Recurrent pregnancy loss (RPL) is defined as the occurrence of two or more spontaneous pregnancy losses from the time of conception until 24 weeks of gestation. Currently, an underlying cause can be identified in only a minority of the losses. Potentially, an impaired maternal immune response targeting the semiallograft pregnancy may lead to miscarriage. While prior studies have explored the use of immune-suppressing corticosteroids to modulate the maternal immune system and hopefully improve pregnancy outcome, the absence of sufficiently powered randomised controlled trials (RCT) underscores the need for further research. The primary aim of this study is to evaluate if prednisolone administration in early pregnancy (20 mg daily for 6 weeks, then tapering doses for 2 weeks) in women with unexplained RPL leads to a higher live birth rate (LBR) in comparison to placebo. Additionally, the study assesses the tolerability, safety and the cost-effectiveness of this intervention. Finally, we will explore the effect of prednisolone in various subgroups (based on maternal age, number of previous pregnancy losses, presence of specific antibodies and pre-pregnancy endometrial immune cell level).

This ongoing multicentre, double-blind RCT will randomise 490 women with unexplained RPL and pregnancy

This study was submitted under the Clinical Trial Regulation (CTR) in Clinical Trials Information System (CTIS) for assessment by the Central Committee on Research Involving Human Subjects (CCMO) under Clinical Trial number: 2023-503220-76-01. It received full approval on 29/01/2024. Study findings will be presented at conferences and published in a peer-reviewed journal. Participants will be informed about the results by publishing them on the publicly available website of the study.

This trial is registered in ClinicalTrials.gov (ID NCT05725512) and in CTIS (2023-503220-76-01).

To quantify the carbon footprint of a sample of clinical trials for neurological disorders.

Cross-sectional study.

Two clinical trial registries were searched on 29 December 2022 for phase 2–4 randomised controlled trials led from and recruiting in the UK, enrolling people with any of the 15 neurological disorders with the highest global burden, that had started recruitment or been registered in the preceding 5 years. Eligible trials were invited to share data to estimate emissions in each of the 10 modules of the Low Carbon Clinical Trials footprinting guidance. The primary outcome measure was kg of carbon dioxide equivalent (CO₂e).

318 randomised controlled trials were found, nine were eligible and six shared data (three completed and three ongoing). The module with the highest estimated CO₂e for each trial was the Clinical Trial Unit staff emissions (median 24 126 kg CO2e, IQR 10 395–78,867; range 45–79% of overall emissions of each trial); commuting accounted for >50% of CO₂e in this module. The second and third highest modules were trial-specific participant assessments (median 11 497 kg CO2e, IQR 825–15,682) and trial supplies and equipment (median 1161 kg CO₂e, IQR 226–6632). The total carbon footprint of these six trials involving 2248 participants at 239 sites was 2 63 215 kg CO₂e.

Emissions by Clinical Trials Unit staff were the top modifiable carbon hotspot in six randomised controlled trials for people with neurological disorders, which had a total carbon footprint equivalent to 1364 passengers’ return aeroplane journeys between London and Edinburgh.

Maternal preconception obesity and adverse gestational metabolic health increase the risk of childhood obesity in offspring, but the preconception period may be an opportune time to intervene, given the motivation of the mother and the epigenetic changes that may be beneficial for the gametes during this period. However, there is a lack of studies evaluating children born to women who have had a preconception intervention. Our group has therefore designed an ancillary study to assess children born to women enrolled in the obesity-fertility randomised controlled trial (RCT), who were 6–12 years of age, with the objective of evaluating the effect of a lifestyle intervention delivered during preconception and pregnancy on adiposity and cardiometabolic parameters in the offspring. This manuscript details the study protocol.

This is an ancillary nested cohort study of the obesity-fertility RCT. Women with obesity and infertility were recruited at an academic fertility clinic and randomised to the control group, which followed usual care, or to the intervention group, which received a lifestyle intervention alone for the first 6 months and then in combination with fertility treatments for up to 18 months or until the end of pregnancy. Those who have given birth to a single child are invited to participate in this follow-up study with their child aged 6–12 years. This study started in November 2023 and is expected to end in May 2025. The primary outcome is age-adjusted and sex-adjusted body mass index z-scores in children. Secondary outcomes are anthropometry, body composition, lifestyle, physical fitness level and blood or saliva markers of cardiometabolic health in both mothers and children. Of the 130 women who participated in the obesity-fertility RCT, 52 mother-child dyads (24 in the control group; 28 in the intervention group) were potentially eligible for this follow-up study. Comparisons between groups will be performed using unpaired tests and adjusted for potential confounders using multivariable regression models. This study will provide important new data on the impact of a preconception lifestyle intervention, maintained throughout pregnancy, on the health trajectory of children and mothers 6–12 years after delivery.

The study has been approved by the institutional research ethics review boards of the Centre intégré universitaire de santé et de services sociaux de l’Estrie – Centre hospitalier universitaire de Sherbrooke. The results will be widely disseminated to the scientific community, relevant health professionals and general public.

ClinicalTrials.gov (NCT06402825).

Selection of antiseizure medications (ASMs) for newly diagnosed epilepsy remains largely a trial-and-error process. We have developed a machine learning (ML) model using retrospective data collected from five international cohorts that predicts response to different ASMs as the initial treatment for individual adults with new-onset epilepsy. This study aims to prospectively evaluate this model in Australia using a randomised controlled trial design.

At least 234 adult patients with newly diagnosed epilepsy will be recruited from 14 centres in Australia. Patients will be randomised 1:1 to the ML group or usual care group. The ML group will receive the ASM recommended by the model unless it is considered contraindicated by the neurologist. The usual care group will receive the ASM selected by the neurologist alone. Both the patient and neurologists conducting the follow-up will be blinded to the group assignment. Both groups will be followed up for 52 weeks to assess treatment outcomes. Additional information on adverse events, quality of life, mood and use of healthcare services and productivity will be collected using validated questionnaires. Acceptability of the model will also be assessed.

The primary outcome will be the proportion of participants who achieve seizure-freedom (defined as no seizures during the 12-month follow-up period) while taking the initially prescribed ASM. Secondary outcomes include time to treatment failure, time to first seizure after randomisation, changes in mood assessment score and quality of life score, direct healthcare costs, and loss of productivity during the treatment period.

This trial will provide class I evidence for the effectiveness of a ML model as a decision support tool for neurologists to select the first ASM for adults with newly diagnosed epilepsy.

This study is approved by the Alfred Health Human Research Ethics Committee (Project 130/23). Findings will be presented in academic conferences and submitted to peer-reviewed journals for publication.

ACTRN12623000209695.