Randomized Trial of BCG Vaccine to Protect against Covid-19 in Health Care Workers.

BACKGROUND: The bacille Calmette-Guérin (BCG) vaccine has immunomodulatory "off-target" effects that have been hypothesized to protect against coronavirus disease 2019 (Covid-19). METHODS: In this international, double-blind, placebo-controlled trial, we randomly assigned health care workers to receive the BCG-Denmark vaccine or saline placebo and followed them for 12 months. Symptomatic Covid-19 and severe Covid-19, the primary outcomes, were assessed at 6 months; the primary analyses involved the modified intention-to-treat population, which was restricted to participants with a negative test for severe acute respiratory syndrome coronavirus 2 at baseline. RESULTS: A total of 3988 participants underwent randomization; recruitment ceased before the planned sample size was reached owing to the availability of Covid-19 vaccines. The modified intention-to-treat population included 84.9% of the participants who underwent randomization: 1703 in the BCG group and 1683 in the placebo group. The estimated risk of symptomatic Covid-19 by 6 months was 14.7% in the BCG group and 12.3% in the placebo group (risk difference, 2.4 percentage points; 95% confidence interval [CI], -0.7 to 5.5; P = 0.13). The risk of severe Covid-19 by 6 months was 7.6% in the BCG group and 6.5% in the placebo group (risk difference, 1.1 percentage points; 95% CI, -1.2 to 3.5; P = 0.34); the majority of participants who met the trial definition of severe Covid-19 were not hospitalized but were unable to work for at least 3 consecutive days. In supplementary and sensitivity analyses that used less conservative censoring rules, the risk differences were similar but the confidence intervals were narrower. There were five hospitalizations due to Covid-19 in each group (including one death in the placebo group). The hazard ratio for any Covid-19 episode in the BCG group as compared with the placebo group was 1.23 (95% CI, 0.96 to 1.59). No safety concerns were identified. CONCLUSIONS: Vaccination with BCG-Denmark did not result in a lower risk of Covid-19 among health care workers than placebo. (Funded by the Bill and Melinda Gates Foundation and others; BRACE ClinicalTrials.gov number, NCT04327206.).

Handling missing data when estimating causal effects with targeted maximum likelihood estimation.

Targeted maximum likelihood estimation (TMLE) is increasingly used for doubly robust causal inference, but how missing data should be handled when using TMLE with data-adaptive approaches is unclear. Based on data (1992-1998) from the Victorian Adolescent Health Cohort Study, we conducted a simulation study to evaluate 8 missing-data methods in this context: complete-case analysis, extended TMLE incorporating an outcome-missingness model, the missing covariate missing indicator method, and 5 multiple imputation (MI) approaches using parametric or machine-learning models. We considered 6 scenarios that varied in terms of exposure/outcome generation models (presence of confounder-confounder interactions) and missingness mechanisms (whether outcome influenced missingness in other variables and presence of interaction/nonlinear terms in missingness models). Complete-case analysis and extended TMLE had small biases when outcome did not influence missingness in other variables. Parametric MI without interactions had large bias when exposure/outcome generation models included interactions. Parametric MI including interactions performed best in bias and variance reduction across all settings, except when missingness models included a nonlinear term. When choosing a method for handling missing data in the context of TMLE, researchers must consider the missingness mechanism and, for MI, compatibility with the analysis method. In many settings, a parametric MI approach that incorporates interactions and nonlinearities is expected to perform well.

Short-term outcomes in infants following general anesthesia with low-dose sevoflurane/dexmedetomidine/remifentanil versus standard dose sevoflurane (The TREX trial).

BACKGROUND: The TREX (Trial Remifentanil DEXmedetomidine) trial aimed to determine if, in children < 2 years old, low-dose sevoflurane/dexmedetomidine/remifentanil anesthesia (LD-SEVO) is superior to standard dose sevoflurane (STD-SEVO) anesthesia in terms of global cognitive function at 3 years of age. The aim of the present secondary analyses was to compare incidence of intraoperative hypotension and bradycardia, postoperative pain, time to recovery, need for treatment of intraoperative hypotension and bradycardia, incidence of light anesthesia and need for treatment, need for postoperative pain medications, and morbidity and mortality outcomes at 5 days between the two arms. METHODS: This Phase III randomized active controlled, parallel group, assessor blinded, multicenter, superiority trial was performed in 20 centers in Australia, Italy, and the United States. Four hundred and fifty-five infants <2 years of age expected to undergo general anesthesia for at least 2 hours were enrolled. They were randomized between LD-SEVO and STD-SEVO. The short-term perioperative outcomes noted above were compared between these two groups. RESULTS: There was less hypotension (risk difference -11.6%, 95% confidence interval (CI) -18.9% to -4.3%) and more bradycardia (risk difference 18.2%, 95% CI 8.8% to 27.7%) in the LD-SEVO compared to the STD-SEVO arm. There were more patients with episodes of light anesthesia (89 vs. 4), and protocol abandonments (1 vs. 0) in the LD-SEVO arm. Time from eye-opening to Post Anesthesia Care Unit (PACU) discharge was similar in both arms, as were morbidity and mortality. One patient in each arm suffered a life-threatening event but neither suffered long-term sequelae. CONCLUSIONS: These early postoperative results suggest that in children less than 2 years of age receiving greater than 2 hours of general anesthesia, the low-dose sevoflurane/dexmedetomidine/remifentanil anesthesia technique and the standard sevoflurane anesthesia technique are broadly clinically similar, with no clear evidence to support choosing one technique over the other.

Overcoming aggregation with laser heated nanoelectrospray mass spectrometry: thermal stability and pathways for loss of bicarbonate from carbonic anhydrase II.

Variable temperature electrospray mass spectrometry is useful for multiplexed measurements of the thermal stabilities of biomolecules, but the ionization process can be disrupted by aggregation-prone proteins/complexes that have irreversible unfolding transitions. Resistively heating solutions containing a mixture of bovine carbonic anhydrase II (BCAII), a CO2 fixing enzyme involved in many biochemical pathways, and cytochrome c leads to complete loss of carbonic anhydrase signal and a significant reduction in cytochrome c signal above ∼72 °C due to aggregation. In contrast, when the tips of borosilicate glass nanoelectrospray emitters are heated with a laser, complete thermal denaturation curves for both proteins are obtained in <1 minute. The simultaneous measurements of the melting temperature of BCAII and BCAII bound to bicarbonate reveal that the bicarbonate stabilizes the folded form of this protein by ∼6.4 °C. Moreover, the temperature dependences of different bicarbonate loss pathways are obtained. Although protein analytes are directly heated by the laser for only 140 ms, heat conduction further up the emitter leads to a total analyte heating time of ∼41 s. Pulsed laser heating experiments could reduce this time to ∼0.5 s for protein aggregation that occurs on a faster time scale. Laser heating provides a powerful method for studying the detailed mechanisms of cofactor/ligand loss with increasing temperature and promises a new tool for studying the effect of ligands, drugs, growth conditions, buffer additives, or other treatments on the stabilities of aggregation-prone biomolecules.

Gaps in the usage and reporting of multiple imputation for incomplete data: findings from a scoping review of observational studies addressing causal questions.

BACKGROUND: Missing data are common in observational studies and often occur in several of the variables required when estimating a causal effect, i.e. the exposure, outcome and/or variables used to control for confounding. Analyses involving multiple incomplete variables are not as straightforward as analyses with a single incomplete variable. For example, in the context of multivariable missingness, the standard missing data assumptions ("missing completely at random", "missing at random" [MAR], "missing not at random") are difficult to interpret and assess. It is not clear how the complexities that arise due to multivariable missingness are being addressed in practice. The aim of this study was to review how missing data are managed and reported in observational studies that use multiple imputation (MI) for causal effect estimation, with a particular focus on missing data summaries, missing data assumptions, primary and sensitivity analyses, and MI implementation. METHODS: We searched five top general epidemiology journals for observational studies that aimed to answer a causal research question and used MI, published between January 2019 and December 2021. Article screening and data extraction were performed systematically. RESULTS: Of the 130 studies included in this review, 108 (83%) derived an analysis sample by excluding individuals with missing data in specific variables (e.g., outcome) and 114 (88%) had multivariable missingness within the analysis sample. Forty-four (34%) studies provided a statement about missing data assumptions, 35 of which stated the MAR assumption, but only 11/44 (25%) studies provided a justification for these assumptions. The number of imputations, MI method and MI software were generally well-reported (71%, 75% and 88% of studies, respectively), while aspects of the imputation model specification were not clear for more than half of the studies. A secondary analysis that used a different approach to handle the missing data was conducted in 69/130 (53%) studies. Of these 69 studies, 68 (99%) lacked a clear justification for the secondary analysis. CONCLUSION: Effort is needed to clarify the rationale for and improve the reporting of MI for estimation of causal effects from observational data. We encourage greater transparency in making and reporting analytical decisions related to missing data.

Electronic Structure and Photophysics of Low Spin d5 Metallocenes.

The electronic structure and photophysics of two low spin metallocenes, decamethylmanganocene (MnCp*2) and decamethylrhenocene (ReCp*2), were investigated to probe their promise as photoredox reagents. Computational studies support the assignment of 2E2 ground state configurations and low energy ligand-to-metal charge transfer transitions for both complexes. Weak emission is observed at room temperature for ReCp*2 with τ = 1.8 ns in pentane, whereas MnCp*2 is not emissive. Calculation of the excited state reduction potentials for both metallocenes reveal their potential potency as excited state reductants (E°'([MnCp*2]+/0*) = -3.38 V and E°'([ReCp*2]+/0*) = -2.61 V vs Fc+/0). Comparatively, both complexes exhibit mild potentials for photo-oxidative processes (E°'([MnCp*2]0*/-) = -0.18 V and E°'([ReCp*2]0*/-) = -0.20 V vs Fc+/0). These results showcase the rich electronic structure of low spin d5 metallocenes and their promise as excited state reductants.

Advancing randomized controlled trial methodologies: The place of innovative trial design in eating disorders research.

Randomized controlled trials can be used to generate evidence on the efficacy and safety of new treatments in eating disorders research. Many of the trials previously conducted in this area have been deemed to be of low quality, in part due to a number of practical constraints. This article provides an overview of established and more innovative clinical trial designs, accompanied by pertinent examples, to highlight how design choices can enhance flexibility and improve efficiency of both resource allocation and participant involvement. Trial designs include individually randomized, cluster randomized, and designs with randomizations at multiple time points and/or addressing several research questions (master protocol studies). Design features include the use of adaptations and considerations for pragmatic or registry-based trials. The appropriate choice of trial design, together with rigorous trial conduct, reporting and analysis, can establish high-quality evidence to advance knowledge in the field. It is anticipated that this article will provide a broad and contemporary introduction to trial designs and will help researchers make informed trial design choices for improved testing of new interventions in eating disorders. PUBLIC SIGNIFICANCE: There is a paucity of high quality randomized controlled trials that have been conducted in eating disorders, highlighting the need to identify where efficiency gains in trial design may be possible to advance the eating disorder research field. We provide an overview of some key trial designs and features which may offer solutions to practical constraints and increase trial efficiency.

Recoverability and estimation of causal effects under typical multivariable missingness mechanisms.

In the context of missing data, the identifiability or "recoverability" of the average causal effect (ACE) depends not only on the usual causal assumptions but also on missingness assumptions that can be depicted by adding variable-specific missingness indicators to causal diagrams, creating missingness directed acyclic graphs (m-DAGs). Previous research described canonical m-DAGs, representing typical multivariable missingness mechanisms in epidemiological studies, and examined mathematically the recoverability of the ACE in each case. However, this work assumed no effect modification and did not investigate methods for estimation across such scenarios. Here, we extend this research by determining the recoverability of the ACE in settings with effect modification and conducting a simulation study to evaluate the performance of widely used missing data methods when estimating the ACE using correctly specified g-computation. Methods assessed were complete case analysis (CCA) and various implementations of multiple imputation (MI) with varying degrees of compatibility with the outcome model used in g-computation. Simulations were based on an example from the Victorian Adolescent Health Cohort Study (VAHCS), where interest was in estimating the ACE of adolescent cannabis use on mental health in young adulthood. We found that the ACE is recoverable when no incomplete variable (exposure, outcome, or confounder) causes its own missingness, and nonrecoverable otherwise, in simplified versions of 10 canonical m-DAGs that excluded unmeasured common causes of missingness indicators. Despite this nonrecoverability, simulations showed that MI approaches that are compatible with the outcome model in g-computation may enable approximately unbiased estimation across all canonical m-DAGs considered, except when the outcome causes its own missingness or causes the missingness of a variable that causes its own missingness. In the latter settings, researchers may need to consider sensitivity analysis methods incorporating external information (e.g., delta-adjustment methods). The VAHCS case study illustrates the practical implications of these findings.

A comparison of strategies for selecting auxiliary variables for multiple imputation.

Multiple imputation (MI) is a popular method for handling missing data. Auxiliary variables can be added to the imputation model(s) to improve MI estimates. However, the choice of which auxiliary variables to include is not always straightforward. Several data-driven auxiliary variable selection strategies have been proposed, but there has been limited evaluation of their performance. Using a simulation study we evaluated the performance of eight auxiliary variable selection strategies: (1, 2) two versions of selection based on correlations in the observed data; (3) selection using hypothesis tests of the "missing completely at random" assumption; (4) replacing auxiliary variables with their principal components; (5, 6) forward and forward stepwise selection; (7) forward selection based on the estimated fraction of missing information; and (8) selection via the least absolute shrinkage and selection operator (LASSO). A complete case analysis and an MI analysis using all auxiliary variables (the "full model") were included for comparison. We also applied all strategies to a motivating case study. The full model outperformed all auxiliary variable selection strategies in the simulation study, with the LASSO strategy the best performing auxiliary variable selection strategy overall. All MI analysis strategies that we were able to apply to the case study led to similar estimates, although computational time was substantially reduced when variable selection was employed. This study provides further support for adopting an inclusive auxiliary variable strategy where possible. Auxiliary variable selection using the LASSO may be a promising alternative when the full model fails or is too burdensome.

Mental health in young adults born extremely preterm or extremely low birthweight with contemporary neonatal intensive care.

BACKGROUND: For infants born in the contemporary era of neonatal care, little is known about adult mental health outcomes of extremely preterm birth (EP; <28 weeks' gestation) or extremely low birthweight (ELBW; <1000 g). This study aimed to compare attention deficit hyperactivity disorder (ADHD), anxiety, mood, and substance use disorder prevalence in young adults born EP/ELBW and normal birthweight (NBW; >2499 g) controls, and to compare change in prevalence of mental health symptoms and disorders from 18 to 25 years. METHODS: Participants were a prospective geographical cohort of 297 consecutive survivors born EP/ELBW during 1991-1992 and 260 NBW controls. At age 25 years, 174 EP/ELBW and 139 NBW participants completed the Adult ADHD Rating Scale, Structured Clinical Interview for DSM-IV Disorders, Beck Anxiety Inventory, and Center for Epidemiologic Studies Depression Scale-Revised. Data from follow-up at 18 years were also utilized. Multiple imputation was used to account for attrition. RESULTS: Mental health outcomes at 25 years were similar between groups: prevalence rates were ADHD 7% v. 5%; anxiety 32% v. 27%; mood 38% v. 35%; substance use 12% v. 14% in the EP/ELBW and NBW groups, respectively. In both groups, ADHD declined between 18 and 25 years [odds ratio (OR) per year = 0.87, 95% confidence interval (CI) 0.79-0.95], and generalized anxiety disorder and major depressive episode became more common (OR 1.22, 95% CI 1.10-1.35 per year; OR 1.20, 95% CI 1.10-1.30 respectively). CONCLUSIONS: This contemporary EP/ELBW cohort has comparable young adult mental health outcomes to controls, and similar patterns of change in mental health from late adolescence.

Umbilical Cord Blood Cell Clearance Post-Infusion in Immune-Competent Children with Cerebral Palsy.

Umbilical cord blood cells have therapeutic potential for neurological disorders, through a paracrine mechanism of action. A greater understanding of the safety and immunological effects of allogeneic donor cord blood cells in the context of a healthy recipient immune system, such as in cerebral palsy, is needed. This study aimed to determine how quickly donor cord blood cells were cleared from the circulation in children with cerebral palsy who received a single intravenous infusion of 12/12 human leucocyte antigen (HLA)-matched sibling cord blood cells. Twelve participants with cerebral palsy aged 2-12 years received cord blood cell infusions as part of a phase I trial of umbilical blood infusion for cerebral palsy. Digital droplet PCR analysis of DNA copy number variants specific to donor and recipient was used to assess donor DNA clearance at five timepoints post-infusion, a surrogate measure of cell clearance. Donor cells were cleared by 3 months post-infusion in 11/12 participants. When detected, donor DNA was at a fraction of 0.01-0.31% of total DNA with no signs of graft-versus-host disease in any participant. The donor DNA clearance times provided by this study have important implications for understanding the safety of allogeneic cord blood cell infusion for cerebral palsy and translational tissue engineering or regenerative medicine research in other disorders.

TreEAT trial: Protocol for a randomized controlled trial investigating the efficacy and safety of early introduction of tree nuts for the prevention of tree nut allergy in infants with peanut allergy.

INTRODUCTION: Children with peanut allergy are at increased risk of developing tree nut allergies, which can be severe and for most lifelong. Introduction of peanut in the first year of life can reduce the risk of peanut allergy; however, prevention strategies for tree nut allergies have not been established. We aimed to test the efficacy and safety of a novel strategy, a supervised multi-nut oral food challenge (OFC) compared with standard care for tree nut allergy prevention in infants at high risk of developing tree nut allergy, TreEAT. METHODS AND ANALYSIS: TreEAT is a 2-armed, open-label, randomized, controlled trial (RCT). Infants (n = 212) aged 4-11 months with peanut allergy will be randomized 1:1 at peanut allergy diagnosis to either a hospital-based multi-tree nut (almond, cashew, hazelnut, and walnut) OFC using multi-nut butter or standard care (home introduction of individual tree nuts). All infants will be assessed at age 18 months, with questionnaires and SPT to peanut and tree nuts. Peanut and tree nut OFCs will be performed as required to determine the allergy status for each nut. The primary outcome is tree nut allergy at age 18 months. Secondary outcomes include peanut allergy resolution, proportion, and severity of adverse events related to tree nut ingestion, number and frequency of tree nuts ingested, quality of life and parental anxiety, and allergy-related healthcare visits from randomization to 18 months of age. Analyses will be performed on an intention-to-treat basis. ETHICS AND DISSEMINATION: TreEAT was approved by the Royal Children's Hospital Human Research Ethics Committee (#70489). Outcomes will be presented at scientific conferences and disseminated through publication. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov ID: NCT04801823.

Handling misclassified stratification variables in the analysis of randomised trials with continuous outcomes.

Many trials use stratified randomisation, where participants are randomised within strata defined by one or more baseline covariates. While it is important to adjust for stratification variables in the analysis, the appropriate method of adjustment is unclear when stratification variables are affected by misclassification and hence some participants are randomised in the incorrect stratum. We conducted a simulation study to compare methods of adjusting for stratification variables affected by misclassification in the analysis of continuous outcomes when all or only some stratification errors are discovered, and when the treatment effect or treatment-by-covariate interaction effect is of interest. The data were analysed using linear regression with no adjustment, adjustment for the strata used to perform the randomisation (randomisation strata), adjustment for the strata if all errors are corrected (true strata), and adjustment for the strata after some errors are discovered and corrected (updated strata). The unadjusted model performed poorly in all settings. Adjusting for the true strata was optimal, while the relative performance of adjusting for the randomisation strata or the updated strata varied depending on the setting. As the true strata are unlikely to be known with certainty in practice, we recommend using the updated strata for adjustment and performing subgroup analyses, provided the discovery of errors is unlikely to depend on treatment group, as expected in blinded trials. Greater transparency is needed in the reporting of stratification errors and how they were addressed in the analysis.

On the use of multiple imputation to address data missing by design as well as unintended missing data in case-cohort studies with a binary endpoint.

BACKGROUND: Case-cohort studies are conducted within cohort studies, with the defining feature that collection of exposure data is limited to a subset of the cohort, leading to a large proportion of missing data by design. Standard analysis uses inverse probability weighting (IPW) to address this intended missing data, but little research has been conducted into how best to perform analysis when there is also unintended missingness. Multiple imputation (MI) has become a default standard for handling unintended missingness and is typically used in combination with IPW to handle the intended missingness due to the case-control sampling. Alternatively, MI could be used to handle both the intended and unintended missingness. While the performance of an MI-only approach has been investigated in the context of a case-cohort study with a time-to-event outcome, it is unclear how this approach performs with a binary outcome. METHODS: We conducted a simulation study to assess and compare the performance of approaches using only MI, only IPW, and a combination of MI and IPW, for handling intended and unintended missingness in the case-cohort setting. We also applied the approaches to a case study. RESULTS: Our results show that the combined approach is approximately unbiased for estimation of the exposure effect when the sample size is large, and was the least biased with small sample sizes, while MI-only and IPW-only exhibited larger biases in both sample size settings. CONCLUSIONS: These findings suggest that a combined MI/IPW approach should be preferred to handle intended and unintended missing data in case-cohort studies with binary outcomes.

Should multiple imputation be stratified by exposure group when estimating causal effects via outcome regression in observational studies?

BACKGROUND: Despite recent advances in causal inference methods, outcome regression remains the most widely used approach for estimating causal effects in epidemiological studies with a single-point exposure and outcome. Missing data are common in these studies, and complete-case analysis (CCA) and multiple imputation (MI) are two frequently used methods for handling them. In randomised controlled trials (RCTs), it has been shown that MI should be conducted separately by treatment group. In observational studies, causal inference is now understood as the task of emulating an RCT, which raises the question of whether MI should be conducted by exposure group in such studies. METHODS: We addressed this question by evaluating the performance of seven methods for handling missing data when estimating causal effects with outcome regression. We conducted an extensive simulation study based on an illustrative case study from the Victorian Adolescent Health Cohort Study, assessing a range of scenarios, including seven outcome generation models with exposure-confounder interactions of differing strength. RESULTS: The simulation results showed that MI by exposure group led to the least bias when the size of the smallest exposure group was relatively large, followed by MI approaches that included the exposure-confounder interactions. CONCLUSIONS: The findings from our simulation study, which was designed based on a real case study, suggest that current practice for the conduct of MI in causal inference may need to shift to stratifying by exposure group where feasible, or otherwise including exposure-confounder interactions in the imputation model.

Parental Mental Health and Parenting Behaviors Following Very Preterm Birth: Associations in Mothers and Fathers and Implications for Child Cognitive Outcome.

OBJECTIVES: To investigate the longitudinal associations between parental mental health symptoms within 4 weeks of birth, parenting behaviors at 1 year, and child general cognitive ability at 4.5-5 years in a sample of children born very preterm (VP). This study also examined whether these associations differed based on level of family social risk. METHODS: Participants were 143 children born <30 weeks' gestation and their parents. Within 4 weeks of birth, mothers' and fathers' depressive and anxiety symptoms were assessed using the Center for Epidemiologic Studies Depression Scale and Hospital Anxiety Depression Scale-Anxiety Subscale. Parents' sensitive and structuring parenting behaviors were assessed at 1 year using the Emotional Availability Scales. Child general cognitive ability was assessed at 4.5-5 years using the Wechsler Preschool & Primary Scale of Intelligence-Fourth Edition. RESULTS: Higher maternal depressive symptoms were associated with lower levels of sensitive and structuring parenting behavior, while higher maternal anxiety symptoms were associated with higher levels of structuring parenting behavior. There was weak evidence for positive associations between mothers' sensitive parenting behavior and fathers' structuring parenting behavior and child general cognitive ability. There was also weak evidence for stronger associations between mothers' mental health symptoms, parenting behaviors, and child general cognitive ability, in families of higher compared with lower social risk. CONCLUSIONS: Depressive and anxiety symptoms experienced by mothers in the initial weeks following VP birth can have long-term effects on their parenting behaviors. Enquiring about parents' mental health during their child's hospitalization in the neonatal intensive care unit is crucial.

Parenting and Neurobehavioral Outcomes in Children Born Moderate-to-Late Preterm and at Term.

OBJECTIVES: To compare the parenting environment and the relationships between parenting behaviors and concurrent child neurobehavioral outcomes at 2 years of corrected age between children born moderate-to-late preterm (MLP; 32-36 weeks of gestation) and at term (≥37 weeks of gestation). STUDY DESIGN: Participants were 129 children born MLP and 110 children born at term and their mothers. Mothers' parenting behaviors (sensitivity, structuring, nonintrusiveness, nonhostility) were assessed at 2 years of corrected age using the Emotional Availability Scales. Child cognitive and language development were assessed using the Bayley Scales of Infant and Toddler Development, and social-emotional competence using the Infant Toddler Social and Emotional Assessment. RESULTS: Mothers of children born MLP and at term displayed similar parenting behaviors overall, with slightly lower nonintrusiveness in mothers of children born MLP (adjusted mean difference -0.32 [-0.60, -0.04]; P = .03). In both groups of children, greater maternal sensitivity was associated with better cognitive development (P < .001 MLP; P = .02 term), increased maternal structuring was associated with better social-emotional competence (P = .02 MLP; P = .03 term), and higher maternal nonintrusiveness was associated with better cognitive, language, and social-emotional outcomes (all P < .04). Greater maternal sensitivity and structuring were associated with better language development in children born MLP but not in children born at term. CONCLUSIONS: Parenting behaviors are important for neurobehavioral outcomes in children born MLP and at term. Language development may be more strongly influenced by select parenting behaviors in children born MLP compared with children born at term.

Safety of sibling cord blood cell infusion for children with cerebral palsy.

Cerebral palsy (CP) is a nonprogressive neurological disorder and the most common physical disability of childhood. There is no cure for CP, but stem cells have the potential to improve brain injury and hence function. This phase 1 clinical trial investigated the safety of the intravenous infusion of full-matched sibling cord blood cells for children with CP aged 1 to 16 years. Preliminary efficacy outcomes were also investigated. Twelve participants received 12/12 HLA-matched sibling cord blood cell infusions. One treatable serious adverse reaction to cryoprotectant was observed, and no adverse reactions occurred beyond 24 h after infusion. Gross motor function measure (GMFM-66) scores did not improve compared with baseline beyond what could be expected from developmental levels, and participants had varied changes in the Quality of Upper Extremity Skills Test (QUEST) and Vineland Adaptive Behavior Scales (VABS-II) scores. In conclusion, matched sibling cord blood cell infusion for children with CP is relatively safe when conducted in an appropriate facility. Australian and New Zealand Clinical Trials Registry (ACTRN12616000403437) and Clinicaltrials.gov (NCT03087110).

Evaluation of multiple imputation approaches for handling missing covariate information in a case-cohort study with a binary outcome.

BACKGROUND: In case-cohort studies a random subcohort is selected from the inception cohort and acts as the sample of controls for several outcome investigations. Analysis is conducted using only the cases and the subcohort, with inverse probability weighting (IPW) used to account for the unequal sampling probabilities resulting from the study design. Like all epidemiological studies, case-cohort studies are susceptible to missing data. Multiple imputation (MI) has become increasingly popular for addressing missing data in epidemiological studies. It is currently unclear how best to incorporate the weights from a case-cohort analysis in MI procedures used to address missing covariate data. METHOD: A simulation study was conducted with missingness in two covariates, motivated by a case study within the Barwon Infant Study. MI methods considered were: using the outcome, a proxy for weights in the simple case-cohort design considered, as a predictor in the imputation model, with and without exposure and covariate interactions; imputing separately within each weight category; and using a weighted imputation model. These methods were compared to a complete case analysis (CCA) within the context of a standard IPW analysis model estimating either the risk or odds ratio. The strength of associations, missing data mechanism, proportion of observations with incomplete covariate data, and subcohort selection probability varied across the simulation scenarios. Methods were also applied to the case study. RESULTS: There was similar performance in terms of relative bias and precision with all MI methods across the scenarios considered, with expected improvements compared with the CCA. Slight underestimation of the standard error was seen throughout but the nominal level of coverage (95%) was generally achieved. All MI methods showed a similar increase in precision as the subcohort selection probability increased, irrespective of the scenario. A similar pattern of results was seen in the case study. CONCLUSIONS: How weights were incorporated into the imputation model had minimal effect on the performance of MI; this may be due to case-cohort studies only having two weight categories. In this context, inclusion of the outcome in the imputation model was sufficient to account for the unequal sampling probabilities in the analysis model.

Development of regional brain gray matter volume across the first 13 years of life is associated with childhood math computation ability for children born very preterm and full term.

Very preterm birth (VP; <32 weeks' gestation) is associated with altered brain gray matter development and lower math ability. In typically developing children, the neural correlates of math ability may change dynamically with age, though evidence in VP children is limited. In a prospective longitudinal cohort of children born VP and full term (FT), we aimed to investigate associations between 1) concurrent regional brain volumes and math ability at 7 (n = 148 VP; n = 34 FT) and 13-years (n = 130 VP; n = 46 FT), and 2) regional volumetric growth across childhood (term-equivalent age (TEA) to 7-years; 7 to 13-years) and math ability from 7 to 13-years, and improvement in ability from 7 to 13 years. For both aims we investigated whether associations differed between birth groups. Cross-sectionally, frontal, temporal and subcortical regional volumes were positively associated with math ability for both birth groups. For FT children, greater growth of specific temporal regions was associated with higher math ability, and greater improvements. For VP children, similar associations were only observed for growth from TEA to 7-years with 13-year ability and improvements in ability. In conclusion, VP birth appears to alter associations of brain development across the first 13 years with childhood math ability.