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Early worsening of plasma lipid levels (EWL; ≥5% change after 1 month) induced by at-risk psychotropic treatments predicts considerable exacerbation of plasma lipid levels and/or dyslipidaemia development in the longer term.
Aims
We aimed to determine which clinical and genetic risk factors could predict EWL.
Method
Predictive values of baseline clinical characteristics and dyslipidaemia-associated single nucleotide polymorphisms (SNPs) on EWL were evaluated in a discovery sample (n = 177) and replicated in two samples from the same cohort (PsyMetab; n1 = 176; n2 = 86).
Results
Low baseline levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C) and triglycerides, and high baseline levels of high-density lipoprotein cholesterol (HDL-C), were risk factors for early increase in total cholesterol (P = 0.002), LDL-C (P = 0.02) and triglycerides (P = 0.0006), and early decrease in HDL-C (P = 0.04). Adding genetic parameters (n = 17, 18, 19 and 16 SNPs for total cholesterol, LDL-C, HDL-C and triglycerides, respectively) improved areas under the curve for early worsening of total cholesterol (from 0.66 to 0.91), LDL-C (from 0.62 to 0.87), triglycerides (from 0.73 to 0.92) and HDL-C (from 0.69 to 0.89) (P ≤ 0.00003 in discovery sample). The additive value of genetics to predict early worsening of LDL-C levels was confirmed in two replication samples (P ≤ 0.004). In the combined sample (n ≥ 203), adding genetics improved the prediction of new-onset dyslipidaemia for total cholesterol, LDL-C and HDL-C (P ≤ 0.04).
Conclusions
Clinical and genetic factors contributed to the prediction of EWL and new-onset dyslipidaemia in three samples of patients who started at-risk psychotropic treatments. Future larger studies should be conducted to refine SNP estimates to be integrated into clinically applicable predictive models.
Bacterial infection risk in work environments has been extensively reported for healthcare workers, while this risk is rarely researched in other occupations. This study aimed to identify occupational environments in Taiwan’s agricultural and healthcare industries with elevated bacterial infection risks by comparing risks for general bacterial infections and pneumonia. Using labour and health insurance claim data from 3.3 million workers (January 2004–December 2020), a retrospective cohort was constructed to estimate occupational infection risks with Cox regression and the Anderson-Gill extension. Significantly elevated hazard ratios were found for workers in vegetable growing, crop cultivation service, mushroom growing, flower growing, and fruit growing, ranging from 1.13 to 1.39 for general bacterial infections and 1.68 to 3.06 for pneumonia infections. In afforestation and the inland fishing industry, pneumonia risk was significantly elevated with, respectively, 1.87 and 1.21. In the healthcare section, especially workers in residential care services and residential care services for elderly stand out regarding their pneumonia risk, with significant hazard ratios of 3.49 and 1.75. The methods used in this study were proven to be effective in identification of occupation environments at risk and can be used in other settings. These findings call for prioritization of bacterial infection prevention by occupation.
Risk is a central concept in modern regulatory studies. In Chapter 2, the general idea of ’risk’ is introduced. The chapter helps readers grasp its scientific and practical relevance for regulation. The chapter also offers an overview of the importance of risk in scholarly work and policy-making. The chapter emphasizes the extensive and diverse nature of risk studies across different academic disciplines including ’technical’ quantitative methods and sociological critique. It explains how risk identification, risk assessment, and risk management are conventionally understood and highlights their shortcomings and complexities. Additionally, it discusses the trend of ’riskification’ – the tendency to frame a growing number of issues in the language of risk.
Summary: The aging of the population poses significant challenges in healthcare, necessitating innovative approaches. Advancements in brain imaging and artificial intelligence now allow for characterizing an individual’s state through their brain age,’’ derived from observable brain features. Exploring an individual’s biological age’’ rather than chronological age is becoming crucial to identify relevant clinical indicators and refine risk models for age-related diseases. However, traditional brain age measurement has limitations, focusing solely on brain structure assessment while neglecting functional efficiency.
Our study focuses on developing neurocognitive ages’’ specific to cognitive systems to enhance the precision of decline estimation. Leveraging international (NKI2, ADNI) and Canadian (CIMA- Q, COMPASS-ND) databases with neuroimaging and neuropsychological data from older adults [control subjects with no cognitive impairment (CON): n = 1811; people living with mild cognitive impairment (MCI): n = 1341; with Alzheimer’s disease (AD): n= 513], we predicted individual brain ages within groups. These estimations were enriched with neuropsychological data to generate specific neurocognitive ages. We used longitudinal statistical models to map evolutionary trajectories. Comparing the accuracy of neurocognitive ages to traditional brain ages involved statistical learning techniques and precision measures.
The results demonstrated that neurocognitive age enhances the prediction of individual brain and cognition change trajectories related to aging and dementia. This promising approach could strengthen diagnostic reliability, facilitate early detection of at-risk profiles, and contribute to the emergence of precision gerontology/geriatrics.
Focusing on the physics of the catastrophe process and addressed directly to advanced students, this innovative textbook quantifies dozens of perils, both natural and man-made, and covers the latest developments in catastrophe modelling. Combining basic statistics, applied physics, natural and environmental sciences, civil engineering, and psychology, the text remains at an introductory level, focusing on fundamental concepts for a comprehensive understanding of catastrophe phenomenology and risk quantification. A broad spectrum of perils are covered, including geophysical, hydrological, meteorological, climatological, biological, extraterrestrial, technological and socio-economic, as well as events caused by domino effects and global warming. Following industry standards, the text provides the necessary tools to develop a CAT model from hazard to loss assessment. Online resources include a CAT risk model starter-kit and a CAT risk modelling 'sandbox' with Python Jupyter tutorial. Every process, described by equations, (pseudo)codes and illustrations, is fully reproducible, allowing students to solidify knowledge through practice.
Humanity’s situation with climate change is sometimes compared to that of a frog in a slowly boiling pot of water. Most of our climate science takes the form of prediction: telling the frog that in five minutes’ time he will be a little bit warmer. We need more risk assessment: telling the frog that the worst that could happen is he could boil to death, and that this is becoming increasingly likely over time. This approach can give a much clearer picture of the risks of climate change to human health, food security, and coastal cities.
The year 2021 saw extreme weather events outside the range of what experts had thought possible, signs of a growing acknowledgement among scientists of the need to take risk assessment more seriously, and the launch of a new initiative that might finally tell heads of government what they need to know.
Neither scientists, nor economists, nor insurers, nor military planners have assessed the risks of climate change in full. Heads of government are left to guess. A clear understanding of the scale of the risks will not on its own guarantee a proportionate response. But unless we have such an understanding, we can hardly be surprised if our response is inadequate.
Most research into the impacts of climate change concentrates on what would happen at low degrees of change. We know a great deal about best-case scenarios. Thanks to wilful ignorance among policymakers, and the cultural preferences of scientists, worst-case scenarios are much less considered. We know the least about what matters most.
Science can only tell us a part of what we need to know about the risks of climate change. We also need to make judgements about politics, technology, and international security. To tell truth to power, we need to bring these fields of knowledge together.
The Russian–Ukrainian War of 2022 (RUW-2022) was accompanied by the subsequent risk of accidents at a nuclear power plant in Ukraine. This study investigated posttraumatic stress (PTS) symptoms related to media reports of an attack on a Ukrainian nuclear power plant during the RUW-2022 among victims of the Fukushima nuclear disaster and revealed their association with radiation risk perception (RRP) of the accident.
Methods
This cross-sectional study targeted 1193 residents of Naraha Town in Fukushima Prefecture. PTS symptoms were measured using the Japanese version of the Impact of Events Scale-Revised (IES-R). Univariate and multivariate analyses explored the association between IES-R scores and background factors, particularly RRP.
Results
Participants with higher RRP showed significantly higher IES-R scores; furthermore, the proportion of disruption because of radiation anxiety was significantly larger among higher RRP residents. Radiation anxiety mediated the association between RRP and PTS symptoms (total IES-R score and sub-item of intrusion).
Conclusions
People with higher RRP in Fukushima may continue to be at risk of persistent, unwanted PTS symptoms due to future nuclear crises. Therefore, mental health practitioners need to continue providing support in affected areas for a longer period than anticipated. Moreover, a population-based approach to cope with these stressors from media reports is essential.
Edited by
Laurie J. Mckenzie, University of Texas MD Anderson Cancer Center, Houston,Denise R. Nebgen, University of Texas MD Anderson Cancer Center, Houston
More women are surviving gynecological cancer with advancements in screening, diagnosis, and treatment. Survivorship care of gynecological cancer includes surveillance for recurrence of disease, monitoring for late effects of treatment, reducing the risk and early detection of other cancer, and assessment of psychosocial function. Even if the surveillance of gynecological cancer survivors has some common features, non-invasive and invasive breast, cervical, endometrial, and ovarian cancer will require an individualized therapeutic approach. Many survivors of gynecologic cancer will have long lasting effects on bone and sexual heath, so these areas should be addressed on a regular basis. In addition, it is important to use every encounter as an opportunity to assess the risk of other cancer and provide appropriate early detection. Survivorship care will also incorporate strategies to decrease the risk of other cancer through lifestyle modifications. Many female cancer survivors will have lifelong issues related to distress, body image, finance, and social support. Assessment of psychosocial issues and referral to appropriate services should be performed at every patient encounter.
Questions often follow the suicide of someone who presented to general adult psychiatry (GAP) when expressing suicidal thoughts: ‘Why were they not admitted, or managed differently, when they said they were suicidal?’ Answering these questions requires knowledge of the prevalence of suicidal ideation in patients presenting to GAP. Therefore, we determined the general clinical characteristics, including suicidal ideation, of a large sample of patients presenting to a GAP emergency assessment service or referred as non-emergencies to a GAP service.
Results
Suicidal ideation was very common, being present in 76.4% of emergency presentations and 33.4% of non-emergency referrals. It was very weakly associated with suicide, varied between different diagnostic categories, and previous assessment by GAP did not appear to affect it. The suicide rate during the contingent episode of care was estimated as 66 per 100 000 episodes.
Clinical implications
This, and other evidence, shows that suicide cannot be predicted with an accuracy that is useful for clinical decision-making. This is not widely appreciated but has serious consequences for patients and healthcare resources.
Domestic abuse – abusive behaviour perpetrated by an adult towards another adult to whom they are personally connected (e.g. partners, ex-partners or family members) – damages mental health, increases mental health service use and challenges clinical management. Training and guidance for mental health professionals on identifying and responding to patients exposed to domestic abuse are available, but there has been less development of resources for mental health professionals in identifying, assessing and responding to perpetrators of domestic abuse. In this article, we describe a framework for responding to domestic abuse perpetration in clinical settings in general adult mental health services, aimed at improving practice. This could support mental health professionals in sensitive enquiry and assessment for domestic abuse perpetration, and guide appropriate responses, as part of routine training and continuing professional development.
Navigating the complex relationship between violence and psychosis can frequently be challenging. Psychiatrists may find assessing and managing the risk of violence in this context daunting. In their article on the topic, Anderson et al helpfully summarise the role that psychopathology can play in this process. However, although careful elucidation of an individual's experiences may assist in the nuanced formulation of their risk and could offer a specific focus for interventions, the approach has potential shortcomings in certain settings. For some phenomena the link with violence is unclear and it may be constellations of symptoms that are important. Causal pathways are not always linear and there may be important mediators linking psychopathological features to behavioural outcomes. In the resource-limited settings in which many contemporary health services operate, a detailed assessment of psychopathology may be hampered by time or other constraints. Alternative, more scalable solutions may therefore be needed in particular scenarios.
The malicious use of artificial intelligence is growing rapidly, creating major security threats for individuals and the healthcare sector. Individuals with mental illness may be especially vulnerable. Healthcare provider data are a prime target for cybercriminals. There is a need to improve cybersecurity to detect and prevent cyberattacks against individuals and the healthcare sector, including the use of artificial intelligence predictive tools.
Probability-based estimates of the future suicide of psychiatric patients are of little assistance in clinical practice. This article proposes strategic management of the interaction between the clinician and the patient in the assessment of potentially suicidal patients, using principles derived from game theory, to achieve a therapeutic outcome that minimises the likelihood of suicide. Further developments in the applications of large language models could allow us to quantify the basis for clinical decisions in individual patients. Documenting the basis of those decisions would help to demonstrate an adequate standard of care in every interaction.
If livestock at risk of poor welfare could be identified using a risk assessment tool, more targeted response strategies could be developed by enforcement agencies to facilitate early intervention, prompt welfare improvement and a decrease in reoffending. This study aimed to test the ability of an Animal Welfare Risk Assessment Tool (AWRAT) to identify livestock at risk of poor welfare in extensive farming systems in Australia. Following farm visits for welfare- and non-welfare-related reasons, participants completed a single welfare rating (WR) and an assessment using the AWRAT for the farm just visited. A novel algorithm was developed to generate an AWRAT-Risk Rating (AWRAT-RR) based on the AWRAT assessment. Using linear regression, the relationship between the AWRAT-RR and the WR was tested. The AWRAT was good at identifying farms with poor livestock welfare based on this preliminary testing. As the AWRAT relies upon observation, the intra- and inter-observer agreement were compared in an observation study. This included rating a set of photographs of farm features, on two occasions. Intra-observer reliability was good, with 83% of Intra-class Correlation Coefficients (ICCs) for observers ≥ 0.8. Inter-observer reliability was moderate with an ICC of 0.67. The AWRAT provides a structured framework to improve consistency in livestock welfare assessments. Further research is necessary to determine the AWRAT’s ability to identify livestock at risk of poor welfare by studying animal welfare incidents and reoffending over time.
Tropical glaciers are rapidly disappearing, particularly in isolated mountain peaks below 5,000 m elevation. These glaciers are fundamental substrates for unique cryogenic ecosystems in high tropical environments where the ice, melting water and rocky substrate sustain microbiological communities and other meso- and macro-biota. This study uses the Red List of Ecosystems guidelines to diagnose the collapse of the tropical glacier ecosystem of the Cordillera de Mérida, Venezuela. We undertook the assessment with existing estimates of glacier ice extent, indirect historical estimates of ice mass balance and global mechanistic models of future ice mass balance. We complemented these with additional statistical analysis of trends and bioclimatic suitability modelling to calculate and predict rates of decline and relative severity of degradation in selected ecosystem indicators. The evidence suggests an extreme risk of collapse (Critically Endangered) because of a prolonged and acute reduction in ice extent and changes in climatic conditions that are leading to the complete loss of ice mass. The ice substrate has declined 90% in the last 20 years, and observed acceleration of the rate of decline suggests it will probably disappear within the next 5 years. Loss of ice substrate will trigger an immediate loss of supraglacial, englacial and subglacial biotic compartments and initiate a decades-long succession of forefield vegetation. However, ongoing inventories of native biota and monitoring of ecosystem transitions can provide valuable insights and lessons for other ecosystems facing similar risks. The Red List of Ecosystems assessment protocol provides a useful framework for comparative analysis of cryogenic ecosystems.
The Parole Board for England and Wales advises on the release, recall and licence conditions of a small subgroup of prisoners serving determinate sentences and the majority of those serving indeterminate sentences. Since the establishment of the Parole Board in 1968, the parole process has been shaped and clarified by further legislation and case law. In certain scenarios, psychiatric expert evidence may be sought to inform the Board's determination of whether a prisoner can be safely released into the community. Psychiatrists preparing expert reports for the Parole Board should be familiar with the current operationalisation of parole. This involves an understanding not only of the functioning of the Parole Board, but also of the criminal justice context in which prisoners subject to parole are managed. Having set the scene, by describing the role of the Parole Board and the wider context, this article examines how to undertake assessments and complete psychiatric reports for the Board.