Development and validation of a predictive model of in-hospital mortality in COVID-19 patients.
PLoS One
; 16(3): e0247676, 2021.
Article
in English
| MEDLINE | ID: covidwho-1575816
ABSTRACT
We retrospectively evaluated 2879 hospitalized COVID-19 patients from four hospitals to evaluate the ability of demographic data, medical history, and on-admission laboratory parameters to predict in-hospital mortality. Association of previously published risk factors (age, gender, arterial hypertension, diabetes mellitus, smoking habit, obesity, renal failure, cardiovascular/ pulmonary diseases, serum ferritin, lymphocyte count, APTT, PT, fibrinogen, D-dimer, and platelet count) with death was tested by a multivariate logistic regression, and a predictive model was created, with further validation in an independent sample. A total of 2070 hospitalized COVID-19 patients were finally included in the multivariable analysis. Age 61-70 years (p<0.001; OR 7.69; 95%CI 2.93 to 20.14), age 71-80 years (p<0.001; OR 14.99; 95%CI 5.88 to 38.22), age >80 years (p<0.001; OR 36.78; 95%CI 14.42 to 93.85), male gender (p<0.001; OR 1.84; 95%CI 1.31 to 2.58), D-dimer levels >2 ULN (p = 0.003; OR 1.79; 95%CI 1.22 to 2.62), and prolonged PT (p<0.001; OR 2.18; 95%CI 1.49 to 3.18) were independently associated with increased in-hospital mortality. A predictive model performed with these parameters showed an AUC of 0.81 in the development cohort (n = 1270) [sensitivity of 95.83%, specificity of 41.46%, negative predictive value of 98.01%, and positive predictive value of 24.85%]. These results were then validated in an independent data sample (n = 800). Our predictive model of in-hospital mortality of COVID-19 patients has been developed, calibrated and validated. The model (MRS-COVID) included age, male gender, and on-admission coagulopathy markers as positively correlated factors with fatal outcome.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
COVID-19
Type of study:
Cohort study
/
Diagnostic study
/
Experimental Studies
/
Observational study
/
Prognostic study
Limits:
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Language:
English
Journal:
PLoS One
Journal subject:
Science
/
Medicine
Year:
2021
Document Type:
Article
Affiliation country:
Journal.pone.0247676
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