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The coronavirus disease 2019 (COVID-19) pandemic has resulted in shortages of personal protective equipment (PPE), underscoring the urgent need for simple, efficient, and inexpensive methods to decontaminate masks and respirators exposed to severe acute respiratory coronavirus virus 2 (SARS-CoV-2). We hypothesized that methylene blue (MB) photochemical treatment, which has various clinical applications, could decontaminate PPE contaminated with coronavirus.
The 2 arms of the study included (1) PPE inoculation with coronaviruses followed by MB with light (MBL) decontamination treatment and (2) PPE treatment with MBL for 5 cycles of decontamination to determine maintenance of PPE performance.
MBL treatment was used to inactivate coronaviruses on 3 N95 filtering facepiece respirator (FFR) and 2 medical mask models. We inoculated FFR and medical mask materials with 3 coronaviruses, including SARS-CoV-2, and we treated them with 10 µM MB and exposed them to 50,000 lux of white light or 12,500 lux of red light for 30 minutes. In parallel, integrity was assessed after 5 cycles of decontamination using multiple US and international test methods, and the process was compared with the FDA-authorized vaporized hydrogen peroxide plus ozone (VHP+O3) decontamination method.
Overall, MBL robustly and consistently inactivated all 3 coronaviruses with 99.8% to >99.9% virus inactivation across all FFRs and medical masks tested. FFR and medical mask integrity was maintained after 5 cycles of MBL treatment, whereas 1 FFR model failed after 5 cycles of VHP+O3.
MBL treatment decontaminated respirators and masks by inactivating 3 tested coronaviruses without compromising integrity through 5 cycles of decontamination. MBL decontamination is effective, is low cost, and does not require specialized equipment, making it applicable in low- to high-resource settings.
Understanding core statistical properties and data features in mortality data are fundamental to the development of machine learning methods for demographic and actuarial applications of mortality projection. The study of statistical features in such data forms the basis for classification, regression and forecasting tasks. In particular, the understanding of key statistical structure in such data can aid in improving accuracy in undertaking mortality projection and forecasting when constructing life tables. The ability to accurately forecast mortality is a critical aspect for the study of demography, life insurance product design and pricing, pension planning and insurance-based decision risk management. Though many stylised facts of mortality data have been discussed in the literature, we provide evidence for a novel statistical feature that is pervasive in mortality data at a national level that is as yet unexplored. In this regard, we demonstrate in this work a strong evidence for the existence of long memory features in mortality data, and second that such long memory structures display multifractality as a statistical feature that can act as a discriminator of mortality dynamics by age, gender and country. To achieve this, we first outline the way in which we choose to represent the persistence of long memory from an estimator perspective. We make a natural link between a class of long memory features and an attribute of stochastic processes based on fractional Brownian motion. This allows us to use well established estimators for the Hurst exponent to then robustly and accurately study the long memory features of mortality data. We then introduce to mortality analysis the notion from data science known as multifractality. This allows us to study the long memory persistence features of mortality data on different timescales. We demonstrate its accuracy for sample sizes commensurate with national-level age term structure historical mortality records. A series of synthetic studies as well a comprehensive analysis of real mortality death count data are studied in order to demonstrate the pervasiveness of long memory structures in mortality data, both mono-fractal and multifractal functional features are verified to be present as stylised facts of national-level mortality data for most countries and most age groups by gender. We conclude by demonstrating how such features can be used in kernel clustering and mortality model forecasting to improve these actuarial applications.
Several recent reports have raised concern that infected coworkers may be an important source of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) acquisition by healthcare personnel. In a suspected outbreak among emergency department personnel, sequencing of SARS-CoV-2 confirmed transmission among coworkers. The suspected 6-person outbreak included 2 distinct transmission clusters and 1 unrelated infection.
This article analyzes the ambitious Case Quality Assessment System (CQAS) that the Supreme People’s Court of China (SPC) promoted during the first half of the 2010s. It offers a case-study of Court J, a grassroots court located in an affluent urban metropolis of China that struggled to come out ahead in the CQAS competition. The article discusses how the SPC quantified judging and the problems created by the metricization process. The CQAS project is analyzed as a case of metric fixation. By identifying the problems that doomed the CQAS, the article points out the challenges facing the authoritarian regime in subjecting good judging to quantitative output standards. The CQAS is a metric that judges judging. It reveals how judging is viewed by the party-state. The article concludes by discussing the legacy of the CQAS. Though it nominally ended in 2014, key indicators that it introduced for supervising judges are still used by the Chinese courts today. The CQAS presaged the growing centralization that the Chinese judicial system is undergoing today. Though the SPC has terminated the tournament-style competition that defined the CQAS, the metric remains the template used to evaluate judging.
Mortality projection and forecasting of life expectancy are two important aspects of the study of demography and life insurance modelling. We demonstrate in this work the existence of long memory in mortality data. Furthermore, models incorporating long memory structure provide a new approach to enhance mortality forecasts in terms of accuracy and reliability, which can improve the understanding of mortality. Novel mortality models are developed by extending the Lee–Carter (LC) model for death counts to incorporate a long memory time series structure. To link our extensions to existing actuarial work, we detail the relationship between the classical models of death counts developed under a Generalised Linear Model (GLM) formulation and the extensions we propose that are developed under an extension to the GLM framework known in time series literature as the Generalised Linear Autoregressive Moving Average (GLARMA) regression models. Bayesian inference is applied to estimate the model parameters. The Deviance Information Criterion (DIC) is evaluated to select between different LC model extensions of our proposed models in terms of both in-sample fits and out-of-sample forecasts performance. Furthermore, we compare our new models against existing models structures proposed in the literature when applied to the analysis of death count data sets from 16 countries divided according to genders and age groups. Estimates of mortality rates are applied to calculate life expectancies when constructing life tables. By comparing different life expectancy estimates, results show the LC model without the long memory component may provide underestimates of life expectancy, while the long memory model structure extensions reduce this effect. In summary, it is valuable to investigate how the long memory feature in mortality influences life expectancies in the construction of life tables.
Fifty to ninety percent of individuals with Major Neurocognitive Disorder (MNCD) have Neuropsychiatric Symptoms (NPS)1. Agitation and aggression are amongst the most persistent and treatment-refractory symptom clusters. Patients with these NPS are associated with increased risk of institutionalization, psychotropic medication use, caregiver burden, and mortality2.
Safe and effective treatments for NPS are lacking. Consensus guidelines emphasize the initial use of non-pharmacologic approaches though supportive evidence is limited3.
Extensive research has established the safety and efficacy of ECT in elderly patients with depression and other psychiatric conditions6. Clinical experience suggests that ECT is a valuable treatment option in MNCD-related treatment refractory NPS cases7-10. However, data supporting the efficacy and safety of this practice is scant.
Materials and Method:
Patients admitted to the geriatric psychiatry inpatient units who meet the inclusion criteria, were recruited from 2 Vancouver sites and 3 unit at Ontario Shores. These patients had an anesthesia consultation to evaluate their safety of going through ECT. Consent was obtained from their substitute decision makers. All patients enrolled are already on psychotropic medications.
Maternal and child health are intrinsically linked. With accumulating evidence over the past two decades supporting the developmental origins of health and diseases hypothesis, it is now widely recognised that nutrition in the first 1000 d sets the foundation for long-term health. Maternal diet before, during and after pregnancy can influence the developmental pathways of the fetus and lead to health consequences later in life. While maternal and infant mortality rates have declined significantly in the past two decades, the growing burden of obesity and chronic non-communicable diseases in women of reproductive age and children is on a rapid rise worldwide, in developed and developing countries. A key contributory factor is malnutrition, which is a consequence of consuming poor quality diets. Suboptimal macronutrient balance and micronutrient inadequacies can lead to undesirable maternal body composition and metabolism, in turn influencing the health of the mother and leading to longer-term metabolic and cognitive health consequences in the infant. The GUSTO (Growing Up in Singapore Towards healthy Outcomes) study, a mother–offspring multi-ethnic cohort study in Singapore, has contributed to this body of evidence over the past 10 years. This review will illustrate how nutritional epidemiological research through a birth cohort has illuminated the importance and urgency of maternal and child nutrition and health in a modern, industrialised setting. It underscores the importance of a number of critical nutrients during pregnancy, in combination with healthy dietary patterns and appropriate meal timing, for optimal maternal and child health.
The existence of long memory in mortality data improves the understandings of features of mortality data and provides a new approach for establishing mortality models. The findings of long-memory phenomena in mortality data motivate us to develop new mortality models by extending the Lee–Carter (LC) model to death counts and incorporating long-memory model structure. Furthermore, there are no identification issues arising in the proposed model class. Hence, the constraints which cause many computational issues in LC models are removed. The models are applied to analyse mortality death count data sets from three different countries divided according to genders. Bayesian inference with various selection criteria is applied to perform the model parameter estimation and mortality rate forecasting. Results show that multivariate long-memory mortality model with long-memory cohort effect model outperforms multivariate extended LC cohort model in both in-sample fitting and out-sample forecast. Increasing the accuracy of forecasting of mortality rates and improving the projection of life expectancy is an important consideration for insurance companies and governments since misleading predictions may result in insufficient funds for retirement and pension plans.
Item 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most positive responses are not associated with suicidality. The PHQ-8, which omits Item 9, is thus increasingly used in research. We assessed equivalency of total score correlations and the diagnostic accuracy to detect major depression of the PHQ-8 and PHQ-9.
We conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic accuracy.
16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard (N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (−0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies (N = 27), with similar results for studies that used other types of interviews (N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01).
PHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.
Although relapse in psychosis is common, a small proportion of patients will not relapse in the long term. We examined the proportion and predictors of patients who never relapsed in the 10 years following complete resolution of positive symptoms from their first psychotic episode.
Patients who previously enrolled in a 12-month randomized controlled trial on medication discontinuation and relapse following first-episode psychosis (FEP) were followed up after 10 years. Relapse of positive symptoms was operationalized as a change from a Clinical Global Impression scale positive score of <3 for at least 3 consecutive months to a score of ⩾3 (mild or more severe). Baseline predictors included basic demographics, premorbid functioning, symptoms, functioning, and neurocognitive functioning.
Out of 178 first-episode patients, 37 (21%) never relapsed during the 10-year period. Univariate predictors (p ⩽ 0.1) of patients who never relapsed included a duration of untreated psychosis (DUP) ⩽30 days, diagnosed with non-schizophrenia spectrum disorders, having less severe negative symptoms, and performing better in logical memory immediate recall and verbal fluency tests. A multivariate logistic regression analysis further suggested that the absence of any relapsing episodes was significantly related to better short-term verbal memory, shorter DUP, and non-schizophrenia spectrum disorders.
Treatment delay and neurocognitive function are potentially modifiable predictors of good long-term prognosis in FEP. These predictors are informative as they can be incorporated into an optimum risk prediction model in the future, which would help with clinical decision making regarding maintenance treatment in FEP.
Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.
To evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics.
Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit.
A total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15–3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98–10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7–15) (OR = 0.96; 95% CI = 0.56–1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26–0.97).
The MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.
Declaration of interest
Drs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain. Dr Chan is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD and Pfizer. She has received sponsorships and honorarium for giving lectures and providing consultancy and her affiliated institution has received research grants from these companies. Dr Hegerl declares that within the past 3 years, he was an advisory board member for Lundbeck, Servier and Otsuka Pharma; a consultant for Bayer Pharma; and a speaker for Medice Arzneimittel, Novartis, and Roche Pharma, all outside the submitted work. Dr Inagaki declares that he has received grants from Novartis Pharma, lecture fees from Pfizer, Mochida, Shionogi, Sumitomo Dainippon Pharma, Daiichi-Sankyo, Meiji Seika and Takeda, and royalties from Nippon Hyoron Sha, Nanzando, Seiwa Shoten, Igaku-shoin and Technomics, all outside of the submitted work. Dr Yamada reports personal fees from Meiji Seika Pharma Co., Ltd., MSD K.K., Asahi Kasei Pharma Corporation, Seishin Shobo, Seiwa Shoten Co., Ltd., Igaku-shoin Ltd., Chugai Igakusha and Sentan Igakusha, all outside the submitted work. All other authors declare no competing interests. No funder had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.
Early life nutrition and feeding practices are important modifiable determinants of subsequent obesity, yet little is known about the circadian feeding pattern of 12-month-old infants. We aimed to describe the 24-h feeding patterns of 12-month-old infants and examine their associations with maternal and infant characteristics. Mothers from a prospective birth cohort study (n 431) reported dietary intakes of their 12-month-old infants and respective feeding times using 24-h dietary recall. Based on their feeding times, infants were classified into post-midnight (00.00–05.59 hours) and pre-midnight (06.00–23.59 hours) feeders. Mean daily energy intake was 3234 (sd 950) kJ (773 (sd 227) kcal), comprising 51·8 (sd 7·8) % carbohydrate, 33·9 (sd 7·2) % fat and 14·4 (sd 3·2) % protein. Mean hourly energy intake and proportion of infants fed were lower during post-midnight than pre-midnight hours. There were 251 (58·2 %) pre-midnight and 180 (41·8 %) post-midnight feeders. Post-midnight feeders consumed higher daily energy, carbohydrate, fat and protein intakes than pre-midnight feeders (all P<0·001). The difference in energy intake originated from energy content consumed during the post-midnight period. Majority (n 173) of post-midnight feeders consumed formula milk during the post-midnight period. Using multivariate logistic regression with confounder adjustment, exclusively breast-feeding during the first 6 months of life was negatively associated with post-midnight feeding at 12 months (adjusted OR 0·31; 95 % CI 0·11, 0·82). This study provides new insights into the circadian pattern of energy intake during infancy. Our findings indicated that the timing of feeding at 12 months was associated with daily energy and macronutrient intakes, and feeding mode during early infancy.
Ketamine has emerged as a novel therapeutic agent for major depressive episodes, spurring interest in its potential to augment electroconvulsive therapy (ECT).
We sought to update our preliminary systematic review and meta-analysis, focusing on randomised controlled trials (RCTs) involving an index course of ECT, and testing the hypothesis that lack of efficacy is due to barbiturate anaesthetic co-administration.
We searched EMBASE, CENTRAL and Medline to identify RCTs examining the efficacy of ketamine during a course of ECT. Data were synthesised from ten trials (ketamine group n = 333, comparator group n = 269) using pooled random effects models.
Electroconvulsive therapy with ketamine was not associated with greater improvements in depressive symptoms or higher rates of clinical response or remission, nor did it result in pro-cognitive effects. This held true when limiting analysis to trials without barbiturate anaesthetic co-administration. Increased rates of confusion were reported.
Overall, our analyses do not support using ketamine over other induction agents in ECT.
Stonehenge is a site that continues to yield surprises. Excavation in 2009 added a new and unexpected feature: a smaller, dismantled stone circle on the banks of the River Avon, connected to Stonehenge itself by the Avenue. This new structure has been labelled ‘Bluestonehenge’ from the evidence that it once held a circle of bluestones that were later removed to Stonehenge. Investigation of the Avenue closer to Stonehenge revealed deep periglacial fissures within it. Their alignment on Stonehenge's solstitial axis (midwinter sunset–midsummer sunrise) raises questions about the early origins of this ritual landscape.
Research suggests that an 8-week mindfulness-based cognitive therapy
(MBCT) course may be effective for generalised anxiety disorder
To compare changes in anxiety levels among participants with GAD randomly
assigned to MBCT, cognitive–behavioural therapy-based psychoeducation and
In total, 182 participants with GAD were recruited (trial registration
number: CUHK_CCT00267) and assigned to the three groups and followed for
5 months after baseline assessment with the two intervention groups
followed for an additional 6 months. Primary outcomes were anxiety and
Linear mixed models demonstrated significant group × time interaction
(F(4,148) = 5.10, P = 0.001) effects
for decreased anxiety for both the intervention groups relative to usual
care. Significant group × time interaction effects were observed for
worry and depressive symptoms and mental health-related quality of life
for the psychoeducation group only.
These results suggest that both of the interventions appear to be
superior to usual care for the reduction of anxiety symptoms.
Little is known about the influence of meal timing and energy consumption patterns throughout the day on glucose regulation during pregnancy. We examined the association of maternal feeding patterns with glycaemic levels among lean and overweight pregnant women. In a prospective cohort study in Singapore, maternal 24-h dietary recalls, fasting glucose (FG) and 2-h postprandial glucose (2HPPG) concentrations were measured at 26–28 weeks of gestation. Women (n 985) were classified into lean (BMI<23 kg/m2) or overweight (BMI≥23 kg/m2) groups. They were further categorised as predominantly daytime (pDT) or predominantly night-time (pNT) feeders according to consumption of greater proportion of energy content from 07.00 to 18.59 hours or from 19.00 to 06.59 hours, respectively. On stratification by weight status, lean pNT feeders were found to have higher FG than lean pDT feeders (4·36 (sd 0·38) v. 4·22 (sd 0·35) mmol/l; P=0·002); however, such differences were not observed between overweight pDT and pNT feeders (4·49 (sd 0·60) v. 4·46 (sd 0·45) mmol/l; P=0·717). Using multiple linear regression with confounder adjustment, pNT feeding was associated with higher FG in the lean group (β=0·16 mmol/l; 95 % CI 0·05, 0·26; P=0·003) but not in the overweight group (β=0·02 mmol/l; 95 % CI −0·17, 0·20; P=0·879). No significant association was found between maternal feeding pattern and 2HPPG in both the lean and the overweight groups. In conclusion, pNT feeding was associated with higher FG concentration in lean but not in overweight pregnant women, suggesting that there may be an adiposity-dependent effect of maternal feeding patterns on glucose tolerance during pregnancy.
We develop quantile functions from regression models in order to derive risk margin and to evaluate capital in non-life insurance applications. By utilizing the entire range of conditional quantile functions, especially higher quantile levels, we detail how quantile regression is capable of providing an accurate estimation of risk margin and an overview of implied capital based on the historical volatility of a general insurers loss portfolio. Two modeling frameworks are considered based around parametric and non-parametric regression models which we develop specifically in this insurance setting. In the parametric framework, quantile functions are derived using several distributions including the flexible generalized beta (GB2) distribution family, asymmetric Laplace (AL) distribution and power-Pareto (PP) distribution. In these parametric model based quantile regressions, we detail two basic formulations. The first involves embedding the quantile regression loss function from the nonparameteric setting into the argument of the kernel of a parametric data likelihood model, this is well known to naturally lead to the AL parametric model case. The second formulation we utilize in the parametric setting adopts an alternative quantile regression formulation in which we assume a structural expression for the regression trend and volatility functions which act to modify a base quantile function in order to produce the conditional data quantile function. This second approach allows a range of flexible parametric models to be considered with different tail behaviors. We demonstrate how to perform estimation of the resulting parametric models under a Bayesian regression framework. To achieve this, we design Markov chain Monte Carlo (MCMC) sampling strategies for the resulting Bayesian posterior quantile regression models. In the non-parametric framework, we construct quantile functions by minimizing an asymmetrically weighted loss function and estimate the parameters under the AL proxy distribution to resemble the minimization process. This quantile regression model is contrasted to the parametric AL mean regression model and both are expressed as a scale mixture of uniform distributions to facilitate efficient implementation. The models are extended to adopt dynamic mean, variance and skewness and applied to analyze two real loss reserve data sets to perform inference and discuss interesting features of quantile regression for risk margin calculations.