Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial’s course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented.We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. This tutorial paper provides guidance on key aspects of adaptive designs that are relevant to clinical triallists. We explain the basic rationale behind adaptive designs, clarify ambiguous terminology and summarise the utility and pitfalls of adaptive designs. We discuss practical aspects around funding, ethical approval, treatment supply and communication with stakeholders and trial participants. Our focus, however, is on the interpretation and reporting of results from adaptive design trials, which we consider vital for anyone involved in medical research. We emphasise the general principles of transparency and reproducibility and suggest how best to put them into practice.

The third most common stroke complication is infection. We studied the rates of aspiration pneumonia and urinary tract infection (UTI), their risk factors and their effect on outcome in the 1455 Glycine Antagonist (Gavestinel) in Neuroprotection (GAIN) International patients with ischaemic stroke. Forward stepwise logistic regression and Cox proportional hazards modelling identified baseline factors that predicted events and the independent effect of events up to day 7 on poor stroke outcome at 3 months in patients alive at day 7, after correcting for prognostic factors. Higher baseline National Institute of Health Stroke Scale (NIHSS) and age, male gender, history of diabetes and stroke subtype predicted pneumonia, which occurred in 13.6% of patients. Female gender and higher baseline NIHSS and age predicted UTI, which occurred in 17.2% of patients. Pneumonia was associated with poor outcome by mortality (hazard ratio, 2.2; 95% confidence interval, 1.5-3.3), Barthel index (<60) (odds ratio, 3.8; 2.2-6.7), NIHSS (4.9; 1.7-14) and Rankin scale (>/=2) (3.4; 1.4-8.3). UTI was associated with Barthel index (1.9; 1.2-2.9), NIHSS (2.2; 1.2-4.0) and Rankin scale (3.1; 1.6-4.9). Pneumonia and UTI are independently associated with stroke poor outcome. Patients with identified risk factors must be closely monitored for infection.

Interpretation of these results is complicated by methodological factors including variations in study populations, upper limb motor outcome scales, timing of baseline and outcome assessments and predictors selected. The most important predictive factors for upper limb recovery following stroke appears to the initial severity of motor impairment or function.

SummaryBackgroundHigh-sensitivity cardiac troponin assays permit use of lower thresholds for the diagnosis of myocardial infarction, but whether this improves clinical outcomes is unknown. We aimed to determine whether the introduction of a high-sensitivity cardiac troponin I (hs-cTnI) assay with a sex-specific 99th centile diagnostic threshold would reduce subsequent myocardial infarction or cardiovascular death in patients with suspected acute coronary syndrome.MethodsIn this stepped-wedge, cluster-randomised controlled trial across ten secondary or tertiary care hospitals in Scotland, we evaluated the implementation of an hs-cTnI assay in consecutive patients who had been admitted to the hospitals' emergency departments with suspected acute coronary syndrome. Patients were eligible for inclusion if they presented with suspected acute coronary syndrome and had paired cardiac troponin measurements from the standard care and trial assays. During a validation phase of 6–12 months, results from the hs-cTnI assay were concealed from the attending clinician, and a contemporary cardiac troponin I (cTnI) assay was used to guide care. Hospitals were randomly allocated to early (n=5 hospitals) or late (n=5 hospitals) implementation, in which the high-sensitivity assay and sex-specific 99th centile diagnostic threshold was introduced immediately after the 6-month validation phase or was deferred for a further 6 months. Patients reclassified by the high-sensitivity assay were defined as those with an increased hs-cTnI concentration in whom cTnI concentrations were below the diagnostic threshold on the contemporary assay. The primary outcome was subsequent myocardial infarction or death from cardiovascular causes at 1 year after initial presentation. Outcomes were compared in patients reclassified by the high-sensitivity assay before and after its implementation by use of an adjusted generalised linear mixed model. This trial is registered with ClinicalTrials.gov, number NCT01852123.FindingsBetween June 10, 2013, and March 3, 2016, we enrolled 48 282 consecutive patients (61 [SD 17] years, 47% women) of whom 10 360 (21%) patients had cTnI concentrations greater than those of the 99th centile of the normal range of values, who were identified by the contemporary assay or the high-sensitivity assay. The high-sensitivity assay reclassified 1771 (17%) of 10 360 patients with myocardial injury or infarction who were not identified by the contemporary assay. In those reclassified, subsequent myocardial infarction or cardiovascular death within 1 year occurred in 105 (15%) of 720 patients in the validation phase and 131 (12%) of 1051 patients in the implementation phase (adjusted odds ratio for implementation vs validation phase 1·10, 95% CI 0·75 to 1·61; p=0·620).InterpretationUse of a high-sensitivity assay prompted reclassification of 1771 (17%) of 10 360 patients with myocardial injury or infarction, but was not associated with a lower subsequent incidence of myocardial infarction or cardiovascular death at 1 year. Our finding...

Background and Purpose-Serum urate concentration is associated with cardiovascular disease, and hyperuricemia predicts first-ever stroke. We explored the association of admission urate level with mortality, placement, and risk of further vascular events after acute stroke. Methods-In patients with ischemic stroke or primary intracranial hemorrhage, we determined the association of urate level with 90-day placement (alive at home, good outcome; dead or living in care, poor outcome) and with the subsequent occurrence of ischemic stroke, myocardial infarction, or vascular death. In multivariate analysis (logistic regression for 90-day placement, proportional-hazards regression for time to further vascular event), we adjusted for stroke severity (modified National Institutes of Health stroke scale) and other clinical, biochemical, and radiological variables known to influence stroke outcome. Results-We

BackgroundRigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis.MethodsWe undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios.ResultsFor missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results.ConclusionsMethods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses.Electronic supplementary materialThe online version of this article (10.1186/s12874-018-0483-0) contains supplementary material, which is available to authorized users.

ObjectiveThe objective of this study was to compare international trends in pre-eclampsia rates and in overall pregnancy hypertension rates (including gestational hypertension, pre-eclampsia and eclampsia).DesignPopulation data (from birth and/or hospital records) on all women giving birth were available from Australia (two states), Canada (Alberta), Denmark, Norway, Scotland, Sweden and the USA (Massachusetts) for a minimum of 6 years from 1997 to 2007. All countries used the 10th revision of the International Classification of Diseases, except Massachusetts which used the 9th revision. There were no major changes to the diagnostic criteria or methods of data collection in any country during the study period. Population characteristics as well as rates of pregnancy hypertension and pre-eclampsia were compared.ResultsAbsolute rates varied across the populations as follows: pregnancy hypertension (3.6% to 9.1%), pre-eclampsia (1.4% to 4.0%) and early-onset pre-eclampsia (0.3% to 0.7%). Pregnancy hypertension and/or pre-eclampsia rates declined over time in most populations. This was unexpected given that factors associated with pregnancy hypertension such as pre-pregnancy obesity and maternal age are generally increasing. However, there was also a downward shift in gestational age with fewer pregnancies reaching 40 weeks.ConclusionThe rate of pregnancy hypertension and pre-eclampsia decreased in northern Europe and Australia from 1997 to 2007, but increased in Massachusetts. The use of a different International Classification of Diseases coding version in Massachusetts may contribute to the difference in trend. Elective delivery prior to the due date is the most likely explanation for the decrease observed in Europe and Australia. Also, the use of interventions that reduce the risk of pregnancy hypertension and/or progression to pre-eclampsia (low-dose aspirin, calcium supplementation and early delivery for mild hypertension) may have contributed to the decline.

SummaryBackground2·6 million pregnancies were estimated to have ended in stillbirth in 2015. The aim of the AFFIRM study was to test the hypothesis that introduction of a reduced fetal movement (RFM), care package for pregnant women and clinicians that increased women's awareness of the need for prompt reporting of RFM and that standardised management, including timely delivery, would alter the incidence of stillbirth.MethodsThis stepped wedge, cluster-randomised trial was done in the UK and Ireland. Participating maternity hospitals were grouped and randomised, using a computer-generated allocation scheme, to one of nine intervention implementation dates (at 3 month intervals). This date was concealed from clusters and the trial team until 3 months before the implementation date. Each participating hospital had three observation periods: a control period from Jan 1, 2014, until randomised date of intervention initiation; a washout period from the implementation date and for 2 months; and the intervention period from the end of the washout period until Dec 31, 2016. Treatment allocation was not concealed from participating women and caregivers. Data were derived from observational maternity data. The primary outcome was incidence of stillbirth. The primary analysis was done according to the intention-to-treat principle, with births analysed according to whether they took place during the control or intervention periods, irrespective of whether the intervention had been implemented as planned. This study is registered with www.ClinicalTrials.gov, number NCT01777022.Findings37 hospitals were enrolled in the study. Four hospitals declined participation, and 33 hospitals were randomly assigned to an intervention implementation date. Between Jan 1, 2014, and Dec, 31, 2016, data were collected from 409 175 pregnancies (157 692 deliveries during the control period, 23 623 deliveries in the washout period, and 227 860 deliveries in the intervention period). The incidence of stillbirth was 4·40 per 1000 births during the control period and 4·06 per 1000 births in the intervention period (adjusted odds ratio [aOR] 0·90, 95% CI 0·75–1·07; p=0·23).InterpretationThe RFM care package did not reduce the risk of stillbirths. The benefits of a policy that promotes awareness of RFM remains unproven.FundingChief Scientist Office, Scottish Government (CZH/4/882), Tommy's Centre for Maternal and Fetal Health, Sands.