WBC = White Blood Cells; RBC =
Red Blood Cells; HGB = Hemoglobin; PLT = Platelets; %Neu = Neutrophils
(percentage); %Lymph = Lymphocytes (percentage); %Mon = Monocytes
(percentage); #Neu = Neutrophils (number); #Lymph = Lymphocytes
(number); #Mon = Monocytes (number); HCT = Hematocrit; MCV = Mean
Corpuscular Volume; MCHC = Mean Corpuscular Hemoglobin Concentration;
MCH = Mean Corpuscular Hemoglobin; RDW-SD = Red Cell Distribution
Width-Standard Deviation; RDW-CV = Red Cell Distribution
Width-Coefficient of Variation; PDW = Platelet Distribution Width; MPV =
Mean Platelet Volume; PCT = Plateletcrit; P-LCR = Platelet Large Cell
Ratio; InCRP = natural log-transformed value of CRP; %Eos = Eosinophils
(percentage); #Eos = Eosinophils (number); %Bas = Basophils
(percentage); #Bas = Basophils (number).
Construction and evaluation of the nomogram prediction model.
Multivariable logistic regression analysis established a nomogram model
based on the final selected predictor variables(FIGURE 3. A).
The AUC of the pneumonia risk
model was 0.7820 (95% CI: 0.7254-0.8439) in the training cohort and
0.8432 (95% CI: 0.7588-0.9151) in the validation cohort(FIGURE 3. B,
C); at the cut-off value of 0.5, the sensitivity and specificity of the
pneumonia risk model were 70.75%, 66. 33% (training cohort), 76.09%,
and 73.91% (validation cohort), respectively; the calibration curve
showed good agreement between the predicted probability of pneumonia
from the pneumonia risk model and the actually observed probability.
Decision curve analysis (DCA) showed good clinical validity of the
pneumonia risk model in the training and validation cohort (FIGURE 3. F,
G). Other diagnostic parameters of the model are shown in TABLE 3.
Comparison of the AUC and DCA for the pneumonia risk model with
predictors incorporated in the model alone in the whole study cohort
were shown in FIGURE 4, showing that the pneumonia risk model combining
multiple predictors has better diagnostic performance than a single
predictor.
TABLE 3. Diagnostic parameters ofthe pneumonia risk
model.