First-trimester prediction of preterm prelabour rupture of membranes incorporating cervical length measurement

Objectives: To examine early pregnancy risk factors for preterm prelabour rupture of membranes (PPROM) and develop a predictive model. Study design: Retrospective analysis of a cohort of mixed-risk singleton pregnancies screened in the first and second trimesters in three Danish tertiary fetal medicine centres, including a cervical length measurement at 11–14 weeks, at 19–21 weeks and at 23–24 weeks of gestation. Univariable and multivariable logistic regression analyses were employed to identify predictive maternal characteristics, biochemical and sonographic factors. Receiver operating characteristic (ROC) curve analysis was used to determine predictors for the most accurate model. Results: Of 3477 screened women, 77 (2.2%) had PPROM. Maternal factors predictive of PPROM in univariable analysis were nulliparity (OR 2.0 (95% CI 1.2–3.3)), PAPP-A < 0.5 MoM (OR 2.6 (1.1–6.2)), previous preterm birth (OR 4.2 (1.9–8.9)), previous cervical conization (OR 3.6 (2.0–6.4)) and cervical length ≤ 25 mm on transvaginal imaging (first-trimester OR 15.9 (4.3–59.3)). These factors all remained statistically significant in a multivariable adjusted model with an AUC of 0.72 in the most discriminatory first-trimester model. The detection rate using this model would be approximately 30% at a false-positive rate of 10%. Potential predictors such as bleeding in early pregnancy and pre-existing diabetes mellitus affected very few cases and could not be formally assessed. Conclusions: Several maternal characteristics, placental biochemical and sonographic features are predictive of PPROM with moderate discrimination. Larger numbers are required to validate this algorithm and additional biomarkers, not currently used for first-trimester screening, may improve model performance

Project Half Double: results of phase 1 and phase 2 - June 2019

The purpose of this report in a series of reports from Project Half Double is to present the final overall results from phase 1 and phase 2 of Project Half Double as well as to describe the nine pilot projects from phase 2 in detail

Is smoking heaviness causally associated with alcohol use? A Mendelian randomization study in four European cohorts

BACKGROUND: Observational studies have shown that tobacco and alcohol use co-occur, but it is not clear whether this relationship is causal. METHODS: Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank, we used observational methods to test the hypothesis that smoking heaviness increases alcohol consumption. Mendelian randomization (MR) analyses were then used to test the causal relationship between smoking heaviness and alcohol consumption using 55 967 smokers from four European studies [ALSPAC, The Nord-Trøndelag Health Study (HUNT), the Copenhagen General Population Study (CGPS) and UK Biobank]. MR analyses used rs1051730/rs16969968 as a genetic proxy for smoking heaviness. RESULTS: Observational results provided evidence of an association between cigarettes per day and weekly alcohol consumption (increase in units of alcohol per additional cigarette smoked per day = 0.10, 95% confidence interval (CI) 0.05 to 0.15, P ≤ 0.001 in ALSPAC; and 0.48, 95% CI 0.45 to 0.52, P ≤ 0.001 in UK Biobank). However, there was little evidence for an association between rs1051730/rs16969968 and units of alcohol consumed per week across ALSPAC, HUNT, CGPS and UK Biobank (standard deviation increase in units of alcohol per additional copy of the risk allele = –0.004, 95% CI –0.023 to 0.016, P=0.708, I² = 51.9%). We had 99% and 88% power to detect a change of 0.03 and 0.02 standard deviation units of alcohol per additional copy of the risk allele, respectively. CONCLUSIONS: Previously reported associations between smoking and alcohol are unlikely to be causal, and may be the result of confounding and/or reverse causation. This has implications for public health research and intervention research

Progestogens to prevent preterm birth in twin pregnancies: an individual participant data meta-analysis of randomized trials

<p>Abstract</p> <p>Background</p> <p>Preterm birth is the principal factor contributing to adverse outcomes in multiple pregnancies. Randomized controlled trials of progestogens to prevent preterm birth in twin pregnancies have shown no clear benefits. However, individual studies have not had sufficient power to evaluate potential benefits in women at particular high risk of early delivery (for example, women with a previous preterm birth or short cervix) or to determine adverse effects for rare outcomes such as intrauterine death.</p> <p>Methods/design</p> <p>We propose an individual participant data meta-analysis of high quality randomized, double-blind, placebo-controlled trials of progestogen treatment in women with a twin pregnancy. The primary outcome will be adverse perinatal outcome (a composite measure of perinatal mortality and significant neonatal morbidity). Missing data will be imputed within each original study, before data of the individual studies are pooled. The effects of 17-hydroxyprogesterone caproate or vaginal progesterone treatment in women with twin pregnancies will be estimated by means of a random effects log-binomial model. Analyses will be adjusted for variables used in stratified randomization as appropriate. Pre-specified subgroup analysis will be performed to explore the effect of progestogen treatment in high-risk groups.</p> <p>Discussion</p> <p>Combining individual patient data from different randomized trials has potential to provide valuable, clinically useful information regarding the benefits and potential harms of progestogens in women with twin pregnancy overall and in relevant subgroups.</p

Data from: Gender equity at scientific events

Although the proportion of women in science, and in evolutionary biology in particular, has substantially increased over the last century, women remain underrepresented in academia, especially at senior levels. Moreover, their scientific achievements do not always receive the same level of recognition as do men’s, which can be reflected in a lower relative representation of women among invited speakers at conferences or specialized courses. Using announcements sent to the EvolDir mailing list between April 2016 and July 2017, and the symposium programs of three large evolutionary biology congresses held in summer 2017, we quantified the representation of women announced as invited speakers in conferences, congress symposia and specialized courses. We compared the proportion of invited women to a baseline estimated using membership data of the associated scientific societies, and surveyed organizers to investigate their influence and that of potential gender-ratio guidelines on the proportion of invited women. We find that the average proportion of invited women is comparable (conferences), significantly lower (specialized courses) or significantly higher (congress symposia) than the current baseline (32% women). It is positively correlated to the proportion of women among the organizers, and it is on average higher for events whose organizers considered gender when choosing speakers than for those whose organizers did not. To investigate the impact of Equal Opportunity guidelines, we then collected longitudinal data on the proportion of invited women at two series of conferences, covering the 2001-2017 period. The proportion of invited women is higher when Equal Opportunity guidelines are announced. Encouraging women to sit on organizing committees of scientific events, and the establishment of visible Equal Opportunity guidelines, thus could be ways to ensure higher number of invited female speakers in the future. Our results suggest that change, if desired, requires deliberate actions