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Overstating the impact of interventions through incomplete or inaccurate reporting can lead to inappropriate scale-up of interventions with low impact. Accurate reporting of the impact of interventions is of great importance in global health research to protect scarce resources. In global health, the cluster randomised trial design is commonly used to evaluate complex, multicomponent interventions, and outcomes are often binary. Complete reporting of impact for binary outcomes means reporting both relative and absolute measures. We did a systematic review to assess reporting practices and potential to overstate impact in contemporary cluster randomised trials with binary primary outcome. We included all reports registered in the Cochrane Central Register of Controlled Trials of two-arm parallel cluster randomised trials with at least one binary primary outcome that were published in 2017. Of 73 cluster randomised trials, most (60 [82%]) showed incomplete reporting. Of 64 cluster randomised trials for which it was possible to evaluate, most (40 [63%]) reported results in such a way that impact could be overstated. Care is needed to report complete evidence of impact for the many interventions evaluated using the cluster randomised trial design worldwide.

Objectives To explore the effect of introducing 24/7 resident labour ward consultant presence on neonatal and maternal outcomes in a large obstetric unit in England. Design Retrospective time sequence analysis of routinely collected data. Setting Obstetric unit of large teaching hospital in England. Participants Women and babies delivered between1 July 2011 and 30 June 2017. Births Main outcome measures The primary composite outcome comprised intrapartum stillbirth, neonatal death, babies requiring therapeutic hypothermia, or admission to neonatal intensive care within three hours of birth. Secondary outcomes included markers of neonatal and maternal morbidity. Planned subgroup analyses investigated gestation ( Results 17324 babies delivered before and 16110 after 24/7 consultant presence. The prevalence of the primary outcome increased by 0.65%, from 2.07% (359/17324) before 24/7 consultant presence to 2.72% (438/16110, P < 0.001) after 24/7 consultant presence which was consistent with an upward trend over time already well established before 24/7 consultant presence began (OR 1.09 p.a.; CI 1.04 to 1.13). Overall, there was no change in this trend associated with the transition to 24/7. However, in babies born ≥37 weeks gestation, the upward trend was reversed after implementation of 24/7 (OR 0.67 p.a.; CI 0.49 to 0.93; P = 0.017). No substantial differences were shown in other outcomes or subgroups. Conclusions Overall, resident consultant obstetrician presence 24/7 on labour ward was not associated with a change in a pre-existing trend of increasing adverse infant outcomes. However, 24/7 presence was associated with a reversal in increasing adverse outcomes for term babies.

Background Emergency abdominal surgery is associated with poor patient outcomes. We studied the effectiveness of a national quality improvement (QI) programme to implement a care pathway to improve survival for these patients. Objectives The objectives were to assess whether or not the QI programme improves 90-day survival after emergency abdominal surgery; to assess effects on 180-day survival, hospital stay and hospital readmission; and to better understand these findings through an integrated process evaluation, ethnographic study and cost-effectiveness analysis. Design This was a stepped-wedge cluster randomised trial. Hospitals were organised into 15 geographical clusters, and commenced the QI programme in random order over 85 weeks. Analyses were performed on an intention-to-treat basis. The primary outcome was analysed using a mixed-effects parametric survival model, adjusting for time-related effects. Ethnographic and economics data were collected in six hospitals. The process evaluation included all hospitals. Setting The trial was set in acute surgical services of 93 NHS hospitals. Participants Patients aged ≥ 40 years who were undergoing emergency abdominal surgery were eligible. Intervention The intervention was a QI programme to implement an evidence-based care pathway. Main outcome measures The primary outcome measure was mortality within 90 days of surgery. Secondary outcomes were mortality within 180 days, length of hospital stay and hospital readmission within 180 days. The main economic measure was the quality-adjusted life-years. Data sources Data were obtained from the National Emergency Laparotomy Audit database; qualitative interviews and ethnographic observations; quality-of-life and NHS resource use data were collected via questionnaires. Results Of 15,873 eligible patients from 93 NHS hospitals, primary outcome data were analysed for 8482 participants in the usual care group and 7374 in the QI group. The primary outcome occurred in 1393 participants in the usual care group (16%), compared with 1210 patients in the QI group (16%) [QI vs. usual care hazard ratio (HR) 1.11, 95% confidence interval (CI) 0.96 to 1.28]. No differences were found in mortality at 180 days or hospital readmission; there was a small increase in hospital stay in the QI group (HR for discharge 0.90, 95% CI 0.83 to 0.97). There were only modest improvements in care processes following QI implementation. The ethnographic study revealed good QI engagement, but limited time and resources to implement change, affecting which processes teams addressed, the rate of change and eventual success. In some sites, there were challenges around prioritising the intervention in busy environments and in obtaining senior engagement. The intervention is unlikely to be cost-effective at standard cost-effectiveness thresholds, but may be cost-effective over the lifetime horizon. Limitations Substantial delays were encountered in securing data access to national registries. Fewer patients than expected underwent surgery and the mortality rate was lower than anticipated. Conclusions There was no survival benefit from a QI programme to implement a care pathway for patients undergoing emergency abdominal surgery. The modest impact of the intervention on process measures, despite good clinician engagement, may have been limited by the time and resources needed to improve patient care. Future work Future QI programmes must balance intervention complexity with the practical realities of NHS services to ensure that such programmes can be delivered with the resources available. Trial registration Current Controlled Trials ISRCTN80682973 and The Lancet protocol 13PRT/7655. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 7, No. 32. See the NIHR Journals Library website for further project information.

ObjectiveTo determine whether the higher weekend admission mortality risk is attributable to increased severity of illness.DesignRetrospective analysis of 4 years weekend and weekday adult emergency admissions to a university teaching hospital in England.Outcome measures30-day postadmission weekend:weekday mortality ratios adjusted for severity of illness (baseline National Early Warning Score (NEWS)), routes of admission to hospital, transfer to the intensive care unit (ICU) and demographics.ResultsDespite similar emergency department daily attendance rates, fewer patients were admitted on weekends (mean admission rate 91/day vs 120/day) because of fewer general practitioner referrals. Weekend admissions were sicker than weekday (mean NEWS 1.8 vs 1.7, p=0.008), more likely to undergo transfer to ICU within 24 hours (4.2% vs 3.0%), spent longer in hospital (median 3 days vs 2 days) and less likely to experience same-day discharge (17.2% vs 21.9%) (all p values The crude 30-day postadmission mortality ratio for weekend admission (OR=1.13; 95% CI 1.08 to 1.19) was attenuated using standard adjustment (OR=1.11; 95% CI 1.05 to 1.17). In patients for whom NEWS values were available (90%), the crude OR (1.07; 95% CI 1.01 to 1.13) was not affected with standard adjustment. Adjustment using NEWS alone nullified the weekend effect (OR=1.02; 0.96–1.08).NEWS completion rates were higher on weekends (91.7%) than weekdays (89.5%). Missing NEWS was associated with direct transfer to intensive care bypassing electronic data capture. Missing NEWS in non-ICU weekend patients was associated with a higher mortality and fewer same-day discharges than weekdays.ConclusionsPatients admitted to hospital on weekends are sicker than those admitted on weekdays. The cause of the weekend effect may lie in community services.

This report presents the Consolidated Standards of Reporting Trials (CONSORT) extension for the stepped wedge cluster randomised trial (SW-CRT). The SW-CRT involves randomisation of clusters to different sequences that dictate the order (or timing) at which each cluster will switch to the intervention condition. The statement was developed to allow for the unique characteristics of this increasingly used study design. The guideline was developed using a Delphi survey and consensus meeting; and is informed by the CONSORT statements for individual and cluster randomised trials. Reporting items along with explanations and examples are provided. We include a glossary of terms, and explore the key properties of the SW-CRT which require special consideration in their reporting.\ud \ud

Summary Background Emergency abdominal surgery is associated with poor patient outcomes. We studied the effectiveness of a national quality improvement (QI) programme to implement a care pathway to improve survival for these patients. Methods We did a stepped-wedge cluster-randomised trial of patients aged 40 years or older undergoing emergency open major abdominal surgery. Eligible UK National Health Service (NHS) hospitals (those that had an emergency general surgical service, a substantial volume of emergency abdominal surgery cases, and contributed data to the National Emergency Laparotomy Audit) were organised into 15 geographical clusters and commenced the QI programme in a random order, based on a computer-generated random sequence, over an 85-week period with one geographical cluster commencing the intervention every 5 weeks from the second to the 16th time period. Patients were masked to the study group, but it was not possible to mask hospital staff or investigators. The primary outcome measure was mortality within 90 days of surgery. Analyses were done on an intention-to-treat basis. This study is registered with the ISRCTN registry, number ISRCTN80682973. Findings Treatment took place between March 3, 2014, and Oct 19, 2015. 22 754 patients were assessed for elegibility. Of 15 873 eligible patients from 93 NHS hospitals, primary outcome data were analysed for 8482 patients in the usual care group and 7374 in the QI group. Eight patients in the usual care group and nine patients in the QI group were not included in the analysis because of missing primary outcome data. The primary outcome of 90-day mortality occurred in 1210 (16%) patients in the QI group compared with 1393 (16%) patients in the usual care group (HR 1·11, 0·96–1·28). Interpretation No survival benefit was observed from this QI programme to implement a care pathway for patients undergoing emergency abdominal surgery. Future QI programmes should ensure that teams have both the time and resources needed to improve patient care. Funding National Institute for Health Research Health Services and Delivery Research Programme.

BackgroundIn this UK study, we investigated the impact of computerised physician order entry (CPOE) and clinical decision support (CDS) implementation on the rate of 78 high-risk prescribing errors amenable to CDS.MethodsWe conducted a preintervention/postintervention study in three acute hospitals in England. A predefined list of prescribing errors was incorporated into an audit tool. At each site, approximately 4000 prescriptions were reviewed both pre-CPOE and 6 months post-CPOE implementation. The number of opportunities for error and the number of errors that occurred were collated. Error rates were then calculated and compared between periods, as well as by the level of CDS.ResultsThe prescriptions of 1244 patients were audited pre-CPOE and 1178 post-CPOE implementation. A total of 28 526 prescriptions were reviewed, with 21 138 opportunities for error identified based on 78 defined errors. Across the three sites, for those prescriptions where opportunities for error were identified, the error rate was found to reduce significantly post-CPOE implementation, from 5.0% to 4.0% (PConclusionsImplementation of CPOE with CDS was associated with clinically important reductions in the rate of high-risk prescribing errors. Given the pre-post design, these findings however need to be interpreted with caution. The occurrence of errors was found to be highly dependent on the level of restriction of CDS presented to the prescriber, with the effect that different configurations of the same CPOE system can produce very different results.

IntroductionThis protocol concerns the evaluation of increased specialist staffing at weekends in hospitals in England. Seven-day health services are a key policy for the UK government and other health systems trying to improve use of infrastructure and resources. A particular motivation for the 7-day policy has been the observed increase in the risk of death associated with weekend admission, which has been attributed to fewer hospital specialists being available at weekends. However, the causes of the weekend effect have not been adequately characterised; many of the excess deaths associated with the ‘weekend effect’ may not be preventable, and the presumed benefits of improved specialist cover might be offset by the cost of implementation.Methods/designThe Bayesian-founded method we propose will consist of four major steps. First, the development of a qualitative causal model. Specialist presence can affect multiple, interacting causal processes. One or more models will be developed from the results of an expert elicitation workshop and probabilities elicited for each model and relevant model parameters. Second, systematic review of the literature. The model from the first step will provide search limits for a review to identify relevant studies. Third, a statistical model for the effects of specialist presence on care quality and patient outcomes. Fourth, valuation of outcomes. The expected net benefits of different levels of specialist intensity will then be evaluated with respect to the posterior distributions of the parameters.Ethics and disseminationThe study was approved by the Review Subcommittee of the South West Wales REC on 11 November 2013. Informed consent was not required for accessing anonymised patient case records from which patient identifiers had been removed. The findings of this study will be published in peer-reviewed journals; the outputs from this research will also form part of the project report to the HS&DR Programme Board.

Background\ud Standardised mortality ratios do not provide accurate measures of preventable mortality. This has generated interest in using case-notes to assess the preventable component of mortality. But different methods of measurement have not been compared. We compared the reliability of two scales for assessing preventability and the correspondence between them.\ud Methods\ud Medical specialists reviewed case-notes of patients who had died in hospital using two instruments: a five-point Likert scale and a continuous (0-100) scale of preventability. To enhance generalisability we used two different hospital datasets with different types of acute medical patients across different epochs and in two jurisdictions (UK and US). We investigated the reliability of measurement and correspondence of preventability estimates across the two scales. Ordinal mixed effects regression methods were used to analyse the Likert scale and to calibrate it against the continuous scale. We report the estimates of the probability a death could have been prevented accounting for reviewer inconsistency.\ud Results \ud Correspondence between the two scales was strong; the Likert categories explained most of the variation (76% UK, 73% US) in the continuous scale. Measurement reliability was low but similar across the two instruments in each dataset (intra-class correlation 0.27 UK, 0.23 US). Adjusting for the inconsistency of reviewer judgements reduced the proportion of cases with high preventability, such that the proportion of all deaths judged probably or definitely preventable on the balance of probability was under 1%.\ud Conclusions \ud The correspondence is high between a Likert and continuous scale, although the low reliability of both would suggest careful measurement design would be needed to use either scale. Few to no cases are above the threshold when using a balance of probability approach to determining a preventable death, and in any case there is little evidence supporting anything more than an ordinal correspondence between these reviewer estimates of probability and the true probability. Thus, it would be more defensible to use them as an ordinal measure of the quality of care received by patients who died in the hospital.\ud

Unfortunately, the original version of this article [1] contained an error in abstract S1. The corresponding author for the abstract ‘Gabriele Meyer’ was included in the 'Correspondence' section but accidentally omitted from the author list. The correct author list should be as below: Gabriele Meyer1*, Sascha Kopke2, Jane Noyes3, Jackie Chandler4 1Martin Luther University Halle-Wittenberg, Magdeburger Str. 8, D-06112 Halle (Saale), Germany 2University of Lubeck, Germany 3Bangor University, UK 4Cochrane Collaboration, Oxford, UK Correspondence: Gabriele Meyer (Gabriele.Meyer@medizin.uni-halle.de) – Martin Luther University Halle-Wittenberg, Magdeburger Str. 8, D-06112 Halle (Saale), Germany

Background We explored the use of routine blood tests and national early warning scores (NEWS) reported within ±24 hours of admission to predict in-hospital mortality in emergency admissions, using empirical decision Tree models because they are intuitive and may ultimately be used to support clinical decision making. Methodology A retrospective analysis of adult emergency admissions to a large acute hospital during April 2009 to March 2010 in the West Midlands, England, with a full set of index blood tests results (albumin, creatinine, haemoglobin, potassium, sodium, urea, white cell count and an index NEWS undertaken within ±24 hours of admission). We developed a Tree model by randomly splitting the admissions into a training (50%) and validation dataset (50%) and assessed its accuracy using the concordance (c-) statistic. Emergency admissions (about 30%) did not have a full set of index blood tests and/or NEWS and so were not included in our analysis. Results There were 23248 emergency admissions with a full set of blood tests and NEWS with an in-hospital mortality of 5.69%. The Tree model identified age, NEWS, albumin, sodium, white cell count and urea as significant (p

Risk-adjustment schemes are used to monitor hospital performance, on the assumption that excess mortality not explained by case mix is largely attributable to suboptimal care. We have developed a model to\ud estimate the proportion of the variation in standardised mortality ratios (SMRs) that can be accounted for by variation in preventable mortality. The model was populated with values from the literature to estimate a\ud predictive value of the SMR in this context— specifically the proportion of those hospitals with SMRs among the highest 2.5% that fall among the worst 2.5% for preventable mortality. The extent to which SMRs reflect preventable mortality rates is highly sensitive to the proportion of deaths that are preventable. If 6% of hospital deaths are preventable (as suggested by the literature), the predictive value of\ud the SMR can be no greater than 9%. This value could rise to 30%, if 15% of deaths are preventable. The model offers a ‘reality check’ for case mix adjustment schemes designed to isolate the preventable\ud component of any outcome rate.

Objective To independently evaluate the impact of the second phase of the Health Foundation’s Safer Patients Initiative (SPI2) on a range of patient safety measures.\ud \ud Design A controlled before and after design. Five substudies: survey of staff attitudes; review of case notes from high risk (respiratory) patients in medical wards; review of case notes from surgical patients; indirect evaluation of hand hygiene by measuring hospital use of handwashing materials; measurement of outcomes (adverse events, mortality among high risk patients admitted to medical wards, patients’ satisfaction, mortality in intensive care, rates of hospital acquired infection).\ud \ud Setting NHS hospitals in England.\ud \ud Participants Nine hospitals participating in SPI2 and nine matched control hospitals.\ud \ud Intervention The SPI2 intervention was similar to the SPI1, with somewhat modified goals, a slightly longer intervention period, and a smaller budget per hospital.\ud \ud Results One of the scores (organisational climate) showed a significant (P=0.009) difference in rate of change over time, which favoured the control hospitals, though the difference was only 0.07 points on a five point scale. Results of the explicit case note reviews of high risk medical patients showed that certain practices improved over time in both control and SPI2 hospitals (and none deteriorated), but there were no significant differences between control and SPI2 hospitals. Monitoring of vital signs improved across control and SPI2 sites. This temporal effect was significant for monitoring the respiratory rate at both the six hour (adjusted odds ratio 2.1, 99% confidence interval 1.0 to 4.3; P=0.010) and 12 hour (2.4, 1.1 to 5.0; P=0.002) periods after admission. There was no significant effect of SPI for any of the measures of vital signs. Use of a recommended system for scoring the severity of pneumonia improved from 1.9% (1/52) to 21.4% (12/56) of control and from 2.0% (1/50) to 41.7% (25/60) of SPI2 patients. This temporal change was significant (7.3, 1.4 to 37.7; P=0.002), but the difference in difference was not significant (2.1, 0.4 to 11.1; P=0.236). There were no notable or significant changes in the pattern of prescribing errors, either over time or between control and SPI2 hospitals. Two items of medical history taking (exercise tolerance and occupation) showed significant improvement over time, across both control and SPI2 hospitals, but no additional SPI2 effect. The holistic review showed no significant changes in error rates either over time or between control and SPI2 hospitals. The explicit case note review of perioperative care showed that adherence rates for two of the four perioperative standards targeted by SPI2 were already good at baseline, exceeding 94% for antibiotic prophylaxis and 98% for deep vein thrombosis prophylaxis. Intraoperative monitoring of temperature improved over time in both groups, but this was not significant (1.8, 0.4 to 7.6; P=0.279), and there were no additional effects of SPI2. A dramatic rise in consumption of soap and alcohol hand rub was similar in control and SPI2 hospitals (P=0.760 and P=0.889, respectively), as was the corresponding decrease in rates of Clostridium difficile and meticillin resistant Staphylococcus aureus infection (P=0.652 and P=0.693, respectively). Mortality rates of medical patients included in the case note reviews in control hospitals increased from 17.3% (42/243) to 21.4% (24/112), while in SPI2 hospitals they fell from 10.3% (24/233) to 6.1% (7/114) (P=0.043). Fewer than 8% of deaths were classed as avoidable; changes in proportions could not explain the divergence of overall death rates between control and SPI2 hospitals. There was no significant difference in the rate of change in mortality in intensive care. Patients’ satisfaction improved in both control and SPI2 hospitals on all dimensions, but again there were no significant changes between the two groups of hospitals.\ud \ud Conclusions Many aspects of care are already good or improving across the NHS in England, suggesting considerable improvements in quality across the board. These improvements are probably due to contemporaneous policy activities relating to patient safety, including those with features similar to the SPI, and the emergence of professional consensus on some clinical processes. This phenomenon might have attenuated the incremental effect of the SPI, making it difficult to detect. Alternatively, the full impact of the SPI might be observable only in the longer term. The conclusion of this study could have been different if concurrent controls had not been used.

Background and objective Utilities (values representing preferences) for healthcare priority setting are typically obtained indirectly by asking patients to fill in a quality of life questionnaire and then converting the results to a utility using population values. We compared such utilities with those obtained directly from patients or the public. Design Review of studies providing both a direct and indirect utility estimate. Selection criteria Papers reporting comparisons of utilities obtained directly (standard gamble or time trade off) or indirectly (European quality of life 5D [EQ-5D], short form 6D [SF-6D], or health utilities index [HUI]) from the same patient. Data sources PubMed and Tufts database of utilities. Statistical methods Sign test for paired comparisons between direct and indirect utilities; least squares regression to describe average relations between the different methods. Main outcome measures Mean utility scores (or median if means unavailable) for each method, and differences in mean (median) scores between direct and indirect methods. Results We found 32 studies yielding 83 instances where direct and indirect methods could be compared for health states experienced by adults. The direct methods used were standard gamble in 57 cases and time trade off in 60 (34 used both); the indirect methods were EQ-5D (67 cases), SF-6D (13), HUI-2 (5), and HUI-3 (37). Mean utility values were 0.81 (standard gamble) and 0.77 (time trade off) for the direct methods; for the indirect methods: 0.59 (EQ-5D), 0.63 (SF-6D), 0.75 (HUI-2) and 0.68 (HUI-3). Discussion Direct methods of estimating utilities tend to result in higher health ratings than the more widely used indirect methods, and the difference can be substantial. Use of indirect methods could have important implications for decisions about resource allocation: for example, non-lifesaving treatments are relatively more favoured in comparison with lifesaving interventions than when using direct methods.

Objectives:Medical device companies are under growing pressure to provide health-economic evaluations of their products. Cost-effectiveness analyses are commonly undertaken as a one-off exercise at the late stage of development of new technologies; however, the benefits of an iterative use of economic evaluation during the development process of new products have been acknowledged in the literature. Furthermore, the use of Bayesian methods within health technology assessment has been shown to be of particular value in the dynamic framework of technology appraisal when new information becomes available in the life cycle of technologies.Methods:In this study, we set out a methodology to adapt these methods for their application to directly support investment decisions in a commercial setting from early stages of the development of new medical devices.Results and Conclusions:Starting with relatively simple analysis from the very early development phase and proceeding to greater depth of analysis at later stages, a Bayesian approach facilitates the incorporation of all available evidence and would help companies to make better informed choices at each decision point.

Results The use of the SW-CRT is rapidly increasing and that areas of use are diverse. We illustrate how the design is being used to evaluate the effectiveness of a complex intervention, being rolled-out across 90 UK hospitals, to reduce mortality in patients undergoing emergency laparotomy. Quality of reporting is found to be low. In a SW-CRT more clusters are exposed to the intervention towards the end of the study than in its early stages. A result which prima facia might look to be suggestive of an effect of the intervention may therefore transpire to be the result of a positive underlying temporal trend. A large number of studies do not report how they allowed for temporal trends in the design or analysis.

Background: At the concept stage, many uncertainties surround the commercial viability of a new medical device. These include the ultimate functionality of the device, the cost of producing it and whether, and at what price, it can be sold to a health-care provider (HCP). Simple assessments of value can be made by estimating such unknowns, but the levels of uncertainty may mean that their operational value for investment decisions is unclear. However, many decisions taken at the concept stage are reversible and will be reconsidered later before the product is brought to market. This flexibility can be exploited to enhance early-stage valuations. Objectives: To develop a framework for valuing a new medical device at the concept stage that balances benefit to the HCP against commercial costs. This is done within a simplified stage-gated model of the development cycle for new products. The approach is intended to complement existing proposals for the evaluation of the commercial headroom available to new medical products. Conclusions: A model based on two decision gates can lead to lower bounds (underestimates) for product value that can serve to support a decision to develop the product. Quantifiable uncertainty that can be resolved before the device is brought to market will generally enhance early-stage valuations of the device, and this remains true even when some components of uncertainty cannot be fully described. Clinical trials and other evidence-gathering activities undertaken as part of the development process can contribute to early-stage estimates of value.

BackgroundTo examine the effects of physical activity on the development and progression of microvascular complications in patients with type 1 diabetes.MethodsA retrospective analysis of data from the Diabetes Control and Complications trial was undertaken. Physical activity data was collected at baseline for each of 1441 recruits, converted to metabolic equivalent of task values, and categorised according to the American College of Sports Medicine recommendations. The rates of development/progression of diabetic retinopathy, nephropathy and neuropathy were compared in those who achieved over twice recommended, up to twice recommended, and less than recommended metabolic equivalent of task levels of activity. The DCCT study had a mean duration of follow up of 6.5 years ending in 1993.ResultsA total of 271 subjects had a sustained three-step progression in diabetic retinopathy. The rates of development or progression of retinopathy showed no significant association with physical activity level. The number of outcomes for nephropathy and neuropathy were small and there was no significant association with physical activity level.ConclusionsWe found no evidence that physical activity improves microvascular outcomes in type 1 diabetes. However we demonstrate no evidence of harm. We suggest that physical activity continues to play an important role in the management of type 1 diabetes.

Background Liver function tests (LFTs) are ordered in large numbers in primary care, and the Birmingham and Lambeth Liver Evaluation Testing Strategies (BALLETS) study was set up to assess their usefulness in patients with no pre-existing or self-evident liver disease. All patients were tested for chronic viral hepatitis thereby providing an opportunity to compare various strategies for detection of this serious treatable disease. Methods This study uses data from the BALLETS cohort to compare various testing strategies for viral hepatitis in patients who had received an abnormal LFT result. The aim was to inform a strategy for identification of patients with chronic viral hepatitis. We used a cost-minimisation analysis to define a base case and then calculated the incremental cost per case detected to inform a strategy that could guide testing for chronic viral hepatitis. Results Of the 1,236 study patients with an abnormal LFT, 13 had chronic viral hepatitis (nine hepatitis B and four hepatitis C). The strategy advocated by the current guidelines (repeating the LFT with a view to testing for specific disease if it remained abnormal) was less efficient (more expensive per case detected) than a simple policy of testing all patients for viral hepatitis without repeating LFTs. A more selective strategy of viral testing all patients for viral hepatitis if they were born in countries where viral hepatitis was prevalent provided high efficiency with little loss of sensitivity. A notably high alanine aminotransferase (ALT) level (greater than twice the upper limit of normal) on the initial ALT test had high predictive value, but was insensitive, missing half the cases of viral infection. Conclusions Based on this analysis and on widely accepted clinical principles, a "fast and frugal" heuristic was produced to guide general practitioners with respect to diagnosing cases of viral hepatitis in asymptomatic patients with abnormal LFTs. It recommends testing all patients where a clear clinical indication of infection is present (e.g. evidence of intravenous drug use), followed by testing all patients who originated from countries where viral hepatitis is prevalent, and finally testing those who have a notably raised ALT level (more than twice the upper limit of normal). Patients not picked up by this efficient algorithm had a risk of chronic viral hepatitis that is lower than the general population.

Background Cluster randomised controlled trials (CRCTs) are frequently used in health service evaluation. Assuming an average cluster size, required sample sizes are readily computed for both binary and continuous outcomes, by estimating a design effect or inflation factor. However, where the number of clusters are fixed in advance, but where it is possible to increase the number of individuals within each cluster, as is frequently the case in health service evaluation, sample size formulae have been less well studied. Methods We systematically outline sample size formulae (including required number of randomisation units, detectable difference and power) for CRCTs with a fixed number of clusters, to provide a concise summary for both binary and continuous outcomes. Extensions to the case of unequal cluster sizes are provided. Results For trials with a fixed number of equal sized clusters (k), the trial will be feasible provided the number of clusters is greater than the product of the number of individuals required under individual randomisation (nI) and the estimated intra-cluster correlation (ρ). So, a simple rule is that the number of clusters (k) will be sufficient provided: Where this is not the case, investigators can determine the maximum available power to detect the pre-specified difference, or the minimum detectable difference under the pre-specified value for power. Conclusions Designing a CRCT with a fixed number of clusters might mean that the study will not be feasible, leading to the notion of a minimum detectable difference (or a maximum achievable power), irrespective of how many individuals are included within each cluster.

Methods We consider a meta-analysis of nine randomised Phase II trials comparing the efficacy of two therapies for acute myocardial infarction. Results for four outcomes were collected: intracranial haemorrhage, stroke, reinfarction and total mortality. We apply univariate and multivariate random-effects meta-analysis methods, and use the obtained summary results to derive 95% prediction intervals, which give the predicted treatment effects for the four outcomes in a future trial. The multivariate approach jointly synthesizes all outcomes whilst accounting for their correlation. The methods are applicable in both frequentist and Bayesian frameworks. Predictions calculated are compared to results from subsequent Phase III trials.

The stepped wedge research design is becoming increasingly popular, particularly in the field of implementation science. It is a form of cluster randomised controlled trial with unidirectional cross-over (normally from control to intervention). This trial design may be biased however because the effect of calendar time is unbalanced between control and intervention periods. Hence there is concern that this design may produce biased results compared to using a parallel cluster randomised controlled trial. Authors have previously compared these two designs on the grounds of data collection burden and cost. However, it is arguably more important to compare these designs in terms of whether they are equally likely to generate results that are free from bias. This paper discusses the potential sources of bias relevant to these designs, examines how empirical evidence of bias has previously been generated, and then outlines the “within-wedge” analysis approach - a new method for generating evidence of potential bias in the stepped-wedge design. There have been four strategies previously used to generate empirical evidence of bias with different research designs. These include; i) direct comparison of results from trials that have used different designs to answer the same question, ii) meta-epidemiology, iii) resampling from existing studies, and iv) resampling from custom-developed datasets. Each approach has strengths and limitations in the evidence they can generate. For example, approach i) requires minimal variation in the study designs and populations in order to minimise confounding when making comparisons, while approach ii) requires data from large numbers of studies to be gathered. The within-wedge analysis approach is a variation on approach i) made possible through the realisation that data from a parallel cluster randomised trial is hidden within a stepped wedge design. The two effect estimates generated (one from the stepped-wedge design, one from the parallel cluster trial design) can be compared in a ratio of ratios. The within-wedge analysis approach has an advantage over approach i) in that many study characteristics are held constant, and an advantage over approach ii) in that this approach can be applied to individual studies (and to multiple outcomes within individual studies). Meta-regression can be applied to within-wedge analysis outcomes to identify situations that may make stepped-wedge designs more or less prone to bias. We recommend that the within-wedge analysis reported as a secondary analysis from stepped-wedge designs in future.