Objective: In a simultaneous care model, patients have concurrent access to both cancer-directed therapies and palliative care. As oncologists play a critical role in determining the need/timing of referral to palliative care programs, their understanding of the service and ability to communicate this with patients is of paramount importance. Our study aimed to examine oncologists' perceptions of the supportive care program at M.D. Anderson Cancer Center, and to determine whether renaming “palliative care” to “supportive care” influenced communication regarding referrals.
Method: This qualitative study used semi-directed interviews, and we analyzed data using grounded theory and qualitative methods.
Results: We interviewed 17 oncologists. Supportive care was perceived as an important time-saving application, and symptom control, transitioning to end-of-life care, family counseling, and improving patients' ability to tolerate cancer therapies were cited as important functions. Although most claimed that early referrals to the service are preferable, oncologists identified several challenges, related to the timing and communication with patients regarding the referral, as well as with the supportive care team after the referral was made. Whereas oncologists stated that the name change had no impact on their referral patterns, the majority supported it, as they perceived their patients preferred it.
Significance Of Results: Although the majority of oncologists favorably viewed supportive care, communication barriers were identified, which need further confirmation. Simultaneous care models that effectively incorporate palliative care with cancer treatments need further development.
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http://dx.doi.org/10.1017/S1478951512000685 | DOI Listing |
Sci Rep
December 2024
Department of Diagnostic Radiology, Dalhousie University, Halifax, Canada.
The goal of this study was to determine how radiologists' rating of image quality when using 0.5T Magnetic Resonance Imaging (MRI) compares to Computed Tomography (CT) for visualization of pathology and evaluation of specific anatomic regions within the paranasal sinuses. 42 patients with clinical CT scans opted to have a 0.
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December 2024
The School of Nursing, Fujian Medical University, No. 1 Xuefu North Road, Fuzhou, 350122, Fujian, China.
Diabetes Mellitus combined with Mild Cognitive Impairment (DM-MCI) is a high incidence disease among the elderly. Patients with DM-MCI have considerably higher risk of dementia, whose daily self-care and life management (i.e.
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December 2024
Department of Chemistry, University of Washington, Box 351700, Seattle, Washington, 98195, USA.
Trigger valves are fundamental features in capillary-driven microfluidic systems that stop fluid at an abrupt geometric expansion and release fluid when there is flow in an orthogonal channel connected to the valve. The concept was originally demonstrated in closed-channel capillary circuits. We show here that trigger valves can be successfully implemented in open channels.
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December 2024
Research Centre for Biomedical Engineering (RCBE), School of Science and Technology, City, University of London, Northampton Square, London, EC1V 0HB, UK.
Traditional methods for management of mental illnesses in the post-pandemic setting can be inaccessible for many individuals due to a multitude of reasons, including financial stresses and anxieties surrounding face-to-face interventions. The use of a point-of-care tool for self-management of stress levels and mental health status is the natural trajectory towards creating solutions for one of the primary contributors to the global burden of disease. Notably, cortisol is the main stress hormone and a key logical indicator of hypothalamic-pituitary adrenal (HPA) axis activity that governs the activation of the human stress system.
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December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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