The emergency presented through the COVID-19 pandemic exposed the need to adopt remote, technology-driven solutions and make healthcare services more resilient. To do so, we need technological ...applications (i.e., telemedicine) that are designed and tailored to the end-users (i.e., chronic patients) needs and the type of healthcare service they get (i.e., cancer care). The requirements above are especially relevant to Greece, being a country with numerous sparsely populated regions (e.g., islands, regions at the borders) and a deteriorating access to healthcare for all citizens. Trying to address such diverse problems and needs, there have been multiple, different telemedicine and telecare projects in Greece in the past years. To support the future design and implementation of such endeavours, in this study we translated a questionnaire measuring the acceptance of telemedicine by patients and adapted it to the Greek context. We continued by running a small-scale pilot with 73 Greek women with breast cancer to assess the adapted instrument for its reliability and construct validity. The created questionnaire had good overall and internal reliability scores for most sub-scales. Factor analysis did not identify the same number of latent dimensions as the original theoretical model. Reverse wording items needing to be recoded were identified, and items that could be omitted in future versions of the questionnaire. Increasing the sample size for the purposes of a longitudinal study, the construct, convergent, and discriminant validity are elements to be further examined in future studies. It is envisaged that the creation of this questionnaire will support the adoption of telemedicine by Greek healthcare services into more routine areas of patient care provision.
Oncology patients undergoing cancer treatment experience an average of fifteen unrelieved symptoms that are highly variable in both their severity and distress. Recent advances in Network Analysis ...(NA) provide a novel approach to gain insights into the complex nature of co-occurring symptoms and symptom clusters and identify core symptoms. We present findings from the first study that used NA to examine the relationships among 38 common symptoms in a large sample of oncology patients undergoing chemotherapy. Using two different models of Pairwise Markov Random Fields (PMRF), we examined the nature and structure of interactions for three different dimensions of patients' symptom experience (i.e., occurrence, severity, distress). Findings from this study provide the first direct evidence that the connections between and among symptoms differ depending on the symptom dimension used to create the network. Based on an evaluation of the centrality indices, nausea appears to be a structurally important node in all three networks. Our findings can be used to guide the development of symptom management interventions based on the identification of core symptoms and symptom clusters within a network.
: Dementia affects more than 55 million patients worldwide, with a significant societal, economic, and psychological impact. However, many patients with Alzheimer's disease (AD) and other related ...dementias have limited access to effective and individualized treatment. Care provision for dementia is often unequal, fragmented, and inefficient. The COVID-19 pandemic accelerated telemedicine use, which holds promising potential for addressing this important gap. In this narrative review, we aim to analyze and discuss how telemedicine can improve the quality of healthcare for AD and related dementias in a structured manner, based on the seven dimensions of healthcare quality defined by the World Health Organization (WHO), 2018: effectiveness, safety, people-centeredness, timeliness, equitability, integrated care, and efficiency.
: MEDLINE and Scopus databases were searched for peer-reviewed articles investigating the role of telemedicine in the quality of care for patients with dementia. A narrative synthesis was based on the seven WHO dimensions.
: Most studies indicate that telemedicine is a valuable tool for AD and related dementias: it can improve effectiveness (better access to specialized care, accurate diagnosis, evidence-based treatment, avoidance of preventable hospitalizations), timeliness (reduction of waiting times and unnecessary transportation), patient-centeredness (personalized care for needs and values), safety (appropriate treatment, reduction of infection risk),integrated care (interdisciplinary approach through several dementia-related services), efficiency (mainly cost-effectiveness) and equitability (overcoming geographical barriers, cultural diversities). However, digital illiteracy, legal and organizational issues, as well as limited awareness, are significant potential barriers.
: Telemedicine may significantly improve all aspects of the quality of care for patients with dementia. However, future longitudinal studies with control groups including participants of a wide educational level spectrum will aid in our deeper understanding of the real impact of telemedicine in quality care for this population.
Scavenger receptor class B type I (SR-BI) is primarily responsible for the selective uptake of cholesteryl esters (CE) of high-density lipoprotein (HDL) by the liver and other tissues. In the present ...study, we show that SR-BI-deficient (scarb1 –/– ) mice are resistant to diet-induced obesity, hepatic lipid deposition, and glucose intolerance after 24 weeks of being fed a western-type diet. No differences in energy expenditure or mitochondrial function could account for the observed phenotype. Kinetic and gene expression analyses suggested reduced de novo fatty acid synthesis in scarb1 –/– mice. Furthermore, adenosine monophosphate-activated protein kinase (AMPK)-stimulated hepatic FFA catabolism was reduced in these mice, leaving direct dietary lipid uptake from plasma as the major modulator of hepatic lipid content. Analysis of the apolipoprotein composition of plasma lipoproteins revealed a significant accumulation of apolipoprotein E (ApoE)-containing HDL and TG-rich lipoproteins in scarb1 –/– mice that correlated with reduced plasma LpL activity. Our data suggest that scarb1 –/– mice fed a western-type diet for 24 weeks accumulate CE- and ApoE-rich HDL of abnormal density and size. The elevated HDL-ApoE levels inhibit plasma LpL activity, blocking the clearance of triglyceride-rich lipoproteins and preventing the shuttling of dietary lipids to the liver.
Effective symptom management is a critical component of cancer treatment. Computational tools that predict the course and severity of these symptoms have the potential to assist oncology clinicians ...to personalize the patient's treatment regimen more efficiently and provide more aggressive and timely interventions. Three common and inter-related symptoms in cancer patients are depression, anxiety, and sleep disturbance. In this paper, we elaborate on the efficiency of Support Vector Regression (SVR) and Non-linear Canonical Correlation Analysis by Neural Networks (n-CCA) to predict the severity of the aforementioned symptoms between two different time points during a cycle of chemotherapy (CTX). Our results demonstrate that these two methods produced equivalent results for all three symptoms. These types of predictive models can be used to identify high risk patients, educate patients about their symptom experience, and improve the timing of pre-emptive and personalized symptom management interventions.
Recently, we showed that deficiency in apolipoprotein A-I (ApoA-I) sensitizes mice to diet-induced obesity, glucose intolerance and NAFLD. Here we investigated the potential involvement of ApoA-I in ...the pharmacological effects of metformin on glucose intolerance and NAFLD development. Groups of apoa1-deficient (apoa1-/-) and C57BL/6 mice fed western-type diet were either treated with a daily dose of 300mg/kg metformin for 18 weeks or left untreated for the same period. Then, histological and biochemical analyses were performed. Metformin treatment led to a comparable reduction in plasma insulin levels in both C57BL/6 and apoa1-/- mice following intraperitoneal glucose tolerance test. However, only metformin-treated C57BL/6 mice maintained sufficient peripheral insulin sensitivity to effectively clear glucose following the challenge, as indicated by a 3H-2-deoxy-D-glucose uptake assay in isolated soleus muscle. Similarly, deficiency in ApoA-I ablated the effect of metformin on hepatic lipid deposition and NAFLD development. Gene expression analysis indicated that the effects of ApoA-I on metformin treatment may be independent of adenosine monophosphate-activated protein kinase (AMPK) activation and de novo lipogenesis. Interestingly, metformin treatment reduced mitochondrial oxidative phosphorylation function only in apoa1-/- mice. Our data show that the role of ApoA-I in diabetes extends to the modulation of the pharmacological actions of metformin, a common drug for the treatment of type 2 diabetes.
Delayed diagnosis is a major contributing factor to the UK's lower cancer survival compared to many European countries. In the UK, there is a significant national variation in early cancer diagnosis. ...Healthcare providers can offer an insight into local priorities for timely cancer diagnosis. In this study, we aimed to identify the main problems and solutions relating to delay cancer diagnosis according to cancer care clinicians.
We developed and implemented a new priority-setting approach called PRIORITIZE and invited North West London cancer care clinicians to identify and prioritize main causes for and solutions to delayed diagnosis of cancer care.
Clinicians identified a number of concrete problems and solutions relating to delayed diagnosis of cancer. Raising public awareness, patient education as well as better access to specialist care and diagnostic testing were seen as the highest priorities. The identified suggestions focused mostly on the delays during referrals from primary to secondary care.
Many identified priorities were feasible, affordable and converged around common themes such as public awareness, care continuity and length of consultation. As a timely, proactive and scalable priority-setting approach, PRIORITZE could be implemented as a routine preventative system for determining patient safety issues by frontline staff.
Cancer care is liable to medication errors due to the complex nature of cancer treatment, the common presence of comorbidities and the involvement of a number of clinicians in cancer care. While the ...frequency of medication errors in cancer care has been reported, little is known about their causal factors and effective prevention strategies. With a unique insight into the main safety issues in cancer treatment, frontline staff can help close this gap. In this study, we aimed to identify medication safety priorities in cancer patient care according to clinicians in North West London using PRIORITIZE, a novel priority-setting approach.
The project steering group determined the scope, the context and the criteria for prioritization. We then invited North West London cancer care clinicians to identify and prioritize main causes for, and solutions to, medication errors in cancer care. Forty cancer care providers submitted their suggestions which were thematically synthesized into a composite list of 20 distinct problems and 22 solutions. A group of 26 clinicians from the initial cohort ranked the composite list of suggestions using predetermined criteria.
The top ranked problems focused on patients' poor understanding of treatments due to language or education difficulties, clinicians' insufficient attention to patients' psychological distress, and inadequate information sharing among health care providers. The top ranked solutions were provision of guidance to patients and their carers on what to do when unwell, pre-chemotherapy work-up for all patients and better staff training. Overall, clinicians considered improved communication between health care providers, quality assurance procedures (during prescription and monitoring stages) and patient education as key strategies for improving cancer medication safety. Prescribing stage was identified as the most vulnerable to medication safety threats. The highest ranked suggestions received the strongest agreement among the clinicians.
Clinician-identified priorities for reducing medication errors in cancer care addressed various aspects of cancer treatment. Our findings open up an opportunity to assess the congruence between health care professional suggestions, currently implemented patient safety policies and evidence base.
To navigate the field of digital cancer care and define and discuss key aspects and applications of big data analytics, artificial intelligence (AI), and data-driven interventions.
Peer-reviewed ...scientific publications and expert opinion.
The digital transformation of cancer care, enabled by big data analytics, AI, and data-driven interventions, presents a significant opportunity to revolutionize the field. An increased understanding of the lifecycle and ethics of data-driven interventions will enhance development of innovative and applicable products to advance digital cancer care services.
As digital technologies become integrated into cancer care, nurse practitioners and scientists will be required to increase their knowledge and skills to effectively use these tools to the patient's benefit. An enhanced understanding of the core concepts of AI and big data, confident use of digital health platforms, and ability to interpret the outputs of data-driven interventions are key competencies. Nurses in oncology will play a crucial role in patient education around big data and AI, with a focus on addressing any arising questions, concerns, or misconceptions to foster trust in these technologies. Successful integration of data-driven innovations into oncology nursing practice will empower practitioners to deliver more personalized, effective, and evidence-based care.
Purpose
Artificial intelligence (AI) in the form of automated machine learning (AutoML) offers a new potential breakthrough to overcome the barrier of entry for non-technically trained physicians. A ...Clinical Decision Support System (CDSS) for screening purposes using AutoML could be beneficial to ease the clinical burden in the radiological workflow for paranasal sinus diseases.
Methods
The main target of this work was the usage of automated evaluation of model performance and the feasibility of the Vertex AI image classification model on the Google Cloud AutoML platform to be trained to automatically classify the presence or absence of sinonasal disease. The dataset is a consensus labelled Open Access Series of Imaging Studies (OASIS-3) MRI head dataset by three specialised head and neck consultant radiologists. A total of 1313 unique non-TSE T2w MRI head sessions were used from the OASIS-3 repository.
Results
The best-performing image classification model achieved a precision of 0.928. Demonstrating the feasibility and high performance of the Vertex AI image classification model to automatically detect the presence or absence of sinonasal disease on MRI.
Conclusion
AutoML allows for potential deployment to optimise diagnostic radiology workflows and lay the foundation for further AI research in radiology and otolaryngology. The usage of AutoML could serve as a formal requirement for a feasibility study.
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