Impaired endothelium-dependent vasodilatation is a novel predictor of mortality in intensive care

Objective: Endothelial function may be impaired in critical illness. We hypothesized that impaired endothelium-dependent vasodilatation is a predictor of mortality in critically ill patients.
Design: Prospective observational cohort study.
Setting: Seventeen-bed adult intensive care unit in a tertiary referral university teaching hospital. Patients: Patients were recruited within 24 hrs of admission to the intensive care unit.
Interventions: The SphygmoCor Mx system was used to derive the aortic augmentation index from radial artery pulse pressure waveforms. Endothelium-dependent vasodilatation was calculated as the change in augmentation index in response to an endothelium-dependent vasodilator (salbutamol).
Measurements and Main Results: Demographics, severity of illness scores, and physiological parameters were collected. Statistically significant predictors of mortality identified using single regressor analysis were entered into a multiple logistic regression model. Receiver operator characteristic curves were generated. Ninety-four patients completed the study. There were 80 survivors and 14 nonsurvivors. The Simplified Acute Physiology Score II, the Sequential Organ Failure Assessment score, leukocyte count, and endothelium-dependent vasodilatation conferred an increased risk of mortality. In logistic regression analysis, endothelium-dependent vasodilatation was the only predictor of mortality with an adjusted odds ratio of 26.1 (95% confidence interval [CI], 4.3-159.5). An endothelium-dependent vasodilatation value of 0.5% or less predicted intensive care unit mortality with a sensitivity of 79% (CI, 59-88%) and specificity of 98% (CI, 94-99%).
Conclusions: In vivo bedside assessment of endothelium-dependent vasodilatation is an independent predictor of mortality in the critically ill. We have shown it to be superior to other validated severity of illness scores with high sensitivity and specificity.

An efficient feature selection method for mobile devices with application to activity recognition

This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.

School Neighborhood Disadvantage as a Predictor of Long-Term Sick Leave Among Teachers: Prospective Cohort Study

This ongoing prospective study examined characteristics of school neighborhood and neighborhood of residence as predictors of sick leave among school teachers. School neighborhood income data for 226 lower-level comprehensive schools in 10 towns in Finland were derived from Statistics Finland and were linked to register-based data on 3,063 teachers with no long-term sick leave at study entry. Outcome was medically certified (> 9 days) sick leave spells during a mean follow-up of 4.3 years from data collection in 2000-2001. A multilevel, cross-classified Poisson regression model, adjusted for age, type of teaching job, length and type of job contract, school size, baseline health status, and income level of the teacher's residential area, showed a rate ratio of 1.30 (95% confidence interval: 1.03, 1.63) for sick leave among female teachers working in schools located in low-income neighborhoods compared with those working in high-income neighborhoods. A low income level of the teacher's residential area was also independently associated with sick leave among female teachers (rate ratio = 1.50, 95% confidence interval: 1.18, 1.91). Exposure to both low-income school neighborhoods and low-income residential neighborhoods was associated with the greatest risk of sick leave (rate ratio = 1.71, 95% confidence interval: 1.27, 2.30). This study indicates that working and living in a socioeconomically disadvantaged neighborhood is associated with increased risk of sick leave among female teachers.

Coxiella burnetii (Q fever) seroprevalence in cattle

Human cases of Q fever appear to be common in Northern Ireland compared to the rest of the British Isles. The purpose of this study was to describe the seroepidemiology of Coxiella burnetii infection in cattle in Northern Ireland in terms of seroprevalence and determinants of infection. A total of 5182 animals (from a stratified systematic random sample of 273 herds) were tested with a commercial C. burnetii phase 2 IgG ELISA. A total of 6.2% of animals and 48.4% of herds tested positively. Results from a multilevel logistic regression model indicated that the odds of cattle being infected with Q fever increased with age, Friesian breed, being from large herds and from dairy herds. Large dairy herd animal prevalence was 12.5% compared to 2.1% for small beef herds. Preliminary seroprevalence in sheep (12.3%), goats (9.3%), pigs (0%) rats (9.7%) and mice (3.2%) using indirect immunofluorescence is reported.

CoMFA and homology-based models of the glycine binding site of N-methyl-D-aspartate receptor

Homology modeling was used to build 3D models of the N-methyl-D-aspartate (NMDA) receptor glycine binding site on the basis of an X-ray structure of the water-soluble AMPA-sensitive receptor. The docking of agonists and antagonists to these models was used to reveal binding modes of ligands and to explain known structure-activity relationships. Two types of quantitative models, 3D-QSAR/CoMFA and a regression model based on docking energies, were built for antagonists (derivatives of 4-hydroxy-2-quinolone, quinoxaline-2,3-dione, and related compounds). The CoMFA steric and electrostatic maps were superimposed on the homology-based model, and a close correspondence was marked. The derived computational models have permitted the evaluation of the structural features crucial for high glycine binding site affinity and are important for the design of new ligands.

Associations between maternal characteristics and pregnancy-related stress among low-risk mothers: An observational cross-sectional study

Background: Pregnancy is viewed as a major life event and, while the majority of healthy, low-risk women adapt well to pregnancy, there are those whose levels of stress are heightened by the experience.

Objectives: To determine the level of pregnancy-related stress experienced by a group of healthy, low-risk pregnant women and to relate the level of stress with a number of maternal characteristics.

Design: An observational cross-sectional study.

Setting: A large, urban maternity centre in Northern Ireland.

Participants: Of the 306 pregnant women who were invited to participate, 278 provided informed consent and were administered one self-complete questionnaire. Due to the withdrawal criteria, 15 questionnaires were removed from the analysis, resulting in a final sample of 263 healthy, low-risk pregnant women.

Methods: Levels of stress were measured using a self-report measure designed to assess specific worries and concerns relating to pregnancy. Maternal characteristics collected included age, marital status, social status, parity, obstetric history, perceived health status and 'wantedness' for the pregnancy. Regression analysis was undertaken using an ordinary linear regression model.

Results: The mean prenatal distress score in the sample was 15.1 (SD = 7.4; range 0-46). The regression model showed that women who had had previous pregnancies, with or without complications, had significantly lower mean prenatal distress scores than primiparous women (p < 0.01). Women reporting poorer physical health had higher mean prenatal distress scores than those who reported at least average health, while women aged 16-20 experienced a mean increase in the reported prenatal distress score (p < 0.05) in comparison to the reference group of 36 years and over.

Conclusions: This study brings to light the prevalence of pregnancy-related stress within a sample representative of healthy, low-risk women. Current antenatal care is ill-equipped to identify women suffering from high levels of stress; yet a growing body of research evidence links stress with adverse pregnancy outcomes. This study emphasises that healthy, low-risk women experience a range of pregnancy-related stress and identification of stress levels, either through the use of a simple stress measurement tool or through the associated factors identified within this research study, provides valuable data on maternal well-being. (C) 2010 Elsevier Ltd. All rights reserved.

Retinal pigment epithelial atrophy in patients with exudative age-related macular degeneration undergoing anti-vascular endothelial growth factor therapy

PURPOSE:: To evaluate the occurrence of retinal pigment epithelial atrophy in patients with age-related macular degeneration undergoing anti-vascular endothelial growth factor therapy. METHODS:: The study is a retrospective review. Eligible were patients with age-related macular degeneration and choroidal neovascular membranes treated with anti-vascular endothelial growth factor between October 2007 and February 2011; they were followed for >3 months, with fundus photographs and fluorescein angiography at baseline and with autofluorescence and near-infrared autofluorescence images at baseline and follow-up. Demographics, visual acuity, the type of choroidal neovascular membranes, the number of treatments performed, and the length of follow-up were recorded. Autofluorescence and near-infrared autofluorescence images were evaluated for the presence or absence of areas of reduced signal. A multilevel logistic regression model was used to investigate the factors that may be associated with progression of atrophy at follow-up, which was the primary outcome of this study. RESULTS:: Sixty-three patients (72 eyes) were followed for a median of 16 months (range, 3-36 months). Atrophy at baseline was observed in 47% (34/72) of eyes; progression of atrophy occurred in 62% (45/72) of eyes at the last visit. The number of anti-vascular endothelial growth factor injections received was statistically significantly associated with the progression of atrophy at follow-up (odds ratio, 1.35; 95% confidence interval, 1.05-1.73; P = 0.02). CONCLUSION:: Atrophy was frequently observed in patients with age-related macular degeneration and choroidal neovascular membranes undergoing anti-vascular endothelial growth factor therapy.

Progression of retinal pigment epithelial atrophy in stargardt disease

• PURPOSE: To evaluate retinal pigment epithelial (RPE) atrophy in patients with Stargardt disease using autofluorescence imaging (AF). • DESIGN: Retrospective observational case series. • METHODS: Demographics, best-corrected visual acuity (BCVA), AF images, and electrophysiology responses (group 1, macular dysfunction; group 2, macula + cone dysfunction; group 3, macula + cone-rod dysfunction) were evaluated at presentation and follow-up in a group of 12 patients (24 eyes) with Stargardt disease. The existence, development, and rate of enlargement of areas of RPE atrophy over time were evaluated using AF imaging. A linear regression model was used to investigate the effects of AF and electrophysiology on rate of atrophy enlargement and BCVA, adjusting for age of onset and duration of disease. • RESULTS: Eight male and 4 female patients (median age 42 years; range 24-69 years) were followed for a median of 41.5 months (range 13-66 months). All 12 patients had reduced AF compatible with RPE atrophy at presentation and in all patients the atrophy enlarged during follow-up. The mean rate of atrophy enlargement for all patients was 1.58 mm /y (SD 1.25 mm /y; range 0.13-5.27 mm /y). Only the pattern of functional loss present as detected by electrophysiology was statistically significantly associated with the rate of atrophy enlargement when correcting for other variables (P <.001), with patients in group 3 (macula + cone-rod dysfunction) having the fastest rate of atrophy enlargement (1.97 mm /y, SD 0.70 mm /y) (group 1 [macula] 1.09 mm /y, SD 0.53 mm /y; group 2 [macula + cone] 1.89 mm /y, SD 2.27 mm /y). • CONCLUSION: Variable rates of atrophy enlargement were observed in patients with Stargardt disease. The pattern of functional loss detected on electrophysiology was strongly associated with the rate of atrophy enlargement over time, thus serving as the best prognostic indicator for patients with this inherited retinal disease. © 2012 Elsevier Inc. All rights reserved.

A Randomized Controlled Trial of Interventions to Promote Adjustment in Children With Congenital Heart Disease Entering School and Their Families

Objective: To report on a randomized controlled trial of psychological interventions to promote adjustment in children with congenital heart disease and their families.
Method: Following baseline assessment, 90 children (aged 4–5 years) and their families were randomly assigned to an Intervention or Control group before entering school. 68 (76%) were retained at 10-month follow-up.
Results: Gains were observed on measures of maternal mental health and family functioning. Although no differences were found on measures of child behavior at home or school, children in the intervention group were perceived as “sick” less often by their mother and missed fewer days from school. A regression model, using baseline measures as predictors, highlighted the importance of maternal mental health, worry and child neurodevelopmental functioning for child behavioral outcomes almost a year later.
Conclusions: The intervention promoted clinically significant gains for the child and family. The program is of generalizable significance.

Haplotype association analysis of genes within the WNT signalling pathways in diabetic nephropathy

Background: Renal interstitial fibrosis and glomerular sclerosis are hallmarks of diabetic nephropathy (DN) and several studies have implicated members of the WNT pathways in these pathological processes. This study comprehensively examined common genetic variation within the WNT pathway for association with DN.

Methods: Genes within the WNT pathways were selected on the basis of nominal significance and consistent direction of effect in the GENIE meta-analysis dataset. Common SNPs and common haplotypes were examined within the selected WNT pathway genes in a white population with type 1 diabetes, discordant for DN (cases: n = 718; controls: n = 749). SNPs were genotyped using Sequenom or Taqman assays. Association analyses were performed using PLINK, to compare allele and haplotype frequencies in cases and controls. Correction for multiple testing was performed by either permutation testing or using false discovery rate.

Results: A logistic regression model including collection centre, duration of diabetes, and average HbA1c as covariates highlighted three SNPs in GSK3B (rs17810235, rs17471, rs334543), two in DAAM1 (rs1253192, rs1252906) and one in NFAT5 (rs17297207) as being significantly (P< 0.05) associated with DN, however these SNPs did not remain significant after correction for multiple testing. Logistic regression of haplotypes, with ESRD as the outcome, and pairwise interaction analyses did not yield any significant results after correction for multiple testing.

Conclusions: These results indicate that both common SNPs and common haplotypes of WNT pathway genes are not strongly associated with DN. However, this does not completely exclude these or the WNT pathways from association with DN, as unidentified rare genetic or copy number variants could still contribute towards the genetic architecture of DN.© 2013 Kavanagh et al.; licensee BioMed Central Ltd.

Centennial-scale climate change in Ireland during the Holocene

We examine mid- to late Holocene centennial-scale climate variability in Ireland using proxy data from peatlands, lakes and a speleothem. A high degree of between-record variability is apparent in the proxy data and significant chronological uncertainties are present. However, tephra layers provide a robust tool for correlation and improve the chronological precision of the records. Although we can find no statistically significant coherence in the dataset as a whole, a selection of high-quality peatland water table reconstructions co-vary more than would be expected by chance alone. A locally weighted regression model with bootstrapping can be used to construct a ‘best-estimate’ palaeoclimatic reconstruction from these datasets. Visual comparison and cross-wavelet analysis of peatland water table compilations from Ireland and Northern Britain show that there are some periods of coherence between these records. Some terrestrial palaeoclimatic changes in Ireland appear to coincide with changes in the North Atlantic thermohaline circulation and solar activity. However, these relationships are inconsistent and may be obscured by chronological uncertainties. We conclude by suggesting an agenda for future Holocene climate research in Ireland. ©2013 Elsevier B.V. All rights reserved.

Prediction of surface roughness during hard turning of AISI 4340 steel (69 HRC)

In this study, 39 sets of hard turning (HT) experimental trials were performed on a Mori-Seiki SL-25Y (4-axis) computer numerical controlled (CNC) lathe to study the effect of cutting parameters in influencing the machined surface roughness. In all the trials, AISI 4340 steel workpiece (hardened up to 69 HRC) was machined with a commercially available CBN insert (Warren Tooling Limited, UK) under dry conditions. The surface topography of the machined samples was examined by using a white light interferometer and a reconfirmation of measurement was done using a Form Talysurf. The machining outcome was used as an input to develop various regression models to predict the average machined surface roughness on this material. Three regression models - Multiple regression, Random Forest, and Quantile regression were applied to the experimental outcomes. To the best of the authors’ knowledge, this paper is the first to apply Random Forest or Quantile regression techniques to the machining domain. The performance of these models was compared to each other to ascertain how feed, depth of cut, and spindle speed affect surface roughness and finally to obtain a mathematical equation correlating these variables. It was concluded that the random forest regression model is a superior choice over multiple regression models for prediction of surface roughness during machining of AISI 4340 steel (69 HRC).

Root Cause Analysis by a Combined Sparse Classification and Monte Carlo Approach

Classification methods with embedded feature selection capability are very appealing for the analysis of complex processes since they allow the analysis of root causes even when the number of input variables is high. In this work, we investigate the performance of three techniques for classification within a Monte Carlo strategy with the aim of root cause analysis. We consider the naive bayes classifier and the logistic regression model with two different implementations for controlling model complexity, namely, a LASSO-like implementation with a L1 norm regularization and a fully Bayesian implementation of the logistic model, the so called relevance vector machine. Several challenges can arise when estimating such models mainly linked to the characteristics of the data: a large number of input variables, high correlation among subsets of variables, the situation where the number of variables is higher than the number of available data points and the case of unbalanced datasets. Using an ecological and a semiconductor manufacturing dataset, we show advantages and drawbacks of each method, highlighting the superior performance in term of classification accuracy for the relevance vector machine with respect to the other classifiers. Moreover, we show how the combination of the proposed techniques and the Monte Carlo approach can be used to get more robust insights into the problem under analysis when faced with challenging modelling conditions.

Characterisation of the frequent exacerbator phenotype in COPD patients in a large UK primary care population

BACKGROUND: The 'frequent exacerbator' is recognised as an important phenotype in COPD. Current understanding about this phenotype comes from prospective longitudinal clinical trials in secondary/tertiary care with little information reported in primary care populations.

AIMS: To characterize the frequent-exacerbator phenotype and identify associated risk factors in a large UK primary care COPD population.

METHODS: Using a large database of primary care patients from 80 UK general practices, patients were categorised using GOLD 2014 criteria into high and low risk groups based on exacerbation history. A multivariate logistic regression model was used to investigate covariates associated with the frequent-exacerbator phenotype and risk of experiencing a severe exacerbation (leading to hospitalisation).

RESULTS: Of the total study population (n = 9219), 2612 (28%) fulfilled the criteria for high risk frequent-exacerbators. Independent risk factors (adjusted odds ratio [95% CI]) for ≥2 exacerbations were: most severely impaired modified Medical Research Council (mMRC) dyspnoea score (mMRC grade 4: 4.37 [2.64-7.23]), lower FEV1 percent predicted (FEV1 <30%: 2.42 [1.61-3.65]), co-morbid cardiovascular disease (1.42 [1.19-1.68]), depression (1.56 [1.22-1.99]) or osteoporosis (1.54 [1.19-2.01]), and female gender (1.20 [1.01-1.43]). Older patients (≥75 years), those with most severe lung impairment (FEV1 <30%), those with highest mMRC score and those with co-morbid osteoporosis were identified as most at risk of experiencing exacerbations requiring hospitalisation.

CONCLUSIONS: Although COPD exacerbations occur across all grades of disease severity, female patients with high dyspnoea scores, more severely impaired lung function and co-morbidities are at greatest risk. Elderly patients, with severely impaired lung function, high mMRC scores and osteoporosis are associated with experience of severe exacerbations requiring hospitalisation.

Metastatic non-small cell lung cancer: a benchmark for quality end-of-life cancer care?

Objectives: To investigate the quality of end-of-life care for patients with metastatic non-small cell lung cancer (NSCLC). Design and participants: Retrospective cohort study of patients from first hospitalisation for metastatic disease until death, using hospital, emergency department and death registration data from Victoria, Australia, between 1 July 2003 and 30 June 2010. Main outcome measures: Emergency department and hospital use; aggressiveness of care including intensive care and chemotherapy in last 30 days; palliative and supportive care provision; and place of death. Results: Metastatic NSCLC patients underwent limited aggressive treatment such as intensive care (5%) and chemotherapy (< 1%) at the end of life; however, high numbers died in acute hospitals (42%) and 61% had a length of stay of greater than 14 days in the last month of life. Although 62% were referred to palliative care services, this occurred late in the illness. In a logistic regression model adjusted for year of metastasis, age, sex, metastatic site and survival, the odds ratio (OR) of dying in an acute hospital bed compared with death at home or in a hospice unit decreased with receipt of palliative care (OR, 0.25; 95% CI, 0.21–0.30) and multimodality supportive care (OR, 0.65; 95% CI, 0.56–0.75). Conclusion: Because early palliative care for patients with metastatic NSCLC is recommended, we propose that this group be considered a benchmark of quality end-of-life care. Future work is required to determine appropriate quality-of-care targets in this and other cancer patient cohorts, with particular focus on the timeliness of palliative care engagement.