RACE-IT - Rapid Acute Coronary Syndrome Exclusion using the Beckman Coulter Access high-sensitivity cardiac troponin I: A stepped-wedge cluster randomized trial.
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ABSTRACT: Background
Protocols utilizing high-sensitivity cardiac troponin (hs-cTn) assays for the evaluation of suspected acute coronary syndrome (ACS) in the emergency department (ED) have been gaining popularity across the US and the world. These protocols more rapidly rule-out ACS and more accurately identify the presence of acute myocardial injury. At this time, few randomized trials have evaluated the safety and operational impact of these assays, resulting in limited evidence to guide the use and implementation of hs-cTn in the ED.Objective
The main study objective is to test the effectiveness of a rapid ACS rule-out pathway using hs-cTnI in safely discharging patients from the ED for whom clinical suspicion for ACS exists.Design
This prospective, implementation trial (n = 11,070) will utilize a stepped wedge cluster randomized trial design. The design will allow for all participating sites to capture benefit from the implementation of the hs-cTnI pathway while providing data evaluating the effectiveness in providing safe and rapid evaluation of patients with clinical suspicion for ACS.Summary
Demonstrating that clinical pathways using hs-cTnI can be effectively implemented to rapidly rule-out ACS while conserving costly hospital resources has significant implications for the care of patients with possible acute cardiac conditions in EDs across the US.Clinicaltrialsgov identifier
NCT04488913.
SUBMITTER: Miller J
PROVIDER: S-EPMC8114080 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundHigh-sensitivity cardiac troponin assays enable myocardial infarction to be ruled out earlier, but the safety and efficacy of this approach is uncertain. We investigated whether an early rule-out pathway is safe and effective for patients with suspected acute coronary syndrome.MethodsWe performed a stepped-wedge cluster randomized controlled trial in the emergency departments of 7 acute care hospitals in Scotland. Consecutive patients presenting with suspected acute coronary syndrome between December 2014 and December 2016 were included. Sites were randomized to implement an early rule-out pathway where myocardial infarction was excluded if high-sensitivity cardiac troponin I concentrations were <5 ng/L at presentation. During a previous validation phase, myocardial infarction was ruled out when troponin concentrations were <99th percentile at 6 to 12 hours after symptom onset. The coprimary outcome was length of stay (efficacy) and myocardial infarction or cardiac death after discharge at 30 days (safety). Patients were followed for 1 year to evaluate safety and other secondary outcomes.ResultsWe enrolled 31 492 patients (59±17 years of age [mean±SD]; 45% women) with troponin concentrations <99th percentile at presentation. Length of stay was reduced from 10.1±4.1 to 6.8±3.9 hours (adjusted geometric mean ratio, 0.78 [95% CI, 0.73-0.83]; P<0.001) after implementation and the proportion of patients discharged increased from 50% to 71% (adjusted odds ratio, 1.59 [95% CI, 1.45-1.75]). Noninferiority was not demonstrated for the 30-day safety outcome (upper limit of 1-sided 95% CI for adjusted risk difference, 0.70% [noninferiority margin 0.50%]; P=0.068), but the observed differences favored the early rule-out pathway (0.4% [57/14 700] versus 0.3% [56/16 792]). At 1 year, the safety outcome occurred in 2.7% (396/14 700) and 1.8% (307/16 792) of patients before and after implementation (adjusted odds ratio, 1.02 [95% CI, 0.74-1.40]; P=0.894), and there were no differences in hospital reattendance or all-cause mortality.ConclusionsImplementation of an early rule-out pathway for myocardial infarction reduced length of stay and hospital admission. Although noninferiority for the safety outcome was not demonstrated at 30 days, there was no increase in cardiac events at 1 year. Adoption of this pathway would have major benefits for patients and health care providers. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03005158.
| S-EPMC8177493 | biostudies-literature
Project description:BackgroundHigh-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 findings question whether the diagnostic threshold for myocardial infarction should be based on the 99th centile derived from a normal reference population.FundingThe British Heart Foundation.
| S-EPMC6137538 | biostudies-literature
Project description:ObjectivesWe evaluated and defined the analytical performance of the Beckman Coulter DxC 700 AU analyzer compared to the Siemens Dimension Vista 500 analyzer.Designand Methods: Performance characteristics included intra and inter-run precision, linearity/analytical measurement range, method correlation, and reference range verification. A total of 53 assays including 11 critical care, 19 general chemistries, 11 proteins, 10 urines, and 2 CSF analytes were tested. We also evaluated similarities and differences in assay methodologies between the 2 systems.ResultsThe DxC 700 AU demonstrated excellent precision, comparable analytical measurement ranges and strong method correlation with the Dimension Vista 500 for most serum/plasma assays. 95% of the intra-run and 95% of the inter-run precision QC levels showed <3.0%CV and <6.0%CV, respectively. None of the deviations were clinically significant. The AMRs for all analytes except 5 met the manufacturer's stated range. ALP, Lactate, U-glucose and CSF-glucose all recovered above the stated upper limit range, while prealbumin showed a smaller range. All analytes, except 14, showed slopes between 0.9 and 1.1 and/or biases <10%. Only ammonia, ferritin and lipase required significant reference range changes. The urine and CSF assays correlated very well with no adjustments in reference ranges required.ConclusionsThe analytical performance of the DxC 700 AU analyzer was acceptable with only a small number of analytes requiring significant reference range changes.
| S-EPMC6909053 | biostudies-literature
Project description:Numerous publications have now addressed the principles of designing, analyzing, and reporting the results of stepped-wedge cluster randomized trials. In contrast, there is little research available pertaining to the design and analysis of multiarm stepped-wedge cluster randomized trials, utilized to evaluate the effectiveness of multiple experimental interventions. In this paper, we address this by explaining how the required sample size in these multiarm trials can be ascertained when data are to be analyzed using a linear mixed model. We then go on to describe how the design of such trials can be optimized to balance between minimizing the cost of the trial and minimizing some function of the covariance matrix of the treatment effect estimates. Using a recently commenced trial that will evaluate the effectiveness of sensor monitoring in an occupational therapy rehabilitation program for older persons after hip fracture as an example, we demonstrate that our designs could reduce the number of observations required for a fixed power level by up to 58%. Consequently, when logistical constraints permit the utilization of any one of a range of possible multiarm stepped-wedge cluster randomized trial designs, researchers should consider employing our approach to optimize their trials efficiency.
| S-EPMC6491976 | biostudies-literature
Project description:BACKGROUND:Cluster randomised trials with unequal sized clusters often have lower precision than with clusters of equal size. To allow for this, sample sizes are inflated by a modified version of the design effect for clustering. These inflation factors are valid under the assumption that randomisation is stratified by cluster size. We investigate the impact of unequal cluster size when that constraint is relaxed, with particular focus on the stepped-wedge cluster randomised trial, where this is more difficult to achieve. METHODS:Assuming a multi-level mixed effect model with exchangeable correlation structure for a cross-sectional design, we use simulation methods to compare the precision for a trial with clusters of unequal size to a trial with clusters of equal size (relative efficiency). For a range of scenarios we illustrate the impact of various design features (the cluster-mean correlation - a function of the intracluster correlation and the cluster size, the number of clusters, number of randomisation sequences) on the average and distribution of the relative efficiency. RESULTS:Simulations confirm that the average reduction in precision, due to varying cluster sizes, is smaller in a stepped-wedge trial compared to the parallel trial. However, the variance of the distribution of the relative efficiency is large; and is larger under the stepped-wedge design compared to the parallel design. This can result in large variations in actual power, depending on the allocation of clusters to sequences. Designs with larger variations in cluster sizes, smaller number of clusters and studies with smaller cluster-mean correlations (smaller cluster sizes or smaller intra-cluster correlation) are particularly at risk. CONCLUSION:The actual realised power in a stepped-wedge trial might be substantially higher or lower than that estimated. This is particularly important when there are a small number of clusters or the variability in cluster sizes is large. Constraining the randomisation on cluster size, where feasible, might mitigate this effect.
| S-EPMC6570871 | biostudies-other
Project description:Permutation tests are useful in stepped-wedge trials to provide robust statistical tests of intervention-effect estimates. However, the Stata command permute does not produce valid tests in this setting because individual observations are not exchangeable. We introduce the swpermute command that permutes clusters to sequences to maintain exchangeability. The command provides additional functionality to aid users in performing analyses of stepped-wedge trials. In particular, we include the option "withinperiod" that performs the specified analysis separately in each period of the study with the resulting period-specific intervention-effect estimates combined as a weighted average. We also include functionality to test non-zero null hypotheses to aid the construction of confidence intervals. Examples of the application of swpermute are given using data from a trial testing the impact of a new tuberculosis diagnostic test on bacterial confirmation of a tuberculosis diagnosis.
| S-EPMC7305031 | biostudies-literature
Project description:OBJECTIVES:To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. SETTING:Any, not limited to healthcare settings. PARTICIPANTS:Any taking part in an SW-CRT published up to March 2016. PRIMARY AND SECONDARY OUTCOME MEASURES:The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. RESULTS:Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22-0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. CONCLUSIONS:Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed.
| S-EPMC5695383 | biostudies-literature
Project description:In stepped-wedge trials (SWTs), the intervention is rolled out in a random order over more than 1 time-period. SWTs are often analysed using mixed-effects models that require strong assumptions and may be inappropriate when the number of clusters is small. We propose a non-parametric within-period method to analyse SWTs. This method estimates the intervention effect by comparing intervention and control conditions in a given period using cluster-level data corresponding to exposure. The within-period intervention effects are combined with an inverse-variance-weighted average, and permutation tests are used. We present an example and, using simulated data, compared the method to (1) a parametric cluster-level within-period method, (2) the most commonly used mixed-effects model, and (3) a more flexible mixed-effects model. We simulated scenarios where period effects were common to all clusters, and when they varied according to a distribution informed by routinely collected health data. The non-parametric within-period method provided unbiased intervention effect estimates with correct confidence-interval coverage for all scenarios. The parametric within-period method produced confidence intervals with low coverage for most scenarios. The mixed-effects models' confidence intervals had low coverage when period effects varied between clusters but had greater power than the non-parametric within-period method when period effects were common to all clusters. The non-parametric within-period method is a robust method for analysing SWT. The method could be used by trial statisticians who want to emphasise that the SWT is a randomised trial, in the common position of being uncertain about whether data will meet the assumptions necessary for mixed-effect models.
| S-EPMC6032886 | biostudies-other
Project description:BackgroundWith the increase in the number of long-term survivors, interest is shifting from cancer survival to life and quality of life after cancer. These include consequences of long-term side effects of treatment, such as gonadotoxicity. Fertility preservation is becoming increasingly important in cancer management. International recommendations agree on the need to inform patients prior to treatments about the risk of fertility impairment and refer them to specialized centers to discuss fertility preservation. However, the literature reveals suboptimal access to fertility preservation on an international scale, and particularly in France, making information for patients and oncologists a potential lever for action. Our overall goal is to improve access to fertility preservation consultations for women with breast cancer through the development and evaluation of a combined intervention targeting the access and diffusion of information for these patients and brief training for oncologists.MethodsFirstly, we will improve existing information tools and create brief training content for oncologists using a qualitative, iterative, user-centred and participatory approach (objective 1). We will then use these tools in a combined intervention to conduct a stepped-wedge cluster randomized trial (objective 2) including 750 women aged 18 to 40 newly treated with chemotherapy for breast cancer at one of the 6 participating centers. As the primary outcome of the trial will be the access to fertility preservation counselling before and after using the combined intervention (brochures and brief training for oncologists), we will compare the rate of fertility preservation consultations between the usual care and intervention phases using linear regression models. Finally, we will analyse our approach using a context-sensitive implementation analysis and provide key elements for transferability to other contexts in France (objective 3).DiscussionWe expect to observe an increase in access to fertility preservation consultations as a result of the combined intervention. Particular attention will be paid to the effect of this intervention on socially disadvantaged women, who are known to be at greater risk of inappropriate treatment. The user-centred design principles and participatory approaches used to optimize the acceptability, usability and feasibility of the combined intervention will likely enhance its impact, diffusion and sustainability.Trial registrationRegistry: ClinicalTrials.gov.Trial registration numberNCT05989776. Date of registration: 7th September 2023. URL: https://classic.Clinicaltrialsgov/ct2/show/NCT05989776 .Protocol versionManuscript based on study protocol version 2.0, 21st may 2023.
| S-EPMC10797742 | biostudies-literature
Project description:Standard sample size calculation formulas for stepped wedge cluster randomized trials (SW-CRTs) assume that cluster sizes are equal. When cluster sizes vary substantially, ignoring this variation may lead to an under-powered study. We investigate the relative efficiency of a SW-CRT with varying cluster sizes to equal cluster sizes, and derive variance estimators for the intervention effect that account for this variation under a mixed effects model-a commonly used approach for analyzing data from cluster randomized trials. When cluster sizes vary, the power of a SW-CRT depends on the order in which clusters receive the intervention, which is determined through randomization. We first derive a variance formula that corresponds to any particular realization of the randomized sequence and propose efficient algorithms to identify upper and lower bounds of the power. We then obtain an "expected" power based on a first-order approximation to the variance formula, where the expectation is taken with respect to all possible randomization sequences. Finally, we provide a variance formula for more general settings where only the cluster size arithmetic mean and coefficient of variation, instead of exact cluster sizes, are known in the design stage. We evaluate our methods through simulations and illustrate that the average power of a SW-CRT decreases as the variation in cluster sizes increases, and the impact is largest when the number of clusters is small.
| S-EPMC7165039 | biostudies-literature