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Abstract
Objective
To develop a model based on non-invasive variables to predict the probability of subsequent maternal and/or neonatal clinical infection in women admitted to hospital for preterm labor with intact membranes.
Methods
Transvaginal ultrasound for measurement of cervical length was performed and maternal blood was collected for the determination of white blood cell (WBC) count at admission in 165 consecutive women with preterm labor (between 20.0 and 35.0 weeks). Clinical infection was defined as the presence of clinical chorioamnionitis at delivery or early onset neonatal sepsis. Receiver operating characteristic (ROC) curves and logistic regression analysis were used for statistical analyses.
Results
The prevalence of clinical infection was 5% (8/165). Women who developed clinical infection had a significantly lower median gestational age at admission, a lower shorter median cervical length, and a higher median WBC count as compared to those who did not develop clinical infection. Logistic regression analysis was performed and a final model was chosen, which included maternal blood WBC, cervical length, and gestational age as the best predictors of clinical infection. A risk score was calculated containing these 3 variables for each patient. The model was shown to have an adequate goodness of fit (P=0.202), and the area under the ROC curve was 0.822, indicating reasonably good discrimination.
Figures and Tables
Figure 1
Receiver-operator characteristic curves for cervical length (A), white blood cell (B), gestational age (C) in predicting the occurrence of clinical infection. Numbers next to solid dots represent each cutoff value (cervical length: area under the curve 0.721; standard error [SE] 0.068; P=0.030, white blood cell: area under the curve 0.793; SE 0.073; P=0.005, gestational age: area under the curve 0.721; SE 0.076; P=0.035).
Figure 2
Receiver operator characteristic curve for multivariate prediction model of clinical infection (area under curve 0.822, standard error 0.096, P < 0.002).
Table 1
Demographic and clinical characteristics of the study population according to the clinical infection
Table 2
Regression coefficients, odds ratios, and 95% confidence intervals of the final model to predict the probability of clinical infection
Formula to predict clinical infection: Y=loge (Z)=-5.694+1.680×[cervical length (mm)>20=0, ≤20=1]+1.767×[WBC count (cells/mm3)<12,600=0, ≥12,600=1]+1.619×[gestational age (weeks)>29=0, ≤29=1].
Z=ey, risk (%)=(Z/1+Z)×100
SE: standard error, CI: confidence interval, WBC: white blood cell, GA: gestational age.
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