The role of gestational diabetes, pre-pregnancy body mass index and gestational weight gain on the risk of newborn macrosomia: results from a prospective multicentre study.

BACKGROUND: It is crucial to identify in large population samples the most important determinants of excessive fetal growth. The aim of the study was to evaluate the independent role of pre-pregnancy body mass index (BMI), gestational weight gain and gestational diabetes on the risk of macrosomia. METHODS: A prospective study collected data on mode of delivery and maternal/neonatal outcomes in eleven Hospitals in Italy. Multiple pregnancies and preterm deliveries were excluded. The sample included 14109 women with complete records. Associations between exposure variables and newborn macrosomia were analyzed using Pearson's chi squared test. Multiple logistic regression models were built to assess the independent association between potential predictors and macrosomia. RESULTS: Maternal obesity (adjusted OR 1.7, 95% CI 1.4-2.2), excessive gestational weight gain (adjusted OR 1.9, 95% CI 1.6-2.2) and diabetes (adjusted OR 2.1, 95% CI 1.5-3.0 for gestational; adjusted OR 3.0, 95% CI 1.2-7.6 for pre-gestational) resulted to be independent predictors of macrosomia, when adjusted for other recognized risk factors. Since no significant interaction was found between pre-gestational BMI and gestational weight gain, excessive weight gain should be considered an independent risk factor for macrosomia. In the sub-group of women affected by gestational or pre-gestational diabetes, pre-gestational BMI was not significantly associated to macrosomia, while excessive pregnancy weight gain, maternal height and gestational age at delivery were significantly associated. In this sub-population, pregnancy weight gain less than recommended was not significantly associated to a reduction in macrosomia. CONCLUSIONS: Our findings indicate that maternal obesity, gestational weight gain excess and diabetes should be considered as independent risk factors for newborn macrosomia. To adequately evaluate the clinical evolution of pregnancy all three variables need to be carefully assessed and monitored.

The application of the Ten Group classification system (TGCS) in caesarean delivery case mix adjustment. A multicenter prospective study.

BACKGROUND: Caesarean delivery (CD) rates are commonly used as an indicator of quality in obstetric care and risk adjustment evaluation is recommended to assess inter-institutional variations. The aim of this study was to evaluate whether the Ten Group classification system (TGCS) can be used in case-mix adjustment. METHODS: Standardized data on 15,255 deliveries from 11 different regional centers were prospectively collected. Crude Risk Ratios of CDs were calculated for each center. Two multiple logistic regression models were herein considered by using: Model 1- maternal (age, Body Mass Index), obstetric variables (gestational age, fetal presentation, single or multiple, previous scar, parity, neonatal birth weight) and presence of risk factors; Model 2- TGCS either with or without maternal characteristics and presence of risk factors. Receiver Operating Characteristic (ROC) curves of the multivariate logistic regression analyses were used to assess the diagnostic accuracy of each model. The null hypothesis that Areas under ROC Curve (AUC) were not different from each other was verified with a Chi Square test and post hoc pairwise comparisons by using a Bonferroni correction. RESULTS: Crude evaluation of CD rates showed all centers had significantly higher Risk Ratios than the referent. Both multiple logistic regression models reduced these variations. However the two methods ranked institutions differently: model 1 and model 2 (adjusted for TGCS) identified respectively nine and eight centers with significantly higher CD rates than the referent with slightly different AUCs (0.8758 and 0.8929 respectively). In the adjusted model for TGCS and maternal characteristics/presence of risk factors, three centers had CD rates similar to the referent with the best AUC (0.9024). CONCLUSIONS: The TGCS might be considered as a reliable variable to adjust CD rates. The addition of maternal characteristics and risk factors to TGCS substantially increase the predictive discrimination of the risk adjusted model.