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Primary healthcare costs associated with the AstraZeneca COVID-19 vaccine in England
No full textData availability:
The authors do not have permission to share data.Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S0264410X25013659#ec0005 .Current research on the effectiveness of COVID-19 vaccines has demonstrated their role in reducing hospitalizations and deaths due to SARS-CoV-2. However, evidence regarding the healthcare costs incurred by vaccinated versus unvaccinated individuals in the community remains limited, especially in primary care, the first point of access for most patients. This study estimated the total (all-cause) primary healthcare costs for individuals who received the AstraZeneca COVID-19 vaccine (AZD1222) in England between 2020 and 2021. We conducted an economic analysis utilizing electronic primary healthcare records from the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub (ORCHID) database, with costs valued according to NHS tariffs. Exact coarsened matching in a time-varying setting was employed to balance patient characteristics between the vaccinated and unvaccinated groups. Our results indicate that vaccinated individuals who received the first dose of the AstraZeneca vaccine incurred significantly lower primary healthcare costs compared to their unvaccinated counterparts. Specifically, at 15 days post-vaccination, vaccinated individuals had total costs that were £47.5 (95 % CI: £42.6 to £52.4) lower. This difference increased to £87.1 (95 % CI: £79.6 to £94.6) at 30 days and £124.0 (95 % CI: £114.3 to £133.7) at 45 days post-vaccination, reflecting a reduction of approximately 33.1 % during this period. These findings carry important implications for healthcare budgeting, resource allocation, and pandemic response policies.SP receives support as a UK National Institute for Health Research (NIHR) Senior Investigator (NF-SI-0616-10103) and from the UK NIHR Applied Research Collaboration Oxford and Thames Valley. CN receives support from UK NIHR Applied Research Collaboration Oxford and Thames Valley
A non‐judgmental companion: connections to the natural environment for people affected by dementia
Get PDFThe "Dementia Care Research and Psychosocial Factors" poster sessions were part of the larger Alzheimer's Association International Conference (AAIC) 2025, which was held from July 27-31, 2025, in Toronto, Canada.Background:
Evidence suggests that social connections are often disrupted by a dementia diagnosis. Eco-mapping, a common practice in social work, allows the visualization of interconnected lives and permits an opportunity to explore the nature and quality of social connections, and their protective or adverse risk factors for isolation. Their use in a research context with a focus on connections to the natural environment rather than people, is less familiar. Given the strong evidence suggesting the importance of the natural environment to our well-being, we conducted a qualitative multi-method study to identify the nature, quality and essence of connections to the natural environment for people affected by dementia and explore these in the context of their well-being.
Methods:
Care partners, and where possible their partner living with different dementia diagnoses, developed eco-maps during virtual research interviews to illustrate their “blue-green-white” connections to the environment and their quality. This was followed by a series of open-ended questions to further explore their various connections and a subjective assessment of their social and environmental health. We also conducted walking interviews with a subset of participants to further contextualize mapping data and capture the relationship between well-being and environment. Drawing on participatory methods, we photographed aspects during the walk deemed as significant by the participant. The different data sets were analyzed using thematic analysis and integrated at the interpretation and conceptualization stage.
Results:
Our sample included nineteen participants, four of whom provided data as a dyad. The eco-maps provided an effective visual representation of the complexity of fluctuating social and environmental connections, and together with the interviews and images allowed for a more comprehensive understanding on how blue-green-white connections affected their well-being, and their relationship with their partner. Our findings suggest that connections to nature provided energy, which participants were able to draw on and seek strength from, allowed them to (re) connect with themselves and their partner, and nature being a non-judgmental companion contributing to a sense of safety and calmness.
Conclusion:
Connection to the natural environment can be protective for families affected by dementia and its assessment can contribute to family-centred supports
Holistic Care Clinic for People with Parkinson’s Disease: Outcome from a Newly Developed Service
Get PDFData Availability Statement:
The data presented in this study are available on request from the corresponding author due to ethical restrictions.Supplementary Materials:
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/brainsci16010043/s1. Table S1: Sustainability and Reproducibility Measures of the Holistic Care Clinic Model.Background/Objectives: Non-motor symptoms (NMS) in Parkinson’s disease (PD), particularly neuropsychiatric disturbances such as anxiety, significantly impact quality of life. The Holistic Care Clinic for Parkinson’s disease at St George’s Hospital offers multidisciplinary assessments and personalized care to address both motor and non-motor symptoms, aiming to improve patient well-being and empower patients to manage their health and enhance their quality of life. This study evaluated the effectiveness of a holistic management approach for PD patients with prominent non-motor symptoms, particularly neuropsychiatric issues, by analyzing clinical outcomes and patient feedback. Methods: A retrospective analysis was conducted on patients referred to the clinic between June 2022 and June 2023 for non-motor symptoms. Patients received comprehensive assessments, including clinical exams and interviews focused on neuropsychiatric symptoms, followed by individualized care plans. Interventions for anxiety included online psychoeducation and cardiac biofeedback. Outcomes were assessed using the Clinical Global Impression (CGI) scale and patient feedback on interventions. Results: Thirty patients (mean age 65.7 years, mean disease duration 7.8 years) were included. Anxiety was the primary referral reason (66%). CGI scores indicated that 62% of patients experienced improvement. Medications were adjusted in 14 patients and 65% improved. For anxiety, 13 patients attended the psychoeducation session, with 91% rating it “very likely”/”likely” to recommend. Ten patients completed cardiac biofeedback training, showing a significant reduction in Parkinson’s Anxiety Scale scores (p = 0.03), and 90% recommending it. Conclusions: The holistic care approach of PD patients resulted in significant improvements in clinical outcomes. Patient feedback indicates high satisfaction with the interventions, supporting their acceptability and overall satisfaction with the interventions.This research received no external funding
A machine learning method for predicting the elongation to failure of Al–Si alloy in high pressure die casting combining experiment and modeling
Get PDFHigh-pressure die casting (HPDC) of Al–Si alloys faces challenges in improving mechanical properties and early failure due to process-induced defects. Traditional quality assessment experiments and modeling methods are costly and lack predictive capability. This study proposed a machine learning (ML) method integrating numerical simulations and experimental data to predict elongation. The data were extracted from experiments and well validated mathematical models of the HPDC process and underwent preprocessing such as standardization and feature selection. The performance of twelve common ML models was evaluated, among which the eXtreme Gradient Boosting (XGBoost) and Gradient Boosting (GB) algorithms performed the best. By using the Crested Porcupine Optimizer (CPO) and Bayesian Optimization for hyperparameter optimization, the accuracy of the models was further improved. The R2 value of the CPO-XGBoost model reached the optimal value of 0.882. The SHapley Additive exPlanations (SHAP) analysis revealed that total shrinkage volume dominantly reduced elongation (El), while die temperature and pouring temperature negatively affected El. Validation with independent experiments demonstrated that the difference between the predicted values and the measured values was within 5 %. This work establishes a novel methodology combining physics-based simulations and experiments to comprehensively predict and analyze the failures of HPDC Al–Si alloys from multiple perspectives. It can be further extended to the prediction of various types of alloys or multiple mechanical properties.The financial supports from the Key Research and Development Program of Xiangjiang Laboratory (22XJ01002), the National Science Foundation of China (52304360) and the National Key Research and Development Program of China (No. 2023YFB3710202) are greatly acknowledged
From Benchmarking to Optimisation: A Comprehensive Study of Aircraft Component Segmentation for Apron Safety Using YOLOv8-Seg
Get PDFData Availability Statement:
The dataset used in this study was created by the authors and is currently hosted in a private workspace. The dataset will be made publicly available on Roboflow upon the publication of this article.Supplementary Materials:
The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/app152111582/s1, Table S1: Label Distribution per Class; Table S2: Number of Labels per Image; Table S3: Image Size Categories; Table S4: Image Aspect Ratio Distribution; Table S5: Architectural Components of YOLO Model Variants; Table S6: Architectural Components of YOLO-Seg Models; Table S7: Architectural Components of Faster R-CNN and DETR Models; Table S8: Experimental Setup Parameters for 12 Models; Table S9: Summary of Hardware, Software, and Training Parameters for All Optimisation Steps and Final Optimised Model.Apron incidents remain a critical safety concern in aviation, yet progress in vision-based surveillance has been limited by the lack of open-source datasets with detailed aircraft component annotations and systematic benchmarks. This study addresses these limitations through three contributions. First, a novel hybrid dataset was developed, integrating real and synthetic imagery with pixel-level labels for aircraft, fuselage, wings, tail, and nose. This publicly available resource fills a longstanding gap, reducing reliance on proprietary datasets. Second, the dataset was used to benchmark twelve advanced object detection and segmentation models, including You Only Look Once (YOLO) variants, two-stage detectors, and Transformer-based approaches, evaluated using mean Average Precision (mAP), Precision, Recall, and inference speed (FPS). Results revealed that YOLOv9 delivered the highest bounding box accuracy, whereas YOLOv8-Seg outperformed in segmentation, surpassing some of its newer successors and showing that architectural advancements do not always equate to superiority. Third, YOLOv8-Seg was systematically optimised through an eight-step ablation study, integrating optimisation strategies across loss design, computational efficiency, and data processing. The optimised model achieved an 8.04-point improvement in [email protected]:0.95 compared to the baseline and demonstrated enhanced robustness under challenging conditions. Overall, these contributions provide a reliable foundation for future vision-based apron monitoring and collision risk prevention systems.This research received no specific external funding. The first author’s PhD studies are supported by a scholarship from the Ministry of National Education of Türkiye, but this did not directly fund the present work
How to (Re)Inspire the Next Generation of Simulation Modelers
Get PDFDespite the rising relevance of simulation in the twin transformation of sustainability and digitalization, simulation education often struggles to attract and retain learners. We introduce a generic, adaptable Constructive Alignment Simulation Framework that supports instructors in designing motivating, learner-centered, and coherently structured simulation courses. The framework emerged from the collective teaching experience of the authors in Austria, the UK, and the USA, covering a broad range of student profiles, institutional contexts, and educational levels. Building on key principles such as constructive alignment, revised Bloom’s Taxonomy, and blended learning, the framework includes structured learning objectives, modular teaching formats, and a portfolio of assessment methods. We show how individual components of the framework have already been implemented across different simulation courses and demonstrate its flexibility and modular applicability for gradual and context-sensitive adoption
A Fully Transformer-Based Multimodal Framework for Explainable Breast Cancer Image Segmentation Using Radiology Reports
Get PDFWe introduce Med-CTX, a fully transformer based multimodal framework for explainable breast cancer ultrasound segmentation. We integrate clinical radiology reports to boost both performance and interpretability. Med-CTX achieves exact lesion delineation by using a dual-branch visual encoder that combines ViT and Swin transformers, as well as uncertainty aware fusion. Clinical language structured with BI-RADS semantics is encoded by BioClinicalBERT and combined with visual features utilising cross-modal attention, allowing the model to provide clinically grounded, model generated explanations. Our methodology generates segmentation masks, uncertainty maps, and diagnostic rationales all at once, increasing confidence and transparency in computer assisted diagnosis. On the BUS-BRA dataset, Med-CTX achieves a Dice score of 90% and an IoU of 82.7%, beating existing baselines U-Net, ViT, and Swin. Clinical text plays a key role in segmentation accuracy and explanation quality, as evidenced by ablation studies that show a-5.4% decline in Dice score and-31% in CIDEr. Med-CTX achieves good multimodal alignment (CLIP score: 85%) and increased confidence calibration (ECE: 3.2%), setting a new bar for trustworthy, multimodal medical architecture
Commissioning Official History versus Paying for Official History
Get PDFFollowing the conclusion of the First World War the Royal Navy was so keen to learn the lessons of the conflict that they commissioned no less than five different types of official history and were also involved in the production of two others. No other department commissioned quite so much official history, and the Admiralty was far from open about what it was doing, hiding the resources needed for some series in the estimates for others. As a result, throughout the 1920s and 1930s, it found itself engaged in a protracted dispute with the Treasury about what was being done and how to pay for it. This article explores why the Admiralty sought so many different routes into the historical record and charts the numerous battles between the Admiralty and the Treasury over the writing and publication of these histories. In so doing, the article highlights the navy’s understanding of the term ‘official history’, the value that the service placed upon such histories, the different value accorded to them by the Treasury, as well as the underestimate of the time and effort required to produce such histories by those responsible for the national finances
Missing Nepali women
Get PDFRama (name changed) left her home in 2012 to work as a domestic worker in Kuwait. She migrated to support her family. For years, she sent regular remittances and assured her mother that she was safe. Then, on August 9, 2015, she made her last call and told her mother that she was planning to leave soon and would send some things home. Eleven years later, her mother still waits, raising Rama’s children without knowing if her daughter is alive or dead
Towards a new Value-based scenario for the management of dementia in Italy: a SINdem delphi consensus study
Get PDFCode availability:
On request to the corresponding Author.Consortia:
On behalf of the SINdem DELPHI Consensus Group:
Rossano Angeloni, Gennarina Arabia, Andrea Arighi, Sergio Bagnato, Claudio Babiloni, Roberta Baschi, Giuseppe Bellelli, Valentina Bessi, Edoardo Domenico Giorgio Canu, Sabina Capellari, Moira Ceci, Rosanna Colao, Laura De Togni, Gennaro Della Rocca, Lucia Di Giorgi, Sabrina Esposito, Katia Fabi, Elisabetta Farina, Massimo Filippi, Chiara Fiori, Gianluca Floris, Gianluigi Forloni, Franco Giubilei, Daniela Gragnaniello, Maria Guarino, Alessandro Iavarone, Daniele Imperiale, Valeria Isella, Antonina Luca, Donata Luiselli, Simona Luzzi, Susanna Malagù, Michela Marcon, Alessandro Marti, Alessandro Martorana, Maria Giuseppina Mascia, Patrizia Mecocci, Daniele Mei, Paola Merlo, Fabio Moda, Roberto Monastero, Giuseppe Mura, Anna Maria Musso, Anna Vittoria Marta Orsini, Piero Parchi, Matteo Pardini, Lucilla Parnetti, Andrea Plutino, Gianfranco Puccio, Sabina Roncacci, Mara Rosso, Elisa Rubino, Stefano Sensi, Grazia Sibilia, Marco Spallazzi, Patrizia Sucapane, Pietro Tiraboschi, Gloria Tognoni, Gabriele Tripi, Alessandro Vacca, Marco Vista, Gianluigi Zanusso & Marta Zuffi.Supplementary Information is available at: https://link.springer.com/article/10.1007/s10072-025-08143-5#Sec7 .This national expert-based Delphi-consensus aims at formulating recommendations on the management of dementia care in Italy. This effort seems important and timely given in light of a new scenario arising from a new biological definition of Alzheimer’s disease (AD) and the availability of disease-modifying treatments (DMTs).
Methods:
the Steering Committee of the Italian Neurological Society for dementia (SINdem) created appropriate statements. Invited SINdem experts were requested to vote on the statements according to a modified three-round Delphi method. Only those statements reaching Grade A (full agreement ≥ 75%) or B (overall agreement ≥ 80% and full disagreement < 5%) were included in the final document. Round answers’ consistency was graded using the Cohen’s k and within-class correlation coefficient.
Results:
Forty-six experts voted on 20 statements, which focused on the following aspects: i) organization of care services from early diagnosis to the management of advanced clinical stages; ii) access to biomarkers for a biological diagnosis of AD; iii) requirements necessary for the administration of DMTs; iv) main actors and pathways for the management of patients suffering from cognitive disorders. At the end of the process, 4 statements (20%) received a Grade A consensus, while 16 (80%) reached a Grade B consensus. Although the responses reflect heterogeneity among Italian regions, there was a fair degree of consistency for all statements.
Conclusion:
The high strength of this expert-based Delphi-consensus may offer guidance for improving the patient’s journey of individuals with cognitive decline from a biological diagnosis to DMTs administration and may possibly offer hints to the Health Systems on dementia.Open access funding provided by Università degli Studi di Padova within the CRUI-CARE Agreement. No funds, grants, or other support was received
Data sources:
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