Minimal important improvement thresholds for the six-minute walk test in a knee arthroplasty cohort: triangulation of anchor- and distribution-based methods.

BACKGROUND: The 6-minute walk test (6MWT) is a commonly used metric for measuring change in mobility after knee arthroplasty, however, what is considered an improvement after surgery has not been defined. The determination of important change in an outcome assessment tool is controversial and may require more than one approach. This study, nested within a combined randomised and observational trial, aimed to define a minimal important improvement threshold for the 6MWT in a knee arthroplasty cohort through a triangulation of methods including patient-perceived anchor-based thresholds and distribution-based thresholds. METHODS: Individuals with osteoarthritis performed a 6MWT pre-arthroplasty then at 10 and 26 weeks post-surgery. Each rated their perceived improvement in mobility post-surgery on a 7-point transition scale anchored from "much better" to "much worse". Based on these responses the cohort was dichotomised into 'improved' and 'not improved'. The thresholds for patient-perceived improvements were then identified using two receiver operating curve methods producing sensitivity and specificity indices. Distribution-based change thresholds were determined using two methods utilising effect size (ES). Agreement between the anchor- and distribution-based methods was assessed using kappa. RESULTS: One hundred fifty-eight from 166 participants in the randomised cohort and 222 from 243 in the combined randomised and observational cohort were included at 10 and 26 weeks, respectively. The slightly or more patient-perceived improvement threshold at 26 weeks (an absolute improvement of 26 m) was the only one to demonstrate sensitivity and specificity results both better than chance. At 10- and 26-weeks, the ES based on the mean change score divided by the baseline standard deviation (SD), was an absolute change of 24.5 and 37.9 m, respectively. The threshold based on a moderate ES (a 0.5 SD of the baseline score) was a change of 55.0 and 55.4 m at 10- and 26-weeks, respectively. The level of agreement between the 26-week anchor-based and distribution-based minimal absolute changes was very good (k = 0.88 (95 % CI 0.81 0.95)). CONCLUSION: A valid threshold of improvement for the 6MWT can only be proposed for changes identified from baseline to 26 weeks post-surgery. The level of agreement between anchor- and distribution-based methods indicates that a true minimal or more threshold of meaningful improvement following surgery is likely within the ranges proposed by the triangulation of all four methods, that is, 26 to 55 m

The impact of partially missing communities~on the reliability of centrality measures

Network data is usually not error-free, and the absence of some nodes is a very common type of measurement error. Studies have shown that the reliability of centrality measures is severely affected by missing nodes. This paper investigates the reliability of centrality measures when missing nodes are likely to belong to the same community. We study the behavior of five commonly used centrality measures in uniform and scale-free networks in various error scenarios. We find that centrality measures are generally more reliable when missing nodes are likely to belong to the same community than in cases in which nodes are missing uniformly at random. In scale-free networks, the betweenness centrality becomes, however, less reliable when missing nodes are more likely to belong to the same community. Moreover, centrality measures in scale-free networks are more reliable in networks with stronger community structure. In contrast, we do not observe this effect for uniform networks. Our observations suggest that the impact of missing nodes on the reliability of centrality measures might not be as severe as the literature suggests

A shadowing problem in the detection of overlapping communities: lifting the resolution limit through a cascading procedure

Community detection is the process of assigning nodes and links in significant communities (e.g. clusters, function modules) and its development has led to a better understanding of complex networks. When applied to sizable networks, we argue that most detection algorithms correctly identify prominent communities, but fail to do so across multiple scales. As a result, a significant fraction of the network is left uncharted. We show that this problem stems from larger or denser communities overshadowing smaller or sparser ones, and that this effect accounts for most of the undetected communities and unassigned links. We propose a generic cascading approach to community detection that circumvents the problem. Using real and artificial network datasets with three widely used community detection algorithms, we show how a simple cascading procedure allows for the detection of the missing communities. This work highlights a new detection limit of community structure, and we hope that our approach can inspire better community detection algorithms.Comment: 14 pages, 12 figures + supporting information (5 pages, 6 tables, 3 figures

Endogenous production of ghrelin and beneficial effects of its exogenous administration in monocrotaline-induced pulmonary hypertension

We investigated the endogenous production of ghrelin as well as cardiac and pulmonary vascular effects of its administration in a rat model of monocrotaline (MCT)-induced pulmonary hypertension (PH). Adult Wistar rats randomly received a subcutaneous injection of MCT (60 mg/kg) or an equal volume of vehicle. One week later, animals were randomly assigned to receive a subcutaneous injection of ghrelin (100 mug/kg bid for 2 wk) or saline. Four groups were analyzed: normal rats treated with ghrelin (n = 7), normal rats injected with saline (n = 7), MCT rats treated with ghrelin (n = 9), and MCT rats injected with saline (n = 9). At 22-25 days, right ( RV) and left ventricular (LV) pressures were measured, heart and lungs were weighted, and samples were collected for histological and molecular analysis. Endogenous production of ghrelin was almost abolished in normal rats treated with ghrelin. In MCT-treated animals, pulmonary expression of ghrelin was preserved, and RV myocardial expression was increased more than 20 times. In these animals, exogenous administration of ghrelin attenuated PH, RV hypertrophy, wall thickening of peripheral pulmonary arteries, and RV diastolic disturbances and ameliorated LV dysfunction, without affecting its endogenous production. In conclusion, decreased tissular expression of ghrelin in healthy animals but not in PH animals suggests a negative feedback in the former that is lost in the latter. A selective increase of ghrelin mRNA levels in the RV of animals with PH might indicate distinct regulation of its cardiac expression. Finally, ghrelin administration attenuated MCT-induced PH, pulmonary vascular remodeling, and RV hypertrophy, indicating that it may modulate PH

Router-level community structure of the Internet Autonomous Systems

The Internet is composed of routing devices connected between them and organized into independent administrative entities: the Autonomous Systems. The existence of different types of Autonomous Systems (like large connectivity providers, Internet Service Providers or universities) together with geographical and economical constraints, turns the Internet into a complex modular and hierarchical network. This organization is reflected in many properties of the Internet topology, like its high degree of clustering and its robustness. In this work, we study the modular structure of the Internet router-level graph in order to assess to what extent the Autonomous Systems satisfy some of the known notions of community structure. We show that the modular structure of the Internet is much richer than what can be captured by the current community detection methods, which are severely affected by resolution limits and by the heterogeneity of the Autonomous Systems. Here we overcome this issue by using a multiresolution detection algorithm combined with a small sample of nodes. We also discuss recent work on community structure in the light of our results

Tactical Voting in Plurality Elections

How often will elections end in landslides? What is the probability for a head-to-head race? Analyzing ballot results from several large countries rather anomalous and yet unexplained distributions have been observed. We identify tactical voting as the driving ingredient for the anomalies and introduce a model to study its effect on plurality elections, characterized by the relative strength of the feedback from polls and the pairwise interaction between individuals in the society. With this model it becomes possible to explain the polarization of votes between two candidates, understand the small margin of victories frequently observed for different elections, and analyze the polls' impact in American, Canadian, and Brazilian ballots. Moreover, the model reproduces, quantitatively, the distribution of votes obtained in the Brazilian mayor elections with two, three, and four candidates.Comment: 7 pages, 4 figure

A statistical network analysis of the HIV/AIDS epidemics in Cuba

The Cuban contact-tracing detection system set up in 1986 allowed the reconstruction and analysis of the sexual network underlying the epidemic (5,389 vertices and 4,073 edges, giant component of 2,386 nodes and 3,168 edges), shedding light onto the spread of HIV and the role of contact-tracing. Clustering based on modularity optimization provides a better visualization and understanding of the network, in combination with the study of covariates. The graph has a globally low but heterogeneous density, with clusters of high intraconnectivity but low interconnectivity. Though descriptive, our results pave the way for incorporating structure when studying stochastic SIR epidemics spreading on social networks

The Naming Game in Social Networks: Community Formation and Consensus Engineering

We study the dynamics of the Naming Game [Baronchelli et al., (2006) J. Stat. Mech.: Theory Exp. P06014] in empirical social networks. This stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.Comment: The original publication is available at http://www.springerlink.com/content/70370l311m1u0ng3

Female economic dependence and the morality of promiscuity

This article is made available through the Brunel Open Access Publishing Fund. Copyright @ The Author(s) 2014.In environments in which female economic dependence on a male mate is higher, male parental investment is more essential. In such environments, therefore, both sexes should value paternity certainty more and thus object more to promiscuity (because promiscuity undermines paternity certainty). We tested this theory of anti-promiscuity morality in two studies (N = 656 and N = 4,626) using U.S. samples. In both, we examined whether opposition to promiscuity was higher among people who perceived greater female economic dependence in their social network. In Study 2, we also tested whether economic indicators of female economic dependence (e.g., female income, welfare availability) predicted anti-promiscuity morality at the state level. Results from both studies supported the proposed theory. At the individual level, perceived female economic dependence explained significant variance in anti-promiscuity morality, even after controlling for variance explained by age, sex, religiosity, political conservatism, and the anti-promiscuity views of geographical neighbors. At the state level, median female income was strongly negatively related to anti-promiscuity morality and this relationship was fully mediated by perceived female economic dependence. These results were consistent with the view that anti-promiscuity beliefs may function to promote paternity certainty in circumstances where male parental investment is particularly important

Inference of hidden structures in complex physical systems by multi-scale clustering

We survey the application of a relatively new branch of statistical physics--"community detection"-- to data mining. In particular, we focus on the diagnosis of materials and automated image segmentation. Community detection describes the quest of partitioning a complex system involving many elements into optimally decoupled subsets or communities of such elements. We review a multiresolution variant which is used to ascertain structures at different spatial and temporal scales. Significant patterns are obtained by examining the correlations between different independent solvers. Similar to other combinatorial optimization problems in the NP complexity class, community detection exhibits several phases. Typically, illuminating orders are revealed by choosing parameters that lead to extremal information theory correlations.Comment: 25 pages, 16 Figures; a review of earlier work