Associations with early vomiting when using intranasal fentanyl and nitrous oxide for procedural sedation in children: A secondary analysis of a randomised controlled trial.

OBJECTIVE: Intranasal (IN) fentanyl and nitrous oxide (N2O) can be combined to provide procedural sedation and analgesia to children. This combination is advantageous because of rapid onset of action and non-parenteral administration, but is associated with increased vomiting. We sought to describe the associations of demographic and procedural factors with early vomiting when using this combination in children. METHODS: This was a planned secondary analysis of a randomised controlled trial comparing the effect of oral ondansetron versus placebo at a single paediatric hospital. Children aged 3 to <18 years with planned procedural sedation with IN fentanyl and N2O were randomised to receive oral ondansetron or placebo prior to N2O administration. Vomiting was defined as early if occurring during or up to 1 h after N2O delivery. We assessed the relationship between early vomiting, demographic and procedural characteristics. RESULTS: Participants were recruited between October 2016 and January 2019 and 62 out of 436 (14%) had early vomiting. The risk of early vomiting was 30% higher with higher total dose of fentanyl, risk ratio = 1.3 (95% confidence interval = 1.004-1.59). There was little evidence of a relationship between the occurrence of early vomiting and sex, age, weight, type of procedure, fasting duration, time between fentanyl administration and start of procedure, and procedure duration. CONCLUSION: We found that higher doses of IN fentanyl were associated with higher risk of early vomiting when administered with N2O in children. Other factors did not appear to be associated with vomiting.

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.

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.

Initial data analysis for longitudinal studies to build a solid foundation for reproducible analysis.

Initial data analysis (IDA) is the part of the data pipeline that takes place between the end of data retrieval and the beginning of data analysis that addresses the research question. Systematic IDA and clear reporting of the IDA findings is an important step towards reproducible research. A general framework of IDA for observational studies includes data cleaning, data screening, and possible updates of pre-planned statistical analyses. Longitudinal studies, where participants are observed repeatedly over time, pose additional challenges, as they have special features that should be taken into account in the IDA steps before addressing the research question. We propose a systematic approach in longitudinal studies to examine data properties prior to conducting planned statistical analyses. In this paper we focus on the data screening element of IDA, assuming that the research aims are accompanied by an analysis plan, meta-data are well documented, and data cleaning has already been performed. IDA data screening comprises five types of explorations, covering the analysis of participation profiles over time, evaluation of missing data, presentation of univariate and multivariate descriptions, and the depiction of longitudinal aspects. Executing the IDA plan will result in an IDA report to inform data analysts about data properties and possible implications for the analysis plan-another element of the IDA framework. Our framework is illustrated focusing on hand grip strength outcome data from a data collection across several waves in a complex survey. We provide reproducible R code on a public repository, presenting a detailed data screening plan for the investigation of the average rate of age-associated decline of grip strength. With our checklist and reproducible R code we provide data analysts a framework to work with longitudinal data in an informed way, enhancing the reproducibility and validity of their work.

Adaptive platform trials rather than randomised controlled trials for paediatric sepsis.

Adaptive platform trials (APTs) offer a promising alternative to traditional randomised controlled trials for evaluating treatments for paediatric sepsis. Randomised controlled trials, despite being the gold standard for establishing causality between interventions and outcomes, make many assumptions about disease prevalence, severity and intervention effects, which are often incorrect. As a result, the evidence for most treatments for paediatric sepsis are based on low-quality evidence. APTs use accrued data rather than assumptions to power trial adaptations. They can assess multiple treatments simultaneously with shared research infrastructure. As such, APTs offer a more efficient, flexible and more effective way to identify optimal treatments. The proposed Paediatric Adaptive Sepsis Platform Trial, leveraging the Paediatric Research in Emergency Departments International Collaborative network's infrastructure, will evaluate resuscitation fluids, vasoactive medications, corticosteroids and antimicrobials. This trial has the potential to substantially impact clinical practice and reduce global sepsis mortality in children.

Statistical analyses of ordinal outcomes in randomised controlled trials: a scoping review.

BACKGROUND: Randomised controlled trials (RCTs) aim to estimate the causal effect of one or more interventions relative to a control. One type of outcome that can be of interest in an RCT is an ordinal outcome, which is useful to answer clinical questions regarding complex and evolving patient states. The target parameter of interest for an ordinal outcome depends on the research question and the assumptions the analyst is willing to make. This review aimed to provide an overview of how ordinal outcomes have been used and analysed in RCTs. METHODS: The review included RCTs with an ordinal primary or secondary outcome published between 2017 and 2022 in four highly ranked medical journals (the British Medical Journal, New England Journal of Medicine, The Lancet, and the Journal of the American Medical Association) identified through PubMed. Details regarding the study setting, design, the target parameter, and statistical methods used to analyse the ordinal outcome were extracted. RESULTS: The search identified 309 studies, of which 144 were eligible for inclusion. The most used target parameter was an odds ratio, reported in 78 (54%) studies. The ordinal outcome was dichotomised for analysis in 47 ( 33 % ) studies, and the most common statistical model used to analyse the ordinal outcome on the full ordinal scale was the proportional odds model (64 [ 44 % ] studies). Notably, 86 (60%) studies did not explicitly check or describe the robustness of the assumptions for the statistical method(s) used. CONCLUSIONS: The results of this review indicate that in RCTs that use an ordinal outcome, there is variation in the target parameter and the analytical approaches used, with many dichotomising the ordinal outcome. Few studies provided assurance regarding the appropriateness of the assumptions and methods used to analyse the ordinal outcome. More guidance is needed to improve the transparent reporting of the analysis of ordinal outcomes in future trials.

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.

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.

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.

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.

Facial Function in Bell Palsy in a Cohort of Children Randomized to Prednisolone or Placebo 12 Months After Diagnosis.

BACKGROUND: Information on the medium-term recovery of children with Bell palsy or acute idiopathic lower motor neuron facial paralysis is limited. METHODS: We followed up children aged 6 months to <18 years with Bell palsy for 12 months after completion of a randomized trial on the use of prednisolone. We assessed facial function using the clinician-administered House-Brackmann scale and the modified parent-administered House-Brackmann scale. RESULTS: One hundred eighty-seven children were randomized to prednisolone (n = 93) or placebo (n = 94). At six months, the proportion of patients who had recovered facial function based on the clinician-administered House-Brackmann scale was 98% (n = 78 of 80) in the prednisolone group and 93% (n = 76 of 82) in the placebo group. The proportion of patients who had recovered facial function based on the modified parent-administered House-Brackmann scale was 94% (n = 75 of 80) vs 89% (n = 72 of 81) at six months (OR 1.88; 95% CI 0.60, 5.86) and 96% (n = 75 of 78) vs 92% (n = 73 of 79) at 12 months (OR 3.12; 95% CI 0.61, 15.98). CONCLUSIONS: Although the vast majority had complete recovery of facial function at six months, there were some children without full recovery of facial function at 12 months, regardless of prednisolone use.

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.

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.

Pain in children with Bell's palsy: secondary analysis of a randomised controlled trial.

OBJECTIVE: To describe the prevalence and severity of pain experienced by children with Bell's palsy over the first 6 months of illness and its association with the severity of facial paralysis. METHODS: This was a secondary analysis of data obtained in a phase III, triple-blinded, randomised, placebo-controlled trial of prednisolone for the treatment of Bell's palsy in children aged 6 months to <18 years conducted between 13 October 2015 and 23 August 2020 in Australia and New Zealand. Children were recruited within 72 hours of symptom onset and pain was assessed using a child-rated visual analogue scale (VAS), a child-rated Faces Pain Score-Revised (FPS-R) and/or a parent-rated VAS at baseline, and at 1, 3 and 6 months until recovered, and are reported combined across treatment groups. RESULTS: Data were available for 169 of the 187 children randomised from at least one study time point. Overall, 37% (62/169) of children reported any pain at least at one time point. The frequency of any pain reported using the child-rated VAS, child-rated FPS-R and parent-rated VAS was higher at the baseline assessment (30%, 23% and 27%, respectively) compared with 1-month (4%, 0% and 4%, respectively) and subsequent follow-up assessments. At all time points, the median pain score on all three scales was 0 (no pain). CONCLUSIONS: Pain in children with Bell's palsy was infrequent and primarily occurred early in the disease course and in more severe disease. The intensity of pain, if it occurs, is very low throughout the clinical course of disease. TRIAL REGISTRATION NUMBER: ACTRN12615000563561.

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.

Relationship Between Parental Postnatal Distress and 5-Year Mental Health Outcomes of Children Born at <30 Weeks and at Term.

OBJECTIVE: The purpose of this study was to compare mental health symptoms and diagnoses at age 5 years between children born <30 weeks' gestation and their term-born peers and associations with postnatal symptoms of depression and anxiety in their mothers and fathers. METHODS: Parents of children born <30 weeks' gestation (n = 106) and at term (n = 105) completed measures of anxiety and depression symptoms within 4 weeks of birth and questionnaires assessing child socioemotional symptoms and mental health/neurodevelopmental diagnostic criteria at age 5 years. RESULTS: At age 5 years, children born <30 weeks' gestation were more likely to show clinically concerning levels of total difficulties (odds ratio [OR] = 3.97, 95% confidence interval [CI], 1.21-13.05), emotional problems (OR = 3.71, 95% CI, 1.14-12.15), and inattention/hyperactivity problems (OR = 4.34, 95% CI, 1.51-12.47) than term-born peers. They also showed higher rates of mental health/neurodevelopmental diagnoses than their term-born peers (18% vs 9%), although evidence for the group difference was weak ( p = 0.08). Maternal postnatal anxiety and depression symptoms were related to poorer child mental health outcomes in many domains. There was little evidence that paternal postnatal anxiety/depression symptoms were related to child outcomes or that any associations varied by birth group. CONCLUSION: Children born <30 weeks' gestation showed more mental health symptoms than their term-born peers at age 5 years. Maternal postnatal distress was associated with poorer child mental health across both groups, reinforcing the need for early identification and support of mental health distress in the postnatal period to improve longer-term child well-being.

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.

Statistical analyses of ordinal outcomes in randomised controlled trials: protocol for a scoping review.

INTRODUCTION: Randomised controlled trials (RCTs) aim to assess the effect of one (or more) unproven health interventions relative to other reference interventions. RCTs sometimes use an ordinal outcome, which is an endpoint that comprises of multiple, monotonically ordered categories that are not necessarily separated by a quantifiable distance. Ordinal outcomes are appealing in clinical settings as specific disease states can represent meaningful categories that may be of clinical importance to researchers. Ordinal outcomes can also retain information and increase statistical power compared to dichotomised outcomes and can allow multiple clinical outcomes to be comprised in a single endpoint. Target parameters for ordinal outcomes in RCTs may vary depending on the nature of the research question, the modelling assumptions and the expertise of the data analyst. The aim of this scoping review is to systematically describe the use of ordinal outcomes in contemporary RCTs. Specifically, we aim to: [Formula: see text] Identify which target parameters are of interest in trials that use an ordinal outcome, and whether these parameters are explicitly defined. [Formula: see text] Describe how ordinal outcomes are analysed in RCTs to estimate a treatment effect. [Formula: see text] Describe whether RCTs that use an ordinal outcome adequately report key methodological aspects specific to the analysis of the ordinal outcome. Results from this review will outline the current state of practice of the use of ordinal outcomes in RCTs. Ways to improve the analysis and reporting of ordinal outcomes in RCTs will be discussed. METHODS AND ANALYSIS: We will review RCTs that are published in the top four medical journals (British Medical Journal, New England Journal of Medicine, The Lancet and the Journal of the American Medical Association) between 1 January 2012 and 31 July 2022 that use an ordinal outcome as either a primary or a secondary outcome. The review will identify articles through a PubMed-specific search strategy. Our review will adhere to guidelines for scoping reviews as described in the PRISMA-ScR checklist. The study characteristics and details of the study design and analysis, including the target parameter(s) and statistical methods used to analyse the ordinal outcome, will be extracted from eligible studies. The screening, review and data extraction will be conducted using Covidence, a web-based tool for managing systematic reviews. The data will be summarised using descriptive statistics.

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.).

Cost-effectiveness of Prednisolone to Treat Bell Palsy in Children: An Economic Evaluation Alongside a Randomized Controlled Trial.

BACKGROUND AND OBJECTIVES: Bell palsy is the third most frequent diagnosis in children with sudden-onset neurologic dysfunction. The cost-effectiveness of treating Bell palsy with prednisolone in children is unknown. We aimed to assess the cost-effectiveness of prednisolone in treating Bell palsy in children compared with placebo. METHODS: This economic evaluation was a prospectively planned secondary analysis of a double-blinded, randomized, placebo-controlled superiority trial (Bell Palsy in Children [BellPIC]) conducted from 2015 to 2020. The time horizon was 6 months since randomization. Children aged 6 months to <18 years who presented within 72 hours of onset of clinician-diagnosed Bell palsy and who completed the trial were included (N = 180). Interventions were oral prednisolone or taste-matched placebo administered for 10 days. Incremental cost-effectiveness ratio comparing prednisolone with placebo was estimated. Costs were considered from a health care sector perspective and included Bell palsy-related medication cost, doctor visits, and medical tests. Effectiveness was measured using quality-adjusted life-years (QALYs) based on Child Health Utility 9D. Nonparametric bootstrapping was performed to capture uncertainties. Prespecified subgroup analysis by age 12 to <18 years vs <12 years was conducted. RESULTS: The mean cost per patient was A$760 in the prednisolone group and A$693 in the placebo group over the 6-month period (difference A$66, 95% CI -A$47 to A$179). QALYs over 6 months were 0.45 in the prednisolone group and 0.44 in the placebo group (difference 0.01, 95% CI -0.01 to 0.03). The incremental cost to achieve 1 additional recovery was estimated to be A$1,577 using prednisolone compared with placebo, and cost per additional QALY gained was A$6,625 using prednisolone compared with placebo. Given a conventional willingness-to-pay threshold of A$50,000 per QALY gained (equivalent to US$35,000 or £28,000), prednisolone is very likely cost-effective (probability is 83%). Subgroup analysis suggests that this was primarily driven by the high probability of prednisolone being cost-effective in children aged 12 to <18 years (probability is 98%) and much less so for those <12 years (probability is 51%). DISCUSSION: This provides new evidence to stakeholders and policymakers when considering whether to make prednisolone available in treating Bell palsy in children aged 12 to <18 years. TRIAL REGISTRATION INFORMATION: Australian New Zealand Clinical Trials Registry ACTRN12615000563561.