Background: Partially clustered trials are trials that, by design, include a mixture of independent and clustered observations. For example, neonatal trials may include infants from a single, twin or triplet birth. The clustering of observations in partially clustered trials should be accounted for when determining the target sample size to avoid treatment arm comparisons being over or under powered. Limited tools are currently available for calculating the sample size for partially clustered trials, particularly when the maximum cluster size is greater than 2. The aim of this article is to introduce a new online application to calculate the target sample size for partially clustered trials covering a broad range of scenarios.Methods: The target sample size is calculated using design effects recently derived for two-arm partially clustered trials when the clusters exist prior to randomisation and the outcome of interest is continuous or binary. Both cluster and individual randomisation are considered for the clustered observations (resulting in nested and crossed designs, respectively). The sample size depends on quantities needed for typical sample size calculations, such as the effect size of interest, and the desired significance level and power. In addition, the sample size for partially clustered trials also depends on the range of cluster sizes, the proportion of observations that belong to clusters of each size, the intracluster correlation coefficient, the method of randomisation for the clustered observations, and the model that will be used for analysis. We developed an R Shiny web application that implements these methods in an easy-to-use sample size calculator that is freely available online.Results: The sample size calculator is free to access and provides trialists with the ability to determine the target sample size for different types of partially clustered trials. Step-by-step instructions are provided to illustrate the use of the calculator for designing two hypothetical trials. The target sample size that accounts for partial clustering can be quite different to the sample size that is calculated by methods for an independent design that ignore the clustering.Conclusion: Partial clustering affects the power and sample size requirements of clinical trials. The calculator presented in this article allows trialists to account for the clustering that occurs in two-arm partially clustered trials for binary and continuous outcomes and ensure their trials are appropriately powered.

BACKGROUND/AIMS:Multiple imputation is often recommended over complete case analysis for handling missing data in clinical trials due to its ability to recover information from participants with incomplete data. While multiple imputation is generally held to be more efficient than complete case analysis, its planned use in clinical trials is typically not considered during sample size estimation. The standard approach of inflating the sample size for anticipated loss to follow-up is applicable for complete case analysis but could lead to excess power and hence inefficient resource use should multiple imputation be planned for analysis. In this article, we systematically reviewed published clinical trials with the aim of quantifying the precision advantages of multiple imputation over complete case analysis in treatment effect estimation, hence informing sample size planning for future trials. METHODS:We conducted a targeted review of clinical trials published between January 2019 and December 2023 in Lancet, The BMJ, Journal of the American Medical Association and New England Journal of Medicine. Clinical trials were eligible for inclusion if point and variance estimates for the effect of treatment on a primary efficacy or safety outcome could be determined for both multiple imputation and complete case analysis. The design effect due to multiple imputation was calculated as the variance of the treatment effect estimate using multiple imputation divided by the corresponding variance using complete case analysis. As a supplementary analysis, we also conducted an untargeted review of other journals by searching in PubMed for clinical trials with the keywords 'imputation' or 'imputed' in their title or abstract. RESULTS:The targeted search identified 547 articles, of which 59 satisfied eligibility criteria. Included trials tended to be large in size (median 653 participants) and reported a median of 8.6% missing data in the complete case analysis of the primary outcome (range 0.4%-30.5%). Multiple imputation was most frequently applied using chained equations under a missing at random assumption, with auxiliary variables included in the imputation model in most trials. The median design effect due to multiple imputation was 1.00 in both unadjusted (n = 15 trials) and covariate-adjusted analyses (n = 46 trials), suggesting multiple imputation typically was not offering precision advantages over complete case analysis. Similar design effects were observed in the untargeted review (median 0.96 and 1.01 for unadjusted and covariate-adjusted analyses), despite higher rates of missing data overall (median 15.7%, n = 49 trials). DISCUSSION:Multiple imputation did not consistently lead to more precise treatment effect estimates than complete case analysis in the trials included in the review. Findings should not be construed as an argument against the use of multiple imputation but suggest the standard approach of inflating the sample size for anticipated loss to follow-up is reasonable when multiple imputation is planned for analysis.

BACKGROUND:In the last 2 decades, based on systematic reviews of randomized controlled trials, antenatal magnesium sulfate has been variably implemented internationally for fetal neuroprotection. OBJECTIVE:Our objective was to assess the effects of magnesium sulfate exposure prior to extremely preterm/low birthweight birth on survival without cerebral palsy or moderate to severe functional impairment in an Australian and New Zealand cohort. STUDY DESIGN:This population-based retrospective cohort study, using data from the Australian and New Zealand Neonatal Network registry, included neonates born from January 1, 2012 through December 31, 2020 at <30 weeks' gestation; due to data availability, 2 to 3 years of follow-up was restricted to those born through December 31, 2017 at <28 weeks' gestation and/or weighing <1000 g. Analyses were performed using logistic regression with adjustment for potential confounding. RESULTS:The cohort included 16,582 neonates for outcomes to hospital discharge. For primary outcomes at 2 to 3 years, among 6763 infants (4353 [64%] exposed to magnesium sulfate), exposure to magnesium sulfate was associated with a reduced risk of death or cerebral palsy (adjusted relative risk, 0.83; 95% confidence interval, 0.74-0.93) and of death or moderate to severe functional impairment (adjusted relative risk, 0.88; 95% confidence interval, 0.81-0.97). A clear reduction in cerebral palsy was observed for children born from singleton pregnancies (adjusted relative risk, 0.68; 95% confidence interval, 0.47-0.98). When multiples were included, the reduced risk of cerebral palsy was not statistically significant (adjusted relative risk, 0.78; 95% confidence interval, 0.59-1.05). CONCLUSION:Our large, binational study demonstrates real-world benefits of exposure to magnesium sulfate prior to extremely preterm and/or low birthweight birth, including increased survival without cerebral palsy or moderate to severe functional impairment, strongly supporting ongoing and enhanced implementation.

OBJECTIVE:Multiple births are common in randomised trials targeting preterm populations. Clustering due to multiple births is often overlooked in individual trials and may impact the results of meta-analyses that pool their results. We aimed to assess how multiple births have been handled in the reporting and meta-analyses of recent systematic reviews. DESIGN:We conducted a methodological systematic review of Cochrane and non-Cochrane systematic reviews. The search was conducted on 10 September 2024 in the Cochrane Database of Systematic Reviews and PubMed for articles published in the previous 12 months. Reviews were eligible if they involved randomised trials of interventions delivered in pregnancy or infancy, included multiple births and reported results of at least one aggregate data meta-analysis for an infant outcome. RESULTS:After screening 222 articles, 39 had unclear eligibility due to making no mention of multiple births and nine met the eligibility criteria (five Cochrane and four non-Cochrane reviews). Multiple births were inconsistently handled across included reviews. The degree of clustering due to multiple births was poorly described and meta-analyses accounting for clustering were rarely reported (2/9 reviews; 22%). CIs around pooled treatment effect estimates were wider after accounting for clustering. CONCLUSIONS:Clustering due to multiple births is a poorly recognised issue in systematic reviews and meta-analyses. Given the potential for this clustering to alter conclusions about the effectiveness of interventions, we recommend accounting for clustering due to multiple births in future meta-analyses.

Mothers of preterm infants face many challenges in establishing and maintaining an adequate supply of breast milk during their infant’s prolonged hospitalisation. Domperidone has been shown to be superior to placebo for the treatment of lactation insufficiency, however there is significant uncertainty regarding the optimal treatment dose. This trial has been designed to resolve the issue of whether a higher dose of domperidone (20 mg three times daily; 60 mg/day) leads to greater improvements in maternal breast milk supply compared to a lower dose (10 mg three times daily; 30 mg/day), while also evaluating differences in adverse events. This knowledge will be critical for guiding clinical practice and facilitating benefit versus risk evaluations surrounding the use of domperidone in lactation. SUMMIT is a multicentre, double-blinded randomised controlled trial that will assess whether a higher dose of domperidone (60 mg/day) will further increase maternal breast milk supply compared to a lower dose (30 mg/day). Target population are mothers of preterm infants born at less than 34 weeks’ gestation, who are between 7 and 28 days postpartum, with lactation insufficiency, and can give informed consent. Participants will be randomly allocated into two parallel groups in a 1:1 ratio (n = 50 per group) to receive either 60 mg/day or 30 mg/day of domperidone. The primary outcome will be daily expressed breast milk volume over a 24-hour period on Day 21 post randomisation. As part of the main trial, participants and their infants will be followed until the infant reaches term corrected age or is discharged home from the neonatal unit (whichever occurs first). This will be the largest clinical trial to evaluate the efficacy and safety of domperidone for the treatment of lactation insufficiency following preterm birth. This trial will provide critical evidence to guide clinical practice recommendations regarding what the optimal treatment dose of domperidone should be, while also enabling assessment of the impacts of different dosage regimens on longer-term breast milk feeding outcomes, as well as maternal and infant health outcomes. This study was prospectively registered via the Australian and New Zealand Clinical Trials Registry (https://www.anzctr.org.au: ACTRN12621000508875 (registered 30 April 2021)).

High-quality evidence supports the use of pasteurized donor human milk (donor milk) in very preterm infants with insufficient maternal milk available. However, evidence to guide the use of donor milk in more mature preterm infants is lacking. To compare the effect of donor milk vs term infant formula, used to supplement insufficient maternal milk, on the time to establish full enteral feeds in moderate to late preterm infants. This multisite, blinded randomized clinical trial was conducted from July 6, 2021, to April 5, 2023, at 2 Australian neonatal units. Infants 4 days old or younger, born between 32 + 0 and 36 + 6 weeks’ gestation, with a birth weight of 1500 g or higher, and admitted to a neonatal unit were eligible if they were clinically stable, ready to commence or had commenced enteral feeds, and had insufficient maternal milk available. Infants were followed up until 6-month corrected age (CA). Follow-up assessments until 6-month CA were completed by December 4, 2023, and data analyses were completed by January 23, 2025. Infants were randomly assigned to receive supplemental donor milk or term formula for up to 8 days, stratified by site and gestational age at birth. The primary outcome was time to full enteral feeds (defined as 150 mL/kg/day). Secondary outcomes included feed intolerance, growth, body composition, breast milk feeding, and hospital readmissions to 6-month CA. Of 201 infants randomized (99 to donor milk, 102 to formula), the mean (SD) birth gestational age was 34.6 (1.2) weeks, mean (SD) birth weight was 2267.1 (450.8) g, 88 infants (43.8%) were female, and 75 infants (37.3%) were a twin or triplet. Mean (SD) time to reach full enteral feeds did not differ between groups (donor milk group: 5.7 [2.6] days; formula group: 5.8 [3.4] days; adjusted mean difference, −0.07; 95% CI, −0.90 to 0.76). Secondary outcomes were similar between groups, except that infants in the donor milk group had a lower rate of birth weight regain compared with the formula group (mean [SD] time to regain in donor milk group: 10.7 [5.7] days; formula group: 8.4 [4.4] days; hazard ratio, 0.65; 95% CI, 0.47-0.88). In this multisite randomized clinical trial, supplemental donor milk did not reduce time to full enteral feeds in moderate to late preterm infants compared with term formula for up to 8 days. anzctr.org.au Identifier: ACTRN12621000529842

Objective: To evaluate the feasibility and early adoption of the Omega-3 Test-and-Treat Program, a targeted intervention to reduce preterm birth in women with low omega-3 levels, implemented within routine antenatal care. Design: A prospective implementation study using the Quality Enhancement Research Initiative (QUERI) framework, conducted between April 19, 2021, and June 30, 2022. Setting: Antenatal care settings in South Australia, leveraging the South Australia (SA) Pathology, South Australian Serum Antenatal Screening (SAMSAS) program. Participants: Pregnant women with singleton pregnancies <20 weeks' gestation undergoing antenatal screening and healthcare providers responsible for ordering and facilitating omega-3 testing. Intervention: A structured program to identify women with low omega-3 levels in early pregnancy and provide evidence-based supplementation guidance to reduce the risk of preterm birth. Main Outcome Measures: Program feasibility (uptake and fidelity), representativeness of early adopters compared to the broader population, adherence to program criteria (singleton pregnancies <20 weeks' gestation), and omega-3 status distribution. Results: A total of 4,801 omega-3 tests were reported by SA Pathology, with consistent uptake over time. Women tested were demographically and clinically comparable to those not tested. Among early adopters, 702 (14.7%) had low, 1,638 (34.2%) moderate, and 2,442 (51.1%) sufficient omega-3 levels. Program fidelity was high across 5057 omega-3 lab samples with 4,935 (97.6%) analysed within the standard 72-hour timeframe. Adherence to testing criteria was strong, with only 33 (0.7%) samples from pregnancies >20 weeks' and 58 (1.2%) from multiple pregnancies. Conclusion: Early evaluations show the Omega-3 Test-and-Treat Program is feasible and integrates effectively into routine antenatal care. This real-world approach demonstrates strong potential to reduce preterm birth rates through targeted nutritional intervention, supporting its scalability and broader implementation. ### Competing Interest Statement MM served as President of the International Society for the Study of Fatty Acids and Lipids (ISSFAL) from 2021 to 2024 (unpaid role). RG holds a patent titled "Stabilising and analysing fatty acids in a biological sample stored on solid media" (Patent ID AU2013209278). KB served as a member of a Preterm Birth Prevention Trial Data Safety and Monitoring Board (unpaid role). LY received funding from Societe des Produits Nestle for a separate analysis of data from the ORIP trial to identify women likely to benefit from omega-3 supplementation, which was unrelated to this work. All other authors declare no relevant disclosures. ### Funding Statement This work was supported by a project grant from the Thyne Reid Foundation and the Hospital Research Foundation (THRF), as well as an Australian National Health and Medical Research Council (NHMRC) Centre of Research Excellence Grant (APP1135155). The ORIP trial was funded through an NHMRC project grant (APP1050468). MM and PM were supported by Australian NHMRC Investigator Grants (APP2016756 and APP1172870). KB received support from a Women's and Children's Hospital Foundation MS McLeod Postdoctoral Fellowship. The funders had no role in the design, conduct, or analysis of this work. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This work was approved by the Women's and Children's Health Network Human Research Ethics Committee (HREC/20/WCHN/138). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data for this study will not be shared, as we do not have permission from the participants or ethics approval to do so.

AIMS:Low-dose colchicine reduces the risk of cardiovascular events after myocardial infarction (MI). The purpose of this study was to assess the effect of colchicine post-MI on coronary plaque morphology in non-culprit segments by optical coherence tomography (OCT). METHODS AND RESULTS:COCOMO-ACS was a double-blind, placebo-controlled trial that randomized 64 patients (median age 61.5 years; 9.4% female) with acute non-ST-segment elevation MI to colchicine 0.5 mg daily or placebo for a median of 17.8 months in addition to guideline-recommended therapy. Participants underwent serial OCT imaging within a matched segment of non-culprit coronary artery that contained at least one lipid-rich plaque causing ≥20% stenosis. The primary outcome was the change in minimum fibrous cap thickness (FCT) in non-culprit segments from baseline to final visit. Of those randomized, 57 (29 placebo, 28 colchicine) had evaluable imaging at baseline and follow-up. Overall, colchicine had no effect on relative (placebo +48.0 ± 35.1% vs. colchicine +62.4 ± 38.1%, P = 0.18) or absolute changes in minimum FCT (+29.2 ± 20.9 µm vs. + 37.2 ± 21.3 µm, P = 0.18), or change in maximum lipid arc (-38.8 ± 32.2° vs. -54.8 ± 46.9°, P = 0.18) throughout the imaged non-culprit segment. However, in patients assigned colchicine, cap rupture was less frequent (placebo 27.6% vs. colchicine 3.6%, P = 0.03). In post hoc analysis of 43 participants who had been followed for at least 16 months, minimum FCT increased to a greater extent in the colchicine group (placebo +38.7 ± 25.4% vs. colchicine +64.7 ± 34.1%, P = 0.005). CONCLUSION:In this study, OCT failed to detect an effect of colchicine on the minimum FCT or maximum lipid arc of plaques in non-culprit segments post-MI. The post hoc observation that minimum FCT increased to a greater extent with colchicine after more prolonged treatment suggests that longer-term studies may be required to detect the effect of anti-inflammatory therapies on plaque morphology by OCT. CLINICAL TRIAL NUMBER:Australian New Zealand Clinical Trials Registry Identifier, ACTRN12618000809235, registered on the 11 May 2018.

OBJECTIVE:To assess the feasibility of embedding omega-3 fatty acid testing and targeted supplementation (the Omega-3 Test-and-Treat Program) into routine antenatal care to reduce the risk of preterm birth. STUDY DESIGN:Prospective implementation evaluation study, using the Quality Enhancement Research Initiative (QUERI) framework. SETTING, PARTICIPANTS:Women with singleton pregnancies undergoing routine antenatal screening during early pregnancy (before 20 weeks' gestation) and their health care providers, South Australia, 19 April 2021 - 30 June 2022. INTERVENTION:Addition of omega-3 fatty acid testing option to SA Pathology test referral forms for the South Australian Maternal Serum Antenatal Screening (SAMSAS) program, with the aim of identifying women with low omega-3 fatty acid levels during early pregnancy and providing evidence-based supplementation guidance for reducing the risk of preterm birth. MAIN OUTCOME MEASURES:Program feasibility (uptake and fidelity); representativeness of women tested for omega-3 fatty acid status; and omega-3 fatty acid status, by proportion of total serum fatty acids (low, < 3.7%; moderate, 3.7-4.3%; sufficient, > 4.3%). RESULTS:A total of 4801 requests for omega-3 fatty acid tests (26.1% of 18 362 SAMSAS referrals) were submitted to SA Pathology during the initial implementation phase of the Omega-3 Test-and-Treat Program. The monthly number of test requests increased from 15 (2.4% of 627 SAMSAS referrals) in April 2021 to 340 (29.4% of 1156 SAMSAS referrals) in June 2022. The socio-demographic and clinical characteristics of women referred for omega-3 fatty acid testing were similar to those for women who were not. Serum samples were insufficient for omega-3 fatty acid testing in 19 cases; of the 4782 tests performed, omega-3 fatty acid levels were low in 702 (14.7%), moderate in 1638 (34.2%), and sufficient in 2442 tests (51.1%). Of 5057 samples received by the Omega-3 Laboratory, 4935 (97.6%) were analysed within 72 hours. Thirty-three of 4801 omega-3 fatty acid test referrals (0.7%) were for women beyond 20 weeks of pregnancy; 58 referrals (1.2%) were for women with non-singleton pregnancies. CONCLUSION:The Omega-3 Test-and-Treat Program is a feasible approach to reducing the risk of preterm birth with a targeted nutritional intervention that could be integrated into routine antenatal care in Australia.

BACKGROUND:Randomisation forms the foundation of clinical trials, but its implementation can be prone to error. Often randomisation errors affect few participants and do not seriously compromise the integrity of the trial. However, in some cases randomisation errors can have widespread consequences and call into question the validity of trial conclusions. Published articles may be retracted as a result. Valuable insight can be gained from studying past errors to minimise the risk of similar errors and their disastrous consequences impacting future trials. The aims of this article are to (i) describe examples of major failures of randomisation, and (ii) provide guidance on how to avoid them in practice. METHODS:Major failures of randomisation were defined as inadvertent errors that affected many trial participants and occurred during the process of designing the randomisation scheme, generating the randomisation schedule, allocating participants to treatment groups, or providing the assigned treatment. Examples of major failures of randomisation were drawn from author experience and through a review of the published literature, which included a systematic search of the Retraction Watch Database for serious randomisation problems that led to the retraction of a published article. Practice points to avoid such errors were developed by consensus among the authors. RESULTS:Examples are provided of seven broad types of major failures of randomisation: randomisation schedule followed incorrectly, randomisation schedule sorted incorrectly, randomisation schedule too short, clusters handled incorrectly, incorrect or unknown treatment provided at randomisation, poorly designed randomisation scheme, and programming errors in adaptive randomisation schemes. Practice points for avoiding such errors are presented, including suggestions for written documentation, staff training, and thorough testing of the randomisation process prior to trial commencement. CONCLUSIONS:Randomisation is of fundamental importance in clinical trials. Greater consideration should be given to the potential for major failures of randomisation and strategies to avoid them. When major failures of randomisation do occur, greater transparency in reporting is needed.

BACKGROUND:Preterm birth (< 37 weeks gestation) is a leading cause of infant morbidity and mortality, yet the underlying causes remain unknown in many cases. Environmental exposures, including endocrine-disrupting chemicals such as phthalates, have been implicated in preterm birth risk. Phthalates are commonly used as plasticisers in consumer products, resulting in widespread human exposure. While some studies suggest an association between maternal phthalate exposure and reduced gestational length, findings remain inconsistent. This study aimed to investigate the relationship between urinary phthalate metabolite concentrations and gestational length in an Australian pregnancy cohort. METHODS:This prospective cohort study was nested within the Omega-3 to Reduce the Incidence of Prematurity (ORIP) trial. A total of 605 women with singleton pregnancies from South Australia provided urine samples between 22- and 26-weeks' gestation for phthalate metabolite analysis. Thirteen phthalate metabolites were quantified using liquid chromatography-tandem mass spectrometry. Gestational age at birth was determined from medical records. Linear regression models assessed associations between phthalate concentrations and gestational length, adjusting for maternal characteristics including age, BMI, socioeconomic status, education, smoking, and alcohol consumption. RESULTS:Phthalate metabolites were detected in > 99% of urine samples, with the highest concentrations observed for mono-ethyl phthalate (MEP), mono-isobutyl phthalate (MiBP), and mono-butyl phthalate (MBP). There was no evidence of an association between phthalate exposure and gestational length in either unadjusted or adjusted analyses. No significant association was found between phthalate exposure and preterm birth risk. CONCLUSIONS:Despite widespread phthalate exposure, no clear link was identified between maternal phthalate levels and shortened gestation in this Australian cohort. However, continued surveillance is needed to monitor emerging plasticiser exposures and inform public health policies on maternal and infant health. TRIAL REGISTRATION NUMBER:Australian New Zealand Clinical Trials Registry number, ACTRN12613001142729. Date of registration: 27/09/2013.

We assessed the use of magnesium sulphate prior to preterm birth for preventing cerebral palsy in an Australian and New Zealand registry study. Use increased markedly from 32.3% (2012) to 78.8% (2020) (p < 0.001). Binational approaches to sustain and explore the feasibility of further increasing use, informed by evolving evidence and guidelines, are needed.

Partially clustered trials are defined as trials where some observations belong to a cluster and others are independent. For example, neonatal trials may include infants from a single, twin, or triplet birth. The clustering of observations in partially clustered trials should be accounted for when determining the target sample size to avoid being over or underpowered. However, sample size methods have only been developed for limited partially clustered trial designs (e.g., designs with maximum cluster sizes of 2). In this article, we present new design effects that can be used to determine the sample size for two-arm, parallel, partially clustered trials where clusters exist pre-randomization. Design effects are derived algebraically for continuous and binary outcomes, assuming a generalized estimating equations-based approach to estimation with either an independence or exchangeable working correlation structure. Both cluster and individual randomization are considered for the clustered observations. The design effects are shown to depend on the intracluster correlation coefficient, proportion of observations that belong to clusters of each size, method of randomization, type of outcome, and working correlation structure. The design effects are validated through a simulation study. Example sample size calculations are presented to illustrate how the design effects can be used to determine the target sample size for different partially clustered trial designs. The design effects depend on parameters that can be feasibly estimated when planning a trial and can be used to ensure that partially clustered trials are appropriately powered in the future.

Exclusion of meat and fish from the diet can lead to low levels of omega-3 (n-3) long chain polyunsaturated fatty acids (LCPUFAs), leaving the body reliant on dietary intake of n-3 α-linolenic acid (ALA) for endogenous conversion. This study compared dried blood spot fatty acid profiles from a large cohort of pregnant Indian women in Bengaluru, Karnataka, with self-reported vegetarian (n=332) or omnivorous (n=691) diets in the first trimester, to those of pregnant Australian women (n=454) at a similar gestational age. Indian vegetarians and omnivores showed similar fatty acid profiles in dried blood spots but both had markedly lower n-3 fatty acids (mean total n-3 values: Indian 2.01% and 2.36% of total fatty acids respectively; 4.75% in Australian) with ALA, eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid all less than half the Australian values. Both Indian groups also had lower arachidonic acid levels (mean 7.65% and 7.91% respectively, vs 8.50% in Australian omnivores), and higher linoleic acid levels (mean 22.53% and 22.41% respectively, vs 19.96% in Australian omnivores) compared with the Australian participants. In general, the relationships between n-3 fatty acids were stronger in Indian vegetarians than Indian omnivores, and weakest in Australian omnivores. These findings suggest that regardless of diet, Indian women in early pregnancy have lower n-3 LCPUFA status than Australian pregnant women. Our data are consistent with the idea that increasing intake of n-3 ALA-rich oils and reducing n-6 linoleic acid-rich oils in the diet of Indian women could be an efficient way of increasing their n-3 LCPUFA status. Clinical trial registrations ORIP, Australian New Zealand Clinical Trials Registry number, ACTRN12613001142729; BORN, Clinical Trials Registry-India CTRI/2020/08/027146.

To obtain valid inference following stratified randomisation, treatment effects should be estimated with adjustment for stratification variables. Stratification sometimes requires categorisation of a continuous prognostic variable (eg, age), which raises the question: should adjustment be based on randomisation categories or underlying continuous values? In practice, adjustment for randomisation categories is more common. We reviewed trials published in general medical journals and found none of the 32 trials that stratified randomisation based on a continuous variable adjusted for continuous values in the primary analysis. Using data simulation, this article evaluates the performance of different adjustment strategies for continuous and binary outcomes where the covariate-outcome relationship (via the link function) was either linear or non-linear. Given the utility of covariate adjustment for addressing missing data, we also considered settings with complete or missing outcome data. Analysis methods included linear or logistic regression with no adjustment for the stratification variable, adjustment for randomisation categories, or adjustment for continuous values assuming a linear covariate-outcome relationship or allowing for non-linearity using fractional polynomials or restricted cubic splines. Unadjusted analysis performed poorly throughout. Adjustment approaches that misspecified the underlying covariate-outcome relationship were less powerful and, alarmingly, biased in settings where the stratification variable predicted missing outcome data. Adjustment for randomisation categories tends to involve the highest degree of misspecification, and so should be avoided in practice. To guard against misspecification, we recommend use of flexible approaches such as fractional polynomials and restricted cubic splines when adjusting for continuous stratification variables in randomised trials.

Many clinical trials involve partially clustered data, where some observations belong to a cluster and others can be considered independent. For example, neonatal trials may include infants from single or multiple births. Sample size and analysis methods for these trials have received limited attention. A simulation study was conducted to (1) assess whether existing power formulas based on generalized estimating equations (GEEs) provide an adequate approximation to the power achieved by mixed effects models, and (2) compare the performance of mixed models vs GEEs in estimating the effect of treatment on a continuous outcome. We considered clusters that exist prior to randomization with a maximum cluster size of 2, three methods of randomizing the clustered observations, and simulated datasets with uninformative cluster size and the sample size required to achieve 80% power according to GEE-based formulas with an independence or exchangeable working correlation structure. The empirical power of the mixed model approach was close to the nominal level when sample size was calculated using the exchangeable GEE formula, but was often too high when the sample size was based on the independence GEE formula. The independence GEE always converged and performed well in all scenarios. Performance of the exchangeable GEE and mixed model was also acceptable under cluster randomization, though under-coverage and inflated type I error rates could occur with other methods of randomization. Analysis of partially clustered trials using GEEs with an independence working correlation structure may be preferred to avoid the limitations of mixed models and exchangeable GEEs.

AIM:The role of fetal vitamin D [25-hydroxyvitamin D (25(OH)D)], one of the nuclear steroid transcription regulators, and brain development is unclear. We previously found a weak but persistent association between cord blood 25(OH)D and child language abilities at 18 months and 4 years of age, but no association with cognition or behaviour. The aim of this study was to investigate the association between cord blood 25(OH)D and a range of neurodevelopmental outcomes in these same children at 7 years of age. METHODS:Cord blood samples from 250 Australian mother-child pairs were analysed for 25(OH)D by mass spectroscopy. Children underwent tests of cognition, language, academic abilities and executive functions with a trained assessor at 7 years of age. Caregivers completed questionnaires to rate their child's behaviour and executive functioning in the home environment. Associations between standardised 25(OH)D and outcomes were assessed using regression models, taking into account possible social and demographic confounders. RESULTS:Standardised 25(OH)D in cord blood was not associated with any test or parent-rated scores. Nor was there any association with the risk of having a poor test or parent-rated score. Likewise, cord blood 25(OH)D categorised as <25, 25-50 and >50 nmol/L was not associated with test scores or parent-rated scores. CONCLUSIONS:There was no evidence that cord blood vitamin D concentration or deficiency was associated with cognition, language, academic abilities, executive functioning or behaviour at 7 years of age.

Introduction Milk fat globule membrane (MFGM) is a complex lipid–protein structure in mammalian milk and human milk that is largely absent from breastmilk substitutes. The objective of this trial is to investigate whether providing infant formula enriched with MFGM versus standard infant formula improves cognitive development at 12 months of age in exclusively formula-fed full-term infants.Methods and analysis This is a randomised, controlled, clinician-blinded, researcher-blinded and participant-blinded trial of two parallel formula-fed groups and a breastfed reference group that were recruited in the suburban Adelaide (Australia) community by a single study centre (a medical research institute). Healthy, exclusively formula-fed, singleton, term-born infants under 8 weeks of age were randomised to either an MFGM-supplemented formula (intervention) or standard infant formula (control) from enrolment until 12 months of age. The reference group was not provided with formula. The primary outcome is the Cognitive Scale of the Bayley Scales of Infant Development, Fourth Edition (Bayley-IV) at 12 months. Secondary outcomes are the Bayley-IV Cognitive Scale at 24 months, other Bayley-IV domains (language, motor, emotional and behavioural development) at 12 and 24 months of age, infant attention at 4 and 9 months of age, parent-rated language at 12 and 24 months of age, parent-rated development at 6 and 18 months of age as well as growth, tolerance and safety of the study formula. To ensure at least 80% power to detect a 5-point difference in the mean Bayley-IV cognitive score, >200 infants were recruited in each group.Ethics and dissemination The Women’s and Children Health Network Human Research Ethics Committee reviewed and approved the study (HREC/19/WCHN/140). Caregivers gave written informed consent prior to enrolling in the trial. Findings of this study will be disseminated through peer-reviewed publications and conference presentations.Trial registration number ACTRN12620000552987; Australian and New Zealand Clinical Trial Registry: anzctr.org.au.

Objectives We aimed to compare the effects of nutrient-enriched formula with standard term formula on rate of body weight gain of late preterm infants appropriately grown for gestational age. Study design A multi-center, randomized, controlled trial. Late preterm infants (34–37 weeks' gestation), with weight appropriate for gestational age (AGA), were randomized to nutrient enriched formula (NEF) with increased calories (22 kcal/30 ml) from protein, added bovine milk fat globule membrane, vitamin D and butyrate or standard term formula 20 kcal/30 ml (STF). Breastfed term infants were enrolled as an observational reference group (BFR). Primary outcome was rate of body weight gain from enrollment to 120 days corrected age (d/CA). Planned sample size was 100 infants per group. Secondary outcomes included body composition, weight, head circumference and length gain, and medically confirmed adverse events to 365 d/CA. Results The trial was terminated early due to recruitment challenges and sample size was substantially reduced. 40 infants were randomized to NEF ( n = 22) and STF ( n = 18). 39 infants were enrolled in the BFR group. At 120 d/CA there was no evidence of a difference in weight gain between randomized groups (mean difference 1.77 g/day, 95% CI, −1.63 to 5.18, P = 0.31). Secondary outcomes showed a significant reduction in risk of infectious illness in the NEF group at 120 d/CA [relative risk 0.37 (95% CI, 0.16–0.85), P = 0.02]. Conclusion We saw no difference in rate of body weight gain between AGA late preterm infants fed NEF compared to STF. Results should be interpreted with caution due to small sample size. Clinical Trial Registration The Australia New Zealand Clinical Trials Registry (ACTRN 12618000092291). “mailto:maria.makrides@sahmri.com” maria.makrides@sahmri.com .