A Prognostic Model for In-Hospital Mortality in Critically Ill Patients with Pneumonia
Le Hu1,2, Ying Zhang1,2, Jia Wang1,2
1Emergency Medicine Clinical Research Center, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, People's Republic of China.
Purpose:
To determine the utility of a novel serum biomarker for the outcome prediction of critically ill patients with pneumonia.
Patients And Methods:
A retrospective analysis of critically ill patients was performed at an emergency department. The expression and prediction value of parameters were assessed. Binary logistic regression analysis was utilized to determine the indicators associated with in-hospital mortality of pneumonia patients. The Last Absolute Shrinkage and Selection Operator was used to further determine the independent predictors, which were validated by multiple logistic regression. The receiver operator characteristic curve was performed to assess their prediction values. A prognostic nomogram model was finally established for the outcome prediction for critically ill patients with pneumonia.
Results:
Retinol-binding protein (RBP) was significantly reduced in non-survived and pneumonia patients. CURB-65 score, levels of RBP, and blood urea nitrogen (BUN) were associated with in-hospital mortality of critically ill patients with pneumonia. Their combination was determined to be an ideal prognostic predictor (area under the curve of 0.762) and further developed into a nomogram prediction model (c-index 0.764).
Conclusion:
RBP is a novel in-hospital mortality predictor, which well supplements the CURB-65 score for critical pneumonia patients.
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