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Hendra virus (HeV) continues to cause fatal infection in horses and threaten infection in close-contact humans in eastern Australia. Species of Pteropus bats (flying-foxes) are the natural reservoir of the virus. We caught and sampled flying-foxes from a multispecies roost in southeast Queensland, Australia on eight occasions between June 2013 and June 2014. The effects of sample date, species, sex, age class, body condition score (BCS), pregnancy and lactation on HeV antibody prevalence, log-transformed median fluorescent intensity (lnMFI) values and HeV RNA status were assessed using unbalanced generalised linear models. A total of 1968 flying-foxes were sampled, comprising 1012 Pteropus alecto, 742 P. poliocephalus and 214 P. scapulatus. Sample date, species and age class were each statistically associated with HeV RNA status, antibody status and lnMFI values; BCS was statistically associated with HeV RNA status and antibody status. The findings support immunologically naïve sub-adult P. alecto playing an important role in maintaining HeV infection at a population level. The biological significance of the association between BCS and HeV RNA status, and BCS and HeV antibody status, is less clear and warrants further investigation. Contrary to previous studies, we found no direct association between HeV infection and pregnancy or lactation. The findings in P. poliocephalus suggest that HeV exposure in this species may not result in systemic infection and virus excretion, or alternatively, may reflect assay cross-reactivity with another (unidentified) henipavirus.
As depression has a recurrent course, relapse and recurrence prevention is essential.
In our randomised controlled trial (registered with the Nederlands trial register, identifier: NTR1907), we found that adding preventive cognitive therapy (PCT) to maintenance antidepressants (PCT+AD) yielded substantial protective effects versus antidepressants only in individuals with recurrent depression. Antidepressants were not superior to PCT while tapering antidepressants (PCT/−AD). To inform decision-makers on treatment allocation, we present the corresponding cost-effectiveness, cost-utility and budget impact.
Data were analysed (n = 289) using a societal perspective with 24-months of follow-up, with depression-free days and quality-adjusted life years (QALYs) as health outcomes. Incremental cost-effectiveness ratios were calculated and cost-effectiveness planes and cost-effectiveness acceptability curves were derived to provide information about cost-effectiveness. The budget impact was examined with a health economic simulation model.
Mean total costs over 24 months were €6814, €10 264 and €13 282 for AD+PCT, antidepressants only and PCT/−AD, respectively. Compared with antidepressants only, PCT+AD resulted in significant improvements in depression-free days but not QALYs. Health gains did not significantly favour antidepressants only versus PCT/−AD. High probabilities were found that PCT+AD versus antidepressants only and antidepressants only versus PCT/−AD were dominant with low willingness-to-pay thresholds. The budget impact analysis showed decreased societal costs for PCT+AD versus antidepressants only and for antidepressants only versus PCT/−AD.
Adding PCT to antidepressants is cost-effective over 24 months and PCT with guided tapering of antidepressants in long-term users might result in extra costs. Future studies examining costs and effects of antidepressants versus psychological interventions over a longer period may identify a break-even point where PCT/−AD will become cost-effective.
Declaration of interest
C.L.H.B. is co-editor of PLOS One and receives no honorarium for this role. She is also co-developer of the Dutch multidisciplinary clinical guideline for anxiety and depression, for which she receives no remuneration. She is a member of the scientific advisory board of the National Insure Institute, for which she receives an honorarium, although this role has no direct relation to this study. C.L.H.B. has presented keynote addresses at conferences, such as the European Psychiatry Association and the European Conference Association, for which she sometimes receives an honorarium. She has presented clinical training workshops, some including a fee. She receives royalties from her books and co-edited books and she developed preventive cognitive therapy on the basis of the cognitive model of A. T. Beck. W.A.N. has received grants from the Netherlands Organisation for Health Research and Development and the European Union and honoraria and speakers' fees from Lundbeck and Aristo Pharma, and has served as a consultant for Daleco Pharma.
A substantial proportion of persons with mental disorders seek treatment from complementary and alternative medicine (CAM) professionals. However, data on how CAM contacts vary across countries, mental disorders and their severity, and health care settings is largely lacking. The aim was therefore to investigate the prevalence of contacts with CAM providers in a large cross-national sample of persons with 12-month mental disorders.
In the World Mental Health Surveys, the Composite International Diagnostic Interview was administered to determine the presence of past 12 month mental disorders in 138 801 participants aged 18–100 derived from representative general population samples. Participants were recruited between 2001 and 2012. Rates of self-reported CAM contacts for each of the 28 surveys across 25 countries and 12 mental disorder groups were calculated for all persons with past 12-month mental disorders. Mental disorders were grouped into mood disorders, anxiety disorders or behavioural disorders, and further divided by severity levels. Satisfaction with conventional care was also compared with CAM contact satisfaction.
An estimated 3.6% (standard error 0.2%) of persons with a past 12-month mental disorder reported a CAM contact, which was two times higher in high-income countries (4.6%; standard error 0.3%) than in low- and middle-income countries (2.3%; standard error 0.2%). CAM contacts were largely comparable for different disorder types, but particularly high in persons receiving conventional care (8.6–17.8%). CAM contacts increased with increasing mental disorder severity. Among persons receiving specialist mental health care, CAM contacts were reported by 14.0% for severe mood disorders, 16.2% for severe anxiety disorders and 22.5% for severe behavioural disorders. Satisfaction with care was comparable with respect to CAM contacts (78.3%) and conventional care (75.6%) in persons that received both.
CAM contacts are common in persons with severe mental disorders, in high-income countries, and in persons receiving conventional care. Our findings support the notion of CAM as largely complementary but are in contrast to suggestions that this concerns person with only mild, transient complaints. There was no indication that persons were less satisfied by CAM visits than by receiving conventional care. We encourage health care professionals in conventional settings to openly discuss the care patients are receiving, whether conventional or not, and their reasons for doing so.
Elemental, chemical, and structural analysis of polycrystalline materials at the micron scale is frequently carried out using microfocused synchrotron X-ray beams, sometimes on multiple instruments. The Maia pixelated energy-dispersive X-ray area detector enables the simultaneous collection of X-ray fluorescence (XRF) and diffraction because of the relatively large solid angle and number of pixels when compared with other systems. The large solid angle also permits extraction of surface topography because of changes in self-absorption. This work demonstrates the capability of the Maia detector for simultaneous measurement of XRF and diffraction for mapping the short- and long-range order across the grain structure in a Ni polycrystalline foil.
Research on post-traumatic stress disorder (PTSD) course finds a substantial proportion of cases remit within 6 months, a majority within 2 years, and a substantial minority persists for many years. Results are inconsistent about pre-trauma predictors.
The WHO World Mental Health surveys assessed lifetime DSM-IV PTSD presence-course after one randomly-selected trauma, allowing retrospective estimates of PTSD duration. Prior traumas, childhood adversities (CAs), and other lifetime DSM-IV mental disorders were examined as predictors using discrete-time person-month survival analysis among the 1575 respondents with lifetime PTSD.
20%, 27%, and 50% of cases recovered within 3, 6, and 24 months and 77% within 10 years (the longest duration allowing stable estimates). Time-related recall bias was found largely for recoveries after 24 months. Recovery was weakly related to most trauma types other than very low [odds-ratio (OR) 0.2–0.3] early-recovery (within 24 months) associated with purposefully injuring/torturing/killing and witnessing atrocities and very low later-recovery (25+ months) associated with being kidnapped. The significant ORs for prior traumas, CAs, and mental disorders were generally inconsistent between early- and later-recovery models. Cross-validated versions of final models nonetheless discriminated significantly between the 50% of respondents with highest and lowest predicted probabilities of both early-recovery (66–55% v. 43%) and later-recovery (75–68% v. 39%).
We found PTSD recovery trajectories similar to those in previous studies. The weak associations of pre-trauma factors with recovery, also consistent with previous studies, presumably are due to stronger influences of post-trauma factors.
Sexual assault is a global concern with post-traumatic stress disorder (PTSD), one of the common sequelae. Early intervention can help prevent PTSD, making identification of those at high risk for the disorder a priority. Lack of representative sampling of both sexual assault survivors and sexual assaults in prior studies might have reduced the ability to develop accurate prediction models for early identification of high-risk sexual assault survivors.
Data come from 12 face-to-face, cross-sectional surveys of community-dwelling adults conducted in 11 countries. Analysis was based on the data from the 411 women from these surveys for whom sexual assault was the randomly selected lifetime traumatic event (TE). Seven classes of predictors were assessed: socio-demographics, characteristics of the assault, the respondent's retrospective perception that she could have prevented the assault, other prior lifetime TEs, exposure to childhood family adversities and prior mental disorders.
Prevalence of Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) PTSD associated with randomly selected sexual assaults was 20.2%. PTSD was more common for repeated than single-occurrence victimization and positively associated with prior TEs and childhood adversities. Respondent's perception that she could have prevented the assault interacted with history of mental disorder such that it reduced odds of PTSD, but only among women without prior disorders (odds ratio 0.2, 95% confidence interval 0.1–0.9). The final model estimated that 40.3% of women with PTSD would be found among the 10% with the highest predicted risk.
Whether counterfactual preventability cognitions are adaptive may depend on mental health history. Predictive modelling may be useful in targeting high-risk women for preventive interventions.
Research on post-traumatic stress disorder (PTSD) following natural and human-made disasters has been undertaken for more than three decades. Although PTSD prevalence estimates vary widely, most are in the 20–40% range in disaster-focused studies but considerably lower (3–5%) in the few general population epidemiological surveys that evaluated disaster-related PTSD as part of a broader clinical assessment. The World Mental Health (WMH) Surveys provide an opportunity to examine disaster-related PTSD in representative general population surveys across a much wider range of sites than in previous studies.
Although disaster-related PTSD was evaluated in 18 WMH surveys, only six in high-income countries had enough respondents for a risk factor analysis. Predictors considered were socio-demographics, disaster characteristics, and pre-disaster vulnerability factors (childhood family adversities, prior traumatic experiences, and prior mental disorders).
Disaster-related PTSD prevalence was 0.0–3.8% among adult (ages 18+) WMH respondents and was significantly related to high education, serious injury or death of someone close, forced displacement from home, and pre-existing vulnerabilities (prior childhood family adversities, other traumas, and mental disorders). Of PTSD cases 44.5% were among the 5% of respondents classified by the model as having highest PTSD risk.
Disaster-related PTSD is uncommon in high-income WMH countries. Risk factors are consistent with prior research: severity of exposure, history of prior stress exposure, and pre-existing mental disorders. The high concentration of PTSD among respondents with high predicted risk in our model supports the focus of screening assessments that identify disaster survivors most in need of preventive interventions.
Kau Bay Halmahera, Indonesia is a small marine basin that is separated from the adjacent SW Pacific Ocean by a shallow sill, 40m deep. Radiocarbon dating on piston cores in combination with a study on microfossils demonstrate that Kau Bay was a freshwater lake in Weichselian times. At 10,000 BP, the Bay became reconnected with the open ocean. It sill depth did not change in the intervening years, sea level at 10,000 BP stood 40m below the present level.
Near-infrared images of a sample of red, blue and giant low surface brightness disk galaxies (LSBGs) were combined with optical data with the aim of constraining their star formation histories. Most LSBGs have strong colour gradients consistent with mean stellar age gradients. We find that LSBGs have a large range of ages and metallicities, spanning those observed in normal disk galaxies. In particular, red and blue LSBGs have very different star formation histories and represent two independent routes to low B band surface brightness. Blue LSBGs are well described by models with low, roughly constant star formation rates, whereas red LSBGs are better described by a ‘faded disk’ scenario.
Clinicians need guidance to address the heterogeneity of treatment responses of patients with major depressive disorder (MDD). While prediction schemes based on symptom clustering and biomarkers have so far not yielded results of sufficient strength to inform clinical decision-making, prediction schemes based on big data predictive analytic models might be more practically useful.
We review evidence suggesting that prediction equations based on symptoms and other easily-assessed clinical features found in previous research to predict MDD treatment outcomes might provide a foundation for developing predictive analytic clinical decision support models that could help clinicians select optimal (personalised) MDD treatments. These methods could also be useful in targeting patient subsamples for more expensive biomarker assessments.
Approximately two dozen baseline variables obtained from medical records or patient reports have been found repeatedly in MDD treatment trials to predict overall treatment outcomes (i.e., intervention v. control) or differential treatment outcomes (i.e., intervention A v. intervention B). Similar evidence has been found in observational studies of MDD persistence-severity. However, no treatment studies have yet attempted to develop treatment outcome equations using the full set of these predictors. Promising preliminary empirical results coupled with recent developments in statistical methodology suggest that models could be developed to provide useful clinical decision support in personalised treatment selection. These tools could also provide a strong foundation to increase statistical power in focused studies of biomarkers and MDD heterogeneity of treatment response in subsequent controlled trials.
Coordinated efforts are needed to develop a protocol for systematically collecting information about established predictors of heterogeneity of MDD treatment response in large observational treatment studies, applying and refining these models in subsequent pragmatic trials, carrying out pooled secondary analyses to extract the maximum amount of information from these coordinated studies, and using this information to focus future discovery efforts in the segment of the patient population in which continued uncertainty about treatment response exists.
Models of galaxy formation in a hierarchical universe predict substantial scatter in the halo-to-halo stellar properties, owing to stochasticity in galaxies' merger histories. Currently, only few detailed observations of stellar halos are available, mainly for the Milky Way and M31. We present the stellar halo color/metallicity and density profiles of red giant branch stars out to ~60 kpc along the minor axis of six massive nearby Milky Way-like galaxies beyond the Local Group from the Galaxy Halos, Outer disks, Substructure, Thick disks and Star clusters (GHOSTS) HST survey. This enlargement of the sample of galaxies with observations of stellar halo properties is needed to understand the range of possible halo properties, i.e. not only the mean properties but also the halo-to-halo scatter, what a ‘typical’ halo looks like, and how similar the Milky Way halo is to other halos beyond the Local Group.
Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question.
Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes.
Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6–72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors.
Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.
The association between depression after myocardial infarction and increased risk of mortality and cardiac morbidity may be due to cardiac disease severity.
To combine original data from studies on the association between post-infarction depression and prognosis into one database, and to investigate to what extent such depression predicts prognosis independently of disease severity.
An individual patient data meta-analysis of studies was conducted using multilevel, multivariable Cox regression analyses.
Sixteen studies participated, creating a database of 10 175 post-infarction cases. Hazard ratios for post-infarction depression were 1.32 (95% CI 1.26–1.38, P<0.001) for all-cause mortality and 1.19 (95% CI 1.14–1.24, P<0.001) for cardiovascular events. Hazard ratios adjusted for disease severity were attenuated by 28% and 25% respectively.
The association between depression following myocardial infarction and prognosis is attenuated after adjustment for cardiac disease severity. Still, depression remains independently associated with prognosis, with a 22% increased risk of all-cause mortality and a 13% increased risk of cardiovascular events per standard deviation in depression z-score.
Current trends in population aging affect both recipients and providers of informal family caregiving, as the pool of family caregivers is shrinking while demand is increasing. Epidemiological research has not yet examined the implications of these trends for burdens experienced by aging family caregivers.
Cross-sectional community surveys in 20 countries asked 13 892 respondents aged 50+ years about the objective (time, financial) and subjective (distress, embarrassment) burdens they experience in providing care to first-degree relatives with 12 broadly defined serious physical and mental conditions. Differential burden was examined by country income category, kinship status and type of condition.
Among the 26.9–42.5% respondents in high-, upper-middle-, and low-/lower-middle-income countries reporting serious relative health conditions, 35.7–42.5% reported burden. Of those, 25.2–29.0% spent time and 13.5–19.4% money, while 24.4–30.6% felt distress and 6.4–21.7% embarrassment. Mean caregiving hours per week in those giving any time were 16.6–23.6 (169.9–205.8 h/week per 100 people aged 50+ years). Burden in low-/lower-middle-income countries was 2- to 3-fold higher than in higher-income countries, with any financial burden averaging 14.3% of median family income in high-, 17.7% in upper-middle-, and 39.8% in low-/lower-middle-income countries. Higher burden was reported by women than men and for conditions of spouses and children than parents or siblings.
Uncompensated family caregiving is an important societal asset that offsets rising formal healthcare costs. However, the substantial burdens experienced by aging caregivers across multiple family health conditions and geographic regions threaten the continued integrity of their caregiving capacity. Initiatives supporting older family caregivers are consequently needed, especially in low-/lower-middle-income countries.
The GHOSTS survey is the largest study to date of the resolved stellar populations in the outskirts of disk galaxies (Radburn-Smith et al.2011). The sample currently consists of 16 nearby disk galaxies, whose outer disks and halos are imaged with the Hubble Space Telescope (HST). I will present new results obtained from the study of 19 GHOSTS fields in M81's outermost part. The observed fields probe the stellar halo of M81 out to projected distances of ~50 kpc, an unprecedented distance for halo studies outside the Local Group. The 50% completeness levels of the color magnitude diagrams are typically at 2.5 mag below the tip of the red giant branch. When considering only fields located at galactocentric radius R > 15 kpc, we detect no color gradient in the stellar halo of M81. We compare these results with model predictions for the colors of stellar halos formed purely via accretion of satellite galaxies (Bullock & Johnston 2005). When we analyze the cosmologically motivated models in the same way as the HST data, we find that they predict no color gradient for the stellar halos, in good agreement with the observations (see Fig. 1).