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Air pollution is linked to mortality and morbidity. Since humans spend nearly all their time indoors, improving indoor air quality (IAQ) is a compelling approach to mitigate air pollutant exposure. To assess interventions, relying on clinical outcomes may require prolonged follow-up, which hinders feasibility. Thus, identifying biomarkers that respond to changes in IAQ may be useful to assess the effectiveness of interventions.
We conducted a narrative review by searching several databases to identify studies published over the last decade that measured the response of blood, urine, and/or salivary biomarkers to variations (natural and intervention-induced) of changes in indoor air pollutant exposure.
Numerous studies reported on associations between IAQ exposures and biomarkers with heterogeneity across study designs and methods. This review summarizes the responses of 113 biomarkers described in 30 articles. The biomarkers which most frequently responded to variations in indoor air pollutant exposures were high sensitivity C-reactive protein (hsCRP), von Willebrand Factor (vWF), 8-hydroxy-2′-deoxyguanosine (8-OHdG), and 1-hydroxypyrene (1-OHP).
This review will guide the selection of biomarkers for translational studies evaluating the impact of indoor air pollutants on human health.
Introduction: Acute heart failure (AHF) is a common emergency department (ED) presentation and may be associated with poor outcomes. Conversely, many patients rapidly improve with ED treatment and may not need hospital admission. Because there is little evidence to guide disposition decisions by ED and admitting physicians, we sought to create a risk score for predicting short-term serious outcomes (SSO) in patients with AHF. Methods: We conducted prospective cohort studies at 9 tertiary care hospital EDs from 2007 to 2019, and enrolled adult patients who required treatment for AHF. Each patient was assessed for standardized real-time clinical and laboratory variables, as well as for SSO (defined as death within 30 days or intubation, non-invasive ventilation (NIV), myocardial infarction, coronary bypass surgery, or new hemodialysis after admission). The fully pre-specified, logistic regression model with 13 predictors (age, pCO2, and SaO2 were modeled using spline functions with 3 knots and heart rate and creatinine with 5 knots) was fitted to the 10 multiple imputation datasets. Harrell's fast stepdown procedure reduced the number of variables. We calculated the potential impact on sensitivity (95% CI) for SSO and hospital admissions and estimated a sample size of 170 SSOs. Results: The 2,246 patients had mean age 77.4 years, male sex 54.5%, EMS arrival 41.1%, IV NTG 3.1%, ED NIV 5.2%, admission on initial visit 48.6%. Overall there were 174 (7.8%) SSOs including 70 deaths (3.1%). The final risk scale is comprised of five variables (points) and had c-statistic of 0.76 (95% CI: 0.73-0.80): 1.Valvular heart disease (1) 2.ED non-invasive ventilation (2) 3.Creatinine 150-300 (1) ≥300 (2) 4.Troponin 2x-4x URL (1) ≥5x URL (2) 5.Walk test failed (2) The probability of SSO ranged from 2.0% for a total score of 0 to 90.2% for a score of 10, showing good calibration. The model was stable over 1,000 bootstrap samples. Choosing a risk model total point admission threshold of >2 would yield a sensitivity of 80.5% (95% CI 73.9-86.1) for SSO with no change in admissions from current practice (48.6% vs 48.7%). Conclusion: Using a large prospectively collected dataset, we created a concise and sensitive risk scale to assist with admission decisions for patients with AHF in the ED. Implementation of this risk scoring scale should lead to safer and more efficient disposition decisions, with more high-risk patients being admitted and more low-risk patients being discharged.
There is wide acknowledgement that apathy is an important behavioural syndrome in Alzheimer’s disease and in various neuropsychiatric disorders. In light of recent research and the renewed interest in the correlates and impacts of apathy, and in its treatments, it is important to develop criteria for apathy that will be widely accepted, have clear operational steps, and that will be easily applied in practice and research settings. Meeting these needs is the focus of the task force work reported here.
The task force includes members of the Association Française de Psychiatrie Biologique, the European Psychiatric Association, the European Alzheimer’s Disease Consortium and experts from Europe, Australia and North America. An advanced draft was discussed at the consensus meeting (during the EPA conference in April 7th 2008) and a final agreement reached concerning operational definitions and hierarchy of the criteria.
Apathy is defined as a disorder of motivation that persists over time and should meet the following requirements. Firstly, the core feature of apathy, diminished motivation, must be present for at least four weeks; secondly two of the three dimensions of apathy (reduced goal-directed behaviour, goal-directed cognitive activity, and emotions) must also be present; thirdly there should be identifiable functional impairments attributable to the apathy. Finally, exclusion criteria are specified to exclude symptoms and states that mimic apathy.
Recent advances in biomarker technology have allowed for the development of highly predictive tests for Alzheimer's disease (AD) when combined with standard psychometric tests. Current research in AD utilizes the ADAS-Cog and/or the MMSE as standard measures; they do not exclusively address the specific deficits expected in an amnesic syndrome of the hippocampal type as express with AD.
Because episodic memory degradation is most strongly predictive of conversion from mild cognitive impairment (MCI) to AD, a clinical measure targeting this deficit is warranted.
To utilize current knowledge of neural correlates of different stages of episodic memory function and their modulation by AD to develop a psychometrically sound instrument.
The authors developed a brief scale that captures registration, storage and retrieval of information along four identified domains of episodic memory in AD. A second stage was to confirm BEMA in institutionalized subjects, and assess reliability and validity.
Preliminary results indicate good test-retest reliability and adequate sensitivity and specificity. the BEMA was positively and significantly correlated with other measures of episodic memory. the [insert scale name or abbreviation] yields a total score, scores for 3 lifetime periods and the duration of episodic memory impairment.
Findings suggest that a richer understanding of the memory deficits in AD can lead to the development of an instrument which taps different aspects of episodic memory function. This scale can aid in the screening, assessment and treatment of early AD and complement the newly developed one-plus-one strategy.
Prognostic models discriminate between groups of individuals likely to experience better or worse outcomes and to predict response to treatment.
The premise of the analysis was the assumption that baseline PANSS measurements could be a prognostic factor to inform decisions on the expected response (completion or early-termination) to treatment during participation in a clinical trial.
To examine early patterns/profiles based on PANSS and response to treatment (Study-Completer (SC), Early-Termination (ET)).
Receiver Operating Curves (ROC) was conducted on 809 subjects with SC versus ET. Factor structure assessed whether psychopathology constructs are comparable across SC and ET.
Positive-Symptoms: P5.Grandiosity, P7.Hostility and P4.Excitement are not as good as others in predicting ET. 91.1% ET would have scores of 5, 6 or 7 on P1.Delusions.
Negative-Symptoms: N5. Difficulty in Abstract Thinking and N6.Lack of Spontaneity and Flow of Conversation are not as good in predicting ET. 67.9% ET may have scores of 5, 6 or 7 on N1.Blunted Affect. General-Psychopathology: G3.Guilt Feelings, G6.Depression, G7.Motor Retardation, and G10.Disorientation are not as good in predicting ET. 73.2% ET have scores of 5, 6 or 7 on G9.Unusual Thought Content. Positive Factor accounted for the most variance 15.885%, then Negative factor=14.592%, then Hostile-Excitement=11.973% for SC. For ET, Negative Factor=13.713% variance, cognitive factor=12.451%, Excitement Factor=10.396%.
These findings represent patterns of early detection of response in clinical trials, and have led to the development of sophisticated algorithms that may allow investigators to identify ET and SC, which is important in trial success.
Every human being needs to acquire by interacting with peers, learning and gradually adapted to their socio-cultural environment, attitudes, group, class, gender, provided it fits the circumstances of the environment, personal values to their They come again, a reference system which is considered to be “culture”. You cannot assess psychiatric disorders in isolation, so it is essential to study the socio-cultural context in which it occurs. It is dynamic, its historic time and not everyone integrates alike. Through a case we try to show how culture influences the expression of psychiatric pathology. Specifically, in this patient it is evident that we are beings bio-psycho-social. It is a continuation and must integrate these three areas when assessing a patient. Here we start with a family history unrelated to the Mental Health so that adherence to antipsychotic treatment is guaranteed with monthly administration depot preparation. These socio-cultural factors are the main trigger for the breakdown of the subject that cause the patient psicotización (exacerbations related to stressful situations).
Disclosure of interest
The authors have not supplied their declaration of competing interest.
Low-income women are the group with the highest levels of obesity worldwide. In low-income settings, the use of predictive equations, which yield a measure of the individuals’ BMR, is a feasible approach to estimate the individuals’ total energy expenditure (TEE), using the factorial method (calculated-TEE = BMR × physical activity level), an important step of the obesity nutritional care. The present study aimed to identify the predictive equation that, in conjunction with metabolic equivalents of tasks (MET) data from accelerometers, yields the calculated-TEE with better agreement compared with the TEE measured by doubly labelled water (TEE-DLW). Forty-five women aged 19–45 years, with excess weight and mothers of undernourished children, were included. They received DLW to determine TEE (14 d); at the same time, they used triaxial accelerometers (7 d) to estimate their MET. The Bland–Altman method, paired-sample t tests, concordance correlation coefficient and root-mean-square error were used to assess the agreement. Maximum allowed differences were defined as 24 %, based on the within-variance coefficient of the energy intake of the sample. Eleven equations were studied. The calculated-TEE obtained by five equations showed non-significant bias: Dietary Reference Intake (Institute of Medicine (2005) Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids), FAO/WHO/UNU ((2001) Food and Nutrition Technical Report Series), Harris & Benedict ((1919) Proc Natl Acad Sci USA4, 370–373), Henry & Rees ((1991) Eur J Clin Nutr45, 177–185) and Schofield ((1985) Hum Nutr Clin Nutr39, 5–41). The mean percentage differences were –1·5, –0·8, 2·2, –2·2 and 2·0 %, respectively. Considering all parameters, FAO/WHO/UNU ((2001) Food and Nutrition Technical Report Series) equation performed slightly better than the others; nevertheless, no equation in conjunction with the estimated-MET showed a calculated-TEE with its CI for the Bland–Altman limits of agreement inside the pre-defined acceptable range.
The completion of a laser safety course remains a core surgical curriculum requirement for otolaryngologists training in the UK. This project aimed to develop a comprehensive laser safety course utilising both technical and non-technical skills simulation.
Otolaryngology trainees and consultants from the West of Scotland Deanery attended a 1-day course comprising lectures, two high-fidelity simulation scenarios and a technical simulation of safe laser use in practice.
The course, and in particular the use of simulation training, received excellent feedback from otolaryngology trainees and consultants who participated. Both simulation scenarios were validated for future use in laser simulation.
The course has been recognised as a laser safety course sufficient for the otolaryngology Certificate of Completion of Training. To the authors’ knowledge, this article represents the first description of using in situ non-technical skills simulation training for teaching laser use in otolaryngology.
Introduction: We previously derived (N = 559) and validated (N = 1,100) the 10-item Ottawa Heart Failure Risk Scale (OHFRS), to assist with disposition decisions for patients with acute heart failure (AHF) in the emergency department (ED). In the current study we sought to use a larger dataset to develop a more concise and more accurate risk scale. Methods: We analyzed data from the prior two studies and from a new cohort. For all 3 groups we conducted prospective cohort studies that enrolled patients who required treatment for AHF at 8 tertiary care hospital EDs. Patients were followed for 30 days. The primary outcome was short-term serious outcome (SSO), defined as death within 30 days, intubation or non-invasive ventilation (NIV) after admission, myocardial infarction, or relapse resulting in hospital admission within 14 days. The fully pre-specified logistic regression model with 13 predictors (where age, pCO2, and SaO2 were modeled using spline functions) was fitted to 10 multiple imputation datasets. Harrell's fast stepdown procedure reduced the number of variables. We calculated the potential impact on sensitivity (95% CI) for SSO and hospital admissions, and estimated a sample size of 2,000 patients. Results: The 1,986 patients had mean age 77.3 years, male 54.1%, EMS arrival 41.2%, IV NTG 3.3%, ED NIV 5.4%, admission on initial visit 49.5%. Overall there were 236 (11.9%) SSOs including 61 deaths (3.1%), meaning that current admission practice sensitivity for SSO was only 59.7%. The final HEARTRISK6 scale is comprised of 6 variables (points) (C-statistic 0.68): Valvular heart disease (2) Antiarrhythmic medication (2) ED non-invasive ventilation (3) Creatinine 80–150 (1); ≥150 (3) Troponin ≥3x URL (2) Walk test failed (1). The probability of SSO ranged from 4.8% for a total score of 0 to 62.4% for a score of 10, showing good calibration. Choosing a HEARTRISK6 total point admission threshold of ≥3 would yield sensitivity of 70.8% (95%CI 64.5-76.5) for SSO with a slight decrease in admissions to 47.9%. Choosing a threshold of ≥2 would yield a sensitivity of 84.3% (95%CI 79.0-88.7) but require 66.6% admissions. Conclusion: Using a large prospectively collected dataset, we created a more concise and more sensitive risk scale to assist with admission decisions for patients with AHF in the ED. Implementation of the HEARTRISK6 scale should lead to safer and more efficient disposition decisions, with more high-risk patients being admitted and more low-risk patients being discharged.
With the recent discovery of a dozen dusty star-forming galaxies and around 30 quasars at z > 5 that are hyper-luminous in the infrared (μ LIR > 1013 L⊙, where μ is a lensing magnification factor), the possibility has opened up for SPICA, the proposed ESA M5 mid-/far-infrared mission, to extend its spectroscopic studies toward the epoch of reionisation and beyond. In this paper, we examine the feasibility and scientific potential of such observations with SPICA’s far-infrared spectrometer SAFARI, which will probe a spectral range (35–230 μm) that will be unexplored by ALMA and JWST. Our simulations show that SAFARI is capable of delivering good-quality spectra for hyper-luminous infrared galaxies at z = 5 − 10, allowing us to sample spectral features in the rest-frame mid-infrared and to investigate a host of key scientific issues, such as the relative importance of star formation versus AGN, the hardness of the radiation field, the level of chemical enrichment, and the properties of the molecular gas. From a broader perspective, SAFARI offers the potential to open up a new frontier in the study of the early Universe, providing access to uniquely powerful spectral features for probing first-generation objects, such as the key cooling lines of low-metallicity or metal-free forming galaxies (fine-structure and H2 lines) and emission features of solid compounds freshly synthesised by Population III supernovae. Ultimately, SAFARI’s ability to explore the high-redshift Universe will be determined by the availability of sufficiently bright targets (whether intrinsically luminous or gravitationally lensed). With its launch expected around 2030, SPICA is ideally positioned to take full advantage of upcoming wide-field surveys such as LSST, SKA, Euclid, and WFIRST, which are likely to provide extraordinary targets for SAFARI.
We present Phantom, a fast, parallel, modular, and low-memory smoothed particle hydrodynamics and magnetohydrodynamics code developed over the last decade for astrophysical applications in three dimensions. The code has been developed with a focus on stellar, galactic, planetary, and high energy astrophysics, and has already been used widely for studies of accretion discs and turbulence, from the birth of planets to how black holes accrete. Here we describe and test the core algorithms as well as modules for magnetohydrodynamics, self-gravity, sink particles, dust–gas mixtures, H2 chemistry, physical viscosity, external forces including numerous galactic potentials, Lense–Thirring precession, Poynting–Robertson drag, and stochastic turbulent driving. Phantom is hereby made publicly available.
Clinical decision support (CDS) has been implemented in many clinical settings in order to improve decision-making. Their potential to improve diagnostic accuracy and reduce unnecessary testing is well documented; however, their effectiveness in impacting physician practice in real world implementations has been limited by poor physician adherence. The objective of this systematic review and meta-regression was to establish the effectiveness of CDS tools on adherence and identify which characteristics of CDS tools increase physician use of and adherence. Methods: A systematic review and meta-analysis was conducted. MEDLINE, EMBASE, PsychINFO, the Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews were searched from inception to June 2017. Included studies examined CDS in a hospital setting, reported on physician adherence to or use of CDS, utilized a comparative study design, and reported primary data. All tool type was classified based on the Cochrane Effective Practice and Organization of Care (EPOC) classifications. Studies were stratified based on study design (RCT vs. observational). Meta-regression was completed to assess the different effect of characteristics of the tool (e.g. whether the tool was mandatory or voluntary, EPOC classifications). Results: A total of 3,359 candidate articles were identified. Seventy-two met inclusion criteria, of which 46 reported outcomes appropriate for meta-regression (5 RCTs and 41 observational studies). Overall, a trend of increased CDS use was found (pooled RCT OR: 1.36 [95% CI: 0.97-1.89]; pooled observational OR: 2.12 [95% CI: 1.75-2.56]).When type of tool is considered, clinical practice guidelines were superior compared to other interventions (p=.150). Reminders (p=.473) and educational interventions (p=.489) were less successful than other interventions. Multi-modal tools were not more successful that single interventions (p=.810). Lastly, voluntary tools may be supperior to than mandatory tools (p=.148). None of these results are statistically significant. Conclusion: CDS tools accompanied by a planned intervention increases physician utilization and adherence to the tool. Meta-regression found that clinical practice guidelines had the biggest impact on physician adherence although not statistically significant. Further research is required to understand the most effective intervention to maximize physician utilization of CDS tools.
To identify predominant dietary patterns in four African populations and examine their association with obesity.
We used data from the Africa/Harvard School of Public Health Partnership for Cohort Research and Training (PaCT) pilot study established to investigate the feasibility of a multi-country longitudinal study of non-communicable chronic disease in sub-Saharan Africa. We applied principal component analysis to dietary intake data collected from an FFQ developed for PaCT to ascertain dietary patterns in Tanzania, South Africa, and peri-urban and rural Uganda. The sample consisted of 444 women and 294 men.
We identified two dietary patterns: the Mixed Diet pattern characterized by high intakes of unprocessed foods such as vegetables and fresh fish, but also cold cuts and refined grains; and the Processed Diet pattern characterized by high intakes of salad dressing, cold cuts and sweets. Women in the highest tertile of the Processed Diet pattern score were 3·00 times more likely to be overweight (95 % CI 1·66, 5·45; prevalence=74 %) and 4·24 times more likely to be obese (95 % CI 2·23, 8·05; prevalence=44 %) than women in this pattern’s lowest tertile (both P<0·0001; prevalence=47 and 14 %, respectively). We found similarly strong associations in men. There was no association between the Mixed Diet pattern and overweight or obesity.
We identified two major dietary patterns in several African populations, a Mixed Diet pattern and a Processed Diet pattern. The Processed Diet pattern was associated with obesity.
The SPICA mid- and far-infrared telescope will address fundamental issues in our understanding of star formation and ISM physics in galaxies. A particular hallmark of SPICA is the outstanding sensitivity enabled by the cold telescope, optimised detectors, and wide instantaneous bandwidth throughout the mid- and far-infrared. The spectroscopic, imaging, and polarimetric observations that SPICA will be able to collect will help in clarifying the complex physical mechanisms which underlie the baryon cycle of galaxies. In particular, (i) the access to a large suite of atomic and ionic fine-structure lines for large samples of galaxies will shed light on the origin of the observed spread in star-formation rates within and between galaxies, (ii) observations of HD rotational lines (out to ~10 Mpc) and fine structure lines such as [C ii] 158 μm (out to ~100 Mpc) will clarify the main reservoirs of interstellar matter in galaxies, including phases where CO does not emit, (iii) far-infrared spectroscopy of dust and ice features will address uncertainties in the mass and composition of dust in galaxies, and the contributions of supernovae to the interstellar dust budget will be quantified by photometry and monitoring of supernova remnants in nearby galaxies, (iv) observations of far-infrared cooling lines such as [O i] 63 μm from star-forming molecular clouds in our Galaxy will evaluate the importance of shocks to dissipate turbulent energy. The paper concludes with requirements for the telescope and instruments, and recommendations for the observing strategy.
IR spectroscopy in the range 12–230 μm with the SPace IR telescope for Cosmology and Astrophysics (SPICA) will reveal the physical processes governing the formation and evolution of galaxies and black holes through cosmic time, bridging the gap between the James Webb Space Telescope and the upcoming Extremely Large Telescopes at shorter wavelengths and the Atacama Large Millimeter Array at longer wavelengths. The SPICA, with its 2.5-m telescope actively cooled to below 8 K, will obtain the first spectroscopic determination, in the mid-IR rest-frame, of both the star-formation rate and black hole accretion rate histories of galaxies, reaching lookback times of 12 Gyr, for large statistically significant samples. Densities, temperatures, radiation fields, and gas-phase metallicities will be measured in dust-obscured galaxies and active galactic nuclei, sampling a large range in mass and luminosity, from faint local dwarf galaxies to luminous quasars in the distant Universe. Active galactic nuclei and starburst feedback and feeding mechanisms in distant galaxies will be uncovered through detailed measurements of molecular and atomic line profiles. The SPICA’s large-area deep spectrophotometric surveys will provide mid-IR spectra and continuum fluxes for unbiased samples of tens of thousands of galaxies, out to redshifts of z ~ 6.
Our current knowledge of star formation and accretion luminosity at high redshift (z > 3–4), as well as the possible connections between them, relies mostly on observations in the rest-frame ultraviolet, which are strongly affected by dust obscuration. Due to the lack of sensitivity of past and current infrared instrumentation, so far it has not been possible to get a glimpse into the early phases of the dust-obscured Universe. Among the next generation of infrared observatories, SPICA, observing in the 12–350 µm range, will be the only facility that can enable us to trace the evolution of the obscured star-formation rate and black-hole accretion rate densities over cosmic time, from the peak of their activity back to the reionisation epoch (i.e., 3 < z ≲ 6–7), where its predecessors had severe limitations. Here, we discuss the potential of photometric surveys performed with the SPICA mid-infrared instrument, enabled by the very low level of impact of dust obscuration in a band centred at 34 µm. These unique unbiased photometric surveys that SPICA will perform will fully characterise the evolution of AGNs and star-forming galaxies after reionisation.