Development and validation of nomogram to predict severe illness requiring intensive care follow up in hospitalized COVID-19 cases.
BMC Infect Dis
; 21(1): 1004, 2021 Sep 25.
Article
in English
| MEDLINE | ID: covidwho-1438258
ABSTRACT
BACKGROUND:
Early identification of severe COVID-19 patients who will need intensive care unit (ICU) follow-up and providing rapid, aggressive supportive care may reduce mortality and provide optimal use of medical resources. We aimed to develop and validate a nomogram to predict severe COVID-19 cases that would need ICU follow-up based on available and accessible patient values.METHODS:
Patients hospitalized with laboratory-confirmed COVID-19 between March 15, 2020, and June 15, 2020, were enrolled in this retrospective study with 35 variables obtained upon admission considered. Univariate and multivariable logistic regression models were constructed to select potential predictive parameters using 1000 bootstrap samples. Afterward, a nomogram was developed with 5 variables selected from multivariable analysis. The nomogram model was evaluated by Area Under the Curve (AUC) and bias-corrected Harrell's C-index with 95% confidence interval, Hosmer-Lemeshow Goodness-of-fit test, and calibration curve analysis.RESULTS:
Out of a total of 1022 patients, 686 cases without missing data were used to construct the nomogram. Of the 686, 104 needed ICU follow-up. The final model includes oxygen saturation, CRP, PCT, LDH, troponin as independent factors for the prediction of need for ICU admission. The model has good predictive power with an AUC of 0.93 (0.902-0.950) and a bias-corrected Harrell's C-index of 0.91 (0.899-0.947). Hosmer-Lemeshow test p-value was 0.826 and the model is well-calibrated (p = 0.1703).CONCLUSION:
We developed a simple, accessible, easy-to-use nomogram with good distinctive power for severe illness requiring ICU follow-up. Clinicians can easily predict the course of COVID-19 and decide the procedure and facility of further follow-up by using clinical and laboratory values of patients available upon admission.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Nomograms
/
COVID-19
Type of study:
Cohort study
/
Experimental Studies
/
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
BMC Infect Dis
Journal subject:
Communicable Diseases
Year:
2021
Document Type:
Article
Affiliation country:
S12879-021-06656-w
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