Active medical product monitoring systems, such as the Sentinel System, will utilize electronic healthcare data captured during routine health care. Safety signals that arise from these data may be spurious because of chance or bias, particularly confounding bias, given the observational nature of the data. Applying appropriate monitoring designs can filter out many false-positive and false-negative associations from the outset. Designs can be classified by whether they produce estimates based on between-person or within-person comparisons. In deciding which approach is more suitable for a given monitoring scenario, stakeholders must consider the characteristics of the monitored product, characteristics of the health outcome of interest (HOI), and characteristics of the potential link between these. Specifically, three factors drive design decisions: (i) strength of within-person and between-person confounding; (ii) whether circumstances exist that may predispose to misclassification of exposure or misclassification of the timing of the HOI; and (iii) whether the exposure of interest is predominantly transient or sustained. Additional design considerations include whether to focus on new users, the availability of appropriate active comparators, the presence of an exposure time trend, and the measure of association of interest. When the key assumptions of self-controlled designs are fulfilled (i.e., lack of within-person, time-varying confounding; abrupt HOI onset; and transient exposure), within-person comparisons are preferred because they inherently avoid confounding by fixed factors. The cohort approach generally is preferred in other situations and particularly when timing of exposure or outcome is uncertain because cohort approaches are less vulnerable to biases resulting from misclassification.
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http://dx.doi.org/10.1002/pds.2316 | DOI Listing |
BMC Psychiatry
January 2025
Department of Behavioural Science and Health, University College London, London, 1-19 Torrington Place, WC1E 7HB, UK.
Background: Smoking rates in the UK have declined steadily over the past decades, masking considerable inequalities, as little change has been observed among people with a mental health condition. This trial sought to assess the feasibility and acceptability of supplying an electronic cigarette (e-cigarette) starter kit for smoking cessation as an adjunct to usual care for smoking cessation, to smokers with a mental health condition treated in the community, to inform a future effectiveness trial.
Methods: This randomised controlled feasibility trial, conducted March-December 2022, compared the intervention (e-cigarette starter kit with a corresponding information leaflet and demonstration with Very Brief Advice) with a 'usual care' control at 1-month follow-up.
BMC Nurs
January 2025
Department of Clinical Nutrition, School of Medicine, Chongqing University Cancer Hospital, Chongqing University, Chongqing, China.
Background: Nurses serving in infectious disease ward represent a distinct occupational group that has attracted considerable attention following epidemic outbreaks. However, prior to this study, no research had delved into the underlying mechanism linking anxiety to burnout symptoms among infectious disease nurses. This study aimed to explore investigate the association between anxiety and burnout among nurses working in such environments and scrutinized the mediating role of perceived stress and the moderating influence of resilience on the principal relationship.
View Article and Find Full Text PDFCardiovasc Eng Technol
January 2025
Transonic Systems Inc., 34 Dutch Mill Road, Ithaca, New York, 14850, USA.
Purpose: Over time, transit time flow measurement (TTFM) has proven itself as a simple and effective tool for intra-operative evaluation of coronary artery bypass grafts (CABGs). However, metrics used to screen for possible technical error show considerable spread, preventing the definition of sharp cut-off values to distinguish between patent, questionable, and failed grafts. The simulation study presented in this paper aims to quantify this uncertainty for commonly used patency metrics, and to identify the most important physiological parameters influencing it.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical and Computer Engineering, Hawassa University, Hawassa 05, Ethiopia.
Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of guaranteeing public safety. However, existing approaches such as three-dimensional convolutional neural networks (3D CNN) and two-stream neural networks (2SNN) have computational hurdles due to the significant parameterization they require. In this paper, we offer HARNet, a specialized lightweight residual 3D CNN that is built on directed acyclic graphs and was created expressly to handle these issues and achieve effective human action detection.
View Article and Find Full Text PDFTrends Genet
January 2025
Computer Science Division, University of California, Berkeley, CA, USA; Department of Statistics, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA, USA. Electronic address:
Large language models (LLMs) are having transformative impacts across a wide range of scientific fields, particularly in the biomedical sciences. Just as the goal of natural language processing is to understand sequences of words, a major objective in biology is to understand biological sequences. Genomic language models (gLMs), which are LLMs trained on DNA sequences, have the potential to significantly advance our understanding of genomes and how DNA elements at various scales interact to give rise to complex functions.
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