Development and validation of models for two‐week mortality of inpatients with COVID‐19 infection: A large prospective cohort study. (11th January 2022)
- Record Type:
- Journal Article
- Title:
- Development and validation of models for two‐week mortality of inpatients with COVID‐19 infection: A large prospective cohort study. (11th January 2022)
- Main Title:
- Development and validation of models for two‐week mortality of inpatients with COVID‐19 infection: A large prospective cohort study
- Authors:
- Fathi, Mohammad
Markazi Moghaddam, Nader
Kheyrati, Leila - Abstract:
- Abstract: Recognizing COVID‐19 patients at a greater risk of mortality assists medical staff to identify who benefits from more serious care. We developed and validated prediction models for two‐week mortality of inpatients with COVID‐19 infection based on clinical predictors. A prospective cohort study was started in February 2020 and is still continuing. In total, 57, 705 inpatients with both a positive reverse transcription‐polymerase chain reaction test and positive chest CT findings for COVID‐19 were included. The outcome was mortality within 2 weeks of admission. Three prognostic models were developed for young, adult, and senior patients. Data from the capital province (Tehran) of Iran were used for validation, and data from all other provinces were used for development of the models. The model Young, was well‐fitted to the data ( p < 0.001, Nagelkerke R 2 = 0.697, C‐statistics = 0.88) and the models Adult ( p < 0.001, Nagelkerke R 2 = 0.340, C‐statistics = 0.70) and Senior ( p < 0.001, Nagelkerke R 2 = 0.208, C‐statistics = 0.68) were also significant. Intubation, saturated O2 < 93%, impaired consciousness, acute respiratory distress syndrome, and cancer treatment were major risk factors. Elderly people were at greater risk of mortality. Young patients with a history of blood hypertension, vomiting, and fever; and adults with diabetes mellitus and cardiovascular disease had more mortality risk. Young people with myalgia; and adult patients with nausea,Abstract: Recognizing COVID‐19 patients at a greater risk of mortality assists medical staff to identify who benefits from more serious care. We developed and validated prediction models for two‐week mortality of inpatients with COVID‐19 infection based on clinical predictors. A prospective cohort study was started in February 2020 and is still continuing. In total, 57, 705 inpatients with both a positive reverse transcription‐polymerase chain reaction test and positive chest CT findings for COVID‐19 were included. The outcome was mortality within 2 weeks of admission. Three prognostic models were developed for young, adult, and senior patients. Data from the capital province (Tehran) of Iran were used for validation, and data from all other provinces were used for development of the models. The model Young, was well‐fitted to the data ( p < 0.001, Nagelkerke R 2 = 0.697, C‐statistics = 0.88) and the models Adult ( p < 0.001, Nagelkerke R 2 = 0.340, C‐statistics = 0.70) and Senior ( p < 0.001, Nagelkerke R 2 = 0.208, C‐statistics = 0.68) were also significant. Intubation, saturated O2 < 93%, impaired consciousness, acute respiratory distress syndrome, and cancer treatment were major risk factors. Elderly people were at greater risk of mortality. Young patients with a history of blood hypertension, vomiting, and fever; and adults with diabetes mellitus and cardiovascular disease had more mortality risk. Young people with myalgia; and adult patients with nausea, anorexia, and headache showed less risk of mortality than others. … (more)
- Is Part Of:
- Statistical analysis and data mining. Volume 15:Number 5(2022)
- Journal:
- Statistical analysis and data mining
- Issue:
- Volume 15:Number 5(2022)
- Issue Display:
- Volume 15, Issue 5 (2022)
- Year:
- 2022
- Volume:
- 15
- Issue:
- 5
- Issue Sort Value:
- 2022-0015-0005-0000
- Page Start:
- 586
- Page End:
- 597
- Publication Date:
- 2022-01-11
- Subjects:
- corona -- COVID‐19 -- inpatient -- model -- mortality -- risk
Data mining -- Statistical methods -- Periodicals
006.312 - Journal URLs:
- http://www3.interscience.wiley.com/journal/112701062/home ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/sam.11572 ↗
- Languages:
- English
- ISSNs:
- 1932-1864
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8447.424100
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- 23293.xml