Objective: To determine the effects on the vaginal microbiota of an oral probiotic preparation administered from early pregnancy.Design: Randomised, double blind, placebo‐controlled trial.Setting: Four maternity units in the UK.Population: Women aged 16 years or older recruited at 9–14 weeks' gestation.Methods: Participants were randomly allocated to receive oral capsules of probiotic containing Lactobacillus rhamnosus GR‐1 and Lactobacillus reuteri RC‐14 each at 2.5 × 10⁹ colony‐forming units (CFUs) or placebo once daily from recruitment until the end of pregnancy.Main outcome measure: Rates of bacterial vaginosis (BV, defined as Nugent score ≥7) at 18–20 weeks' gestation compared by logistic regression adjusted for possible confounders.Results: The primary analysis included 78% (238/304) of participants who initially consented (probiotic group 123, placebo group 115). Of these participants, 95% (227/238) reported an intake of 93% or more of the required number of capsules. The rates of BV did not differ between groups at 18–20 weeks' gestation (15% (19/123) in the probiotic group vs. 9% (10/115) in the placebo group, adjusted odds ratio 1.82, 95% confidence interval 0.64–5.19). There were also no differences between the groups in the proportion of women colonised with the probiotic strains, Escherichia coli, group B streptococci or other vaginal microbiota. There were no differences in the alpha diversity or composition of the bacterial communities between or within the probiotic and placebo groups at 9–14 and 18–20 weeks’ gestation.Conclusions: Oral probiotics taken from early pregnancy did not modify the vaginal microbiota.Tweetable The oral probiotic preparation used in this study does not prevent BV in pregnant women.

Objective: To evaluate the effectiveness of virtual reality as a distraction technique in the management of acute pain and anxiety during outpatient hysteroscopy.Design: Parallel group, prospective randomised controlled trial.Setting: UK University Hospital.Methods: Forty consenting, eligible women were randomised to virtual reality intervention (immersive video content as a distraction method) or standard care during outpatient hysteroscopy from August to October 2018.Main outcome measures: Pain and anxiety outcomes were measured as a numeric rating score (scale 0–10).Results: Compared with standard care, women with virtual reality intervention experienced less average pain (score 6.0 versus 3.7, mean difference 2.3, 95% CI 0.61–3.99, P = 0.009) and anxiety (score 5.45 versus 3.3, mean difference 2.15, 95% CI 0.38–3.92, P = 0.02).Conclusion: Virtual reality was effective in reducing pain and anxiety during outpatient hysteroscopy in a mixed‐methods randomised control trial. Its wide potential role in ambulatory gynaecological procedures needs further evaluation.Tweetable Virtual reality can be used as a part of a multimodal strategy to reduce acute pain and anxiety in patients undergoing outpatient hysteroscopy.

Unexpected clinical deterioration before 34 weeks gestation is an undesired course in early-onset pre-eclampsia. To safely prolong preterm gestation, accurate and timely prediction of complications is required. Women with confirmed early onset pre-eclampsia were recruited from 53 maternity units in the UK to a large prospective cohort study (PREP-946) for development of prognostic models for the overall risk of experiencing a complication using logistic regression (PREP-L), and for predicting the time to adverse maternal outcome using a survival model (PREP-S). External validation of the models were carried out in a multinational cohort (PIERS-634) and another cohort from the Netherlands (PETRA-216). Main outcome measures were C-statistics to summarise discrimination of the models and calibration plots and calibration slopes. A total of 169 mothers (18%) in the PREP dataset had adverse outcomes by 48 hours, and 633 (67%) by discharge. The C-statistics of the models for predicting complications by 48 hours and by discharge were 0.84 (95% CI, 0.81–0.87; PREP-S) and 0.82 (0.80–0.84; PREP-L), respectively. The PREP-S model included maternal age, gestation, medical history, systolic blood pressure, deep tendon reflexes, urine protein creatinine ratio, platelets, serum alanine amino transaminase, urea, creatinine, oxygen saturation and treatment with antihypertensives or magnesium sulfate. The PREP-L model included the above except deep tendon reflexes, serum alanine amino transaminase and creatinine. On validation in the external PIERS dataset, the reduced PREP-S model showed reasonable calibration (slope 0.80) and discrimination (C-statistic 0.75) for predicting adverse outcome by 48 hours. Reduced PREP-L model showed excellent calibration (slope: 0.93 PIERS, 0.90 PETRA) and discrimination (0.81 PIERS, 0.75 PETRA) for predicting risk by discharge in the two external datasets. PREP models can be used to obtain predictions of adverse maternal outcome risk, including early preterm delivery, by 48 hours (PREP-S) and by discharge (PREP-L), in women with early onset pre-eclampsia in the context of current care. They have a potential role in triaging high-risk mothers who may need transfer to tertiary units for intensive maternal and neonatal care. ISRCTN40384046 , retrospectively registered.

Aims/hypothesis: The aim of this systematic review was to develop core outcome sets (COSs) for trials evaluating interventions for the prevention or treatment of gestational diabetes mellitus (GDM). Methods: We identified previously reported outcomes through a systematic review of the literature. These outcomes were presented to key stakeholders (including patient representatives, researchers and clinicians) for prioritisation using a three-round, e-Delphi study. A priori consensus criteria informed which outcomes were brought forward for discussion at a face-to-face consensus meeting where the COS was finalised. Results: Our review identified 74 GDM prevention and 116 GDM treatment outcomes, which were presented to stakeholders in round 1 of the e-Delphi study. Round 1 was completed by 173 stakeholders, 70% (121/173) of whom went on to complete round 2; 84% (102/121) of round 2 responders completed round 3. Twenty-two GDM prevention outcomes and 30 GDM treatment outcomes were discussed at the consensus meeting. Owing to significant overlap between included prevention and treatment outcomes, consensus meeting stakeholders agreed to develop a single prevention/treatment COS. Fourteen outcomes were included in the final COS. These consisted of six maternal outcomes (GDM diagnosis, adherence to the intervention, hypertensive disorders of pregnancy, requirement and type of pharmacological therapy for hyperglycaemia, gestational weight gain and mode of birth) and eight neonatal outcomes (birthweight, large for gestational age, small for gestational age, gestational age at birth, preterm birth, neonatal hypoglycaemia, neonatal death and stillbirth). Conclusions/interpretation: This COS will enable future GDM prevention and treatment trials to measure similar outcomes that matter to stakeholders and facilitate comparison and combination of these studies. Trial registration: This study was registered prospectively with the Core Outcome Measures in Effectiveness Trials (COMET) database: http://www.comet-initiative.org/studies/details/686/

Objective: This systematic review and meta‐analysis aimed to evaluate the performance of existing externally validated prediction models for pre‐eclampsia (PE) (specifically, any‐onset, early‐onset, late‐onset and preterm PE).Methods: A systematic search was conducted in five databases (MEDLINE, EMBASE, Emcare, CINAHL and Maternity & Infant Care Database) and using Google Scholar/reference search to identify studies based on the Population, Index prediction model, Comparator, Outcome, Timing and Setting (PICOTS) approach until 20 May 2023. We extracted data using the CHARMS checklist and appraised the risk of bias using the PROBAST tool. A meta‐analysis of discrimination and calibration performance was conducted when appropriate.Results: Twenty‐three studies reported 52 externally validated prediction models for PE (one preterm, 20 any‐onset, 17 early‐onset and 14 late‐onset PE models). No model had the same set of predictors. Fifteen any‐onset PE models were validated externally once, two were validated twice and three were validated three times, while the Fetal Medicine Foundation (FMF) competing‐risks model for preterm PE prediction was validated widely in 16 different settings. The most common predictors were maternal characteristics (prepregnancy body mass index, prior PE, family history of PE, chronic medical conditions and ethnicity) and biomarkers (uterine artery pulsatility index and pregnancy‐associated plasma protein‐A). The FMF model for preterm PE (triple test plus maternal factors) had the best performance, with a pooled area under the receiver‐operating‐characteristics curve (AUC) of 0.90 (95% prediction interval (PI), 0.76–0.96), and was well calibrated. The other models generally had poor‐to‐good discrimination performance (median AUC, 0.66 (range, 0.53–0.77)) and were overfitted on external validation. Apart from the FMF model, only two models that were validated multiple times for any‐onset PE prediction, which were based on maternal characteristics only, produced reasonable pooled AUCs of 0.71 (95% PI, 0.66–0.76) and 0.73 (95% PI, 0.55–0.86).Conclusions: Existing externally validated prediction models for any‐, early‐ and late‐onset PE have limited discrimination and calibration performance, and include inconsistent input variables. The triple‐test FMF model had outstanding discrimination performance in predicting preterm PE in numerous settings, but the inclusion of specialized biomarkers may limit feasibility and implementation outside of high‐resource settings. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.