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Background Laceration repairs are a common, yet distressing procedure in children. While a range of strategies is used to treat this distress, there is currently no standard of care. The Anxiolysis for Laceration Repair in Children (ALICE) trial aims to identify the most effective pharmacological agent to manage laceration repair-associated distress. This paper outlines the statistical analysis plan for the ALICE trial.  The ALICE trial is a phase III, Bayesian, open-label trial that will identify the optimal agent for reducing distress among intranasal dexmedetomidine (IND), intranasal midazolam (INM), and inhaled nitrous oxide (N 2 O). The primary outcome, distress, will be measured by the Observational Scale of Behavioural Distress – Revised (OSBD-R). Scores from the OSBD-R will be analyzed using a Bayesian mixed effects model with data-driven prior distributions. Samples from the model’s posterior distributions will be used to calculate the probability of being best statistic (P best ), which will effectively rank the interventions. The trial will also evaluate delayed maladaptive behaviours, need for additional physical restraint, adverse events, and need for additional sedation as secondary outcomes. Furthermore, the trial will determine the costs associated with achieving adequate sedation in each treatment arm. Discussion This statistical analysis plan specifies the outcomes and analyses for the ALICE trial. The ALICE trial will provide evidence for the most effective agent for reducing distress in children receiving laceration repairs. Trial registration ClinicalTrials.gov NCT05383495 . Registered on May 16, 2022. 

Lacerations are the most common traumatic reason for children to visit an emergency department (ED), accounting for almost half of all procedures performed. Children experience considerable distress during laceration repair, despite routine application of local anesthetic. Pharmacologic anxiolysis may mitigate the negative practice of forcefully restraining a child, however, evidence for the most effective agent is lacking. We aim to determine the most effective anxiolytic agent for laceration repair in children. This is a multicentre, phase III, three-arm, adaptive, randomized, open-label, trial. We will include children 2-12 years with a single laceration requiring suture repair in the ED. Participants will be randomized to receive intranasal dexmedetomidine (IND) 3 mcg/kg, intranasal midazolam (INM) 0.4 mg/kg, or inhaled 50% nitrous oxide (N2O). The primary outcome is the weighted mean anxiolysis score using the Observational Scale of Behavioral Distress - Revised (OSBD-R) from initial positioning to tying of the last suture. Secondary outcomes include need for additional anxiolytic, need for physical restraint, adverse events (AEs), and delayed maladaptive behaviors. The primary analysis will be conducted by intention-to-treat. Results will report posterior means, standard deviations (SDs), and 95% high density posterior credible intervals for Total Distress Score on the OSBD-R. We will rank interventions based on the probability that an intervention is superior (Pbest) and the Surface Area Under the Cumulative Ranking Curve (SUCRA) to indicate relative anxiolytic efficacy. The mean difference in Total Distress Score and secondary outcomes will be estimated using Bayesian models. Ethics approval will be obtained from institutional review boards of the participating sites. Informed consent will be obtained from guardians of all participants in addition to assent from all participants. Study data will be submitted for publication. Clinicaltrials.gov NCT05383495.

Background Utilizing Bayesian methods in clinical trials has become increasingly popular, as they can incorporate prior information into the design, and allow for smaller sample sizes while providing reliable and robust statistical results. Various Bayesian methods for sample size determination are available, and while these methods are well justified and understood, it is unclear how they are being used in practice. This study aims to understand how sample sizes for Bayesian efficacy randomized clinical trials (RCTs) are determined and inform future designs of Bayesian trials. Methods A systematic literature review was conducted in May 2023 and updated in July 2025. We included completed RCTs which (a) assessed the efficacy of interventions in humans; (b) utilized a Bayesian framework for the primary data analysis; (c) published in English; and (d) enrolled participants between December 2009 – July 2025. Results The literature search produced 74,833 records, of which 27,890 were duplicates, and 46,943 were screened using manual and automated screening. 283 full texts were screened and 164 studies moved to extraction. Our findings demonstrate a slow increase in RCTs using Bayesian methods to analyse primary efficacy data from 2012 onwards, with a sharp increase during the COVID-19 pandemic (42%). The most common method for sample size determination in Bayesian RCTs was a hybrid approach (58%) in which elements of Bayesian and frequentist theory are combined. Bayesian RCTs predominantly took place in North America (34%) and mainly focused on adult study populations (85%). Bayesian trials were used in a variety of disease areas; the most common being COVID-19 (31%). Conclusion Fully Bayesian methods for sample size determination are rarely used in practice, despite significant theoretical development. Our review revealed a lack of standardized reporting across Bayesian RCTs, making it challenging to review the sample size determination. The CONSORT statement indicates that RCTs must report sample size calculations; adhered to by only 84% of included RCTs. Among RCTs that reported sample size determination, relevant information was frequently omitted from reports and discussed in poorly structured supplementary materials. Thus, there is a critical need for greater transparency, standardization and translation of relevant methodology in Bayesian RCTs.

Strong evidence suggests that maternal-infant skin-to-skin contact (SSC) is effective in reducing behavioural responses to pain. Given the multi-sensory benefits of SSC, it is highly likely that SSC provided during pain in early life may reduce pain-induced brain activity. The aim of this study is to examine the effect of SSC compared to 24% sucrose on pain-induced activity in the preterm infant brain during a medically required heel lance. Secondary objectives include determining (a) differences between behavioural pain response and noxious-related brain activity during heel lance and (b) rate of adverse events across groups. We will randomly assign 126 babies (32 to 36 completed weeks gestational age) admitted to the neonatal intensive care unit, and their mothers within the first seven days of age to receive (i) SSC plus sterile water and (ii) 24% oral sucrose. Each baby will receive a medically indicated heel lance, following a no treatment baseline period. The primary outcome is noxious-related brain activity measured using an electroencephalogram (EEG) pain-specific event-related potential. Secondary outcomes include pain intensity measured using a bio-behavioural infant pain assessment tool (Premature Infant Pain Profile-Revised) and rate of adverse events. This will be the first clinical trial to compare the effect of SSC and 24% sucrose on pain-induced brain activity in the preterm infant brain during a clinical noxious stimulus, measured using EEG. Given the negative neurodevelopmental outcomes associated with unmanaged pain, it is imperative that preterm babies receive the most effective pain-reducing treatments to improve their health outcomes. Our findings will have important implications in informing optimal pain assessment and management in preterm infants. ClinicalTrials.gov NCT03745963 . Registered on November 19, 2018.

Background Strong evidence suggests that maternal-infant skin-to-skin contact (SSC) is effective in reducing behavioural responses to pain. Given the multi-sensory benefits of SSC, it is highly likely that SSC provided during pain in early life may reduce pain-induced brain activity. The aim of this study is to examine the effect of SSC compared to 24% sucrose on pain-induced activity in the preterm infant brain during a medically required heel lance. Secondary objectives include determining (a) differences between behavioural pain response and noxious-related brain activity during heel lance and (b) rate of adverse events across groups. Methods We will randomly assign 126 babies (32 to 36 completed weeks gestational age) admitted to the neonatal intensive care unit, and their mothers within the first seven days of age to receive (i) SSC plus sterile water and (ii) 24% oral sucrose. Each baby will receive a medically indicated heel lance, following a no treatment baseline period. The primary outcome is noxious-related brain activity measured using an electroencephalogram (EEG) pain-specific event-related potential. Secondary outcomes include pain intensity measured using a bio-behavioural infant pain assessment tool (Premature Infant Pain Profile-Revised) and rate of adverse events. Discussion This will be the first clinical trial to compare the effect of SSC and 24% sucrose on pain-induced brain activity in the preterm infant brain during a clinical noxious stimulus, measured using EEG. Given the negative neurodevelopmental outcomes associated with unmanaged pain, it is imperative that preterm babies receive the most effective pain-reducing treatments to improve their health outcomes. Our findings will have important implications in informing optimal pain assessment and management in preterm infants. Trial registration ClinicalTrials.gov NCT03745963 . Registered on November 19, 2018.

Background We previously published the protocol and statistical analysis plan for a randomized controlled trial of Proportional Assist Ventilation for Minimizing the Duration of Mechanical Ventilation: the PROMIZING study in Trials ( https://doi.org/10.1186/s13063-023-07163-w ). This update summarizes changes made to the statistical analysis plan for the trial since the publication of the original protocol and statistical analysis plan. Methods/design The Proportional Assist Ventilation for Minimizing the Duration of Mechanical Ventilation (PROMIZING) study is a multi-center, open-label, randomized controlled trial designed to determine if ventilation with proportional assist ventilation with load-adjustable gain factors will result in a shorter duration of time spent on mechanical ventilation compared to ventilation with pressure support ventilation for patients with acute respiratory failure. The statistical analysis plan for the trial was incorporated into the original publication of the protocol in Trials ( https://doi.org/10.1186/s13063-023-07163-w ) and was based on version 5.0 of the study protocol and version 1.0 of the statistical analysis plan (SAP), which included plans for both frequentist and Bayesian analyses. We have since updated the SAP to refine the Bayesian analysis plan, update the multistate model diagram, and include plans for a cluster analysis to determine if there is heterogeneity of treatment effect. This update summarizes the changes made and their rationale and provides a refined SAP for the PROMIZING trial with additional background information, in adherence with guidelines for the prospective reporting of SAPs for randomized controlled trials. Trial registration ClinicalTrials.gov Identifier: NCT02447692 prospectively registered May 19, 2015.

Prior distributions must be specified for the parameters of interest in a Bayesian clinical trial. When existing evidence on the effects of the trial interventions is limited, prior distributions can be constructed with expert elicitation. However, conventional elicitation requires face-to-face interactions and intensive pre-elicitation training, which can be infeasible. Our remote elicitation was based on established expert elicitation methods. We used bivariate prior distributions for dependencies between elicited quantities. We elicited a prior distribution for the Croup Dosing Trial, which will assess the number of return visits to the emergency department within 7 days in children with croup. This trial evaluates the non-inferiority of 0.15 mg/kg of dexamethasone, compared to the standard dose of 0.60 mg/kg to treat croup. We conducted three remote workshops to elicit expert beliefs on the efficacy of the two doses of dexamethasone. Each workshop consisted of two survey rounds, separated by a group discussion. Prior to the workshop, experts reviewed provided literature on the effects of the two doses of dexamethasone. Beliefs were aggregated with expert-specific bivariate distributions. The aggregated distribution and surveyed non-inferiority margin determined the sample size. Twelve emergency medicine physicians participated in our remote elicitation exercise. The elicitation generated a prior distribution centered at 6% for the 0.60 mg/kg dose and 8% for the 0.15 mg/kg dose. The aggregated prior distribution produced a sample size of 1850, based on a non-inferiority margin of 4%. We elicited a prior distribution that incorporated past evidence and expert opinion. The elicited prior is consistent with literature on the efficacy of the dexamethasone doses in treating croup. Our approach demonstrates the feasibility of remotely eliciting bivariate distributions for clinical trials.

Utilizing Bayesian methods in clinical trials has become increasingly popular, as they can incorporate historical data and expert opinions into the design and allow for smaller sample sizes to reduce costs while providing reliable and robust statistical results. Sample size determination (SSD) is a key aspect of clinical trial design and various methods for Bayesian sample size determination are available. However, it is unclear how these methods are being used in practice. A systematic literature review was conducted to understand how sample sizes for Bayesian randomized clinical trials (RCTs) are determined and inform the design of future Bayesian trials. We searched five databases in May 2023, and updated in January 2025, including efficacy RCTs in humans which utilized a Bayesian framework for the primary data analysis, published in English, and enrolled participants between 2009 and 2024. The literature search produced 19,182 records, of which 105 studies were selected for data extraction. Results show that the most common method for SSD in Bayesian RCTs was a hybrid approach in which elements of Bayesian and frequentist theory are combined. Many RCTs did not provide a justification for SSD, while fully Bayesian methods were rarely used in practice, despite significant theoretical development. Our review also revealed a lack of standardized reporting, making it challenging to review the SSD. The CONSORT statement for reporting RCTs states that sample size calculations must be reported, which was poorly adhered to. Among RCTs that reported SSD, relevant information was frequently omitted from the reports and discussed in poorly structured supplementary materials. Thus, there is a critical need for greater transparency, standardization and translation of relevant methodology in Bayesian RCTs.

Climate change is likely to further worsen ozone pollution in already heavily polluted areas, leading to increased ozone-related health burdens. However, little evidence exists in China, the world's largest greenhouse gas emitter and most populated country. As China is embracing an aging population with changing population size and falling age-standardized mortality rates, the potential impact of population change on ozone-related health burdens is unclear. Moreover, little is known about the seasonal variation of ozone-related health burdens under climate change. We aimed to assess near-term (mid-21st century) future annual and seasonal excess mortality from short-term exposure to ambient ozone in 104 Chinese cities under 2 climate and emission change scenarios and 6 population change scenarios. We collected historical ambient ozone observations, population change projections, and baseline mortality rates in 104 cities across China during April 27, 2013, to October 31, 2015 (2013-2015), which included approximately 13% of the total population of mainland China. Using historical ozone monitoring data, we performed bias correction and spatially downscaled future ozone projections at a coarse spatial resolution (2.0° × 2.5°) for the period April 27, 2053, to October 31, 2055 (2053-2055), from a global chemistry-climate model to a fine spatial resolution (0.25° × 0.25°) under 2 Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs): RCP4.5, a moderate global warming and emission scenario where global warming is between 1.5°C and 2.0°C, and RCP8.5, a high global warming and emission scenario where global warming exceeds 2.0°C. We then estimated the future annual and seasonal ozone-related acute excess mortality attributable to both climate and population changes using cause-specific, age-group-specific, and season-specific concentration-response functions (CRFs). We used Monte Carlo simulations to obtain empirical confidence intervals (eCIs), quantifying the uncertainty in CRFs and the variability across ensemble members (i.e., 3 predictions of future climate and air quality from slightly different starting conditions) of the global model. Estimates of future changes in annual ozone-related mortality are sensitive to the choice of global warming and emission scenario, decreasing under RCP4.5 (-24.0%) due to declining ozone precursor emissions but increasing under RCP8.5 (10.7%) due to warming climate in 2053-2055 relative to 2013-2015. Higher ambient ozone occurs under the high global warming and emission scenario (RCP8.5), leading to an excess 1,476 (95% eCI: 898 to 2,977) non-accidental deaths per year in 2053-2055 relative to 2013-2015. Future ozone-related acute excess mortality from cardiovascular diseases was 5-8 times greater than that from respiratory diseases. Ozone concentrations increase by 15.1 parts per billion (10-9) in colder months (November to April), contributing to a net yearly increase of 22.3% (95% eCI: 7.7% to 35.4%) in ozone-related mortality under RCP8.5. An aging population, with the proportion of the population aged 65 years and above increased from 8% in 2010 to 24%-33% in 2050, will substantially amplify future ozone-related mortality, leading to a net increase of 23,838 to 78,560 deaths (110% to 363%). Our analysis was mainly limited by using a single global chemistry-climate model and the statistical downscaling approach to project ozone changes under climate change. Our analysis shows increased future ozone-related acute excess mortality under the high global warming and emission scenario RCP8.5 for an aging population in China. Comparison with the lower global warming and emission scenario RCP4.5 suggests that climate change mitigation measures are needed to prevent a rising health burden from exposure to ambient ozone pollution in China.

The connexin 43 (Cx43) hemichannel (HC) in the mechanosensory osteocytes is a major portal for the release of factors responsible for the anabolic effects of mechanical loading on bone formation and remodeling. However, little is known about how the Cx43 molecule responds to mechanical stimulation leading to the opening of the HC. Here, we demonstrate that integrin α5β1 interacts directly with Cx43 and that this interaction is required for mechanical stimulation-induced opening of the Cx43 HC. Direct mechanical perturbation via magnetic beads or conformational activation of integrin α5β1 leads to the opening of the Cx43 HC, and this role of the integrin is independent of its association with an extracellular fibronectin substrate. PI3K signaling is responsible for the shear stress-induced conformational activation of integrin α5β1 leading to the opening of the HC. These results identify an unconventional function of integrin that acts as a mechanical tether to induce opening of the HC and provide a mechanism connecting the effect of mechanical forces directly to anabolic function of the bone.