Severe Maternal Morbidity And Near Miss Due To Postpartum Hemorrhage In A National Multicenter Surveillance Study.

To assess the occurrence of severe maternal complications owing to postpartum hemorrhage (PPH) and its associated factors. A secondary analysis of data from a multicenter cross-sectional prospective surveillance study included 9555 cases of severe maternal morbidity at 27 centers in Brazil between July 2009 and June 2010. Complications of PPH, conditions of severity management, and sociodemographic and obstetric characteristics were assessed. Factors independently associated with severe maternal outcome (SMO) were identified using multiple regression analysis. Overall, 1192 (12.5%) of the 9555 women experienced complications owing to PPH (981 had potentially life-threatening conditions, 181 maternal near miss, and 30 had died). The SMO ratio was 2.6 per 1000 live births among women with PPH and 8.5 per 1000 live births among women with other complications. Women with PPH had a higher risk of blood transfusion and return to the operating theater than did those with complications from other causes. Maternal age, length of pregnancy, previous uterine scar, and cesarean delivery were the main factors associated with an increased risk of SMO secondary to PPH. PPH frequently leads to severe maternal morbidity. A surveillance system can identify the main causes of morbidity and could help to improve care, especially among women identified as being at high risk of PPH.

Mixed rain forest in southeastern Brazil: tree species regeneration and floristic relationships in a remaining stretch of forest near the city of Itaberá, Brazil

The aim of this work was to evaluate the floristic composition, richness, and diversity of the upper and lower strata of a stretch of mixed rain forest near the city of Itaberá, in southeastern Brazil. We also investigated the differences between this conservation area and other stretches of mixed rain forest in southern and southeastern Brazil, as well as other nearby forest formations, in terms of their floristic relationships. For our survey of the upper stratum (diameter at breast height [DBH] > 15 cm), we established 50 permanent plots of 10 × 20 m. Within each of those plots, we designated five, randomly located, 1 × 1 m subplots, in order to survey the lower stratum (total height > 30 cm and DBH < 15 cm). In the upper stratum, we sampled 1429 trees and shrubs, belonging to 134 species, 93 genera, and 47 families. In the lower stratum, we sampled 758 trees and shrubs, belonging to 93 species, 66 genera, and 39 families. In our floristic and phytosociological surveys, we recorded 177 species, belonging to 106 genera and 52 families. The Shannon Diversity Index was 4.12 and 3.5 for the upper and lower strata, respectively. Cluster analysis indicated that nearby forest formations had the strongest floristic influence on the study area, which was therefore distinct from other mixed rain forests in southern Brazil and in the Serra da Mantiqueira mountain range.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Contribution Of Antepartum And Intrapartum Hemorrhage To The Burden Of Maternal Near Miss And Death In A National Surveillance Study

Objective To evaluate the occurrence of severe obstetric complications associated with antepartum and intrapartum hemorrhage among women from the Brazilian Network for Surveillance of Severe Maternal Morbidity.Design Multicenter cross-sectional study.Setting Twenty-seven obstetric referral units in Brazil between July 2009 and June 2010.Population A total of 9555 women categorized as having obstetric complications.Methods The occurrence of potentially life-threatening conditions, maternal near miss and maternal deaths associated with antepartum and intrapartum hemorrhage was evaluated. Sociodemographic and obstetric characteristics and the use of criteria for management of severe bleeding were also assessed in these women.Main outcome measures The prevalence ratios with their respective 95% confidence intervals adjusted for the cluster effect of the design, and multiple logistic regression analysis were performed to identify factors independently associated with the occurrence of severe maternal outcome.Results Antepartum and intrapartum hemorrhage occurred in only 8% (767) of women experiencing any type of obstetric complication. However, it was responsible for 18.2% (140) of maternal near miss and 10% (14) of maternal death cases. On multivariate analysis, maternal age and previous cesarean section were shown to be independently associated with an increased risk of severe maternal outcome (near miss or death).Conclusion Severe maternal outcome due to antepartum and intrapartum hemorrhage was highly prevalent among Brazilian women. Certain risk factors, maternal age and previous cesarean delivery in particular, were associated with the occurrence of bleeding.