A predictive score for progression of COVID-19 in hospitalized persons: a cohort study.
NPJ Prim Care Respir Med
; 31(1): 33, 2021 06 03.
Article
in English
| MEDLINE | ID: covidwho-1258582
ABSTRACT
Accurate prediction of the risk of progression of coronavirus disease (COVID-19) is needed at the time of hospitalization. Logistic regression analyses are used to interrogate clinical and laboratory co-variates from every hospital admission from an area of 2 million people with sporadic cases. From a total of 98 subjects, 3 were severe COVID-19 on admission. From the remaining subjects, 24 developed severe/critical symptoms. The predictive model includes four co-variates age (>60 years; odds ratio [OR] = 12 [2.3, 62]); blood oxygen saturation (<97%; OR = 10.4 [2.04, 53]); C-reactive protein (>5.75 mg/L; OR = 9.3 [1.5, 58]); and prothrombin time (>12.3 s; OR = 6.7 [1.1, 41]). Cutoff value is two factors, and the sensitivity and specificity are 96% and 78% respectively. The area under the receiver-operator characteristic curve is 0.937. This model is suitable in predicting which unselected newly hospitalized persons are at-risk to develop severe/critical COVID-19.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
COVID-19
/
Hospitalization
Type of study:
Cohort study
/
Diagnostic study
/
Observational study
/
Prognostic study
Limits:
Adolescent
/
Adult
/
Aged
/
Child
/
Child, preschool
/
Female
/
Humans
/
Infant
/
Male
/
Middle aged
Language:
English
Journal:
NPJ Prim Care Respir Med
Year:
2021
Document Type:
Article
Affiliation country:
S41533-021-00244-w
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