The strange case of the ear and the heart: the auricular vagus nerve and its influence on cardiac control

The human ear seems an unlikely candidate for therapies aimed at improving cardiac function, but the ear and the heart share a common connection: the vagus nerve. In recent years there has been increasing interest in the auricular branch of the vagus nerve (ABVN), a unique cutaneous subdivision of the vagus distributed to the external ear. Non-invasive electrical stimulation of this nerve through the skin may offer a simple, cost-effective alternative to the established method of vagus nerve stimulation (VNS), which requires a surgical procedure and has generated mixed results in a number of clinical trials for heart failure. This review discusses the available evidence in support of modulating cardiac activity using this strange auricular nerve

A Coboundary Morphism For The Grothendieck Spectral Sequence

Given an abelian category $\mathcal{A}$ with enough injectives we show that a short exact sequence of chain complexes of objects in $\mathcal{A}$ gives rise to a short exact sequence of Cartan-Eilenberg resolutions. Using this we construct coboundary morphisms between Grothendieck spectral sequences associated to objects in a short exact sequence. We show that the coboundary preserves the filtrations associated with the spectral sequences and give an application of these result to filtrations in sheaf cohomology.Comment: 18 page

A priori postulated and real power in cluster randomized trials: mind the gap

BACKGROUND: Cluster randomization design is increasingly used for the evaluation of health-care, screening or educational interventions. The intraclass correlation coefficient (ICC) defines the clustering effect and be specified during planning. The aim of this work is to study the influence of the ICC on power in cluster randomized trials. METHODS: Power contour graphs were drawn to illustrate the loss in power induced by an underestimation of the ICC when planning trials. We also derived the maximum achievable power given a specified ICC. RESULTS: The magnitude of the ICC can have a major impact on power, and with low numbers of clusters, 80% power may not be achievable. CONCLUSION: Underestimating the ICC during planning cluster randomized trials can lead to a seriously underpowered trial. Publication of a priori postulated and a posteriori estimated ICCs is necessary for a more objective reading: negative trial results may be the consequence of a loss of power due to a mis-specification of the ICC

Sample size calculations for cluster randomised controlled trials with a fixed number of clusters

Background\ud 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. \ud \ud Methods\ud 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. \ud \ud Results\ud 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 ($n_i$) and the estimated intra-cluster correlation ($\rho$). So, a simple rule is that the number of clusters ($\kappa$) will be sufficient provided: \ud \ud $\kappa$ > $n_i$ x $\rho$\ud \ud 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. \ud \ud Conclusions\ud 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. \ud \u

Development and validation of a clinical prediction model for patient-reported pain and function after primary total knee replacement surgery

To develop and validate a clinical prediction model of patient-reported pain and function after undergoing total knee replacement (TKR). We used data of 1,649 patients from the Knee Arthroplasty Trial who received primary TKR across 34 centres in the UK. The external validation included 595 patients from Southampton University Hospital, and Nuffield Orthopaedic Centre (Oxford). The outcome was the Oxford Knee Score (OKS) 12-month after TKR. Pre-operative predictors including patient characteristics and clinical factors were considered. Bootstrap backward linear regression analysis was used. Low pre-operative OKS, living in poor areas, high body mass index, and patient-reported anxiety or depression were associated with worse outcome. The clinical factors associated with worse outcome were worse pre-operative physical status, presence of other conditions affecting mobility and previous knee arthroscopy. Presence of fixed flexion deformity and an absent or damaged pre-operative anterior cruciate ligament (compared with intact) were associated with better outcome. Discrimination and calibration statistics were satisfactory. External validation predicted 21.1% of the variance of outcome. This is the first clinical prediction model for predicting self-reported pain and function 12 months after TKR to be externally validated. It will help to inform to patients regarding expectations of the outcome after knee replacement surgery

Intracluster correlation coefficients in cluster randomized trials: empirical insights into how should they be reported

BACKGROUND: Increasingly, researchers are recognizing that there are many situations where the use of a cluster randomized trial may be more appropriate than an individually randomized trial. Similarly, the need for appropriate standards of reporting of cluster trials is more widely acknowledged. METHODS: In this paper, we describe the results of a survey to inform the appropriate reporting of the intracluster correlation coefficient (ICC) – the statistical measure of the clustering effect associated with a cluster randomized trial. RESULTS: We identified three dimensions that should be considered when reporting an ICC – a description of the dataset (including characteristics of the outcome and the intervention), information on how the ICC was calculated, and information on the precision of the ICC. CONCLUSIONS: This paper demonstrates the development of a framework for the reporting of ICCs. If adopted into routine practice, it has the potential to facilitate the interpretation of the cluster trial being reported and should help the development of new trials in the area

Cluster randomised trials in the medical literature: two bibliometric surveys

Background: Several reviews of published cluster randomised trials have reported that about half did not take clustering into account in the analysis, which was thus incorrect and potentially misleading. In this paper I ask whether cluster randomised trials are increasing in both number and quality of reporting. Methods: Computer search for papers on cluster randomised trials since 1980, hand search of trial reports published in selected volumes of the British Medical Journal over 20 years. Results: There has been a large increase in the numbers of methodological papers and of trial reports using the term 'cluster random' in recent years, with about equal numbers of each type of paper. The British Medical Journal contained more such reports than any other journal. In this journal there was a corresponding increase over time in the number of trials where subjects were randomised in clusters. In 2003 all reports showed awareness of the need to allow for clustering in the analysis. In 1993 and before clustering was ignored in most such trials. Conclusion: Cluster trials are becoming more frequent and reporting is of higher quality. Perhaps statistician pressure works

'Foreigners are stealing our birth right': Moral panics and the discursive construction of Zimbabwean immigrants in South African media

We examine 575 randomly selected articles on Zimbabwean immigrants from the South African Media (SAM) database to expose discourses of exclusion and the production of the psycho-social condition - moral panic. We use critical discourse analysis, notions of remediation and immediacy to scrutinize discourse structures and other discursive strategies designed to conceal mediation and authorial prejudices, and to make the reader 'experience' the actual content. In addition to making the anti-immigrant rhetoric appear legitimate, and the danger immediate and real, we argue that the apparent seamless content is often biased by selection and structured in such a way as to deny voice to immigrants and their advocates. Among other things, we conclude that since the readers' interpretations are filtered through lenses of subjectivities defined by communicative contexts characterized by job scarcity, poverty, crime and wanting healthcare, the news content heightens anxiety and miseducates more than it enlightens readers on migration issues. Hence there is a danger of SAM becoming unwitting conveyors of the same vices they preach against.IS