Development and validation of a laboratory risk score for the early prediction of COVID-19 severity and in-hospital mortality.
Intensive Crit Care Nurs
; 64: 103012, 2021 Jun.
Article
in English
| MEDLINE | ID: covidwho-1014511
ABSTRACT
BACKGROUND AND AIMS:
Coronavirus Disease 2019 is characterized by a spectrum of clinical severity. This study aimed to develop a laboratory score system to identify high-risk individuals, to validate this score in a separate cohort, and to test its accuracy in the prediction of in-hospital mortality.METHODS:
In this cohort study, biological data from 330 SARS-CoV-2 infected patients were used to develop a risk score to predict progression toward severity. In a second stage, data from 240 additional COVID-19 patients were used to validate this score. Accuracy of the score was measured by the area under the receiver operating characteristic curve (AUC).RESULTS:
In the development cohort, a step-wise decrease in the average survival duration was noted with the increment of the risk score (pANOVA < 0.0001). A similar trend was confirmed when analyzing this association in the validation cohort (p < 0.0001). The AUC was 0.74 [0.66-0.82] and 0.90 [0.87-0.94], p < 0.0001, respectively for severity and mortality prediction.CONCLUSION:
This study provides a useful risk score based on biological routine parameters assessed at the time of admission, which has proven its effectiveness in predicting both severity and short-term mortality of COVID-19. Improved predictive scores may be generated by including other clinical and radiological features.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Severity of Illness Index
/
Hospital Mortality
/
Risk Assessment
/
Clinical Laboratory Techniques
/
Forecasting
/
COVID-19
Type of study:
Cohort study
/
Diagnostic study
/
Observational study
/
Prognostic study
Limits:
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Language:
English
Journal:
Intensive Crit Care Nurs
Journal subject:
Nursing
/
Critical Care
Year:
2021
Document Type:
Article
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