Development and validation of risk prediction models for COVID-19 positivity in a hospital setting.
Int J Infect Dis
; 101: 74-82, 2020 Dec.
Article
in English
| MEDLINE | ID: covidwho-758909
ABSTRACT
OBJECTIVES:
To develop (1) two validated risk prediction models for coronavirus disease-2019 (COVID-19) positivity using readily available parameters in a general hospital setting; (2) nomograms and probabilities to allow clinical utilisation.METHODS:
Patients with and without COVID-19 were included from 4 Hong Kong hospitals. The database was randomly split into 21 for model development database (n = 895) and validation database (n = 435). Multivariable logistic regression was utilised for model creation and validated with the Hosmer-Lemeshow (H-L) test and calibration plot. Nomograms and probabilities set at 0.1, 0.2, 0.4 and 0.6 were calculated to determine sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).RESULTS:
A total of 1330 patients (mean age 58.2 ± 24.5 years; 50.7% males; 296 COVID-19 positive) were recruited. The first prediction model developed had age, total white blood cell count, chest x-ray appearances and contact history as significant predictors (AUC = 0.911 [CI = 0.880-0.941]). The second model developed has the same variables except contact history (AUC = 0.880 [CI = 0.844-0.916]). Both were externally validated on the H-L test (p = 0.781 and 0.155, respectively) and calibration plot. Models were converted to nomograms. Lower probabilities give higher sensitivity and NPV; higher probabilities give higher specificity and PPV.CONCLUSION:
Two simple-to-use validated nomograms were developed with excellent AUCs based on readily available parameters and can be considered for clinical utilisation.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
SARS-CoV-2
/
COVID-19
Type of study:
Diagnostic study
/
Experimental Studies
/
Prognostic study
/
Randomized controlled trials
Limits:
Adult
/
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Language:
English
Journal:
Int J Infect Dis
Journal subject:
Communicable Diseases
Year:
2020
Document Type:
Article
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