division of Thoracic Imaging and Intervention, Department of Radiology, Harvard University, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
  • Zhang EW; Division of Thoracic Imaging and Intervention, Department of Radiology, Harvard University, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
  • Babaei R; Department of Radiology, University of Medical Sciences, Firoozgar Hospital, Tehran, Iran.
  • Karimi Mobin H; Department of Radiology, University of Medical Sciences, Firoozgar Hospital, Tehran, Iran.
  • Sharifian M; Department of Radiology, University of Medical Sciences, Firoozgar Hospital, Tehran, Iran.
  • Mohseni I; Department of Radiology, University of Medical Sciences, Firoozgar Hospital, Tehran, Iran.
  • Kuo A; Division of Cardiovascular Imaging, Department of Radiology, Harvard University, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
  • Arru C; Division of Thoracic Imaging and Intervention, Department of Radiology, Harvard University, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
  • Kalra MK; Division of Thoracic Imaging and Intervention, Department of Radiology, Harvard University, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
  • Digumarthy SR; Division of Thoracic Imaging and Intervention, Department of Radiology, Harvard University, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
PLoS One ; 15(9): e0239519, 2020.
Article in English | MEDLINE | ID: covidwho-792303
ABSTRACT
The new coronavirus disease 2019 (COVID-19) pandemic has challenged many healthcare systems around the world. While most of the current understanding of the clinical features of COVID-19 is derived from Chinese studies, there is a relative paucity of reports from the remaining global health community. In this study, we analyze the clinical and radiologic factors that correlate with mortality odds in COVID-19 positive patients from a tertiary care center in Tehran, Iran. A retrospective cohort study of 90 patients with reverse transcriptase-polymerase chain reaction (RT-PCR) positive COVID-19 infection was conducted, analyzing demographics, co-morbidities, presenting symptoms, vital signs, laboratory values, chest radiograph findings, and chest CT features based on mortality. Chest radiograph was assessed using the Radiographic Assessment of Lung Edema (RALE) scoring system. Chest CTs were assessed according to the opacification pattern, distribution, and standardized severity score. Initial and follow-up Chest CTs were compared if available. Multiple logistic regression was used to generate a prediction model for mortality. The 90 patients included 59 men and 31 women (59.4 ± 16.6 years), including 21 deceased and 69 surviving patients. Among clinical features, advanced age (p = 0.02), low oxygenation saturation (p<0.001), leukocytosis (p = 0.02), low lymphocyte fraction (p = 0.03), and low platelet count (p = 0.048) were associated with increased mortality. High RALE score on initial chest radiograph (p = 0.002), presence of pleural effusions on initial CT chest (p = 0.005), development of pleural effusions on follow-up CT chest (p = 0.04), and worsening lung severity score on follow-up CT Chest (p = 0.03) were associated with mortality. A two-factor logistic model using patient age and oxygen saturation was created, which demonstrates 89% accuracy and area under the ROC curve of 0.86 (p<0.0001). Specific demographic, clinical, and imaging features are associated with increased mortality in COVID-19 infections. Attention to these features can help optimize patient management.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections Type of study: Cohort study / Observational study / Prognostic study Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2020 Document Type: Article Affiliation country: Journal.pone.0239519

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections Type of study: Cohort study / Observational study / Prognostic study Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2020 Document Type: Article Affiliation country: Journal.pone.0239519