Longitudinal discriminant analysis of hemoglobin level for predicting XXXX .

@entity1 @entity1468
BACKGROUND: Preeclampsia is one of the most serious complications during pregnancy with important effects on health of mother and fetus that causes maternal and fetal morbidity and mortality. This study was performed to evaluate whether high levels of hemoglobin may increase the risk of @entity1468 . OBJECTIVES: The present study aimed to predict @entity1468 by the hemoglobin profiles through longitudinal discriminant analysis and comparing the error rate of discrimination in longitudinal and cross sectional data. @entity1 AND METHODS: In a prospective cohort study from October 2010 to July 2011, 650 pregnant @entity1 referred to the prenatal clinic of Milad Hospital in Tehran were evaluated in 3 stages. The hemoglobin level of each @entity1 was measured in the first, second, and third trimester of pregnancy by an expert technician. The subjects were followed up to delivery and @entity1468 was the main outcome under study. The covariance pattern and linear-mixed effects models are common methods that were applied for discriminant analysis of longitudinal data. Also Student t, Mann-Whitney U, and chi-square tests were used for comparing the demographic and clinical characteristics between two groups. Statistical analyses were performed using the SAS software version 9.1. RESULTS: The prevalence rate of @entity1468 was 7.2% (47 @entity1 ). The @entity1 with @entity1468 had a higher mean of hemoglobin values and the difference was 0.46 g/dL (P = 0.003). Also the mean of hemoglobin in the first trimester was higher than that of the second trimester, and was lower than that of the third trimester and the differences were significant (P = 0.015 and P < 0.001, respectively). The sensitivity for longitudinal data and cross-sectional data in three trimesters was 90%, 67%, 72%, and 54% and the specificity was 88%, 55%, 63%, and 50%, respectively. CONCLUSIONS: The levels of hemoglobin can be used to predict @entity1468 and monitoring the pregnant @entity1 and its regular measure in 3 trimesters help us to identify @entity1 at risk for @entity1468 .
