40 research outputs found

    Sustainable Finance Ratings as the Latest Symptom of “Rating Addiction”

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    Using the widely accepted but rarely articulated concept of ‘rating addiction’, this piece aims to examine the recent entrance of the credit rating agencies into the sustainable finance field against the backdrop of ‘rating addiction’. Once the concept of ‘rating addiction’ is positioned, the effects of the addiction can be witnessed by even just a cursory glance at the history of the credit rating agencies, particularly their recent history. On that basis, this article provides a warning for regulators and the field with regards to the potentially negative effect that credit rating agencies can have upon the ever-growing and socially-important sustainable finance sector. Additionally, assessing the aptitude of the agencies in this sector, in comparison to the sector’s utilisation of their products, may provide further evidence of a system addicted to ratings

    Cumulative radiation exposure from diagnostic imaging in intensive care unit patients.

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    AIM: To quantify cumulative effective dose of intensive care unit (ICU) patients attributable to diagnostic imaging. METHODS: This was a prospective, interdisciplinary study conducted in the ICU of a large tertiary referral and level 1 trauma center. Demographic and clinical data including age, gender, date of ICU admission, primary reason for ICU admission, APACHE II score, length of stay, number of days intubated, date of death or discharge, and re-admission data was collected on all patients admitted over a 1-year period. The overall radiation exposure was quantified by the cumulative effective radiation dose (CED) in millisieverts (mSv) and calculated using reference effective doses published by the United Kingdom National Radiation Protection Board. Pediatric patients were selected for subgroup-analysis. RESULTS: A total of 2737 studies were performed in 421 patients. The total CED was 1704 mSv with a median CED of 1.5 mSv (IQR 0.04-6.6 mSv). Total CED in pediatric patients was 74.6 mSv with a median CED of 0.07 mSv (IQR 0.01-4.7 mSv). Chest radiography was the most commonly performed examination accounting for 83% of all studies but only 2.7% of total CED. Computed tomography (CT) accounted for 16% of all studies performed and contributed 97% of total CED. Trauma patients received a statistically significant higher dose [median CED 7.7 mSv (IQR 3.5-13.8 mSv)] than medical [median CED 1.4 mSv (IQR 0.05-5.4 mSv)] and surgical [median CED 1.6 mSv (IQR 0.04-7.5 mSv)] patients. Length of stay in ICU [OR = 1.12 (95%CI: 1.079-1.157)] was identified as an independent predictor of receiving a CED greater than 15 mSv. CONCLUSION: Trauma patients and patients with extended ICU admission times are at increased risk of higher CEDs. CED should be minimized where feasible, especially in young patients

    The legal framework for financial advertising:curbing behavioural exploitation

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    Policy makers and behavioural finance scholars express growing concern that marketing practices by financial institutions exploit retail investors’ behavioural biases. Investor protection regulation should thus address these marketing practices and include mechanisms curbing behavioural exploitation. That raises the question whether the marketing communications regime of the new Markets in Financial Instruments Directive can live up to this demand. This article develops a regulatory model that integrates behavioural finance insights into the new marketing communications regime. It then determines how regulatory authorities can apply this model when they interpret and apply specific regulatory requirements. It demonstrates how a regulatory authority or a court can translate empirical behavioural finance research findings into legal arguments when assessing whether marketing practices can significantly distort a model investor’s decision-making process. The article further establishes that the detailed requirements imposed on investment firms by the new Markets in Financial Instruments Directive are necessary in order to protect investors from behavioural exploitation. Finally, the article submits policy proposals that aim to protect investors more effectively from behavioural exploitation

    Susceptibility of Pancreatic Beta Cells to Fatty Acids Is Regulated by LXR/PPARα-Dependent Stearoyl-Coenzyme A Desaturase

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    Chronically elevated levels of fatty acids-FA can cause beta cell death in vitro. Beta cells vary in their individual susceptibility to FA-toxicity. Rat beta cells were previously shown to better resist FA-toxicity in conditions that increased triglyceride formation or mitochondrial and peroxisomal FA-oxidation, possibly reducing cytoplasmic levels of toxic FA-moieties. We now show that stearoyl-CoA desaturase-SCD is involved in this cytoprotective mechanism through its ability to transfer saturated FA into monounsaturated FA that are incorporated in lipids. In purified beta cells, SCD expression was induced by LXR- and PPARα-agonists, which were found to protect rat, mouse and human beta cells against palmitate toxicity. When their SCD was inhibited or silenced, the agonist-induced protection was also suppressed. A correlation between beta cell-SCD expression and susceptibility to palmitate was also found in beta cell preparations isolated from different rodent models. In mice with LXR-deletion (LXRβ-/- and LXRαβ-/-), beta cells presented a reduced SCD-expression as well as an increased susceptibility to palmitate-toxicity, which could not be counteracted by LXR or PPARα agonists. In Zucker fatty rats and in rats treated with the LXR-agonist TO1317, beta cells show an increased SCD-expression and lower palmitate-toxicity. In the normal rat beta cell population, the subpopulation with lower metabolic responsiveness to glucose exhibits a lower SCD1 expression and a higher susceptibility to palmitate toxicity. These data demonstrate that the beta cell susceptibility to saturated fatty acids can be reduced by stearoyl-coA desaturase, which upon stimulation by LXR and PPARα agonists favors their desaturation and subsequent incorporation in neutral lipids

    Cause of Death and Predictors of All-Cause Mortality in Anticoagulated Patients With Nonvalvular Atrial Fibrillation : Data From ROCKET AF

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    M. Kaste on työryhmän ROCKET AF Steering Comm jäsen.Background-Atrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions. Methods and Results-In the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS(2) score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P= 75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P Conclusions-In a large population of patients anticoagulated for nonvalvular atrial fibrillation, approximate to 7 in 10 deaths were cardiovascular, whereasPeer reviewe

    Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

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    Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

    The United States COVID-19 Forecast Hub dataset

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    Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

    Cumulative radiation exposure from diagnostic imaging in intensive care unit patients.

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    AIM: To quantify cumulative effective dose of intensive care unit (ICU) patients attributable to diagnostic imaging. METHODS: This was a prospective, interdisciplinary study conducted in the ICU of a large tertiary referral and level 1 trauma center. Demographic and clinical data including age, gender, date of ICU admission, primary reason for ICU admission, APACHE II score, length of stay, number of days intubated, date of death or discharge, and re-admission data was collected on all patients admitted over a 1-year period. The overall radiation exposure was quantified by the cumulative effective radiation dose (CED) in millisieverts (mSv) and calculated using reference effective doses published by the United Kingdom National Radiation Protection Board. Pediatric patients were selected for subgroup-analysis. RESULTS: A total of 2737 studies were performed in 421 patients. The total CED was 1704 mSv with a median CED of 1.5 mSv (IQR 0.04-6.6 mSv). Total CED in pediatric patients was 74.6 mSv with a median CED of 0.07 mSv (IQR 0.01-4.7 mSv). Chest radiography was the most commonly performed examination accounting for 83% of all studies but only 2.7% of total CED. Computed tomography (CT) accounted for 16% of all studies performed and contributed 97% of total CED. Trauma patients received a statistically significant higher dose [median CED 7.7 mSv (IQR 3.5-13.8 mSv)] than medical [median CED 1.4 mSv (IQR 0.05-5.4 mSv)] and surgical [median CED 1.6 mSv (IQR 0.04-7.5 mSv)] patients. Length of stay in ICU [OR = 1.12 (95%CI: 1.079-1.157)] was identified as an independent predictor of receiving a CED greater than 15 mSv. CONCLUSION: Trauma patients and patients with extended ICU admission times are at increased risk of higher CEDs. CED should be minimized where feasible, especially in young patients
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