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This paper provides a general framework for conceptualizing triage for intensive care unit admissions in public health emergencies such as the COVID‐19 pandemic. It applies this framework to some of the guidelines issued during the pandemic and addresses some controversial issues, including the role of age, the use of lives or life years, and the relevance of quality of life considerations. The paper defends a view on which triage protocols for public health emergencies should aim to maximize the number of life years saved, may take into account age as a proxy, and should ignore quality of life considerations. [ABSTRACT FROM AUTHOR]

The recent complexity of the university system, with diverse academic trajectories and varying socio‐demographic characteristics of students, has led to increased access for historically underrepresented students. This has resulted in a rising number of adult learners, students with external responsibilities and individuals returning to education. However, despite this enhanced access, it remains unclear whether it has improved graduation. This uncertainty stems from the fact that students' social circumstances and external responsibilities differ significantly based on when they enter university. From a life course perspective, the aim of this paper is to explore the interactive effects of age at university entrance and employment status on the probability of graduating of an entire cohort of new students who entered the Catalan Higher Education System in 2012 (N = 29,463). The results show an interaction effect between age and employment status on the probability of graduation where working decreases the probability of graduation among students younger than 42 years old. Conversely, the negative impact of employment on university graduation diminishes among students entering university at an older age. This underscores the importance of adopting a life course perspective to comprehend students' educational experiences and outcomes within higher education. [ABSTRACT FROM AUTHOR]

Introduction: Tailored prophylaxis is the current treatment regimen for patients with severe haemophilia A. Recently, published guidelines describe two possible approaches, based on clinical characteristics or estimation of pharmacokinetic parameters. However, both have strengths and weaknesses, and their characteristics need to be integrated to optimize treatment appropriately. In this paper, we present a model that considers together the characteristics of prophylaxis and the relevance of each. Methods: The age at initiation of prophylaxis, number of bleeding events, treatment regimen, therapeutic adherence, FVIII trough levels, and joint status were analyzed in 59 patients followed at La Paz University Hospital between January 2000 and December 2019. Results: The mean duration of primary prophylaxis of 113.37 ± 57.79 months. Eighty‐three percent (n = 49) had no joint status involvement at the end of follow‐up (HJHS and HEAD‐US = 0). The median ABR was 0.7 (IQR 0.2 –1.0) and 54.2% presented trough levels of FVIII during follow‐up >1 IU/dL. 72,9% engaged in some type of physical activity and overall adherence was over 85% in all patients evaluated. The regression analysis performed, considering all these factors, showed that the initiation of prophylaxis before 21 months of age was the most relevant protective factor against the appearance of joint involvement (OR 88.33 p.031 CI 95% 1.49‐5224.40) Conclusion: Early initiation of prophylaxis was the most relevant factor in the protection of joint status. More comprehensive analysis models adapted to the characteristics of each population, are needed to adequately individualize treatment. [ABSTRACT FROM AUTHOR]

Background: Low‐Risk Alcohol Drinking Guidelines (LRDGs) aim to reduce the harms caused by alcohol. However, considerable discrepancies exist in the 'low‐risk' thresholds employed by different countries. Argument/analysis: Drawing upon Canada's LRDGs update process, the current paper offers the following propositions for debate regarding the establishment of 'low‐risk' thresholds in national guidelines: (1) as an indicator of health loss, years of life lost (YLL) has several advantages that could make it more suitable for setting guidelines than deaths, premature deaths or disability adjusted years of life (DALYs) lost. (2) Presenting age‐specific guidelines may not be the most appropriate way of providing LRDGs. (3) Given past overemphasis on the so‐called protective effects of alcohol on health, presenting cause‐specific guidelines may not be appropriate compared with a 'whole health' effect derived from a weighted composite risk function comprising conditions that are causally related to alcohol consumption. (4) To help people reduce their alcohol use, presenting different risk zones associated with alcohol consumption instead of a single low risk threshold may be advantageous. Conclusions: National LRDGs should be based on years of life lost and should be neither age‐specific nor cause‐specific. We recommend using risk zones rather than a single drinking threshold to help people assess their own risk and encourage the adoption of behaviours with positive health impacts across the alcohol use spectrum. [ABSTRACT FROM AUTHOR]

Age is an important variable to describe the expected brain's anatomy status across the normal aging trajectory. The deviation from that normative aging trajectory may provide some insights into neurological diseases. In neuroimaging, predicted brain age is widely used to analyze different diseases. However, using only the brain age gap information (i.e., the difference between the chronological age and the estimated age) can be not enough informative for disease classification problems. In this paper, we propose to extend the notion of global brain age by estimating brain structure ages using structural magnetic resonance imaging. To this end, an ensemble of deep learning models is first used to estimate a 3D aging map (i.e., voxel‐wise age estimation). Then, a 3D segmentation mask is used to obtain the final brain structure ages. This biomarker can be used in several situations. First, it enables to accurately estimate the brain age for the purpose of anomaly detection at the population level. In this situation, our approach outperforms several state‐of‐the‐art methods. Second, brain structure ages can be used to compute the deviation from the normal aging process of each brain structure. This feature can be used in a multi‐disease classification task for an accurate differential diagnosis at the subject level. Finally, the brain structure age deviations of individuals can be visualized, providing some insights about brain abnormality and helping clinicians in real medical contexts. [ABSTRACT FROM AUTHOR]