Kinematic Foot Types in Youth with Equinovarus Secondary to Hemiplegia

Background Elevated kinematic variability of the foot and ankle segments exists during gait among individuals with equinovarus secondary to hemiplegic cerebral palsy (CP). Clinicians have previously addressed such variability by developing classification schemes to identify subgroups of individuals based on their kinematics. Objective To identify kinematic subgroups among youth with equinovarus secondary to CP using 3-dimensional multi-segment foot and ankle kinematics during locomotion as inputs for principal component analysis (PCA), and K-means cluster analysis. Methods In a single assessment session, multi-segment foot and ankle kinematics using the Milwaukee Foot Model (MFM) were collected in 24 children/adolescents with equinovarus and 20 typically developing children/adolescents. Results PCA was used as a data reduction technique on 40 variables. K-means cluster analysis was performed on the first six principal components (PCs) which accounted for 92% of the variance of the dataset. The PCs described the location and plane of involvement in the foot and ankle. Five distinct kinematic subgroups were identified using K-means clustering. Participants with equinovarus presented with variable involvement ranging from primary hindfoot or forefoot deviations to deformtiy that included both segments in multiple planes. Conclusion This study provides further evidence of the variability in foot characteristics associated with equinovarus secondary to hemiplegic CP. These findings would not have been detected using a single segment foot model. The identification of multiple kinematic subgroups with unique foot and ankle characteristics has the potential to improve treatment since similar patients within a subgroup are likely to benefit from the same intervention(s)

A Clinical Prediction Score to Guide Referral of Elderly Dialysis Patients for Kidney Transplant Evaluation.

IntroductionDialysis patients aged ≥70 years derive improved life expectancy through kidney transplantation compared to their waitlisted counterparts, but guidelines are not clear about how to identify appropriate transplantation candidates. We developed a clinical prediction score to identify elderly dialysis patients with expected 5-year survival appropriate for kidney transplantation (>5 years).MethodsIncident dialysis patients in 2006-2009 aged ≥70 were identified from the United States Renal Data System database and divided into derivation and validation cohorts. Using the derivation cohort, candidate variables with a significant crude association with 5-year all-cause mortality were included in a multivariable logistic regression model to generate a scoring system. The scoring system was tested in the validation cohort and a cohort of elderly transplant recipients.ResultsCharacteristics most predictive of 5-year mortality included age >80, body mass index (BMI) <18, the presence of congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), immobility, and being institutionalized. Factors associated with increased 5-year survival were non-white race, a primary cause of end stage renal disease (ESRD) other than diabetes, employment within 6 months of dialysis initiation, and dialysis start via arteriovenous fistula (AVF). 5-year mortality was 47% for the lowest risk score group (3.6% of the validation cohort) and >90% for the highest risk cohort (42% of the validation cohort).ConclusionThis clinical prediction score could be useful for physicians to identify potentially suitable candidates for kidney transplantation

Affect, Interpersonal Behaviour and Interpersonal Perception During Open-Label, Uncontrolled Paroxetine Treatment of People with Social Anxiety Disorder: A Pilot Study

Background: Laboratory-based research with community samples has suggested changes in affective, behavioural and cognitive processes as possible explanations for the effects of serotonergic medications. Examining the effects of serotonergic medications using an ecological momentary measure (such as event-contingent recording) in the daily lives of people with social anxiety disorder would contribute to establishing the effects of these medications on affect, behaviour and one form of cognition: perception of others’ behaviour. Methods: The present study assessed changes in affect, interpersonal behaviour and perception of others’ behaviour in adults with social anxiety disorder using ecological momentary assessment at baseline and over 4 months of a single-arm, uncontrolled, open-label trial of treatment with the selective serotonin reuptake inhibitor paroxetine. Results: Anxiety and concurrent depressive symptoms decreased. Participants also reported increased positive and decreased negative affect; increased agreeable and decreased quarrelsome behaviour; increased dominant and decreased submissive behaviour; and increased perception that others behaved agreeably toward them. Moreover, participants demonstrated reduced intraindividual variability in affect, interpersonal behaviour and perception of others’ behaviour. Limitations: Limitations included the lack of a placebo group, the inability to identify the temporal order of changes and the restricted assessment of extreme behaviour. Conclusion: The results of the present study demonstrate changes during pharmacotherapy in the manifestation of affect, interpersonal behaviour and interpersonal perception in the daily lives of people with social anxiety disorder. Given the importance of interpersonal processes to social anxiety disorder, these results may guide future research seeking to clarify mechanisms of action for serotonergic medications

MIXNO: a computer program for mixed-effects nominal logistic regression

MIXNO provides maximum marginal likelihood estimates for mixed-effects nominal logistic regression analysis. These models can be used for analysis of correlated nominal response data, for example, data arising from a clustered or longitudinal design. For such data, the mixed-effects model assumes that data within clusters or sub jects are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from nesting of the data. MIXNO uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated along with the (fixed) effects of explanatory variables. Examples illustrating usage and features of MIXNO are provided

Taking silk: an empirical study of the award of Queen’s Counsel status 1981-2015

This article considers which junior barristers are appointed to the rank of Queen’s Counsel. The criticisms of the old appointments system are discussed and statistical methods are used to assess whether the changes to the QC appointments system introduced in 2004 improved the prospects of appointment for groups, such as women, that were disadvantaged by the previous system. The results show that under the reformed system groups that were historically less likely to be appointed QCs, such as women, continue to be so. However it is discussed how this may (partly) be attributable to lower rates of application, rather than unfair discrimination among applicants

MIXNO: a computer program for mixed-effects nominal logistic regression

MIXNO provides maximum marginal likelihood estimates for mixed-effects nominal logistic regression analysis. These models can be used for analysis of correlated nominal response data, for example, data arising from a clustered or longitudinal design. For such data, the mixed-effects model assumes that data within clusters or sub jects are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from nesting of the data. MIXNO uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated along with the (fixed) effects of explanatory variables. Examples illustrating usage and features of MIXNO are provided.

Integrating personality research and animal contest theory: aggressiveness in the green swordtail <i>Xiphophorus helleri</i>

&lt;p&gt;Aggression occurs when individuals compete over limiting resources. While theoretical studies have long placed a strong emphasis on context-specificity of aggression, there is increasing recognition that consistent behavioural differences exist among individuals, and that aggressiveness may be an important component of individual personality. Though empirical studies tend to focus on one aspect or the other, we suggest there is merit in modelling both within-and among-individual variation in agonistic behaviour simultaneously. Here, we demonstrate how this can be achieved using multivariate linear mixed effect models. Using data from repeated mirror trials and dyadic interactions of male green swordtails, &lt;i&gt;Xiphophorus helleri&lt;/i&gt;, we show repeatable components of (co)variation in a suite of agonistic behaviour that is broadly consistent with a major axis of variation in aggressiveness. We also show that observed focal behaviour is dependent on opponent effects, which can themselves be repeatable but were more generally found to be context specific. In particular, our models show that within-individual variation in agonistic behaviour is explained, at least in part, by the relative size of a live opponent as predicted by contest theory. Finally, we suggest several additional applications of the multivariate models demonstrated here. These include testing the recently queried functional equivalence of alternative experimental approaches, (e. g., mirror trials, dyadic interaction tests) for assaying individual aggressiveness.&lt;/p&gt

Effects of n-3 fatty acids, EPA v. DHA, on depressive symptoms, quality of life, memory and executive function in older adults with mild cognitive impairment: a 6-month randomised controlled trial

First published online 20 September 2011Depressive symptoms may increase the risk of progressing from mild cognitive impairment (MCI) to dementia. Consumption of n-3 PUFA may alleviate both cognitive decline and depression. The aim of the present study was to investigate the benefits of supplementing a diet with n-3 PUFA, DHA and EPA, for depressive symptoms, quality of life (QOL) and cognition in elderly people with MCI. We conducted a 6-month double-blind, randomised controlled trial. A total of fifty people aged >65 years with MCI were allocated to receive a supplement rich in EPA (1·67 g EPA + 0·16 g DHA/d; n 17), DHA (1·55 g DHA + 0·40 g EPA/d; n 18) or the n-6 PUFA linoleic acid (LA; 2·2 g/d; n 15). Treatment allocation was by minimisation based on age, sex and depressive symptoms (Geriatric Depression Scale, GDS). Physiological and cognitive assessments, questionnaires and fatty acid composition of erythrocytes were obtained at baseline and 6 months (completers: n 40; EPA n 13, DHA n 16, LA n 11). Compared with the LA group, GDS scores improved in the EPA (P=0·04) and DHA (P=0·01) groups and verbal fluency (Initial Letter Fluency) in the DHA group (P=0·04). Improved GDS scores were correlated with increased DHA plus EPA (r 0·39, P=0·02). Improved self-reported physical health was associated with increased DHA. There were no treatment effects on other cognitive or QOL parameters. Increased intakes of DHA and EPA benefited mental health in older people with MCI. Increasing n-3 PUFA intakes may reduce depressive symptoms and the risk of progressing to dementia. This needs to be investigated in larger, depressed samples with MCI.Natalie Sinn, Catherine M. Milte, Steven J. Street, Jonathan D. Buckley, Alison M. Coates, John Petkov, and Peter R. C. How

A Bayesian two-step multiple imputation approach based on mixed models for the missing in EMA data

Ecological Momentary Assessments (EMA) capture real-time thoughts and behaviors in natural settings, producing rich longitudinal data for statistical and physiological analyses. However, the robustness of these analyses can be compromised by the large amount of missing in EMA data sets. To address this, multiple imputation, a method that replaces missing values with several plausible alternatives, has become increasingly popular. In this paper, we introduce a two-step Bayesian multiple imputation framework which leverages the configuration of mixed models. We adopt the Random Intercept Linear Mixed model, the Mixed-effect Location Scale model which accounts for subject variance influenced by covariates and random effects, and the Shared Parameter Location Scale Mixed Effect model which links the missing data to the response variable through a random intercept logistic model, to complete the posterior distribution within the framework. In the simulation study and an application on data from a study on caregivers of dementia patients, we further adapt this two-step Bayesian multiple imputation strategy to handle simultaneous missing variables in EMA data sets and compare the effectiveness of multiple imputations across different mixed models. The analyses highlight the advantages of multiple imputations over single imputations. Furthermore, we propose two pivotal considerations in selecting the optimal mixed model for the two-step imputation: the influence of covariates as well as random effects on the within-variance, and the nature of missing data in relation to the response variable