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Abstract Background Several studies have assessed the risks of uteroplacental bleeding disorders in relation to maternal characteristics. The association between uteroplacental bleeding disorders and paternal characteristics, however, has received considerably less attention. Data on paternal demographics, notably race and age, from birth certificate data are becoming increasingly incomplete in recent years. This pattern of increasingly underreporting of paternal demographic data led us to speculate that pregnancies for which paternal characteristics are partially or completely missing may be associated with increased risk for uteroplacental bleeding disorders. The objective of this study is to examine the association between placenta previa and placental abruption and missing paternal age and race. Methods A retrospective cohort study using U.S. linked birth/infant death data from 1995 through 2001 (n = 26,336,549) was performed. Risks of placenta previa and placental abruption among: (i) pregnancies with complete paternal age and race data; (ii) paternal age only missing; (iii) paternal race only missing; and (iv) both paternal age and race missing, were evaluated. Relative risk (RR) with 95% confidence interval (CI) for placenta previa and placental abruption by missing paternal characteristics were derived after adjusting for confounders. Results Adjusted RR for placental abruption were 1.30 (95% CI 1.24, 1.37), 1.00 (95% CI 0.95, 1.05), and 1.08 (95% CI 1.06, 1.10) among pregnancies with "paternal age only", "paternal race only", and "both paternal age and race" missing, respectively. The increased risk of placental abruption among the "paternal age only missing" category is partly explained by increased risks among whites aged 20–29 years, and among blacks aged ≥30 years. However, no clear patterns in the associations between missing paternal characteristics and placenta previa were evident. Conclusion Missing paternal characteristics are associated with increased risk of placental abruption, likely mediated through low socio-economic conditions.

This article examines the applicability of obstetrical randomized controlled trials (RCTs) in the real-world and proposes a classification of the value of these trials based on their potential for achieving sustainable practices. In the context of this discussion, real-world results pertain to the potential impact of the RCT on sustainable interventions and practices, and its implications for healthcare practice or policy, in the country (or countries) that was conducted. While RCTs are generally regarded as the gold standard of medical evidence, their effectiveness in producing meaningful real-world results depends, among various other factors, on the clarity and specificity of the trial definitions used for diagnosis (characteristics of the study group or enrollment criteria) and treatment (intervention). The definitions used for diagnosis and treatment, especially in pragmatic trials, can influence the likelihood for real-world implementation. By analyzing notable obstetrical RCTs, the authors find that trials with well-defined diagnoses and treatments that can be implemented without specialized expertise are more likely to generate results that are relevant to general practice, indicating higher value. In contrast, RCTs with ambiguous or undefined diagnoses and treatments often lead to variations in practice and produce unreliable real-world outcomes and practices suggesting lower value. Recognizing this variability can offer valuable guidance for the design and evaluation of RCTs in obstetrics. [ABSTRACT FROM AUTHOR]

This paper briefly presents the West African Monsoon (WAM) Modeling and Evaluation Project (WAMME) and evaluates WAMME general circulation models’ (GCM) performances in simulating variability of WAM precipitation, surface temperature, and major circulation features at seasonal and intraseasonal scales in the first WAMME experiment. The analyses indicate that models with specified sea surface temperature generally have reasonable simulations of the pattern of spatial distribution of WAM seasonal mean precipitation and surface temperature as well as the averaged zonal wind in latitude-height cross-section and low level circulation. But there are large differences among models in simulating spatial correlation, intensity, and variance of precipitation compared with observations. Furthermore, the majority of models fail to produce proper intensities of the African Easterly Jet (AEJ) and the tropical easterly jet. AMMA Land Surface Model Intercomparison Project (ALMIP) data are used to analyze the association between simulated surface processes and the WAM and to investigate the WAM mechanism. It has been identified that the spatial distributions of surface sensible heat flux, surface temperature, and moisture convergence are closely associated with the simulated spatial distribution of precipitation; while surface latent heat flux is closely associated with the AEJ and contributes to divergence in AEJ simulation. Common empirical orthogonal functions (CEOF) analysis is applied to characterize the WAM precipitation evolution and has identified a major WAM precipitation mode and two temperature modes (Sahara mode and Sahel mode). Results indicate that the WAMME models produce reasonable temporal evolutions of major CEOF modes but have deficiencies/uncertainties in producing variances explained by major modes. Furthermore, the CEOF analysis shows that WAM precipitation evolution is closely related to the enhanced Sahara mode and the weakened Sahel mode, supporting the evidence revealed in the analysis using ALMIP data. An analysis of variability of CEOF modes suggests that the Sahara mode leads the WAM evolution, and divergence in simulating this mode contributes to discrepancies in the precipitation simulation.

We describe the behaviour of 23 dynamical ocean-atmosphere models, in the context of comparison with observations in a common framework. Fields of tropical sea surface temperature (SST), surface wind stress and upper ocean vertically averaged temperature (VAT) are assessed with regard to annual mean, seasonal cycle, and interannual variability characteristics. Of the participating models, 21 are coupled GCMs, of which 13 use no form of flux adjustment in the tropics. The models vary widely in design, components and purpose: nevertheless several common features are apparent. In most models without flux adjustment, the annual mean equatorial SST in the central Pacific is too cool and the Atlantic zonal SST gradient has the wrong sign. Annual mean wind stress is often too weak in the central Pacific and in the Atlantic, but too strong in the west Pacific. Few models have an upper ocean VAT seasonal cycle like that observed in the equatorial Pacific. Interannual variability is commonly too weak in the models: in particular, wind stress variability is low in the equatorial Pacific. Most models have difficulty in reproducing the observed Pacific 'horseshoe' pattern of negative SST correlations with internnual Nino3 SST anomalies, or the observed Indian-Pacific lag correlations. The results for the fields examined indicate that several substantial model improvements are needed, particularly with regard to surface wind stress.

An ensemble of twenty four coupled ocean-atmosphere models has been compared with respect to their performance in the tropical Pacific. The coupled models span a large portion of the parameter space and differ in many respects. The intercomparison includes TOGA (Tropical Ocean Global Atmosphere)-type models consisting of high-resolution tropical ocean models and coarse-resolution global atmosphere models, coarse-resolution global coupled models, and a few global coupled models with high resolution in the equatorial region in their ocean components. The performance of the annual mean state, the seasonal cycle and the interannual variability are investigated. The primary quantity analysed is sea surface temperature (SST). Additionally, the evolution of interannual heat content variations in the tropical Pacific and the relationship between the interannual SST variations in the equatorial Pacific to fluctuations in the strength of the Indian summer monsoon are investigated. The results can be summarised as follows: almost all models (even those employing flux corrections) still have problems in simulating the SST climatology, although some improvements are found relative to earlier intercomparison studies. Only a few of the coupled models simulate the El Niño/Southern Oscillation (ENSO) in terms of gross equatorial SST anomalies realistically. In particular, many models overestimate the variability in the western equatorial Pacific and underestimate the SST variability in the east. The evolution of interannual heat content variations is similar to that observed in almost all models. Finally, the majority of the models show a strong connection between ENSO and the strength of the Indian summer monsoon.