Estimating the burden of disease attributable to diabetes in South Africa in 2000

OBJECTIVES To estimate the burden of disease attributable to diabetes by sex and age group in South Africa in 2000. DESIGN The framework adopted for the most recent World Health Organization comparative risk assessment (CRA) methodology was followed. Small community studies used to derive the prevalence of diabetes by population group were weighted proportionately for a national estimate. Population-attributable fractions were calculated and applied to revised burden of disease estimates. Monte Carlo simulation-modelling techniques were used for uncertainty analysis. SETTING South Africa. SUBJECTS Adults 30 years and older. OUTCOME MEASURES Mortality and disability-adjusted life years (DALYs) for ischaemic heart disease (IHD), stroke, hypertensive disease and renal failure. RESULTS Of South Africans aged >or= 30 years, 5.5% had diabetes which increased with age. Overall, about 14% of IHD, 10% of stroke, 12% of hypertensive disease and 12% of renal disease burden in adult males and females (30+ years) were attributable to diabetes. Diabetes was estimated to have caused 22,412 (95% uncertainty interval 20,755 - 24,872) or 4.3% (95% uncertainty interval 4.0 - 4.8%) of all deaths in South Africa in 2000. Since most of these occurred in middle or old age, the loss of healthy life years comprises a smaller proportion of the total 258,028 DALYs (95% uncertainty interval 236,856 - 290,849) in South Africa in 2000, accounting for 1.6% (95% uncertainty interval 1.5 - 1.8%) of the total burden. CONCLUSIONS Diabetes is an important direct and indirect cause of burden in South Africa. Primary prevention of the disease through multi-level interventions and improved management at primary health care level are needed.

Self-reported circumstances and consequences of driving while sleepy

Driver surveys are indispensable sources of information when estimating the role of sleepiness in crash causation. The purpose of the study was to (1) identify the prevalence of driving while sleepy among Finnish drivers, (2) determine the circumstances of such instances, and (3) identify risk factors and risk groups. Survey data were collected from a representative sample of active Finnish drivers (N = 1121). One-fifth of the drivers (19.5%) reported having fallen asleep at the wheel during their driving career, with 15.9% reporting having been close to falling asleep or having difficulty staying awake when driving during the previous twelve months. Epworth Sleepiness Scale scores were found to be associated with both types of sleepiness-related driving instances, while sleep quality was associated only with the latter. Compared to women, men more often reported falling asleep at the wheel; the differences were somewhat smaller with respect to fighting sleep while driving during the previous twelve months. The reported discrepancy in sleepiness-related instances (high prevalence of fighting sleep while driving during the previous twelve months and lower proportion of actually falling asleep) identifies young men (⩽25 years) as one of the main target groups for safety campaigns. Approximately three-quarters of drivers who had fallen asleep while driving reported taking action against falling asleep before it actually happened. Furthermore, almost all drivers who had fallen asleep while driving offered at least one logical reason that could have contributed to their falling asleep. These data indicate some degree of awareness about driving while sleepy and of the potential pre-trip factors that could lead to sleepiness while driving, and supports the notion that falling asleep at the wheel does not come as a (complete) surprise to the driver.

The relationship between stress, HPA axis functioning and brain structure in first episode psychosis over the first 12 weeks of treatment

Stress and abnormal hypothalamic-pituitary-adrenal axis functioning have been implicated in the early phase of psychosis and may partly explain reported changes in brain structure. This study used magnetic resonance imaging to investigate whether biological measures of stress were related to brain structure at baseline and to structural changes over the first 12 weeks of treatment in first episode patients (n=22) compared with matched healthy controls (n=22). At baseline, no significant group differences in biological measures of stress, cortical thickness or hippocampal volume were observed, but a significantly stronger relationship between baseline levels of cortisol and smaller white matter volumes of the cuneus and anterior cingulate was found in patients compared with controls. Over the first 12 weeks of treatment, patients showed a significant reduction in thickness of the posterior cingulate compared with controls. Patients also showed a significant positive relationship between baseline cortisol and increases in hippocampal volume over time, suggestive of brain swelling in association with psychotic exacerbation, while no such relationship was observed in controls. The current findings provide some support for the involvement of stress mechanisms in the pathophysiology of early psychosis, but the changes are subtle and warrant further investigation.

Pituitary volume in teenagers with first-presentation borderline personality disorder

This study used magnetic resonance imaging to examine pituitary gland volume (PGV) in teenage patients with a first presentation of borderline personality disorder (BPD). No difference in PGV was observed between healthy controls (n=20) and the total BPD cohort (n=20). However, within the BPD cohort, those exposed to childhood trauma (n=9) tended to have smaller pituitaries (-18%) than those with no history of childhood trauma (n=10). These preliminary findings suggest that exposure to childhood trauma, rather than BPD, per se, might be associated with reduced PGV, possibly reflecting hypothalamic-pituitary-adrenal axis dysfunction.

Pituitary volume predicts future transition to psychosis in individuals at ultra-high risk of developing psychosis

Background We examined pituitary volume before the onset of psychosis in subjects who were at ultra-high risk (UHR) for developing psychosis. Methods Pituitary volume was measured on 1.5-mm, coronal, 1.5-T magnetic resonance images in 94 UHR subjects recruited from admissions to the Personal Assessment and Crisis Evaluation Clinic in Melbourne, Australia and in 49 healthy control subjects. The UHR subjects were scanned at baseline and were followed clinically for a minimum of 1 year to detect transition to psychosis. Results Within the UHR group, a larger baseline pituitary volume was a significant predictor of future transition to psychosis. The UHR subjects who later went on to develop psychosis (UHR-P, n = 31) had a significantly larger (+12%; p = .001) baseline pituitary volume compared with UHR subjects who did not go on to develop psychosis (UHR-NP, n = 63). The survival analysis conducted by Cox regression showed that the risk of developing psychosis during the follow-up increased by 20% for every 10% increase in baseline pituitary volume (p = .002). Baseline pituitary volume of the UHR-NP subjects was smaller not only compared with UHR-P (as described above) but also compared with control subjects (−6%; p = .032). Conclusions The phase before the onset of psychosis is associated with a larger pituitary volume, suggesting activation of the HPA axis.

Preoperative bathing or showering with skin antiseptics to prevent surgical site infection

Background Surgical site infections (SSIs) are wound infections that occur after invasive (surgical) procedures. Preoperative bathing or showering with an antiseptic skin wash product is a well-accepted procedure for reducing skin bacteria (microflora). It is less clear whether reducing skin microflora leads to a lower incidence of surgical site infection. Objectives To review the evidence for preoperative bathing or showering with antiseptics for preventing hospital-acquired (nosocomial) surgical site infections. Search methods For this fifth update we searched the Cochrane Wounds Group Specialised Register (searched 18 December 2014); the Cochrane Central Register of Controlled Trials (The Cochrane Library 2014 Issue 11); Ovid MEDLINE (2012 to December Week 4 2014), Ovid MEDLINE (In-Process & Other Non-Indexed Citations December 18, 2014); Ovid EMBASE (2012 to 2014 Week 51), EBSCO CINAHL (2012 to December 18 2014) and reference lists of articles. Selection criteria Randomised controlled trials comparing any antiseptic preparation used for preoperative full-body bathing or showering with non-antiseptic preparations in people undergoing surgery. Data collection and analysis Two review authors independently assessed studies for selection, risk of bias and extracted data. Study authors were contacted for additional information. Main results We did not identify any new trials for inclusion in this fifth update. Seven trials involving a total of 10,157 participants were included. Four of the included trials had three comparison groups. The antiseptic used in all trials was 4% chlorhexidine gluconate (Hibiscrub/Riohex). Three trials involving 7791 participants compared chlorhexidine with a placebo. Bathing with chlorhexidine compared with placebo did not result in a statistically significant reduction in SSIs; the relative risk of SSI (RR) was 0.91 (95% confidence interval (CI) 0.80 to 1.04). When only trials of high quality were included in this comparison, the RR of SSI was 0.95 (95%CI 0.82 to 1.10). Three trials of 1443 participants compared bar soap with chlorhexidine; when combined there was no difference in the risk of SSIs (RR 1.02, 95% CI 0.57 to 1.84). Three trials of 1192 patients compared bathing with chlorhexidine with no washing, one large study found a statistically significant difference in favour of bathing with chlorhexidine (RR 0.36, 95%CI 0.17 to 0.79). The smaller studies found no difference between patients who washed with chlorhexidine and those who did not wash preoperatively. Authors' conclusions This review provides no clear evidence of benefit for preoperative showering or bathing with chlorhexidine over other wash products, to reduce surgical site infection. Efforts to reduce the incidence of nosocomial surgical site infection should focus on interventions where effect has been demonstrated.

Effects of different levels of refractive blur on night-time pedestrian visibility

Purpose The aim of this study was to systematically investigate the effect of different levels of refractive blur and driver age on night-time pedestrian recognition and determine whether clothing that has been shown to improve pedestrian conspicuity is robust to the effects of blur. Methods Night-time pedestrian recognition was measured for 24 visually normal participants (12 younger M=24.9±4.5 years and 12 older adults M=77.6±5.7 years) for three levels of binocular blur (+0.50 D, +1.00 D, +2.00 D) compared to baseline (optimal refractive correction). Pedestrians walked in place on a closed road circuit and wore one of three clothing conditions: i) everyday clothing, ii) a retro-reflective vest and iii) retro-reflective tape positioned on the extremities in a configuration that conveyed biological motion (known as “biomotion”); the order of conditions was randomized between participants. Pedestrian recognition distances were recorded for each blur and pedestrian clothing combination while participants drove an instrumented vehicle around a closed road course. Results The recognition distances for pedestrians were significantly reduced (p<0.05) by all levels of blur compared to baseline. Pedestrians wearing “biomotion” clothing were recognized at significantly longer distances than for the other clothing configurations in all blur conditions. However, these effects were smaller for the older adults, who had much shorter recognition distances for all conditions tested. Conclusions In summary, even small amounts of blur had a significant detrimental effect on night-time pedestrian recognition. Biomotion retro-reflective clothing was effective, even under moderately degraded visibility conditions, for both young and older drivers.

Carbon nanotube-based super nanotubes: Tunable thermal conductivity in three dimensions

Advances in nanomaterials/nanostructures offer the possibility of fabricating multifunctional materials for use in engineering applications. Carbon nanotube (CNT)-based nanostructures are a representative building block for these multifunctional materials. Based on a series of in silico studies, we investigated the possibility of tuning the thermal conductivity of a three-dimensional CNT-based nanostructure: a single-walled CNT-based super-nanotube. The thermal conductivity of the super-nanotubes was shown to vary with different connecting carbon rings and super-nanotubes with longer constituent single-walled CNTs and larger diameters had a smaller thermal conductivity. The inverse of the thermal conductivity of the super-nanotubes showed a good linear relationship with the inverse of the length. The thermal conductivity was approximately proportional to the inverse of the temperature, but was insensitive to the axial strain as a result of the Poisson ratio. These results provide a fundamental understanding of the thermal conductivity of the super-nanotubes and will guide their future design/fabrication and engineering applications.

Complete-linkage clustering for voice activity detection in audio and visual speech

We propose a novel technique for conducting robust voice activity detection (VAD) in high-noise recordings. We use Gaussian mixture modeling (GMM) to train two generic models; speech and non-speech. We then score smaller segments of a given (unseen) recording against each of these GMMs to obtain two respective likelihood scores for each segment. These scores are used to compute a dissimilarity measure between pairs of segments and to carry out complete-linkage clustering of the segments into speech and non-speech clusters. We compare the accuracy of our method against state-of-the-art and standardised VAD techniques to demonstrate an absolute improvement of 15% in half-total error rate (HTER) over the best performing baseline system and across the QUT-NOISE-TIMIT database. We then apply our approach to the Audio-Visual Database of American English (AVDBAE) to demonstrate the performance of our algorithm in using visual, audio-visual or a proposed fusion of these features.

The Driver Behaviour Questionnaire as accident predictor: A methodological re-meta-analysis

Problem The Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include contacting researchers to obtain unpublished results. Method The present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken. Results Outlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, analysis using the proxy of the mean of accidents in studies indicated that studies where effects for violations are unknown have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations that controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r<.07) for violations versus traffic accident involvement, depending upon which systematic tendencies in the data are controlled for. Conclusions: Methodological factors and dissemination bias have inflated the mean effect size of the DBQ in the published literature. Strong evidence of various artefactual effects is apparent. Practical Applications A greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance.

Multivariate variance-components analysis in DTI

Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.

Suitability of diodes for point dose measurements in IMRT/VMAT beams

This study investigated a potential source of inaccuracy for diode measurements in modulated beams; the effect of diode housing asymmetry on measurement results. The possible effects of diode housing asymmetry on the measurement of steep dose gradients were evaluated by measuring 5x5 cm2 beam profiles, with three cylindrical diodes and two commonly used ionization chambers, with each dosimeter positioned in a 3D scanning water tank with its stem perpendicular to the beam axis (horizontal) and parallel to the direction of scanning. The resulting profiles were used to compare the penumbrae measured with the diode stem pointing into (equivalent to a “stem-first” setup) and out of the field (equivalent to a “stem-last” setup) in order to evaluate the effects of dosimeter alignment and thereby identify the effects of dosimeter asymmetry. The stem-first and stem-last orientations resulted in differences of up to 0.2 mm in the measured 20-80% penumbra widths and differences of up to 0.4 mm in the off axis position of the 90% isodose. These differences, which are smaller than previously reported for older model dosimeters, were apparent in the profile results for both diodes and small volume ionization chambers. As an extension to this study, the practical use of all five dosimeters was exemplified by measuring point doses in IMRT test beams. These measurements showed good agreement (within 2%) between the diodes and the small volume ionization chamber, with all of these dosimeters being able to identify a region 3% under-dosage which was not identified by a larger volume (6 mm diameter) ionization chamber. The results of this work should help to remove some of the barriers to the use of diodes for modulated radiotherapy dosimetry in the future.

Cross database training of audio-visual hidden Markov models for phone recognition

Speech recognition can be improved by using visual information in the form of lip movements of the speaker in addition to audio information. To date, state-of-the-art techniques for audio-visual speech recognition continue to use audio and visual data of the same database for training their models. In this paper, we present a new approach to make use of one modality of an external dataset in addition to a given audio-visual dataset. By so doing, it is possible to create more powerful models from other extensive audio-only databases and adapt them on our comparatively smaller multi-stream databases. Results show that the presented approach outperforms the widely adopted synchronous hidden Markov models (HMM) trained jointly on audio and visual data of a given audio-visual database for phone recognition by 29% relative. It also outperforms the external audio models trained on extensive external audio datasets and also internal audio models by 5.5% and 46% relative respectively. We also show that the proposed approach is beneficial in noisy environments where the audio source is affected by the environmental noise.