Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression

Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression

PTF11iqb: cool supergiant mass-loss that bridges the gap between Type IIn and normal supernovae

The supernova (SN) PTF11iqb was initially classified as a Type IIn event caught very early after explosion. It showed narrow Wolf–Rayet (WR) spectral features on day 2 (as in SN 1998S and SN 2013cu), but the narrow emission weakened quickly and the spectrum morphed to resemble Types II-L and II-P. At late times, H? exhibited a complex, multipeaked profile reminiscent of SN 1998S. In terms of spectroscopic evolution, we find that PTF11iqb was a near twin of SN 1998S, although with somewhat weaker interaction with circumstellar material (CSM) at early times, and stronger interaction at late times. We interpret the spectral changes as caused by early interaction with asymmetric CSM that is quickly (by day 20) enveloped by the expanding SN ejecta photosphere, but then revealed again after the end of the plateau when the photosphere recedes. The light curve can be matched with a simple model for CSM interaction (with a mass-loss rate of roughly 10?4 M? yr?1) added to the light curve of a normal SN II-P. The underlying plateau requires a progenitor with an extended hydrogen envelope like a red supergiant at the moment of explosion, consistent with the slow wind speed (<80?km?s?1) inferred from narrow H? emission. The cool supergiant progenitor is significant because PTF11iqb showed WR features in its early spectrum – meaning that the presence of such WR features does not necessarily indicate a WR-like progenitor. Overall, PTF11iqb bridges SNe IIn with weaker pre-SN mass-loss seen in SNe II-L and II-P, implying a continuum between these types

PTF11iqb: cool supergiant mass-loss that bridges the gap between Type IIn and normal supernovae

The supernova (SN) PTF11iqb was initially classified as a Type IIn event caught very early after explosion. It showed narrow Wolf–Rayet (WR) spectral features on day 2 (as in SN 1998S and SN 2013cu), but the narrow emission weakened quickly and the spectrum morphed to resemble Types II-L and II-P. At late times, H? exhibited a complex, multipeaked profile reminiscent of SN 1998S. In terms of spectroscopic evolution, we find that PTF11iqb was a near twin of SN 1998S, although with somewhat weaker interaction with circumstellar material (CSM) at early times, and stronger interaction at late times. We interpret the spectral changes as caused by early interaction with asymmetric CSM that is quickly (by day 20) enveloped by the expanding SN ejecta photosphere, but then revealed again after the end of the plateau when the photosphere recedes. The light curve can be matched with a simple model for CSM interaction (with a mass-loss rate of roughly 10?4 M? yr?1) added to the light curve of a normal SN II-P. The underlying plateau requires a progenitor with an extended hydrogen envelope like a red supergiant at the moment of explosion, consistent with the slow wind speed (<80?km?s?1) inferred from narrow H? emission. The cool supergiant progenitor is significant because PTF11iqb showed WR features in its early spectrum – meaning that the presence of such WR features does not necessarily indicate a WR-like progenitor. Overall, PTF11iqb bridges SNe IIn with weaker pre-SN mass-loss seen in SNe II-L and II-P, implying a continuum between these types

Parallel-in-Space-and-Time Simulation of the Three-Dimensional, Unsteady Navier-Stokes Equations for Incompressible Flow

In this paper we combine the Parareal parallel-in-time method together with spatial parallelization and investigate this space-time parallel scheme by means of solving the three-dimensional incompressible Navier-Stokes equations. Parallelization of time stepping provides a new direction of parallelization and allows to employ additional cores to further speed up simulations after spatial parallelization has saturated. We report on numerical experiments performed on a Cray XE6, simulating a driven cavity flow with and without obstacles. Distributed memory parallelization is used in both space and time, featuring up to 2,048 cores in total. It is confirmed that the space-time-parallel method can provide speedup beyond the saturation of the spatial parallelization

A comprehensive review on non-clinical methods to study transfer of medication into breast milk – A contribution from the ConcePTION project

Breastfeeding plays a major role in the health and wellbeing of mother and infant. However, information on the safety of maternal medication during breastfeeding is lacking for most medications. This leads to discontinuation of either breastfeeding or maternal therapy, although many medications are likely to be safe. Since human lactation studies are costly and challenging, validated non-clinical methods would offer an attractive alternative. This review gives an extensive overview of the non-clinical methods (in vitro, in vivo and in silico) to study the transfer of maternal medication into the human breast milk, and subsequent neonatal systemic exposure. Several in vitro models are available, but model characterization, including quantitative medication transport data across the in vitro blood-milk barrier, remains rather limited. Furthermore, animal in vivo models have been used successfully in the past. However, these models don't always mimic human physiology due to species-specific differences. Several efforts have been made to predict medication transfer into the milk based on physicochemical characteristics. However, the role of transporter proteins and several physiological factors (e.g., variable milk lipid content) are not accounted for by these methods. Physiologically-based pharmacokinetic (PBPK) modelling offers a mechanism-oriented strategy with bio-relevance. Recently, lactation PBPK models have been reported for some medications, showing at least the feasibility and value of PBP

Role of genetic testing for inherited prostate cancer risk: Philadelphia prostate cancer consensus conference 2017

Purpose: Guidelines are limited for genetic testing for prostate cancer (PCA). The goal of this conference was to develop an expert consensus-dri

Astronomical Distance Determination in the Space Age: Secondary Distance Indicators

The formal division of the distance indicators into primary and secondary leads to difficulties in description of methods which can actually be used in two ways: with, and without the support of the other methods for scaling. Thus instead of concentrating on the scaling requirement we concentrate on all methods of distance determination to extragalactic sources which are designated, at least formally, to use for individual sources. Among those, the Supernovae Ia is clearly the leader due to its enormous success in determination of the expansion rate of the Universe. However, new methods are rapidly developing, and there is also a progress in more traditional methods. We give a general overview of the methods but we mostly concentrate on the most recent developments in each field, and future expectations. © 2018, The Author(s)

Performance of novel VUV-sensitive Silicon Photo-Multipliers for nEXO

Liquid xenon time projection chambers are promising detectors to search for neutrinoless double beta decay (0$\nu \beta \beta$), due to their response uniformity, monolithic sensitive volume, scalability to large target masses, and suitability for extremely low background operations. The nEXO collaboration has designed a tonne-scale time projection chamber that aims to search for 0$\nu \beta \beta$ of \ce{^{136}Xe} with projected half-life sensitivity of $1.35\times 10^{28}$~yr. To reach this sensitivity, the design goal for nEXO is $\leq$1\% energy resolution at the decay $Q$-value ($2458.07\pm 0.31$~keV). Reaching this resolution requires the efficient collection of both the ionization and scintillation produced in the detector. The nEXO design employs Silicon Photo-Multipliers (SiPMs) to detect the vacuum ultra-violet, 175 nm scintillation light of liquid xenon. This paper reports on the characterization of the newest vacuum ultra-violet sensitive Fondazione Bruno Kessler VUVHD3 SiPMs specifically designed for nEXO, as well as new measurements on new test samples of previously characterised Hamamatsu VUV4 Multi Pixel Photon Counters (MPPCs). Various SiPM and MPPC parameters, such as dark noise, gain, direct crosstalk, correlated avalanches and photon detection efficiency were measured as a function of the applied over voltage and wavelength at liquid xenon temperature (163~K). The results from this study are used to provide updated estimates of the achievable energy resolution at the decay $Q$-value for the nEXO design