Major impact of body position on arterial stiffness indices derived from radial applanation tonometry in pregnant and nonpregnant women.

OBJECTIVE: To evaluate the impact of body position on the arterial stiffness indices provided by radial applanation tonometry in pregnant and nonpregnant women. METHODS: Twenty-four young women (18-30 years) in the third trimester of a normal pregnancy and 20 healthy nonpregnant women of the same age were enrolled. In each, applanation tonometry was carried out in the sitting and supine position. The following stiffness indices were analyzed: systolic augmentation index (sAix), sAix adjusted for heart rate (sAix@75) and diastolic augmentation index (dAix), all expressed in % of central aortic pulse pressure. RESULTS: The sAix was apparently not influenced by body position, but the transition from seated to supine was associated with a substantial decrease in heart rate. When correcting for this confounder by calculating the sAix@75, systolic augmentation was substantially lower when individuals were supine (mean ± SD: nonpregnant 3.0 ± 14.4%, pregnant 8.8 ± 9.7%) than when they were sitting (nonpregnant 5.7 ± 13.0%, pregnant 11.1 ± 83%, P = 0.005 supine vs. seated in both study groups, P > 0.2 for pregnant vs. nonpregnant). The influence of body position on the dAix went in the opposite direction (supine: nonpregnant 9.7 ± 6.6%, pregnant 4.4 ± 3.5%; seated: nonpregnant 7.7 ± 5.8%, pregnant 3.3 ± 2.4%, P < 0.00001 supine vs. seated in both study groups, P = 0.001 for pregnant vs. nonpregnant). CONCLUSION: Body position has a major impact on the pattern of central aortic pressure augmentation by reflected waves in healthy young women examined either during third trimester pregnancy or in the nonpregnant state.

Validation of the French version of the Hierarchical Personality Inventory for Children (HiPIC): Influence of gender and age on personality traits from 8 to 12 years

The study was designed to investigate the psychometric properties of the French version and the cross-language replicability of the Hierarchical Personality Inventory for Children (HiPIC). The HiPIC is an instrument aimed at assessing the five dimensions of the Five-Factor Model for Children. Subjects were 552 children aged between 8 and 12 years, rated by one or both parents. At the domain level, reliability ranged from .83 to .93 and at the facet level, reliability ranged from .69 to .89. Differences between genders were congruent with those found in the Dutch sample. Girls scored higher on Benevolence and Conscientiousness. Age was negatively correlated with Extraversion and Imagination. For girls, we also observed a decrease of Emotional Stability. A series of exploratory factor analyses confirmed the overall five-factor structure for girls and boys. Targeted factor analyses and congruence coefficients revealed high cross-language replicability at the domain and at the facet levels. The results showed that the French version of the HiPIC is a reliable and valid instrument for assessing personality with children and has a particularly high cross-language replicability.

Relation between intraoperative EMG values and final pedicle screw position as seen on CT images

Introduction: Intraoperative EMG based neurophysiological monitoring is increasingly used to assist pedicle screw insertion. We carried out a study comparing the final screw position in the pedicle measured on CT images in relation to its corresponding intraoperative muscle compound action potential (CMAP) values. Material and methods: A total of 189 screws were inserted in thoracolumbar spines of 31 patients during instrumented fusion under EMG control. An observer, blinded to the CMAP value, assessed the horizontal and vertical 'screw edge to pedicle edge' distance perpendicular to the longitudinal axis of the screw on reformatted CT reconstructions using OsiriX software. These distances were analysed with their corresponding CMAP values. Data from 62 thoracic and 127 lumbar screws were processed separately. Interobserver reliability of distance measurements was assessed. Results: No patient suffered neurological injury secondary to screw insertion. Distance measurements were reliable (paired t-test, P = 0.13/0.98 horizontal/vertical). Two screws had their position altered due to low CMAP values suggesting close proximity of nerve tissue. Seventy five percent of screws had CMAP results above 10mA and had an average distance of 0.35cm (SD 0.23) horizontally and 0.46cm (SD 0.26) vertically from the pedicle edge. Additional 12% had a distance from the edge of the pedicle less than 0mm indicating cortical breach but had CMAP values above 10mA. A poor correlation between CMAP values and screw position was found. Discussion: In this study CMAP values above 10mA indicated correct screw position in the majority of cases. The zone of 10-20mA CMAP carries highest risk of a misplaced screw despite high CMAP value (17% of screws this CMAP range). In order to improve accuracy of EMG predictive value further research is warranted including improvement of probing techniques.

Primary Care - A position paper for the Professions Allied to Medicine (PDF 839 KB)

A Position Paper for the Professions Allied to Medicine

AHP Position Statement (PDF 46 KB)

Research and Development in the Professions Allied to Medicine within NI

Cancer Services - A Position Paper for the Professions Allied to Medicine (PDF 175 KB)

A Position Paper for the Professions Allied to Medicine Patients with cancer are living longer due to early diagnosis and better treatment. In recent years there has been increasing attention to issues related to the quality of life of patients with cancer and a recognition of the potential for habilitation and rehabilitation. As a result, PAMs as members of the multi-disciplinary team are now more actively involved with patients diagnosed with cancer during all phases of their disease. Each person’s life possesses a unique blend of psychological, social, economic and physical factors and comprehensive care requires the needs of the whole person to be addressed. This requires patients and carers having timely access to the most appropriate range of professional skills that will allow individual patients and their carers to retain control of their lives and associated circumstances for as long as possible. It also requires professions, in all locations, to work in a collaborative patient centred manner that affords the best outcome for patients. The need has been highlighted for a multi-professional approach to the delivery of cancer services in “Investing for the Future” and “A Framework for the Multi-professional Contribution to Cancer Care in Northern Ireland”. This need has also been highlighted in the PAM Strategy document. åÊ

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Early Life Influences: A Position Paper Of The Women's Health Council: Executive Summary

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Early Life Influences: A Position Paper Of The Women's Health Council

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An Age Friendly Society: A Position Statement

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Superiority of prone position in free-breathing 3D coronary MRA in patients with coronary disease.

Navigator-gated and corrected 3D coronary MR angiography (MRA) allows submillimeter image acquisition during free breathing. However, cranial diaphragmatic drift and relative phase shifts of chest-wall motion are limiting factors for image quality and scanning duration. We hypothesized that image acquisition in the prone position would minimize artifacts related to chest-wall motion and suppress diaphragmatic drift. Twelve patients with radiographically-confirmed coronary artery disease and six healthy adult volunteers were studied in both the prone and the supine position during free-breathing navigator-gated and corrected 3D coronary MRA. Image quality and the diaphragmatic positions were objectively compared. In the prone position, there was a 36% improvement in signal-to-noise ratio (SNR; 15.5 +/- 2.7 vs. 11.4 +/- 2.6; P < 0.01) and a 34% improvement in CNR (12.5 +/- 3.3 vs. 9.3 +/- 2.5, P < 0.01). The prone position also resulted in a 17% improvement in coronary vessel definition (P < 0.01). Cranial end-expiratory diaphragmatic drift occurred less frequently in the prone position (23% +/- 17% vs. 40% +/- 26% supine; P <0.05), and navigator efficiency was higher. Prone coronary MRA results in improved SNR and CNR with enhanced coronary vessel definition. Cranial end-expiratory diaphragmatic drift also was reduced, and navigator efficiency was enhanced. When feasible, prone imaging is recommended for free-breathing coronary MRA.

An empirical hierarchical Bayesian unification of occupational exposure assessment methods.

In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.