Telerehabilitation consultations with a physiotherapist for chronic knee pain versus in-person consultations in Australia: the PEAK non-inferiority randomised controlled trial.

BACKGROUND: Telerehabilitation whether perceived as less effective than in-person care for musculoskeletal problems. We aimed to determine if physiotherapy video conferencing consultations were non-inferior to in-person consultations for chronic knee pain. METHODS: In this non-inferiority randomised controlled trial, we recruited primary care physiotherapists from 27 Australian clinics. Using computer-generated blocks, participants with chronic knee pain consistent with osteoarthritis were randomly assigned (1:1, stratified by physiotherapist and clinic) in-person or telerehabilitation (ie, video conferencing) physiotherapist consultations. Participants and physiotherapists were unmasked to group assignment. Both groups had five consultations over 3 months for strengthening, physical activity, and education. Primary outcomes were knee pain (on a numerical rating scale of 0-10) and physical function (using the Western Ontario and McMaster Universities osteoarthritis index of 0-68) at 3 months after randomisation. Primary analysis was by modified intention-to-treat using all available data. This trial is registered with the Australian and New Zealand Clinical Trials Registry, ACTRN12619001240134. FINDINGS: Between Dec 10, 2019, and June 17, 2022, 394 adults were enrolled, with 204 allocated to in-person care and 190 to telerehabilitation. 15 primary care physiotherapists were recruited. At 3 months, 383 (97%) participants provided information for primary outcomes and both groups reported improved pain (mean change 2·98, SD 2·23 for in-person care and 3·14, 1·87 for telerehabilitation) and function (10·20, 11·63 and 10·75, 9·62, respectively). Telerehabilitation was non-inferior for pain (mean difference 0·16, 95% CI -0·26 to 0·57) and function (1·65, -0·23 to 3·53). The number of participants reporting adverse events was similar between groups (40 [21%] for in-person care and 35 [19%] for telerehabilitation) and none were serious. INTERPRETATION: Telerehabilitation with a physiotherapist is non-inferior to in-person care for chronic knee pain. FUNDING: National Health and Medical Research Council.

Methotrexate to treat hand osteoarthritis with synovitis (METHODS): an Australian, multisite, parallel-group, double-blind, randomised, placebo-controlled trial.

BACKGROUND: Hand osteoarthritis is a disabling condition with few effective therapies. Hand osteoarthritis with synovitis is a common inflammatory phenotype associated with pain. We aimed to examine the efficacy and safety of methotrexate at 6 months in participants with hand osteoarthritis and synovitis. METHODS: In this multisite, parallel-group, double-blind, randomised, placebo-controlled trial, participants (aged 40-75 years) with hand osteoarthritis (Kellgren and Lawrence grade ≥2 in at least one joint) and MRI-detected synovitis of grade 1 or more were recruited from the community in Melbourne, Hobart, Adelaide, and Perth, Australia. Participants were randomly assigned (1:1) using block randomisation, stratified by study site and self-reported sex, to receive methotrexate 20 mg or identical placebo orally once weekly for 6 months. The primary outcome was pain reduction (measured with a 100 mm visual analogue scale; VAS) in the study hand at 6 months assessed in the intention-to-treat population. Safety outcomes were assessed in all randomly assigned participants. This trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12617000877381). FINDINGS: Between Nov 22, 2017, and Nov 8, 2021, of 202 participants who were assessed for eligibility, 97 (48%) were randomly assigned to receive methotrexate (n=50) or placebo (n=47). 68 (70%) of 97 participants were female and 29 (30%) were male. 42 (84%) of 50 participants in the methotrexate group and 40 (85%) of 47 in the placebo group provided primary outcome data. The mean change in VAS pain at 6 months was -15·2 mm (SD 24·0) in the methotrexate group and -7·7 mm (25·3) in the placebo group, with a mean between-group difference of -9·9 (95% CI -19·3 to -0·6; p=0·037) and an effect size (standardised mean difference) of 0·45 (0·03 to 0·87). Adverse events occurred in 31 (62%) of 50 participants in the methotrexate group and 28 (60%) of 47 participants in the placebo group. INTERPRETATION: Treatment of hand osteoarthritis and synovitis with 20 mg methotrexate for 6 months had a moderate but potentially clinically meaningful effect on reducing pain, providing proof of concept that methotrexate might have a role in the management of hand osteoarthritis with an inflammatory phenotype. FUNDING: National Health and Medical Research Council of Australia.

Unravelling the effect of anaesthesia provider sex on patient outcomes: statistical analyses for sound conclusions.

Unravelling the impact of the sex of the anaesthesia provider on the outcomes of patients requires careful statistical analysis and the validity of many assumptions. A recent study in the British Journal of Anaesthesia investigates the effect of anaesthesia provider sex on patient outcomes, using data from two academic healthcare networks in the USA. The authors show that female provider sex was associated with a lower risk of intraoperative complications. They also show that there was no meaningful difference between male and female providers with respect to postoperative outcomes. There have been several recent studies considering the effect of healthcare provider sex on outcomes. We will discuss the interpretation of these results and the validity of the underlying assumptions.

Efficient designs for three-sequence stepped wedge trials with continuous recruitment.

BACKGROUND/AIMS: The standard approach to designing stepped wedge trials that recruit participants in a continuous stream is to divide time into periods of equal length. But the choice of design in such cases is infinitely more flexible: each cluster could cross from the control to the intervention at any point on the continuous time-scale. We consider the case of a stepped wedge design with clusters randomised to just three sequences (designs with small numbers of sequences may be preferred for their simplicity and practicality) and investigate the choice of design that minimises the variance of the treatment effect estimator under different assumptions about the intra-cluster correlation. METHODS: We make some simplifying assumptions in order to calculate the variance: in particular that we recruit the same number of participants, m, from each cluster over the course of the trial, and that participants present at regularly spaced intervals. We consider an intra-cluster correlation that decays exponentially with separation in time between the presentation of two individuals from the same cluster, from a value of ρ for two individuals who present at the same time, to a value of ρτ for individuals presenting at the start and end of the trial recruitment interval. We restrict attention to three-sequence designs with centrosymmetry - the property that if we reverse time and swap the intervention and control conditions then the design looks the same. We obtain an expression for the variance of the treatment effect estimator adjusted for effects of time, using methods for generalised least squares estimation, and we evaluate this expression numerically for different designs, and for different parameter values. RESULTS: There is a two-dimensional space of possible three-sequence, centrosymmetric stepped wedge designs with continuous recruitment. The variance of the treatment effect estimator for given ρ and τ can be plotted as a contour map over this space. The shape of this variance surface depends on τ and on the parameter mρ/(1-ρ), but typically indicates a broad, flat region of close-to-optimal designs. The 'standard' design with equally spaced periods and 1:1:1 allocation rarely performs well, however. CONCLUSIONS: In many different settings, a relatively simple design can be found (e.g. one based on simple fractions) that offers close-to-optimal efficiency in that setting. There may also be designs that are robustly efficient over a wide range of settings. Contour maps of the kind we illustrate can help guide this choice. If efficiency is offered as one of the justifications for using a stepped wedge design, then it is worth designing with optimal efficiency in mind.

Predicting Death or Disability after Surgery in the Older Adult.

BACKGROUND: Older patients are vulnerable to developing new or worsening disability after surgery. Despite this, patient or surgical characteristics predisposing to postoperative disability are poorly defined. The aim of the study was to develop and validate a model, subsequently transformed to point-score form, to predict 6-month death or disability in older patients after surgery. METHODS: The authors built a prospective, single-center registry to develop and validate the prediction model. The registry included patients 70 yr of age or older undergoing elective and nonelective, cardiac and noncardiac surgery between May 25, 2017, and February 11, 2021, and combined clinical data from the electronic medical record, hospital administrative data (International Classification of Diseases, Tenth Revision, Australian Modification codes) and World Health Organization (Geneva, Switzerland) Disability Assessment Schedule data collected directly from the patients. Death or disability was defined as being dead or having a World Health Organization Disability Assessment Schedule score 16% or greater. Included patients were randomly divided into model development (70%) and internal validation (30%) cohorts. Once constructed, the logistic regression and point-score models were assessed using the internal validation cohort and an external validation cohort comprising data from a separate randomized trial. RESULTS: Of 2,176 patients who completed the World Health Organization Disability Assessment Schedule immediately before surgery, 927 (43%) patients were disabled, and 413 (19%) had significant disability. By 6 months after surgery, 1,640 patients (75%) had data available for the primary outcome analysis. Of these patients, 195 (12%) patients had died, and 691 (42%) were dead or disabled. The developed point-score model included the preoperative World Health Organization Disability Assessment Schedule score, patient age, dementia, and chronic kidney disease. The point score model retained good discrimination in the internal (area under the curve, 0.74; 95% CI, 0.69 to 0.79) and external (area under the curve, 0.77; 95% CI, 0.74 to 0.80) validation data sets. CONCLUSIONS: The authors developed and validated a point score model to predict death or disability in older patients after surgery.

Sample size for partially nested designs and other nested or crossed designs with a continuous outcome when adjusted for baseline.

In a randomized controlled trial, outcomes of different subjects may be independent at baseline, but correlated at a follow-up measurement due to treatment. This treatment-related clustering at follow-up can arise for instance because the treatment is given in a group or because subjects are treated individually but by the same therapist (therapist effect). There is substantial literature on the design and analysis of such trials when estimation of the intervention effect is based on a follow-up measurement (eg, directly after treatment or at a later time point). However, often the baseline measurement of the outcome is highly correlated with the follow-up measurement, and this information can be used in the analysis. For a randomized design with a baseline and a follow-up measurement, we compare sample size requirements for analyses with and without adjustment for this baseline measure. We show that adjusting for baseline reduces required sample size. This reduction depends on the variance of the difference between arms at baseline, the variance of this difference at follow-up, and the correlation between the two. From this, we derive sample size formulas for partially or fully nested designs, and cluster randomized trials with treatment as a partially or fully cross-classified factor. Also, we discuss situations where clusters are already present at baseline or where treatment by cluster interaction is present. For the partially nested design, we work out practical design considerations (eg, use of content-matter input, design factors and optimal allocation ratio) and investigate small sample properties of the sample size formula.

The impact of iterative removal of low-information cluster-period cells from a stepped wedge design.

BACKGROUND: Standard stepped wedge trials, where clusters switch from the control to the intervention condition in a staggered manner, can be costly and burdensome. Recent work has shown that the amount of information contributed by each cluster in each period differs, with some cluster-periods contributing a relatively small amount of information. We investigate the patterns of the information content of cluster-period cells upon iterative removal of low-information cells, assuming a model for continuous outcomes with constant cluster-period size, categorical time period effects, and exchangeable and discrete-time decay intracluster correlation structures. METHODS: We sequentially remove pairs of "centrosymmetric" cluster-period cells from an initially complete stepped wedge design which contribute the least amount of information to the estimation of the treatment effect. At each iteration, we update the information content of the remaining cells, determine the pair of cells with the lowest information content, and repeat this process until the treatment effect cannot be estimated. RESULTS: We demonstrate that as more cells are removed, more information is concentrated in the cells near the time of the treatment switch, and in "hot-spots" in the corners of the design. For the exchangeable correlation structure, removing the cells from these hot-spots leads to a marked reduction in study precision and power, however the impact of this is lessened for the discrete-time decay structure. CONCLUSIONS: Removing cluster-period cells distant from the time of the treatment switch may not lead to large reductions in precision or power, implying that certain incomplete designs may be almost as powerful as complete designs.

Mental health and wellbeing of health and aged care workers in Australia, May 2021 - June 2022: a longitudinal cohort study.

OBJECTIVES: To assess the mental health and wellbeing of health and aged care workers in Australia during the second and third years of the coronavirus disease 2019 (COVID-19) pandemic, overall and by occupation group. DESIGN, SETTING, PARTICIPANTS: Longitudinal cohort study of health and aged care workers (ambulance, hospitals, primary care, residential aged care) in Victoria: May-July 2021 (survey 1), October-December 2021 (survey 2), and May-June 2022 (survey 3). MAIN OUTCOME MEASURES: Proportions of respondents (adjusted for age, gender, socio-economic status) reporting moderate to severe symptoms of depression (Patient Health Questionnaire-9, PHQ-9), anxiety (Generalized Anxiety Disorder scale, GAD-7), or post-traumatic stress (Impact of Event Scale-6, IES-6), burnout (abbreviated Maslach Burnout Inventory, aMBI), or high optimism (10-point visual analogue scale); mean scores (adjusted for age, gender, socio-economic status) for wellbeing (Personal Wellbeing Index-Adult, PWI-A) and resilience (Connor Davidson Resilience Scale 2, CD-RISC-2). RESULTS: A total of 1667 people responded to at least one survey (survey 1, 989; survey 2, 1153; survey 3, 993; response rate, 3.3%). Overall, 1211 survey responses were from women (72.6%); most respondents were hospital workers (1289, 77.3%) or ambulance staff (315, 18.9%). The adjusted proportions of respondents who reported moderate to severe symptoms of depression (survey 1, 16.4%; survey 2, 22.6%; survey 3, 19.2%), anxiety (survey 1, 8.8%; survey 2, 16.0%; survey 3, 11.0%), or post-traumatic stress (survey 1, 14.6%; survey 2, 35.1%; survey 3, 14.9%) were each largest for survey 2. The adjusted proportions of participants who reported moderate to severe symptoms of burnout were higher in surveys 2 and 3 than in survey 1, and the proportions who reported high optimism were smaller in surveys 2 and 3 than in survey 1. Adjusted mean scores for wellbeing and resilience were similar at surveys 2 and 3 and lower than at survey 1. The magnitude but not the patterns of change differed by occupation group. CONCLUSION: Burnout was more frequently reported and mean wellbeing and resilience scores were lower in mid-2022 than in mid-2021 for Victorian health and aged care workers who participated in our study. Evidence-based mental health and wellbeing programs for workers in health care organisations are needed. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12621000533897 (observational study; retrospective).

Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology.

INTRODUCTION: Clinical trial designs based on the assumption of independent observations are well established. Clustered clinical trial designs, where all observational units belong to a cluster and outcomes within clusters are expected to be correlated, have also received considerable attention. However, many clinical trials involve partially clustered data, where only some observational units belong to a cluster. Examples of such trials occur in neonatology, where participants include infants from both singleton and multiple births, and ophthalmology, where one or two eyes per participant may need treatment. Partial clustering can also arise in trials of group-based treatments (e.g. group education or counselling sessions) or treatments administered individually by a discrete number of health care professionals (e.g. surgeons or physical therapists), when this is compared to an unclustered control arm. Trials involving partially clustered data have received limited attention in the literature and the current lack of standardised terminology may be hampering the development and dissemination of methods for designing and analysing these trials. METHODS AND EXAMPLES: In this article, we present an overarching definition of partially clustered trials, bringing together several existing trial designs including those for group-based treatments, clustering due to facilitator effects and the re-randomisation design. We define and describe four types of partially clustered trial designs, characterised by whether the clustering occurs pre-randomisation or post-randomisation and, in the case of pre-randomisation clustering, by the method of randomisation that is used for the clustered observations (individual randomisation, cluster randomisation or balanced randomisation within clusters). Real life examples are provided to highlight the occurrence of partially clustered trials across a variety of fields. To assess how partially clustered trials are currently reported, we review published reports of partially clustered trials. DISCUSSION: Our findings demonstrate that the description of these trials is often incomplete and the terminology used to describe the trial designs is inconsistent, restricting the ability to identify these trials in the literature. By adopting the definitions and terminology presented in this article, the reporting of partially clustered trials can be substantially improved, and we present several recommendations for reporting these trial designs in practice. Greater awareness of partially clustered trials will facilitate more methodological research into their design and analysis, ultimately improving the quality of these trials.

Comparing Video-Based, Telehealth-Delivered Exercise and Weight Loss Programs With Online Education on Outcomes of Knee Osteoarthritis : A Randomized Trial.

BACKGROUND: Scalable knee osteoarthritis programs are needed to deliver recommended education, exercise, and weight loss interventions. OBJECTIVE: To evaluate two 6-month, telehealth-delivered exercise programs, 1 with and 1 without dietary intervention. DESIGN: 3-group, parallel randomized (5:5:2) trial. (Australian New Zealand Clinical Trials Registry: ACTRN12618000930280). SETTING: Australian private health insurance members. PARTICIPANTS: 415 persons with symptomatic knee osteoarthritis and a body mass index between 28 and 40 kg/m2 who were aged 45 to 80 years. INTERVENTION: All groups received access to electronic osteoarthritis information (control). The exercise program comprised 6 physiotherapist consultations via videoconference for exercise, self-management advice, and behavioral counseling, plus exercise equipment and resources. The diet and exercise program included an additional 6 dietitian consultations for a ketogenic very-low-calorie diet (2 formulated meal replacements and a low-carbohydrate meal daily) followed by a transition to healthy eating, as well as nutrition and behavioral resources. MEASUREMENTS: Primary outcomes were changes in knee pain (numerical rating scale [NRS] of 0 to 10, higher indicating worse) and physical function (Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC]; scale, 0 to 68, higher indicating worse) at 6 months (primary time point) and 12 months. Secondary outcomes were weight, physical activity, quality of life, mental health, global change, satisfaction, willingness to have surgery, orthopedic appointments, and knee surgery. RESULTS: A total of 379 participants (91%) provided 6-month primary outcomes, and 372 (90%) provided 12-month primary outcomes. At 6 months, both programs were superior to control for pain (between-group mean difference in change on NRS: diet and exercise, -1.5 [95% CI, -2.1 to -0.8]; exercise, -0.8 [CI, -1.5 to -0.2]) and function (between-group mean difference in change on WOMAC: diet and exercise, -9.8 [CI, -12.5 to -7.0]; exercise, -7.0 [CI, -9.7 to -4.2]). The diet and exercise program was superior to exercise (pain, -0.6 [CI, -1.1 to -0.2]; function, -2.8 [CI, -4.7 to -0.8]). Findings were similar at 12 months. LIMITATION: Participants and clinicians were unblinded. CONCLUSION: Telehealth-delivered exercise and diet programs improved pain and function in people with knee osteoarthritis and overweight or obesity. A dietary intervention conferred modest additional pain and function benefits over exercise. PRIMARY FUNDING SOURCE: Medibank, the Medibank Better Health Foundation Research Fund, and a National Health and Medical Research Council Centre of Research Excellence.

The batched stepped wedge design: A design robust to delays in cluster recruitment.

Stepped wedge designs are an increasingly popular variant of longitudinal cluster randomized trial designs, and roll out interventions across clusters in a randomized, but step-wise fashion. In the standard stepped wedge design, assumptions regarding the effect of time on outcomes may require that all clusters start and end trial participation at the same time. This would require ethics approvals and data collection procedures to be in place in all clusters before a stepped wedge trial can start in any cluster. Hence, although stepped wedge designs are useful for testing the impacts of many cluster-based interventions on outcomes, there can be lengthy delays before a trial can commence. In this article, we introduce "batched" stepped wedge designs. Batched stepped wedge designs allow clusters to commence the study in batches, instead of all at once, allowing for staggered cluster recruitment. Like the stepped wedge, the batched stepped wedge rolls out the intervention to all clusters in a randomized and step-wise fashion: a series of self-contained stepped wedge designs. Provided that separate period effects are included for each batch, software for standard stepped wedge sample size calculations can be used. With this time parameterization, in many situations including when linear models are assumed, sample size calculations reduce to the setting of a single stepped wedge design with multiple clusters per sequence. In these situations, sample size calculations will not depend on the delays between the commencement of batches. Hence, the power of batched stepped wedge designs is robust to unexpected delays between batches.

Evaluating the performance of Bayesian and restricted maximum likelihood estimation for stepped wedge cluster randomized trials with a small number of clusters.

BACKGROUND: Stepped wedge trials are an appealing and potentially powerful cluster randomized trial design. However, they are frequently implemented with a small number of clusters. Standard analysis methods for these trials such as a linear mixed model with estimation via maximum likelihood or restricted maximum likelihood (REML) rely on asymptotic properties and have been shown to yield inflated type I error when applied to studies with a small number of clusters. Small-sample methods such as the Kenward-Roger approximation in combination with REML can potentially improve estimation of the fixed effects such as the treatment effect. A Bayesian approach may also be promising for such multilevel models but has not yet seen much application in cluster randomized trials. METHODS: We conducted a simulation study comparing the performance of REML with and without a Kenward-Roger approximation to a Bayesian approach using weakly informative prior distributions on the intracluster correlation parameters. We considered a continuous outcome and a range of stepped wedge trial configurations with between 4 and 40 clusters. To assess method performance we calculated bias and mean squared error for the treatment effect and correlation parameters and the coverage of 95% confidence/credible intervals and relative percent error in model-based standard error for the treatment effect. RESULTS: Both REML with a Kenward-Roger standard error and degrees of freedom correction and the Bayesian method performed similarly well for the estimation of the treatment effect, while intracluster correlation parameter estimates obtained via the Bayesian method were less variable than REML estimates with different relative levels of bias. CONCLUSIONS: The use of REML with a Kenward-Roger approximation may be sufficient for the analysis of stepped wedge cluster randomized trials with a small number of clusters. However, a Bayesian approach with weakly informative prior distributions on the intracluster correlation parameters offers a viable alternative, particularly when there is interest in the probability-based inferences permitted within this paradigm.

Measurement of quality of recovery after surgery using the 15-item quality of recovery scale: a systematic review and meta-analysis.

BACKGROUND: There are very few patient-centred global outcome measures of recovery in the days or weeks after surgery. This meta-analysis evaluated the psychometric properties and clinical acceptability of the 15-item quality of recovery (QoR-15) scale. METHODS: We searched bibliographic databases for studies undertaking psychometric evaluation of the QoR-15 or using the QoR-15 as an outcome measure after surgery. Record screening, data extraction, and quality assessments were independently done by two researchers. Weighted averages estimating overall summary statistics across all the studies were calculated using random-effects meta-analysis. Pooled correlation coefficients were transformed using a Fisher z-transformation and then back-transformed to calculate pooled results. The four co-primary endpoints were validity, reliability, responsiveness, and clinical utility of the QoR-15 scale. RESULTS: A total of 26 unique studies met the eligibility criteria, yielding up to 22 847 patients across 16 countries, in 15 languages. A further 172 studies in a further 18 countries and six languages used the QoR-15 as an outcome measure. The QoR-15 had excellent discriminant validity, with the mean difference in QoR-15 scores in patients with and without postoperative complications (9.6; 95% confidence interval [CI], 5.9-13.3; P<0.001), and good convergent validity (for a global visual analogue recovery scale, pooled r=0.63; 95% CI, 0.54-0.71). There was excellent reliability: internal consistency (pooled α=0.85; 95% CI, 0.83-0.87), split-half reliability=0.80 (95% CI, 0.75-0.84), and test-retest reliability=0.97 (95% CI, 0.95-0.98). There was also high responsiveness (pooled standardised response mean=0.87; 95% CI, 0.65-1.08), patient recruitment into evaluation studies (96%; 95% CI, 93-99), and excellent completion and return rates (91%; 95% CI, 84-96). The mean time to complete the QoR-15 was 2.7 (95% CI, 2.2-3.1) min. CONCLUSIONS: The QoR-15 is a valid, reliable, and responsive patient-centred outcome metric in surgical patients. It is highly acceptable to both patients and clinicians. REGISTRATION: Open Science Framework Identifier: DOI 10.17605/OSF.IO/78HTA.

Inclusion, characteristics, and outcomes of male and female participants in large international perioperative studies.

BACKGROUND: We compared baseline characteristics and outcomes and evaluated the subgroup effects of randomised interventions by sex in males and females in large international perioperative trials. METHODS: Nine randomised trials and two cohort studies recruiting adult patients, conducted between 1995 and 2020, were included. Baseline characteristics and outcomes common to six or more studies were evaluated. Regression models included terms for sex, study, and an interaction between the two. Comparing outcomes without adjustment for baseline characteristics represents the 'total effect' of sex on the outcome. RESULTS: Of 54 626 participants, 58% were male and 42% were female. Females were less likely to have ASA physical status ≥3 (56% vs 64%), to smoke (15% vs 23%), have coronary artery disease (21% vs 32%), or undergo vascular surgery (10% vs 23%). The pooled incidence of death was 1.6% in females and 1.8% in males (risk ratio [RR] 0.92; 95% confidence interval [CI]: 0.81-1.05; P=0.20), of myocardial infarction was 4.2% vs 4.5% (RR 0.92; 95% CI: 0.81-1.03; P=0.10), of stroke was 0.5% vs 0.6% (RR 1.03; 95% CI: 0.79-1.35; P=0.81), and of surgical site infection was 8.6% vs 8.3% (RR 1.03; 95% CI: 0.79-1.35; P=0.70). Treatment effects of three interventions demonstrated statistically significant effect modification by sex. CONCLUSIONS: Females were in the minority in all included studies. They were healthier than males, but outcomes were comparable. Further research is needed to understand the reasons for this discrepancy. CLINICAL TRIAL REGISTRATION: International Registry of Meta-Research (UID: IRMR_000011; 5 January 2021).

Use of information criteria for selecting a correlation structure for longitudinal cluster randomised trials.

BACKGROUND: When designing and analysing longitudinal cluster randomised trials, such as the stepped wedge, the similarity of outcomes from the same cluster must be accounted for through the choice of a form for the within-cluster correlation structure. Several choices for this structure are commonly considered for application within the linear mixed model paradigm. The first assumes a constant intra-cluster correlation for all pairs of outcomes from the same cluster (the exchangeable/Hussey and Hughes model); the second assumes that correlations of outcomes measured in the same period are higher than outcomes measured in different periods (the block exchangeable model) and the third is the discrete-time decay model, which allows the correlation between pairs of outcomes to decay over time. Currently, there is limited guidance on how to select the most appropriate within-cluster correlation structure. METHODS: We simulated continuous outcomes under each of the three considered within-cluster correlation structures for a range of design and parameter choices, and, using the ASReml-R package, fit each linear mixed model to each simulated dataset. We evaluated the performance of the Akaike and Bayesian information criteria for selecting the correct within-cluster correlation structure for each dataset. RESULTS: For smaller total sample sizes, neither criteria performs particularly well in selecting the correct within-cluster correlation structure, with the simpler exchangeable model being favoured. Furthermore, in general, the Bayesian information criterion favours the exchangeable model. When the cluster auto-correlation (which defines the degree of dependence between observations in adjacent time periods) is large and number of periods is small, neither criteria is able to distinguish between the block exchangeable and discrete time decay models. However, for increasing numbers of clusters, periods, and subjects per cluster period, both the Akaike and Bayesian information criteria perform increasingly well in the detection of the correct within-cluster correlation structure. CONCLUSIONS: With increasing amounts of data, be they number of clusters, periods or subjects per cluster period, both the Akaike and Bayesian information criteria are increasingly likely to select the correct correlation structure. We recommend that if there are sufficient data available when planning a trial, that the Akaike or Bayesian information criterion is used to guide the choice of within-cluster correlation structure in the absence of other compelling justifications for a specific correlation structure. We also suggest that researchers conduct supplementary analyses under alternate correlation structures to gauge sensitivity to the initial choice.

The Effect of Flat Flexible Versus Stable Supportive Shoes on Knee Osteoarthritis Symptoms : A Randomized Trial.

BACKGROUND: Experts recommend that persons with knee osteoarthritis wear stable supportive shoes; however, evidence suggests that flat flexible shoes may be more beneficial. OBJECTIVE: To compare flat flexible with stable supportive shoes for knee osteoarthritis symptoms. DESIGN: Participant- and assessor-blinded randomized trial. (Prospectively registered with the Australian New Zealand Clinical Trials Registry [ACTRN12617001098325]). SETTING: Community. PARTICIPANTS: 164 patients with moderate to severe symptomatic radiographic medial knee osteoarthritis. INTERVENTION: Flat flexible (n = 82) or stable supportive shoes (n = 82), worn for at least 6 hours a day for 6 months. MEASUREMENTS: Primary outcomes were changes in walking pain (measured by an 11-point numerical rating scale) and physical function (as assessed by the Western Ontario and McMaster Universities Osteoarthritis Index subscale of 0 to 68 points) at 6 months. Secondary outcomes included additional pain and function measures, physical activity, and quality of life. Other measures included adverse events. RESULTS: Of 164 participants recruited, 161 (98%) completed 6-month primary outcomes. No evidence was found that flat flexible shoes were superior to stable supportive shoes in primary outcomes. Evidence did show a between-group difference in change in pain favoring stable supportive shoes (mean difference, 1.1 units [95% CI, 0.5 to 1.8 units]; P = 0.001) but not function (mean difference, 2.3 units [CI, -0.9 to 5.5 units]; P = 0.167). Improvements in knee-related quality of life and ipsilateral hip pain favored stable supportive shoes (mean difference, -5.3 units [CI, -10.0 to -0.5 units] and 0.7 units [CI, 0.0 to 1.4 units], respectively). Flat flexible shoes were not superior to stable supportive shoes for any secondary outcome. Fewer participants reported adverse events with stable supportive shoes (n = 12 [15%]) compared with flat flexible shoes (n = 26 [32%]) (risk difference, -0.17 [CI, -0.30 to -0.05]). LIMITATION: No "usual shoes" control group and a select patient subgroup, which may limit generalizability. CONCLUSION: Flat flexible shoes were not superior to stable supportive shoes. Contrary to our hypothesis, stable supportive shoes improved knee pain on walking more than flat flexible shoes. PRIMARY FUNDING SOURCE: National Health and Medical Research Council.

Information content of stepped wedge designs with unequal cluster-period sizes in linear mixed models: Informing incomplete designs.

In practice, stepped wedge trials frequently include clusters of differing sizes. However, investigations into the theoretical aspects of stepped wedge designs have, until recently, typically assumed equal numbers of subjects in each cluster and in each period. The information content of the cluster-period cells, clusters, and periods of stepped wedge designs has previously been investigated assuming equal cluster-period sizes, and has shown that incomplete stepped wedge designs may be efficient alternatives to the full stepped wedge. How this changes when cluster-period sizes are not equal is unknown, and we investigate this here. Working within the linear mixed model framework, we show that the information contributed by design components (clusters, sequences, and periods) does depend on the sizes of each cluster-period. Using a particular trial that assessed the impact of an individual education intervention on log-length of stay in rehabilitation units, we demonstrate how strongly the efficiency of incomplete designs depends on which cells are excluded: smaller incomplete designs may be more powerful than alternative incomplete designs that include a greater total number of participants. This also serves to demonstrate how the pattern of information content can be used to inform a set of incomplete designs to be considered as alternatives to the complete stepped wedge design. Our theoretical results for the information content can be extended to a broad class of longitudinal (ie, multiple period) cluster randomized trial designs.

Intra-cluster correlations from the CLustered OUtcome Dataset bank to inform the design of longitudinal cluster trials.

BACKGROUND: Sample size calculations for longitudinal cluster randomised trials, such as crossover and stepped-wedge trials, require estimates of the assumed correlation structure. This includes both within-period intra-cluster correlations, which importantly differ from conventional intra-cluster correlations by their dependence on period, and also cluster autocorrelation coefficients to model correlation decay. There are limited resources to inform these estimates. In this article, we provide a repository of correlation estimates from a bank of real-world clustered datasets. These are provided under several assumed correlation structures, namely exchangeable, block-exchangeable and discrete-time decay correlation structures. METHODS: Longitudinal studies with clustered outcomes were collected to form the CLustered OUtcome Dataset bank. Forty-four available continuous outcomes from 29 datasets were obtained and analysed using each correlation structure. Patterns of within-period intra-cluster correlation coefficient and cluster autocorrelation coefficients were explored by study characteristics. RESULTS: The median within-period intra-cluster correlation coefficient for the discrete-time decay model was 0.05 (interquartile range: 0.02-0.09) with a median cluster autocorrelation of 0.73 (interquartile range: 0.19-0.91). The within-period intra-cluster correlation coefficients were similar for the exchangeable, block-exchangeable and discrete-time decay correlation structures. Within-period intra-cluster correlation coefficients and cluster autocorrelations were found to vary with the number of participants per cluster-period, the period-length, type of cluster (primary care, secondary care, community or school) and country income status (high-income country or low- and middle-income country). The within-period intra-cluster correlation coefficients tended to decrease with increasing period-length and slightly decrease with increasing cluster-period sizes, while the cluster autocorrelations tended to move closer to 1 with increasing cluster-period size. Using the CLustered OUtcome Dataset bank, an RShiny app has been developed for determining plausible values of correlation coefficients for use in sample size calculations. DISCUSSION: This study provides a repository of intra-cluster correlations and cluster autocorrelations for longitudinal cluster trials. This can help inform sample size calculations for future longitudinal cluster randomised trials.

ISSLS PRIZE IN CLINICAL SCIENCE 2021: What are the risk factors for low back pain flares and does this depend on how flare is defined?

PURPOSE: Although risk factors for new low back pain (LBP) episodes and acute-to-chronic transition have been identified, risk factors for flares of LBP remain largely unknown. This case-crossover study aimed to identify: (1) risk factors LBP flares and (2) whether risk factors differed when flare is defined by pain increase (pain-defined flare: PDF) or identified by participants according to a broader flare definition that considered emotions and coping (self-reported flare: SRF). METHODS: One hundred and twenty-six participants with LBP for > 3 months were included. Candidate risk factors and flares (PDF/SRF) were assessed daily using a smartphone application for 28 days. Data on exposure to risk factors one, two and three days preceding PDF/SRF were compared to control periods. Conditional logistic regression estimated associations between risk factors and PDF/SRF. RESULTS: Odds of PDF and SRF were increased by poor sleep quality and morning pain. Good sleep quality reduced odds of flare. Odds for increased pain (PDF), but not SRF, were increased after days with higher afternoon and evening pain, fatigue, fear of physical activity and leisure physical activity. CONCLUSION: LBP flare has been largely ignored but is more reflective of the LBP experience than conventional definitions of acute, sub-acute and chronic LBP. This study highlights risk factors for flare and that these differ depending on whether flare is defined by pain alone (PDF) or a broad multidimensional definition (SRF). Potential targets to reduce the intensity/frequency of LBP flares are identified, with strong indication for the potential role of sleep intervention to mitigate LBP flare risk.

METHODS - A randomised controlled trial of METhotrexate to treat Hand Osteoarthritis with Synovitis: study protocol for a randomised controlled trial.

BACKGROUND: Hand osteoarthritis is a common and disabling problem without effective therapies. Accumulating evidence suggests the role of local inflammation in causing pain and structural progression in hand osteoarthritis, and hand osteoarthritis with synovitis is a commonly encountered clinical phenotype. Methotrexate is a well-established, low-cost, and effective treatment for inflammatory arthritis with a well-described safety profile. The aim of this multicentre, randomised, double-blind, placebo-controlled trial is to determine whether methotrexate reduces pain over 6 months in patients with hand osteoarthritis and synovitis. METHODS: Ninety-six participants with hand osteoarthritis and synovitis will be recruited through the Osteoarthritis Clinical Trial Network (Melbourne, Hobart, Adelaide, and Perth), and randomly allocated in a 1:1 ratio to receive either methotrexate 20 mg or identical placebo once weekly for 6 months. The primary outcome is pain reduction (assessed by 100 mm visual analogue scale) at 6 months. The secondary outcomes include changes in physical function and quality of life assessed using Functional Index for Hand Osteoarthritis, Australian Canadian Osteoarthritis Hand Index, Health Assessment Questionnaire, Michigan Hand Outcomes Questionnaire, Short-Form-36, tender and swollen joint count, and grip strength, and structural progression assessed using progression of synovitis and bone marrow lesions from magnetic resonance imaging and radiographic progression at 6 months. Adverse events will be recorded. The primary analysis will be by intention to treat, including all participants in their randomised groups. DISCUSSION: This study will provide high-quality evidence to address whether methotrexate has an effect on reducing pain over 6 months in patients with hand osteoarthritis and synovitis, with major clinical and public health importance. While a positive trial will inform international clinical practice guidelines for the management of hand osteoarthritis, a negative trial would be highly topical and change current trends in clinical practice. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR), ACTRN12617000877381. Registered 15 June 2017, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373124.