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Outcomes Related to Bacterial Co-Infection and Antibiotic Use in Adults Hospitalized With Respiratory Syncytial Virus Compared with Influenza
No full textBACKGROUND: Adults hospitalized with respiratory syncytial virus (RSV) face mortality risks comparable to or higher than those with influenza A or B. However, studies on the impact of bacterial co-infections on mortality are inconsistent.METHODS: This multicenter cohort study included adults hospitalized with RSV, influenza A, or B over 3 years at two tertiary care hospitals. Microbiological testing, bacterial co-infections, antibiotic use, and their association with clinical outcomes were analyzed using adjusted linear and logistic regression models.RESULTS: Of 986 patients, 352 (36%) had RSV, 347 (35%) influenza A, and 287 (29%) influenza B. The median age was 74 years, 54% were women, and 76% had at least one comorbidity. Overall, 32% had pneumonia. The prevalence of bacterial co-infections was comparable across patients with RSV (23%), influenza A (25%), and B (28%). Among patients without bacterial co-infection, antibiotic use within 48 hours remained common across all virus groups (77%, 71%, and 75%, respectively). In adjusted analyses, bacterial co-infection in patients with RSV was not associated with mortality at 14, 30, or 90 days, high-flow oxygen therapy, mechanical ventilation, or length of stay (LOS). Early antibiotic treatment was associated with prolonged LOS but not improved survival.CONCLUSIONS: Bacterial co-infections were identified in approximately one-quarter of patients with RSV, influenza A, and B. Among patients with RSV, bacterial co-infection was not associated with adverse clinical outcomes, and early antibiotic treatment did not appear to improve clinical outcomes.</p
Coronary computed tomography angiography versus invasive coronary angiography for interventional triage in acute coronary syndrome:Design of the randomized TRACTION trial
No full textPurposeIn patients admitted with acute coronary syndrome, invasive coronary angiography (ICA) is performed to determine which patients need revascularization. Coronary computed tomography angiography (CCTA) offers a widely available, non-invasive alternative that could reduce patient discomfort, procedural risks, and healthcare costs. The current trial aims to determine whether CCTA is noninferior to ICA in determining the interventional strategy for patients admitted with non-ST elevation acute coronary syndrome (NSTE-ACS)(Central Illustration).MethodsTRACTION (Team-based Interventional Triage in Acute Coronary Syndrome Based on Noninvasive Coronary Computed Tomography Angiography Versus Invasive Coronary Angiography) is a multicenter, randomized, open-label, noninferiority trial enrolling 2,300 patients. Patients hospitalized with non-ST elevation myocardial infarction or unstable angina with ischemic changes on ECG will be randomized 1:1 to CCTA vs ICA (standard of care). In the CCTA group, a Coronary Team reviews the CCTA and clinical information to determine the interventional strategy. The primary composite endpoint is major adverse cardiac events at 1 year, comprised of all-cause mortality, nonfatal myocardial infarction, hospitalization due to refractory angina, or hospitalization due to heart failure. Secondary outcomes include cardiovascular death, revascularization, symptom status, procedure-related adverse events, and resource utilization. The trial is designed to demonstrate noninferiority if the 95% confidence interval excludes an absolute risk difference of the primary endpoint larger than 5%.PerspectivesIf CCTA is shown to be noninferior to ICA in patients admitted with NSTE-ACS, CCTA could become the preferred management in a large group of patients. This could result in fewer patients exposed to invasive procedures and improved resource utilization.ClinicalTrials.gov identifier: NCT06101862Purpose In patients admitted with acute coronary syndrome, invasive coronary angiography (ICA) is performed to determine which patients need revascularization. Coronary computed tomography angiography (CCTA) offers a widely available, non-invasive alternative that could reduce patient discomfort, procedural risks, and healthcare costs. The current trial aims to determine whether CCTA is noninferior to ICA in determining the interventional strategy for patients admitted with non-ST elevation acute coronary syndrome (NSTE-ACS)( Central Illustration ). Methods TRACTION (Team-based Interventional Triage in Acute Coronary Syndrome Based on Noninvasive Coronary Computed Tomography Angiography Versus Invasive Coronary Angiography) is a multicenter, randomized, open-label, noninferiority trial enrolling 2,300 patients. Patients hospitalized with non-ST elevation myocardial infarction or unstable angina with ischemic changes on ECG will be randomized 1:1 to CCTA vs ICA (standard of care). In the CCTA group, a Coronary Team reviews the CCTA and clinical information to determine the interventional strategy. The primary composite endpoint is major adverse cardiac events at 1 year, comprised of all-cause mortality, nonfatal myocardial infarction, hospitalization due to refractory angina, or hospitalization due to heart failure. Secondary outcomes include cardiovascular death, revascularization, symptom status, procedure-related adverse events, and resource utilization. The trial is designed to demonstrate noninferiority if the 95% confidence interval excludes an absolute risk difference of the primary endpoint larger than 5%. Perspectives If CCTA is shown to be noninferior to ICA in patients admitted with NSTE-ACS, CCTA could become the preferred management in a large group of patients. This could result in fewer patients exposed to invasive procedures and improved resource utilization. ClinicalTrials.gov</p
The Role of Gaze in Shaping Forms of Reflective Practice:A Legitimation Code Theory Analysis of Clinical Supervision in Danish Primary Care
No full textAims and ObjectivesThis study aimed to investigate how supervision models may cultivate or constrain different ways of knowing and learning in primary care.Methodological Design and JustificationThe research employed a qualitative methodological design, grounded in Legitimation Code Theory, to gain an in-depth understanding of the dynamics at play within various supervision models. It aligns with the QRSR guidelines.Ethical Issues and ApprovalEthical considerations were thoroughly addressed, and approval was obtained prior to initiating the study, ensuring participant confidentiality and informed consent.Research Methods, Instruments, and InterventionsThe study utilised qualitative interviews as the primary research method, conducting 18 interviews with a diverse range of healthcare professionals, including leaders, nurses, nursing assistants, physiotherapists, and both internal and external supervision consultants.Outcome MeasuresThe analysis focused on identifying how different supervision models influenced reflective practice and shaped the participants' perceptions regarding the effectiveness and utility of these models.ResultsFindings illustrated the complex interplay of cultivated, social, and trained gazes within healthcare settings, highlighting how different forms of legitimation shape what counts as meaningful understanding and reflective practice.Study LimitationsWhile the study provides valuable insights, it is important to acknowledge limitations related to the heterogeneous nature of the material across the interventions.ConclusionsThe concept of gaze not only elucidates the presuppositions underlying different supervision models but also elucidates how the usefulness of different supervision models is legitimated within practice.Aims and Objectives: This study aimed to investigate how supervision models may cultivate or constrain different ways of knowing and learning in primary care. Methodological Design and Justification: The research employed a qualitative methodological design, grounded in Legitimation Code Theory, to gain an in-depth understanding of the dynamics at play within various supervision models. It aligns with the QRSR guidelines. Ethical Issues and Approval: Ethical considerations were thoroughly addressed, and approval was obtained prior to initiating the study, ensuring participant confidentiality and informed consent. Research Methods, Instruments, and Interventions: The study utilised qualitative interviews as the primary research method, conducting 18 interviews with a diverse range of healthcare professionals, including leaders, nurses, nursing assistants, physiotherapists, and both internal and external supervision consultants. Outcome Measures: The analysis focused on identifying how different supervision models influenced reflective practice and shaped the participants' perceptions regarding the effectiveness and utility of these models. Results: Findings illustrated the complex interplay of cultivated, social, and trained gazes within healthcare settings, highlighting how different forms of legitimation shape what counts as meaningful understanding and reflective practice. Study Limitations: While the study provides valuable insights, it is important to acknowledge limitations related to the heterogeneous nature of the material across the interventions. Conclusions: The concept of gaze not only elucidates the presuppositions underlying different supervision models but also elucidates how the usefulness of different supervision models is legitimated within practice.</p
Procedures of data merging in precision cancer medicine:the PRIME-ROSE project
No full textBACKGROUND AND PURPOSE: As more interventional clinical trials in Precision Cancer Medicine (PCM) are introduced, molecular descriptions of tumours have led to multiple subtypes, even within common tumour types. Therefore, the main limitation of these trials is the small number of eligible patients to assess the clinical benefit. The PRIME-ROSE project addresses this limitation by pooling data from multiple European Drug Rediscovery Protocol (DRUP)-like clinical trials, such that slowly accruing cohorts are accelerated. To achieve this task, a well-documented commonly approved procedure for data merging needs to be established. Patient/material and methods: Data sharing is achievable when there is an organisation that includes people from different disciplines who can navigate institutional and country-specific information and governance requirements. Furthermore, alignment of all the study procedures are needed before data are shared. Next, the process of merging data requires harmonisation and standardisation. Implementation of the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) facilitates future data aggregation.RESULTS: By aggregating data from European DRUP-like clinical trials, cohorts are completed that were unable to do so in stand-alone studies. Since initiation, the PRIME-ROSE project monitors over 300 cohorts across more than 20 treatments encompassing over 1,000 patients. At least 20 cohorts have progressed after interim analysis.INTERPRETATION: Data sharing across European trials is feasible and enhances the advancements of PCM studies. The methodologies developed in the PRIME-ROSE project provide a foundation for future data integration efforts in PCM clinical trials, underscoring the viability of conducting robust trials in a global context.</p
Fall Risk Awareness and Experiences Among Adult Users of Opioids in Denmark:A Community Pharmacy-Based Questionnaire Pilot Study
No full textConfirmatory factor analysis of competing PANSS negative symptom models:data from OPTiMiSE first-episode schizophrenia study
No full textBACKGROUND: The negative symptoms of psychosis are heterogeneous, which complicates efforts to understand their pathophysiology and develop effective treatments. Factor analytic studies of the Positive and Negative Syndrome Scale (PANSS) have reported two factorial negative symptom models, expressive deficit and social amotivation, albeit with different compositions. Although models derived from other assessment scales have been directly compared, no study has previously applied this approach to PANSS.AIMS: Our objectives were to (a) to establish which negative PANSS-derived factorial model provided the best fit to our data, (b) test its stability and (c) determine its clinical and demographic correlates.METHOD: A cohort of medication naive or minimally treated patients with first-episode schizophrenia (n = 446) were assessed using the PANSS scale before and 4 weeks after amisulpride treatment. Confirmatory factor analysis was performed to test five PANSS models. Hierarchical multiple regression was conducted to examine the associations between identified dimensions and clinical and demographic variables.RESULTS: A nine-item PANSS model comprising social amotivation and expressive deficit dimensions outperformed the other models: comparative fit index = 0.98, goodness of fit index = 0.97, Tucker-Lewis index = 0.97, root mean square error of approximation = 0.06 (CI 90%: 0.04-0.08), Bayesian information criterion = 191.9, Akaike information criterion = 101.7. At baseline, the social amotivation dimension was associated with more severe depression whereas the expressive deficit dimension was associated with younger age. Both dimensions at baseline were associated with poor functioning, but expressive deficit to a lesser extent.CONCLUSIONS: A nine-item PANSS model incorporating social amotivation and expressive deficit dimensions appeared to best reflect the underlying structure of negative symptoms in our sample.</p
Cybersecurity and International Relations:developing thinking tools for digital world politics
No full textProcesses of digital transformation alter global politics. This is an issue not only for specialists in cybersecurity, but for all scholars of international relations. This introduction to a special section outlines an agenda for cybersecurity research in international relations research and practice. We argue that cybersecurity is not only a specialized subfield of International Relations (IR), but also an intellectual space in which crucial questions concerning international politics, security and digital technology can be examined. Nevertheless, we identify three biases in current cybersecurity research—a focus toward the state, the military and power as domination—that limit the field and hamper broader engagement with IR and critical security scholarship. We argue that cybersecurity and digital technology are neither optional additions to the theory and practice of international relations nor issues that can neatly be isolated from other world affairs. The goal of the special section is hence twofold. First, to provide new directions and foundations for cybersecurity studies. Second, to explore the opportunities and challenges raised by cybersecurity and digital technological phenomena in conversation with IR and critical security studies. Taken together, the special section demonstrates the need to understand cybersecurity through international relations and to understand international relations through cybersecurity.Processes of digital transformation alter global politics. This is an issue not only for specialists in cybersecurity, but for all scholars of international relations. This introduction to a special section outlines an agenda for cybersecurity research in international relations research and practice. We argue that cybersecurity is not only a specialized subfield of International Relations (IR), but also an intellectual space in which crucial questions concerning international politics, security and digital technology can be examined. Nevertheless, we identify three biases in current cybersecurity research—a focus toward the state, the military and power as domination—that limit the field and hamper broader engagement with IR and critical security scholarship. We argue that cybersecurity and digital technology are neither optional additions to the theory and practice of international relations nor issues that can neatly be isolated from other world affairs. The goal of the special section is hence twofold. First, to provide new directions and foundations for cybersecurity studies. Second, to explore the opportunities and challenges raised by cybersecurity and digital technological phenomena in conversation with IR and critical security studies. Taken together, the special section demonstrates the need to understand cybersecurity through international relations and to understand international relations through cybersecurity
Comparing computer vision models for detecting chronic pleurisy in pigs
No full textThis study evaluated the diagnostic performance of three convolutional neural network models within a computer vision system (CVS) for detecting chronic pleurisy in pig carcasses compared to official meat inspection. Knowledge about the true prevalence of chronic pleurisy is important for the pig producer, because this condition is negatively associated with productivity. Registering chronic pleurisy is no longer considered a priority by the Danish competent authorities, as such, the abattoir mainly uses the information for quality assurance. The performance was evaluated using latent class modelling, an approach which is independent of a gold standard to estimate sensitivity and specificity. Data from 85,413 pig carcasses across 15 slaughter days were analysed using traditional agreement statistics and Bayesian latent class modelling. Agreement between meat inspectors and the different CVS was estimated using Cohen’s kappa and prevalence- and bias-adjusted kappa, indicating moderate (κ=0.72–0.77) and near perfect agreement (κ=0.86–0.89), respectively. The CVS models demonstrated superior sensitivity (84.7–90.3 %) compared to the meat inspectors (79.4–83.0 %), while the meat inspectors maintained slightly higher specificity (99.7–99.9 % versus 97.6–98.8 %). The ResNeXt-101 architecture with 1024-pixel resolution (CVS-Complex-HighRes) performed best overall, while aggregating outputs from multiple CVS models improved specificity without compromising sensitivity (CVS-Consensus). Based on the Danish meat inspection codes, no significant associations were found between the CVS’s chronic pleurisy detection and other meat inspection findings except minor slaughter defects. The study demonstrates that uniform registrations can be made precisely by this CVS independently in a context, where the competent authority considers registration redundant. These findings support the implementation of CVS technology within risk-based meat inspection frameworks, though establishing performance thresholds and addressing regulatory considerations remain necessary for widespread adoption in commercial settings
Longitudinal Anatomical Attention Maps for Recognizing Diagnostic Errors from Radiologists’ Eye Movements
No full textWith the rise in respiratory diseases, the workload on radiologists is increasing, leading to a higher risk of diagnostic errors. One approach to improve diagnostic processes is to reduce the frequency of cognitive and perceptual errors made by humans. This study aims to predict radiologists’ diagnostic errors while interpreting chest X-rays using eye-tracking technology. We propose a novel method that combines human attention, derived from the locations of gaze fixation points, with attention from transformer neural networks. The resulting attention maps are combined with the segmentation of anatomical structures, including the lungs, clavicles, hila, heart, mediastinum, and esophagus, which restricts the analysis for regions potentially relevant for thoracic disease diagnosis. Attention maps are computed for each gaze fixation point, creating a longitudinal path representing the X-ray reading process. Finally, we applied Gated Recurrent Units (GRUs) to learn from the longitudinal attention maps and statistical gaze features to predict potential X-ray diagnostic errors. The proposed methodology was validated on 4, 000 chest X-ray readings performed by four radiologists. The model achieved an error detection accuracy of 0.79, measured as the area under the receiver operating characteristic (ROC) curve. The code is available at https://github.com/annshorn/TEGRU.</p
Predictors of longitudinal changes in body composition and body mass index in Brazilian lactating women during the first 8.5 months postpartum
No full textPregnancy and lactation change women's body composition (BC), but few longitudinal studies have investigated postpartum BC trajectories. We aimed to investigate maternal and infant predictors of maternal body fat (BF), fat mass (FM), fat-free mass (FFM), and body mass index (BMI) trajectories during lactation. Longitudinal study with 234 Brazilian mother-infant dyads followed at 1.0-3.49, 3.5-5.99, and 6.0-8.5 months postpartum. Maternal BC was estimated using bioelectrical impedance at all follow-up points. Longitudinal mixed-effects models with interaction terms with time (weeks postpartum) were employed. FFM declined significantly over weeks postpartum (β = -0.02 kg; 95% CI -0.03, - 0.01). Pre-pregnancy overweight women experienced an increase in all body components (BF: β = 4.91%, 95% CI 3.79, 6.04; FM: β = 6.46 kg, 95% CI 5.26, 7.67; FFM: β = 3.72 kg, 95% CI 2.80, 4.65) and BMI (β = 4.51 kg/m2, 95% CI 3.91, 5.12). Multiparous women showed BMI increases (β = 0.76 kg/m2, 95% CI 0.11, 1.41), and those who delivered by caesarean had FFM (β = 1.87 kg, 95% CI 0.67, 3.07) and BMI (β = 1.39 kg/m2, 95% CI 0.61, 2.18) increases. Women who birthed girls had reductions in FM (β = -1.24 kg, 95% CI -2.41, -0.07) and FFM (β = -0.93 kg, 95% CI -1.84, -0.01). Interactions occurred between maternal age ≥30 years, higher family income, multiparity, and infant sex for BC and BMI trajectories. Maternal age, pre-pregnancy BMI, parity, family income, mode of delivery, and infant sex predict maternal BC and BMI trajectories.</p