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Use of hypotonic intravenous fluid to maintain hydration in children in hospital has been associated with hyponatraemia, leading to neurological morbidity and mortality. We aimed to assess whether use of fluid solutions with a higher sodium concentration reduced the risk of hyponatraemia compared with use of hypotonic solutions. We did a randomised controlled double-blind trial of children admitted to The Royal Children's Hospital (Melbourne, VIC, Australia) who needed intravenous maintenance hydration for 6 h or longer. With an online randomisation system that used unequal block sizes, we randomly assigned patients (1:1) to receive either isotonic intravenous fluid containing 140 mmol/L of sodium (Na140) or hypotonic fluid containing 77 mmol/L of sodium (Na77) for 72 h or until their intravenous fluid rate decreased to lower than 50% of the standard maintenance rate. We stratified assignment by baseline sodium concentrations. Study investigators, treating clinicians, nurses, and patients were masked to treatment assignment. The primary outcome was occurrence of hyponatraemia (serum sodium concentration <135 mmol/L with a decrease of at least 3 mmol/L from baseline) during the treatment period, analysed by intention to treat. The trial was registered with the Australian New Zealand Clinical Trials Registry, number ACTRN1260900924257. Between Feb 2, 2010, and Jan 29, 2013, we randomly assigned 690 patients. Of these patients, primary outcome data were available for 319 who received Na140 and 322 who received Na77. Fewer patients given Na140 than those given Na77 developed hyponatraemia (12 patients [4%] vs 35 [11%]; odds ratio [OR] 0·31, 95% CI 0·16–0·61; p=0·001). No clinically apparent cerebral oedema occurred in either group. Eight patients in the Na140 group (two potentially related to intravenous fluid) and four in the Na77 group (none related to intravenous fluid) developed serious adverse events during the treatment period. One patient in the Na140 had seizures during the treatment period compared with seven who received Na77. Use of isotonic intravenous fluid with a sodium concentration of 140 mmol/L had a lower risk of hyponatraemia without an increase in adverse effects than did fluid containing 77 mmol/L of sodium. An isotonic fluid should be used as intravenous fluid for maintenance hydration in children. National Health and Medical Research Council, Murdoch Childrens Research Institute, The Royal Children's Hospital, and the Australian and New Zealand College of Anaesthetists.

BackgroundMental health competence (MHC) involves psychosocial capabilities such as regulating emotions, interacting well with peers and caring for others, and predicts a range of health and social outcomes. This study examines the course of MHC from childhood to adolescence and patterning by gender and disadvantage, in Australian and UK contexts.Methods Data: Longitudinal Study of Australian Children (n=4983) and the Millennium Cohort Study (n=18 296). Measures: A measure capturing key aspects of MHC was derived summing items from the parent-reported Strengths and Difficulties Questionnaire, assessed at 4–5 years, 6–7 years, 10–11 years and 14–15 years. Analysis: Proportions of children with high MHC (scores ≥23 of range 8–24) were estimated by age and country. Random-effects models were used to define MHC trajectories according to baseline MHC and change over time. Sociodemographic patterns were described.ResultsThe prevalence of high MHC steadily increased from 4 years to 15 years (from 13.6% to 15.8% and 20.6% to 26.2% in Australia and the UK, respectively). Examination of trajectories revealed that pathways of some children diverge from this normative MHC progression. For example, 7% and 9% of children in Australia and the UK, respectively, had a low starting point and decreased further in MHC by mid-adolescence. At all ages, and over time, MHC was lower for boys compared with girls and for children from disadvantaged compared with advantaged family backgrounds.ConclusionsApproaches to promoting MHC require a sustained focus from the early years through to adolescence, with more intensive approaches likely needed to support disadvantaged groups and boys.

This article presents the CONSORT (consolidated standards of reporting trials) extension for cluster randomised crossover trials. A cluster randomised crossover trial involves randomisation of groups of individuals (known as clusters) to different sequences of interventions over time. The design has gained popularity in settings where cluster randomisation is required because it can largely overcome the loss in power due to clustering in parallel cluster trials. However, the design has many methodological complexities, requiring tailored reporting guidance. The guideline was developed using a survey and in-person consensus meeting, informed by a systematic review examining the quality of reporting in cluster randomised crossover trials and relevant CONSORT statements for individual, crossover, cluster, and stepped wedge designs. This article also provides recommended reporting items, along with explanations and examples.

Background In a cluster randomised crossover (CRXO) design, a sequence of interventions is assigned to a group, or ‘cluster’ of individuals. Each cluster receives each intervention in a separate period of time, forming ‘cluster-periods’. Sample size calculations for CRXO trials need to account for both the cluster randomisation and crossover aspects of the design. Formulae are available for the two-period, two-intervention, cross-sectional CRXO design, however implementation of these formulae is known to be suboptimal. The aims of this tutorial are to illustrate the intuition behind the design; and provide guidance on performing sample size calculations. Methods Graphical illustrations are used to describe the effect of the cluster randomisation and crossover aspects of the design on the correlation between individual responses in a CRXO trial. Sample size calculations for binary and continuous outcomes are illustrated using parameters estimated from the Australia and New Zealand Intensive Care Society – Adult Patient Database (ANZICS-APD) for patient mortality and length(s) of stay (LOS). Results The similarity between individual responses in a CRXO trial can be understood in terms of three components of variation: variation in cluster mean response; variation in the cluster-period mean response; and variation between individual responses within a cluster-period; or equivalently in terms of the correlation between individual responses in the same cluster-period (within-cluster within-period correlation, WPC), and between individual responses in the same cluster, but in different periods (within-cluster between-period correlation, BPC). The BPC lies between zero and the WPC. When the WPC and BPC are equal the precision gained by crossover aspect of the CRXO design equals the precision lost by cluster randomisation. When the BPC is zero there is no advantage in a CRXO over a parallel-group cluster randomised trial. Sample size calculations illustrate that small changes in the specification of the WPC or BPC can increase the required number of clusters. Conclusions By illustrating how the parameters required for sample size calculations arise from the CRXO design and by providing guidance on both how to choose values for the parameters and perform the sample size calculations, the implementation of the sample size formulae for CRXO trials may improve.

In a cluster randomised crossover (CRXO) design, a sequence of interventions is assigned to a group, or 'cluster' of individuals. Each cluster receives each intervention in a separate period of time, forming 'cluster-periods'. Sample size calculations for CRXO trials need to account for both the cluster randomisation and crossover aspects of the design. Formulae are available for the two-period, two-intervention, cross-sectional CRXO design, however implementation of these formulae is known to be suboptimal. The aims of this tutorial are to illustrate the intuition behind the design; and provide guidance on performing sample size calculations. Graphical illustrations are used to describe the effect of the cluster randomisation and crossover aspects of the design on the correlation between individual responses in a CRXO trial. Sample size calculations for binary and continuous outcomes are illustrated using parameters estimated from the Australia and New Zealand Intensive Care Society - Adult Patient Database (ANZICS-APD) for patient mortality and length(s) of stay (LOS). The similarity between individual responses in a CRXO trial can be understood in terms of three components of variation: variation in cluster mean response; variation in the cluster-period mean response; and variation between individual responses within a cluster-period; or equivalently in terms of the correlation between individual responses in the same cluster-period (within-cluster within-period correlation, WPC), and between individual responses in the same cluster, but in different periods (within-cluster between-period correlation, BPC). The BPC lies between zero and the WPC. When the WPC and BPC are equal the precision gained by crossover aspect of the CRXO design equals the precision lost by cluster randomisation. When the BPC is zero there is no advantage in a CRXO over a parallel-group cluster randomised trial. Sample size calculations illustrate that small changes in the specification of the WPC or BPC can increase the required number of clusters. By illustrating how the parameters required for sample size calculations arise from the CRXO design and by providing guidance on both how to choose values for the parameters and perform the sample size calculations, the implementation of the sample size formulae for CRXO trials may improve.

To assess the design and statistical methods used in cluster-randomized crossover (CRXO) trials. We undertook a systematic review of CRXO trials. Searches of MEDLINE, EMBASE, and CINAHL Plus; and citation searches of CRXO methodological articles were conducted to December 2014. We extracted data on design characteristics and statistical methods for sample size, data analysis, and handling of missing data. Ninety-one trials including 139 end point analyses met the inclusion criteria. Trials had a median of nine clusters [interquartile range (IQR), 4–21] and median cluster-period size of 30 individuals (IQR, 14–77); 58 (69%) trials had two periods, and 27 trials (30%) included the same individuals in all periods. A rationale for the design was reported in only 25 trials (27%). A sample size justification was provided in 53 (58%) trials. Only nine (10%) trials accounted appropriately for the design in their sample size calculation. Ten of the 12 cluster-level analyses used a method that accounted for the clustering and multiple-period aspects of the design. In contrast, only 4 of the 127 individual-level analyses used a potentially appropriate method. There is a need for improved application of appropriate analysis and sample size methods, and reporting, in CRXO trials.

We thank Tadahiro Goto, Kristen Neville and Jan Walker for their letters about our PIMS study, which identified that isotonic intravenous fluid was protective against hyponatraemia compared with hypotonic fluid.

Background The cluster randomised crossover (CRXO) design is gaining popularity in trial settings where individual randomisation or parallel group cluster randomisation is not feasible or practical. Our aim is to stimulate discussion on the content of a reporting guideline for CRXO trials and to assess the reporting quality of published CRXO trials. Methods We undertook a systematic review of CRXO trials. Searches of MEDLINE, EMBASE, and CINAHL Plus as well as citation searches of CRXO methodological articles were conducted to December 2014. Reporting quality was assessed against both modified items from 2010 CONSORT and 2012 cluster trials extension and other proposed quality measures. Results Of the 3425 records identified through database searching, 83 trials met the inclusion criteria. Trials were infrequently identified as “cluster randomis(z)ed crossover” in title ( n  = 7, 8%) or abstract ( n  = 21, 25%), and a rationale for the design was infrequently provided ( n  = 20, 24%). Design parameters such as the number of clusters and number of periods were well reported. Discussion of carryover took place in only 17 trials (20%). Sample size methods were only reported in 58% ( n  = 48) of trials. A range of approaches were used to report baseline characteristics. The analysis method was not adequately reported in 23% ( n  = 19) of trials. The observed within-cluster within-period intracluster correlation and within-cluster between-period intracluster correlation for the primary outcome data were not reported in any trial. The potential for selection, performance, and detection bias could be evaluated in 30%, 81%, and 70% of trials, respectively. Conclusions There is a clear need to improve the quality of reporting in CRXO trials. Given the unique features of a CRXO trial, it is important to develop a CONSORT extension. Consensus amongst trialists on the content of such a guideline is essential.

Objective To determine whether general practice surveillance for childhood obesity, followed by obesity management across primary and tertiary care settings using a shared care model, improves body mass index and related outcomes in obese children aged 3-10 years.Design Randomised controlled trial.Setting 22 family practices (35 participating general practitioners) and a tertiary weight management service (three paediatricians, two dietitians) in Melbourne, Australia.Participants Children aged 3-10 years with body mass index above the 95th centile recruited through their general practice between July 2009 and April 2010.Intervention Children were randomly allocated to one tertiary appointment followed by up to 11 general practice consultations over one year, supported by shared care, web based software (intervention) or “usual care” (control). Researchers collecting outcome measurements, but not participants, were blinded to group assignment.Main outcome measures Children’s body mass index z score (primary outcome), body fat percentage, waist circumference, physical activity, quality of diet, health related quality of life, self esteem, and body dissatisfaction and parents’ body mass index (all 15 months post-enrolment).Results 118 (60 intervention, 56 control) children were recruited and 107 (91%) were retained and analysed (56 intervention, 51 control). All retained intervention children attended the tertiary appointment and their general practitioner for at least one (mean 3.5 (SD 2.5, range 1-11)) weight management consultation. At outcome, children in the two trial arms had similar body mass index (adjusted mean difference −0.1 (95% confidence interval −0.7 to 0.5; P=0.7)) and body mass index z score (−0.05 (−0.14 to 0.03); P=0.2). Similarly, no evidence was found of benefit or harm on any secondary outcome. Outcomes varied widely in the combined cohort (mean change in body mass index z score −0.20 (SD 0.25, range −0.97-0.47); 26% of children resolved from obese to overweight and 2% to normal weight.Conclusions Although feasible, not harmful, and highly rated by both families and general practitioners, the shared care model of primary and tertiary care management did not lead to better body mass index or other outcomes for the intervention group compared with the control group. Improvements in body mass index in both groups highlight the value of untreated controls when determining efficacy.Trial registration Australian New Zealand Clinical Trials Registry ACTRN12608000055303.

The diurnal and seasonal variations of the northern Australian dryline are examined by constructing climatologies of low-level dynamic and thermodynamic variables taken from the high-resolution Australian Bureau of Meteorology’s Limited Area Prediction Scheme (LAPS) forecasts from 2000 to 2003. The development of the dryline is analyzed within the framework of the frontogenesis function applied to the mixing ratio and the airstream diagnostics of Cohen and Schultz. A case study of 12–13 October 2002 illustrating the airmass boundaries over the Australian region is also examined. Daytime surface heating produces sea-breeze circulations around the coast and a large inland heat trough that extends east–west along northern Australia. At night, air parcels accelerate toward low pressure, increasing convergence and deformation within the heat trough. This sharpens the moisture gradient across the tropical and continental airmass boundary into a dryline. This is different than the dryline of the Great Plains in the United States, which generally weakens overnight. The Australian dryline is strongest in spring just poleward of the Gulf of Carpentaria, where the moisture gradient across the heat trough is enhanced by the coast, and the axis of dilatation is closely aligned with mixing ratio isopleths. The dryline is weakest in winter, when the heat trough is weak. The LAPS 3-h forecasts are in good agreement with observations obtained from the Automatic Weather Station network. The 3-h forecasts capture the observed diurnal and seasonal cycle of the airmass boundaries. However, the sea-breeze circulation and ageostrophic flow into the surface heat trough is limited by the model resolution. The LAPS 3-h forecasts may therefore underestimate the nocturnal intensification of the dryline, especially since the inland moisture content is overestimated.