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Background : Physical exercise is crucial in type 2 diabetes management (T2D), and training in the aquatic environment seems to be a promising alternative due to its physical properties and metabolic, functional, cardiovascular, and neuromuscular benefits. Research on combined training in aquatic and dry-land training environments is scarce, especially in long-term interventions. Thus, this study aims to investigate the effects of combined training in both environments on health outcomes related to the management of T2D patients. Methods: This is a randomized, unicentric, single-blinded, comparator clinical trial with two parallel arms. Participants with T2D, of both sexes, aged at 45 to 80 years old, will be randomized into two groups (aquatic combined training (AQUA) and dry-land combined training (LAND)), both performing combined aerobic and resistance training three times a week on alternate days for 24 weeks. Aerobic training will be performed using continuous and pyramidal methods, with linear exercise intensity and duration progression. Intensity will be prescribed by rated effort perception (Borg scale 6 to 20). Resistance training will be performed using exercise for the trunk, upper and lower limbs maximum speed, and target repetition zone in aquatic and dry-land environments, respectively, using multiple sets in a linear dosage progression. Before, at 12 weeks, and after the 24 weeks of training, biochemical analyses, functional capacity, maximum muscle strength, body composition assessments, cardiovascular measures, and the administration of questionnaires to assess mental, cognitive, sleep quality, and quality of life will be conducted. Throughout the 24 weeks, the training load date and acute capillary glucose and blood pressure measurements will also be conducted. The data will be analyzed using the SPSS (29.0) statistical package, using a significance level of 0.05. For intra- and inter-group comparisons, generalized estimating equations will be applied and analyzed by intention-to-treat and per-protocol adopting the Bonferroni post hoc test. Discussion: The obtained results may provide insights to enhance understanding of the benefits of the aquatic and dry-land environment on various health outcomes, as well as acute aspects and safety considerations of the training. Moreover, this could support the development of intervention strategies to optimize the T2D management. Trial registration: Brazilian Clinical Trial Registry (ReBEC) RBR-10fwqmfy. Registered on April 16, 2024. [ABSTRACT FROM AUTHOR]

Background: Osteoarthritis in the thumb base (trapeziometacarpal joint, CMC-1 joint) is prevalent, particularly among middle-aged and elderly women, causing significant disability. Conservative treatments, including steroid injections, have been questioned for their efficacy, prompting exploration into alternative therapies such as platelet-rich plasma (PRP) injections. This randomized, double-blinded, controlled trial aims to evaluate the effectiveness of high-concentration PRP (platelet-rich plasma) injection compared to saline (placebo) in reducing pain and disability in patients with thumb base osteoarthritis. Methods: Patients meeting inclusion criteria will be randomized and blinded, with injections administered under sterile conditions and radiological guidance. With a planned sample size of 90 patients recruited from the Department of Hand Surgery at Södersjukhuset, Stockholm, the study will assess pain relief and functional improvement at 3, 6, and 12 months post-injection. The primary outcome measure is pain on load (numerical rating scale) at 6 months, with secondary outcomes including patient-reported outcomes, key pinch, grip strength, abduction of the thumb, and time to intervention within 1 year. Statistical analyses will employ non-parametric tests, chi-square tests, and generalized estimating equations to compare outcomes between the PRP and placebo groups. Discussion: The study aims to provide evidence regarding the efficacy of high-concentration PRP injections for thumb base osteoarthritis. If PRP proves superior to saline in reducing pain and improving function, it could offer a promising alternative treatment. Conversely, if PRP does not demonstrate significant benefits over placebo, its use for this condition is not justified. This study seeks to address the current gap in evidence regarding the efficacy of PRP injections for thumb base osteoarthritis. Trial registration: The study has been approved by the Swedish Ethical Review Authority (2023–06860-01 and 2024–01238-02) and is registered on ClinicalTrials.gov (NCT06193499) 2024–01-04. [ABSTRACT FROM AUTHOR]

Background: Nearly two-thirds of family caregivers of persons living with Alzheimer's disease or related dementias (AD/ADRD) provide complex care, including medical care. Family caregivers typically receive little to no training on how to provide this care. Furthermore, family caregivers simultaneously grapple with the presence of behavioral and psychological symptoms of dementia (BPSD), diminished communication abilities, and comorbidities such as diabetes. We developed Learning Skills Together (LST), a 6-week digitally delivered psychoeducational program, to facilitate family caregiver abilities to administer complex care tasks. The goal of the present study is to test the efficacy of LST and to reduce adverse outcomes associated with caregiving, such as depressive symptomology and negative appraisal of BPSD. Methods: To test the efficacy of LST, we will conduct a two-arm single-site randomized controlled trial (RCT) with N = 200 family caregivers of persons living with AD/ADRD. Eligible family caregivers will be randomly assigned to participate in either the LST intervention or a structurally equivalent control condition focused on healthy living. All family caregivers will complete four surveys, including a baseline survey administered prior to randomization, a post-intervention survey, and a 3- and 6-month follow-up survey to assess change in study outcomes. Between-group comparisons of each outcome will be evaluated using generalized estimating equation models. Mediation analyses will assess family caregiver self-efficacy as the intervention's mechanism of change in depressive symptomology and BPSD. We will also examine caregiver race, ethnicity, and gender as effect modifiers of the intervention. Discussion: LST findings will inform the field of AD/ADRD and caregiving regarding optimally supporting family caregivers in managing complex care tasks. If efficacious, the LST intervention will support family caregivers in preserving their own mental health while providing complex care. Trial registration: Clinical Trials.gov NCT05846984. This study was registered on May 6, 2023. [ABSTRACT FROM AUTHOR]

Background: Mortality, cerebral injury, and necrotizing enterocolitis (NEC) are common complications of very preterm birth. An important risk factor for these complications is hemodynamic instability. Pre-clinical studies suggest that the timing of umbilical cord clamping affects hemodynamic stability during transition. Standard care is time-based cord clamping (TBCC), with clamping irrespective of lung aeration. It is unknown whether delaying cord clamping until lung aeration and ventilation have been established (physiological-based cord clamping, PBCC) is more beneficial. This document describes the statistical analyses for the ABC3 trial, which aims to assess the efficacy and safety of PBCC, compared to TBCC. Methods: The ABC3 trial is a multicenter, randomized trial investigating PBCC (intervention) versus TBCC (control) in very preterm infants. The trial is ethically approved. Preterm infants born before 30 weeks of gestation are randomized after parental informed consent. The primary outcome is intact survival, defined as the composite of survival without major cerebral injury and/or NEC. Secondary short-term outcomes are co-morbidities and adverse events assessed during NICU admission, parental reported outcomes, and long-term neurodevelopmental outcomes assessed at a corrected age of 2 years. To test the hypothesis that PBCC increases intact survival, a logistic regression model will be estimated using generalized estimating equations (accounting for correlation between siblings and observations in the same center) with treatment and gestational age as predictors. This plan is written and submitted without knowledge of the data. Discussion: The findings of this trial will provide evidence for future clinical guidelines on optimal cord clamping management at birth. Trial registration: ClinicalTrials.gov NCT03808051. Registered on 17 January 2019. [ABSTRACT FROM AUTHOR]

Background: Venous thromboembolism (VTE) remains a priority challenge among orthopedic trauma patients. It is crucial to further improve the prophylaxis against VTE in routine orthopedic treatment. This study aims to compare the efficacy of two low molecular weight heparin (LMWH) regimens and additional intermittent pneumatic compression in preventing VTE among orthopedic trauma patients. Methods and analysis: This is a cluster-randomized crossover clinical study conducted in four hospitals in Shanghai from December 2019 to December 2023. The unit of randomization is orthopedic wards, and each ward will define a cluster. All clusters will implement four diverse intervention measures and one control measure in a given random sequence. Perioperative orthopedic trauma patients aged ≥ 18 years with stable vital signs, Caprini score > 2, and no contraindication of anticoagulation or intermittent pneumatic compression (IPC) devices will be eligible. The sample size will be determined to be 2590, considering cluster effect, period effect, and interactions. We will generally use the intention-to-treat (ITT) at the subject level for each outcome. For the primary outcome of the study, the incidence of VTE will be presented as risk ratio and 95% CIs. Generalized estimating equation (GEE) will be deployed to compare differences and adjust cluster effect, period effect, and interaction among interventions and periods if applicable. Discussion: VTE is a complication that cannot be underestimated after major orthopedic surgery. Early identification, early assessment, and early prevention can significantly reduce the incidence of VTE. Most guidelines recommend both medical and physical prevention, and we hope to demonstrate how they would affect the incidence among perioperative orthopedic patients. We want to explore if there is a difference between the two types of LWMH with or without an IPC device to provide more evidence for future guidelines and prevent more patients from the threat of VTE. Ethics and dissemination: The study received approval from the IRB of the coordinating center and all participating hospitals. Findings will be disseminated through peer-reviewed publications and conference presentations. Trial registration: ChiCTR1900027659. Registered on 17 November 2019 [ABSTRACT FROM AUTHOR]

Background: Mental well-being is poor in long-term care facilities (LTCF) residents. Physical disabilities, impaired social engagement, and environmental stress are also common in LTCF which exacerbate the decline of the mental well-being of older people living in LTCF. Protective elements, including nature-based, reminiscence, outdoor, and group activities, are known to be effective to promote the mental well-being of older people living in LTCF. However, limited by their physical disabilities and poor social support, older people living in LTCF are not likely to benefit from these effective measures. Virtual reality has been proven to be feasible to be environmentally unrestricted to providing LTCF residents with all protective elements promoting mental well-being. However, its effects on the mental well-being of LTCF residents living with physical disabilities are unclear. Methods: This study employs a single-blinded, two-parallel-group (intervention-to-control group ratio = 1:1), non-inferiority, randomized controlled trial. Eligible participants are aged 60 years or above, LTCF residents, and living with physical disabilities. The study will be conducted in LTCF. In the intervention group, participants will receive a 6-week VR experience program. In the control group, participants will receive the usual care provided by the LTCF. The primary outcome is mental well-being, as measured by World Health Organization Five Well-being Index at the time point of baseline (i.e., week 0) and after completion of the intervention (i.e., week 7). This study aims to recruit a total of 216 participants. Generalized estimating equations (GEE) will be used to examine the effects of the intervention. Trial registration: The trial has been registered at ClinicalTrials.gov (Identifier: NCT05818579), Registered on April 5, 2023. The latest version of the protocol was published online on 19 April 2023. All items come from the World Health Organization Trial Registration Data Set. This study has been approved by the Research Ethics Committee of Tung Wah College, Hong Kong (reference number: REC2023158). The findings will be disseminated in peer-reviewed journals, presented at international and local conferences with related themes, and shared in local media. [ABSTRACT FROM AUTHOR]

Introduction: Uganda's community health worker (CHW), or village health team (VHT), program faces significant challenges with poor retention and insufficient financial and program investment. Adequate compensation comprising financial and non-financial components is critical to retaining any workforce, including CHWs. This study evaluates the impact of a recognition-based non-financial incentives package on the motivation, performance, and retention of VHTs, as well as on the utilization of health services by the community. The incentive package and intervention were developed in collaboration with the district-level leadership and award VHTs who have met predetermined performance thresholds with a certificate and a government-branded jacket in a public ceremony. Methods: A two-armed cluster randomized controlled trial (RCT), conducted at the parish level in Uganda's Masindi District, will evaluate the effects of the 12-month intervention. The cluster-RCT will use a mixed-methods approach, which includes a baseline/endline VHT survey to assess the impact of the intervention on key outcomes, with an expected sample of 240 VHTs per study arm; our primary outcome is the total number of household visits per VHT and our multiple secondary outcomes include other performance indicators, motivation, and retention; VHT performance and retention data will be validated using monthly phone surveys tracking key performance indicators and through abstraction of VHT-submitted health facility reports; and focus group discussions will be conducted with VHTs and community members to understand how the intervention was received. Data collection activities will be administered in local languages. To assess the impact of the intervention, the study will conduct a regression analysis using Generalized Estimating Equations adjusting for cluster effect. Further, a difference-in-differences analysis will be conducted. Discussion: This study utilized a cluster-RCT design to assess the impact of a recognition-based incentives intervention on the motivation, performance, and retention of VHTs in Uganda's Masindi District. Utilizing a mixed-methods approach, the study will provide insights on the effectiveness and limitations of the intervention, VHT perspectives on perceived value, and critical insights on how non-financial incentives might support the strengthening of the community health workforce. Trial registration: ClinicalTrials.gov NCT05176106. Retrospectively registered on 4 January 2022. [ABSTRACT FROM AUTHOR]

Background: Community-Based Sociotherapy (CBS) is an approach that was introduced in Rwanda in 2005, with the aim of improving psychosocial well-being among its participants and facilitating reconciliation processes. Over the years, CBS has been adapted contextually and the effectiveness of the approach has been measured in different ways, using qualitative and quantitative study designs. This study specifically assesses the effectiveness of CBS in terms of fostering the social dignity of participants as the primary outcome. Methods/design: A cluster randomized controlled trial design with person-level outcomes whereas the CBS treatment is delivered at the cluster level. A total of 1200 eligible participants will be randomly assigned to two groups in a 1:1 ratio. Participants in the intervention group will receive the CBS intervention, while the control group will be waitlisted. The primary outcome measure is a self-designed and psychometrically validated Social Dignity Scale. The secondary outcome measures will be the WHO (Five) Well-Being Index (WHO-5), the Multidimensional Scale of Perceived Social Support (MSPSS), the Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5), the Self-reporting Questionnaire (SRQ-20), and the perceived parental self-efficacy scale. The primary analysis will be performed following an intention to treat analysis, using generalized estimating equation modeling. Discussion: We expect this cluster randomized controlled trial to provide insight into the effectiveness of CBS on social dignity and secondary psychosocial outcomes among its group participants, who have different socio-historical backgrounds including genocide survivors, perpetrators, bystanders and their descendants, people in conflicts (family/community), and local leaders. This study will inform CBS implementers, policymakers, practitioners, and other stakeholders on the role of social dignity in interventions that focus on psychosocial healing. Trial registration: ISRCTN ISRCTN11199072. It was registered on 2 April 2022. [ABSTRACT FROM AUTHOR]

Abstract Background Clustered or correlated outcome data is common in medical research studies, such as the analysis of national or international disease registries, or cluster-randomized trials, where groups of trial participants, instead of each trial participant, are randomized to interventions. Within-group correlation in studies with clustered data requires the use of specific statistical methods, such as generalized estimating equations and mixed-effects models, to account for this correlation and support unbiased statistical inference. Methods We compare different approaches to estimating generalized estimating equations and mixed effects models for a continuous outcome in R through a simulation study and a data example. The methods are implemented through four popular functions of the statistical software R, “geese”, “gls”, “lme”, and “lmer”. In the simulation study, we compare the mean squared error of estimating all the model parameters and compare the coverage proportion of the 95% confidence intervals. In the data analysis, we compare estimation of the intervention effect and the intra-class correlation. Results In the simulation study, the function “lme” takes the least computation time. There is no difference in the mean squared error of the four functions. The “lmer” function provides better coverage of the fixed effects when the number of clusters is small as 10. The function “gls” produces close to nominal scale confidence intervals of the intra-class correlation. In the data analysis and the “gls” function yields a positive estimate of the intra-class correlation while the “geese” function gives a negative estimate. Neither of the confidence intervals contains the value zero. Conclusions The “gls” function efficiently produces an estimate of the intra-class correlation with a confidence interval. When the within-group correlation is as high as 0.5, the confidence interval is not always obtainable.

Background: In cluster randomised controlled trials (cRCTs), groups of individuals (rather than individuals) are randomised to minimise the risk of contamination and/or efficiently use limited resources or solve logistic and administrative problems. A major concern in the primary analysis of cRCT is the use of appropriate statistical methods to account for correlation among outcomes from a particular group/cluster. This review aimed to investigate the statistical methods used in practice for analysing the primary outcomes in publicly funded cluster randomised controlled trials, adherence to the CONSORT (Consolidated Standards of Reporting Trials) reporting guidelines for cRCTs and the recruitment abilities of the cluster trials design.Methods: We manually searched the United Kingdom's National Institute for Health Research (NIHR) online Journals Library, from 1 January 1997 to 15 July 2021 chronologically for reports of cRCTs. Information on the statistical methods used in the primary analyses was extracted. One reviewer conducted the search and extraction while the two other independent reviewers supervised and validated 25% of the total trials reviewed.Results: A total of 1942 reports, published online in the NIHR Journals Library were screened for eligibility, 118 reports of cRCTs met the initial inclusion criteria, of these 79 reports containing the results of 86 trials with 100 primary outcomes analysed were finally included. Two primary outcomes were analysed at the cluster-level using a generalized linear model. At the individual-level, the generalized linear mixed model was the most used statistical method (80%, 80/100), followed by regression with robust standard errors (7%) then generalized estimating equations (6%). Ninety-five percent (95/100) of the primary outcomes in the trials were analysed with appropriate statistical methods that accounted for clustering while 5% were not. The mean observed intracluster correlation coefficient (ICC) was 0.06 (SD, 0.12; range, - 0.02 to 0.63), and the median value was 0.02 (IQR, 0.001-0.060), although 42% of the observed ICCs for the analysed primary outcomes were not reported.Conclusions: In practice, most of the publicly funded cluster trials adjusted for clustering using appropriate statistical method(s), with most of the primary analyses done at the individual level using generalized linear mixed models. However, the inadequate analysis and poor reporting of cluster trials published in the UK is still happening in recent times, despite the availability of the CONSORT reporting guidelines for cluster trials published over a decade ago. [ABSTRACT FROM AUTHOR]

Background: Clustered or correlated outcome data is common in medical research studies, such as the analysis of national or international disease registries, or cluster-randomized trials, where groups of trial participants, instead of each trial participant, are randomized to interventions. Within-group correlation in studies with clustered data requires the use of specific statistical methods, such as generalized estimating equations and mixed-effects models, to account for this correlation and support unbiased statistical inference.Methods: We compare different approaches to estimating generalized estimating equations and mixed effects models for a continuous outcome in R through a simulation study and a data example. The methods are implemented through four popular functions of the statistical software R, "geese", "gls", "lme", and "lmer". In the simulation study, we compare the mean squared error of estimating all the model parameters and compare the coverage proportion of the 95% confidence intervals. In the data analysis, we compare estimation of the intervention effect and the intra-class correlation.Results: In the simulation study, the function "lme" takes the least computation time. There is no difference in the mean squared error of the four functions. The "lmer" function provides better coverage of the fixed effects when the number of clusters is small as 10. The function "gls" produces close to nominal scale confidence intervals of the intra-class correlation. In the data analysis and the "gls" function yields a positive estimate of the intra-class correlation while the "geese" function gives a negative estimate. Neither of the confidence intervals contains the value zero.Conclusions: The "gls" function efficiently produces an estimate of the intra-class correlation with a confidence interval. When the within-group correlation is as high as 0.5, the confidence interval is not always obtainable. [ABSTRACT FROM AUTHOR]

Background: Russia has a high prevalence of human immunodeficiency virus (HIV) infections. In 2018, over one million persons were living with HIV (PLWH); over a third were women. A high proportion of HIV-infected women are co-infected with hepatitis C virus (HCV), and many consume alcohol, which adversely affects HIV and HCV treatment and prognosis. Despite the triple epidemics of alcohol use, HIV and HCV, and the need for interventions to reduce alcohol use among HIV/HCV co-infected women, evidence-based alcohol reduction interventions for this vulnerable population are limited. To address this gap, we developed a clinical trial to evaluate the efficacy of a computer-based intervention to reduce alcohol consumption among HIV/HCV co-infected women in clinical care.Methods: In this two-arm parallel randomized controlled trial, we propose to evaluate the efficacy of a culturally adapted alcohol reduction intervention delivered via a computer for HIV/HCV co-infected Russian women. The study population consists of women 21-45 years old with confirmed HIV/HCV co-infection who currently use alcohol. Intervention efficacy is assessed by a novel alcohol biomarker, ethyl glucuronide (EtG), and biomarkers of HIV and HCV disease progression. Women are randomized to trial conditions in a 1:1 allocation ratio, using a computer-generated algorithm to develop the assignment sequence and concealment of allocation techniques to minimize assignment bias. Women are randomized to either (1) the computer-based alcohol reduction intervention or (2) the standard-of-care control condition. We will use an intent-to-treat analysis and logistic and linear generalized estimating equations to evaluate intervention efficacy, relative to the standard of care, in enhancing the proportion of women with a laboratory-confirmed negative EtG at each research study visit over the 9-month follow-up period. Additional analyses will evaluate intervention effects on HIV (viral load and CD4+ levels) and HCV markers of disease progression (FibroScan).Discussion: The proposed trial design and analysis provides an appropriate conceptual and methodological framework to assess the efficacy of the computer-based intervention. We propose to recruit 200 participants. The intervention, if efficacious, may be an efficient and cost-effective alcohol reduction strategy that is scalable and can be readily disseminated and integrated into clinical care in Russia to reduce women's alcohol consumption and enhance HIV/HCV prognosis.Trial Registration: ClinicalTrials.gov NCT03362476 . Registered on 5 December 2017. [ABSTRACT FROM AUTHOR]

Background: More than 50% of patients with type 2 diabetes have hypertension in Uganda. Diabetic patients with elevated systolic blood pressure experience higher all-cause mortality and cardiovascular events compared with normotensive diabetic individuals, hence escalating resource utilization and cost of care. The aim of this study is to determine the effect of a nurse-led lifestyle choice and coaching intervention on systolic blood pressure among type 2 diabetic patients with a high atherosclerotic cardiovascular risk.Methods: This is a cluster-randomized study comprising two arms (intervention and non-intervention-control arm) with four clusters per arm with 388 diabetic patients with a high predicted 10-year atherosclerotic cardiovascular risk. The study will be implemented in 8 health facilities in Uganda. The intervention arm will employ a nurse-led lifestyle choice and coaching intervention. Within the intervention, nurses will be trained to provide structured health education, protocol-based hypertension management, and general atherosclerotic cardiovascular risk factor management, 24-h phone calls, and 2-monthly text messaging. The control group will be constituted by the usual care. The primary outcome measure is the mean difference in systolic blood pressure between the intervention and usual care groups after 6 months. The study is designed to have an 80% statistical power to detect an 8.5-mmHg mean reduction in systolic blood pressure from baseline to 6 months. The unit of analysis for the primary outcome is the individual participants. To monitor the effect of within-cluster correlation, generalized estimating equations will be used to assess the changes over time in systolic blood pressure as a continuous variable.Discussion: The data generated from this trial will inform change in the policy of shifting task of screening of hypertension and atherosclerotic cardiovascular disease from doctors to nurses.Trial Registration: Pan African Trials Registry PACTR 202001916873358 . Registered on 6 October 2019. [ABSTRACT FROM AUTHOR]

Background: Chronic pain is highly prevalent in the working population. People tend to attempt self-initiated treatments to manage their pain. The self-efficacy of behavioural change is a suitable model for guiding the development of an electronic pain management programme (ePain). The aim in this study is to develop ePain and to evaluate its effectiveness at improving pain self-efficacy, reducing pain intensity and negative emotions, and increasing quality of life.Methods: This study will be a randomized controlled trial. ePain will take the form of a 6-week online pain management programme. Participants will be aged 15 years or above, have chronic pain, and be employed. They must complete the baseline questionnaire and will be randomized into intervention and control groups. They will receive notifications to encourage their participation in ePain and complete the evaluation questionnaires. They will complete the process evaluation at week 3, the post assessment at week 6, and the follow-up assessment at week 12. The study will focus on pain self-efficacy; pain situations; negative emotions including levels of depression, anxiety, and stress; and quality of life. The participants' opinions of ePain will be collected as feedback. Data will be analysed on an intention-to-treat basis and generalized estimating equations will be used to investigate the time-averaged difference and differences at each follow-up time.Discussion: The study will provide information about the pain situations of online users in the working population. The participants will benefit from improvements in pain self-efficacy, pain situations, emotional status, and quality of life. The study will illustrate whether online learning is an effective intervention for improving the pain self-efficacy of the working population.Trial Registration: ClinicalTrials.gov, NCT03718702. Registered on 23 October 2018. [ABSTRACT FROM AUTHOR]

Abstract Background Analyses of multicenter studies often need to account for center clustering to ensure valid inference. For binary outcomes, it is particularly challenging to properly adjust for center when the number of centers or total sample size is small, or when there are few events per center. Our objective was to evaluate the performance of generalized estimating equation (GEE) log-binomial and Poisson models, generalized linear mixed models (GLMMs) assuming binomial and Poisson distributions, and a Bayesian binomial GLMM to account for center effect in these scenarios. Methods We conducted a simulation study with few centers (≤30) and 50 or fewer subjects per center, using both a randomized controlled trial and an observational study design to estimate relative risk. We compared the GEE and GLMM models with a log-binomial model without adjustment for clustering in terms of bias, root mean square error (RMSE), and coverage. For the Bayesian GLMM, we used informative neutral priors that are skeptical of large treatment effects that are almost never observed in studies of medical interventions. Results All frequentist methods exhibited little bias, and the RMSE was very similar across the models. The binomial GLMM had poor convergence rates, ranging from 27% to 85%, but performed well otherwise. The results show that both GEE models need to use small sample corrections for robust SEs to achieve proper coverage of 95% CIs. The Bayesian GLMM had similar convergence rates but resulted in slightly more biased estimates for the smallest sample sizes. However, it had the smallest RMSE and good coverage across all scenarios. These results were very similar for both study designs. Conclusions For the analyses of multicenter studies with a binary outcome and few centers, we recommend adjustment for center with either a GEE log-binomial or Poisson model with appropriate small sample corrections or a Bayesian binomial GLMM with informative priors.

Background: Analyses of multicenter studies often need to account for center clustering to ensure valid inference. For binary outcomes, it is particularly challenging to properly adjust for center when the number of centers or total sample size is small, or when there are few events per center. Our objective was to evaluate the performance of generalized estimating equation (GEE) log-binomial and Poisson models, generalized linear mixed models (GLMMs) assuming binomial and Poisson distributions, and a Bayesian binomial GLMM to account for center effect in these scenarios.Methods: We conducted a simulation study with few centers (≤30) and 50 or fewer subjects per center, using both a randomized controlled trial and an observational study design to estimate relative risk. We compared the GEE and GLMM models with a log-binomial model without adjustment for clustering in terms of bias, root mean square error (RMSE), and coverage. For the Bayesian GLMM, we used informative neutral priors that are skeptical of large treatment effects that are almost never observed in studies of medical interventions.Results: All frequentist methods exhibited little bias, and the RMSE was very similar across the models. The binomial GLMM had poor convergence rates, ranging from 27% to 85%, but performed well otherwise. The results show that both GEE models need to use small sample corrections for robust SEs to achieve proper coverage of 95% CIs. The Bayesian GLMM had similar convergence rates but resulted in slightly more biased estimates for the smallest sample sizes. However, it had the smallest RMSE and good coverage across all scenarios. These results were very similar for both study designs.Conclusions: For the analyses of multicenter studies with a binary outcome and few centers, we recommend adjustment for center with either a GEE log-binomial or Poisson model with appropriate small sample corrections or a Bayesian binomial GLMM with informative priors. [ABSTRACT FROM AUTHOR]

Background: Cluster randomised trials (CRTs) are commonly analysed using mixed-effects models or generalised estimating equations (GEEs). However, these analyses do not always perform well with the small number of clusters typical of most CRTs. They can lead to increased risk of a type I error (finding a statistically significant treatment effect when it does not exist) if appropriate corrections are not used.Methods: We conducted a small simulation study to evaluate the impact of using small-sample corrections for mixed-effects models or GEEs in CRTs with a small number of clusters. We then reanalysed data from TRIGGER, a CRT with six clusters, to determine the effect of using an inappropriate analysis method in practice. Finally, we reviewed 100 CRTs previously identified by a search on PubMed in order to assess whether trials were using appropriate methods of analysis. Trials were classified as at risk of an increased type I error rate if they did not report using an analysis method which accounted for clustering, or if they had fewer than 40 clusters and performed an individual-level analysis without reporting the use of an appropriate small-sample correction.Results: Our simulation study found that using mixed-effects models or GEEs without an appropriate correction led to inflated type I error rates, even for as many as 70 clusters. Conversely, using small-sample corrections provided correct type I error rates across all scenarios. Reanalysis of the TRIGGER trial found that inappropriate methods of analysis gave much smaller P values (P ≤ 0.01) than appropriate methods (P = 0.04-0.15). In our review, of the 99 trials that reported the number of clusters, 64 (65 %) were at risk of an increased type I error rate; 14 trials did not report using an analysis method which accounted for clustering, and 50 trials with fewer than 40 clusters performed an individual-level analysis without reporting the use of an appropriate correction.Conclusions: CRTs with a small or medium number of clusters are at risk of an inflated type I error rate unless appropriate analysis methods are used. Investigators should consider using small-sample corrections with mixed-effects models or GEEs to ensure valid results. [ABSTRACT FROM AUTHOR]

Background: Clustering of outcomes at centers involved in multicenter trials is a type of center effect. The Consolidated Standards of Reporting Trials Statement recommends that multicenter randomized controlled trials (RCTs) should account for center effects in their analysis, however most do not. The Early External Cephalic Version (EECV) trials published in 2003 and 2011 stratified by center at randomization, but did not account for center in the analyses, and due to the nature of the intervention and number of centers, may have been prone to center effects. Using data from the EECV trials, we undertook an empirical study to compare various statistical approaches to account for center effect while estimating the impact of external cephalic version timing (early or delayed) on the outcomes of cesarean section, preterm birth, and non-cephalic presentation at the time of birth. Methods: The data from the EECV pilot trial and the EECV2 trial were merged into one dataset. Fisher's exact method was used to test the overall effect of external cephalic version timing unadjusted for center effects. Seven statistical models that accounted for center effects were applied to the data. The models included: i) the Mantel-Haenszel test, ii) logistic regression with fixed center effect and fixed treatment effect, iii) center-size weighted and iv) un-weighted logistic regression with fixed center effect and fixed treatment-by-center interaction, iv) logistic regression with random center effect and fixed treatment effect, v) logistic regression with random center effect and random treatment-by-center interaction, and vi) generalized estimating equations. Results: For each of the three outcomes of interest approaches to account for center effect did not alter the overall findings of the trial. The results were similar for the majority of the methods used to adjust for center, illustrating the robustness of the findings. Conclusions: Despite literature that suggests center effect can change the estimate of effect in multicenter trials, this empirical study does not show a difference in the outcomes of the EECV trials when accounting for center effect. [ABSTRACT FROM AUTHOR]

Introduction: In a five-arm randomized clinical trial (RCT) with stratified randomization across 54 sites, we encountered low primary outcome event proportions, resulting in multiple sites with zero events either overall or in one or more study arms. In this paper, we systematically evaluated different statistical methods of accounting for center in settings with low outcome event proportions.Methods: We conducted a simulation study and a reanalysis of a completed RCT to compare five popular methods of estimating an odds ratio for multicenter trials with stratified randomization by center: (i) no center adjustment, (ii) random intercept model, (iii) Mantel-Haenszel model, (iv) generalized estimating equation (GEE) with an exchangeable correlation structure, and (v) GEE with small sample correction (GEE-small sample correction). We varied the number of total participants (200, 500, 1000, 5000), number of centers (5, 50, 100), control group outcome percentage (2%, 5%, 10%), true odds ratio (1, > 1), intra-class correlation coefficient (ICC) (0.025, 0.075), and distribution of participants across the centers (balanced, skewed).Results: Mantel-Haenszel methods generally performed poorly in terms of power and bias and led to the exclusion of participants from the analysis because some centers had no events. Failure to account for center in the analysis generally led to lower power and type I error rates than other methods, particularly with ICC = 0.075. GEE had an inflated type I error rate except in some settings with a large number of centers. GEE-small sample correction maintained the type I error rate at the nominal level but suffered from reduced power and convergence issues in some settings when the number of centers was small. Random intercept models generally performed well in most scenarios, except with a low event rate (i.e., 2% scenario) and small total sample size (n ≤ 500), when all methods had issues.Discussion: Random intercept models generally performed best across most scenarios. GEE-small sample correction performed well when the number of centers was large. We do not recommend the use of Mantel-Haenszel, GEE, or models that do not account for center. When the expected event rate is low, we suggest that the statistical analysis plan specify an alternative method in the case of non-convergence of the primary method. [ABSTRACT FROM AUTHOR]

Background: Opioid use has risen to epidemic proportions across Canada, with increasing evidence of harms including accidental overdose and death. Policy-makers have called for effective approaches to promote opioid reduction. One promising method from deprescribing randomized trials is to empower patients through direct-to-patient education. The current trial will evaluate the effectiveness of a government-led mail-out of educational information to adult community-dwelling, chronic opioid users on the reduction of opioids compared to usual care.Methods: This is a pragmatic, prospective, cluster randomized, parallel-arm controlled trial, comparing mailed distribution of a direct-to-patient educational brochure for chronic opioid use (intervention arm) to usual care (control arm). Eligible participants from across Manitoba, Canada, will be identified by the Provincial Drug Programs Branch within the Manitoba Health, Seniors and Active Living Department of the Manitoba Government, allocated to primary care providers, and the latter will be randomized in clusters of family medicine practices to achieve a 1:1 ratio. The primary outcome is complete cessation of opioids after 6 months assessed using Drug Program Information Network data. Secondary outcomes include ≥ 25% dose reduction in the mean morphine milligram equivalent (MME) daily dose, reduction of daily dose to < 90 mg MME, or therapeutic switch to another opioid or non-opioid medication. Data will be analyzed using intent-to-treat generalized estimating equations.Discussion: This trial will test the efficacy of a population-based, wide-scale, government-led direct-to-patient educational initiative to drive reductions in chronic opioid use by community-dwelling adults across Manitoba.Trial Registration: ClinicalTrials.gov, ID: NCT03400384 . Registered on 18 January 2018. [ABSTRACT FROM AUTHOR]

Background: Venipuncture is one of the most painful and distressing procedure experienced by pediatric patients. Evidence suggests that distraction combined with age-appropriate procedural information can effectively decrease procedural pain and anxiety in pediatric patients. Immersive virtual reality (IVR) can simultaneously provide complete distraction and procedural information to patients.Methods: Guided by the gate control theory and Lazarus and Folkman's theory, this study aims to examine the effects of IVR intervention on reducing the pain, anxiety and stress, the duration of venipuncture, and the satisfaction of healthcare providers for the procedure. A randomized controlled trial with repeated assessments will be conducted. A total of 200 pediatric patients aged 4-12 years will be recruited from a regional public hospital and randomly assigned to either the intervention or control group. The study will use two age-appropriate IVR modules that consist of procedural information. The intervention group will receive IVR intervention, whereas the control group will receive standard care only. The cost-effectiveness of IVR intervention will be compared with that of standard care. Outcome evaluation will be conducted at four time points: 10 min before, during, immediately after, and 30 min after the procedure. Intention to treat and generalized estimating equation model will be used to analyze the data.Discussion: This study is the first of its kind to adopt IVR intervention with age-appropriate procedural information for pediatric patients undergoing venipuncture. Findings of the proposed study may: (1) provide a novel, facile, and cost-effective intervention that can be used virtually at any time and place to manage pain and anxiety; and (2) shed light on the global trends of research and clinical development of IVR as an intervention for other painful and stressful medical procedures.Trial Registration: Chinese Clinical Trial Registry, ChiCTR1800018817 . Registered on 11 October 2018. [ABSTRACT FROM AUTHOR]