The Single Site Order – a policy restricting staff from working at multiple long-term care homes – was mandated by the Public Health Agency of Canada to control the spread of COVID-19 in long-term care homes, where nearly 70% of COVID-19-related deaths in Canada occurred. This mixed methods study assesses the impact of Single Site Order on long-term care residents in British Columbia. Interviews were conducted (residents (n=6), family members (n=9), staff (n=18), and leadership (n=10) from long-term care homes (n=4)) and analyzed using thematic analysis. Administrative data was collected between April 2019 – March 2020 and April 2020 – March 2021 and analyzed using descriptive statistics and data visualization. Qualitative and quantitative data were triangulated and demonstrate staffing challenges became worse during implementation of the SSO resulting in the mental and physical health deterioration of LTC residents. Qualitative data demonstrated decreased time for personalized and proactive care, increased communication challenges, and increased loneliness and isolation. Quantitative data showed a decline in activities of daily living, increased antipsychotic medication use, pressure ulcers, behavioural symptoms, and an increase in falls. Addressing staff workload and staffing shortages during SSO-related policy implementation is essential to avoid resident health deterioration.

Background. Ovarian cysts are common in premenopausal women but can present with vague, non-specific symptoms, making discovery more challenging. Most are benign and resolve spontaneously; however, they can present, as in this case, as ovarian torsions, which is a gynecological emergency. Case presentation. A twenty-year-old female had presented over 3–4 times per year for the last 6 years to her primary doctor citing intermittent abdominal pain, irregular menstruation, dyspnea, and an enlarging abdomen circumference. The doctor stated, she was “just fat” and could, benefit from a “special camp to lose weight”, so she stopped mentioning her concerns. Upon presenting to the emergency department with acute onset abdominal pain, a computed tomography scan showed a large cyst lesion filling the abdominal and pelvic cavity. Its origin appeared to be from the left adnexa. Surgery was performed, and an acute ovarian torsion caused by a 36 cm craniocaudal left ovarian cyst was found and removed along with the left fallopian tube and 16 L of fluid. Conclusions. The value of respecting the “third presentation” rule indicates to health care providers that any patient who presents with any /or other symptoms or complaint needs to be thoroughly investigated. In this case the patient presented recurring pelvic/abdominal concerns, irregular menstruation, which warranted further investigation to safeguard fertility and prevent errors of omission. It is important to consider the differentials and be aware of vague symptoms that may lead to early recognition and effective management to prevent adverse consequences, complications, or even death.

Mortality and readmission rates for decompensated acute heart failure (AHF) is overall increasing and risk stratification might be challenging. We sought to evaluate the prognostic role of systemic venous ultraso-nography in patients hospitalized for AHF. We prospectively recruited 74 AHF patients with a NT-proBNP level above 500 pg/mL. Then, a multiorgan ultrasound assessment (lung, inferior vena cava, Doppler of hepatic, portal, intrarenal and femoral veins) were performed at admission, discharge, and follow-up (for 90 days). An intrarenal monophasic pattern (AUC 0.923, Sn 90%, Sp 81%, PPV 43%, NPV 98%), a portal pulsatility >50% (AUC 0.749, Sn 80%, Sp 69%, PPV 30%, NPV 96%) and a VExUS score of 3 (AUC 0.885, sensitivity 80%, specificity 75%, PPV 33%, NPV 96%) predicted death during hospitalization. An IVC above 2 cm (AUC 0.758, Sn 93.l% and Sp 58.3) and the presence of an intrarenal monophasic pattern (AUC 0. 834, sensitivity 0.917, specificity 67.4%) in the follow-up visit predicted AHF related readmission. Addi-tional scans during hospitalization or calculate a VExUS score probably adds unnecessary complexity to the assessment of AHF patients. In conclusion, VExUS score does not contribute to guide therapy or the predic-tion of complications, compared to the presence of an inferior vena cava greater than 2 cm, a venous mo-nophasic intrarenal pattern or a pulsatility > 50% of the portal vein in AHF patients. Early and multidisci-plinary follow-up visit remains necessary to improve prognosis of this highly prevalent disease.

Current clinical treatment options for symptomatic, partial-thickness rotator cuff tear (sPTRCT) offer only limited potential for true tissue healing and improvement of clinical results. In animal models, injections of adult stem cells isolated from adipose tissue into tendon injuries evidenced histological regeneration of tendon tissue. However, it is unclear whether such beneficial effects could also be observed in a human tendon treated with fresh, uncultured, autologous, adipose derived regenerative cells (UA-ADRCs). A specific challenge in this regard is that UA-ADRCs cannot be labeled and, thus, not unequivocally identified in the host tissue. Therefore, histological regeneration of injured human tendons after injection of UA-ADRCs must be assessed using comprehensive, immunohistochemical and microscopic analysis of biopsies taken from the treated tendon a few weeks after injection of UA-ADRCs.

Africa was the only continent not to achieve the 2015 Millennium Development Goal of 50% poverty reduction. This paper asks whether Africa will fare better in meeting Sustainable Development Goals (SDGs) addressing poverty and hunger by 2030. To answer this question we examine literature, including our field research published over the last thirteen years. We find that ‘sustainable development’ is a failed concept immersed in the contemporary global economic system that favors growth over ecosystem stability and patriarchal systems of governance that undervalue women’s capacity for sustainability in their care-work as food providers. We examine barriers to women’s farming (climate change, gender bias, limited access to land, technology, finance) and provide examples of women’s innovative strategies for overcoming these barriers in their care practices toward family and community well-being and ecosystem health. We conclude that sustainability is only possible through transformation of thinking away from approaches that value profit over people and ecosystems and toward gender-based approaches for achieving the goals laid out in the SDGs through holistic, integrative systems of ecosystem fit.

The shift towards Personalized Cancer Medicine (PCM) represents a significant transformation in cancer care, emphasizing tailored treatments based on genetic understanding of cancer at the cellular level. This review draws on recent literature to explore key factors influencing PCM implementation, highlighting the role of innovative leadership, interdisciplinary collaboration, and coordinated funding and regulatory strategies. Success in PCM relies on overcoming challenges such as integrating diverse medical disciplines, securing sustainable investment for shared infrastructures, and navigating complex regulatory landscapes. Effective leadership is crucial for fostering a culture of innovation and teamwork, essential for translating complex biological insights into personalized treatment strategies. The transition to PCM necessitates not only organizational adaptation but also the development of new professional roles and training programs, underscoring the need for a multidisciplinary approach and the importance of team science in overcoming the limitations of traditional medical paradigms. The conclusion underscores that PCM's success hinges on creating collaborative environments that support innovation, adaptability, and shared vision among all stakeholders involved in cancer care.

This study investigated co-constructed research poetry as a way to understand the lived experiences of people affected by rarer dementia and as a means to use poetry to convey those experiences to healthcare professionals. Using mixed-methods, 71 people living with rarer dementia and care-partners (stakeholders) contributed to co-constructing 27 poems with professional poets; stakeholders’ verbatim words were analysed with descriptive qualitative analysis. Stakeholders were also surveyed and interviewed about their participation. Healthcare professionals (n = 93) were surveyed to elicit their responses to learning through poetry and its acceptability as a learning tool. Poems conveyed a shared narrative of different aspects of lived experience, often owing to atypical symptoms, misunderstandings by professionals, lack of support pathways, and a continuous struggle to adapt. Stakeholder surveys indicated it was a valuable experience to both co-create and respond to the poems, whilst group interviews revealed people’s experiences of the research poetry were characterised by reflection on lived experience, curiosity and exploration. Healthcare professionals’ responses reinforced the poetry’s capacity to stimulate cognitive and affective learning specific to rare dementia support and prompt both empathy and critical thinking in practice. As the largest poetry-based study that we are aware of, this novel accessible approach of creating group poems yielded substantial information about the experiences and needs of those affected by rarer dementia and how poetry can contribute to healthcare education and training.

The complex progression, specialized care, and comorbidities of chronic diseases place a financial and health burden on society. In some instances, the high hospital readmission rate is also a result of chronic diseases. The readmission rates can be decreased if the quality of life for patients is increased and healthcare costs are reduced through effective management and preventive measures. As a result, healthcare professionals, service providers, and policy-makers are looking for innovative approaches to reduce healthcare costs while enhancing the quality of care. There is an emerging trend in deploying technological advancements like artificial intelligence (AI), the Internet of Things (IoT), sensors, wearables, social media, mobile apps, and genomics to decrease hospital readmissions. In some instances, predictive analytics, early warning systems, personal-ized care management, remote monitoring and Telehealth, decision support systems, patient education and engagement, and other areas of artificial intelligence and machine learning have outperformed traditional approaches in lowering hospital readmissions. Although AI effectively reduces readmission, there are potential risks if it is not combined with efficient interventions. Therefore, real-time monitoring and intervention are required for AI systems to increase patient safety and decrease hospital readmissions. To achieve autonomy, prevent harm, achieve fairness, and achieve explicability, the ethical principles relating to AI systems should be taken into ac-count. This study examines the significant impact on health and the economy of hospital read-missions for chronic diseases and the role of AI in reducing readmissions.

People from Black and Asian backgrounds are more likely to die from Covid-19 but less likely to be vaccinated, threatening to exacerbate health inequalities already experienced by ethnic minority groups. Literature suggests that mistrust rooted in structural inequality may be a key barrier to Covid-19 vaccine uptake. We need to better understand how structural inequalities influence vaccine confidence. Understanding and addressing these processes is likely to lead to longer-term impacts than information alone. We draw on health and sociological theories of structure and agency to inform our understanding of structural factors. We conducted qualitative interviews and focus groups with 22 people from London and surrounding areas in December 2021 to March 2022. Fifteen participants were members of the public from ethnic minority backgrounds and 7 were professionals working with the public to address concerns and encourage vaccine uptake. Our findings suggest that people from ethnic minority backgrounds make decisions regarding Covid-19 vaccination based on a combination of how they experience external social structures (including political authority, social positioning and racial inequality) and internal processes (what they believe and understand about Covid-19 vaccines). We may be able to support knowledge accumulation through the provision of reliable and accessible information, particularly through primary and community care. But we recommend a number of changes to research, policy and practice which address structural inequalities. These include working with communities to improve ethnicity data collection, increasing funding allocation to health conditions where ethnic minority communities experience poorer outcomes, greater transparency and public engagement in the vaccine development process, and culturally adapted research recruitment processes.

On April 17, 2019, a coach with tourists from Germany crashed in Madeira requiring repatriation by the German Air Force. The Advance Trauma Life Support (ATLS) concept was the central component of patient care. Data in Madeira were collected through a structured interview. The analysis of the Aeromedical Evacuation was based on intensive care transport records. In Germany all available were reviewed for data collection. Quality of life (HRQoL) was evaluated by the 12-item Short-Form Health Survey (SF-12). Twenty-eight prehospital patients were transported to the Level III Trauma Center in Funchal (Madeira). Five operative procedures were performed. Fifteen patients were eligible for Aeromedical Evacuation (AE). In the second hospital phase in Germany in total 82 radiological images and nine operations were performed. Hospital stay lasted 11 days (median, IQR 10–18). Median Follow-up (14 of 15 patients) was 16 months (IQR 16–21). 80% (8 out of 10) showed an increased risk for post-traumatic stress disorder (PTSD). Six key findings were identified in this study: divergent injury classification, impact of AE mission on health status, lack of communication, need of PTSD prophylaxis, patient identification, media coverage. Those findings may improve AE missions in the future e.g. required after armed conflicts.

Online digital mental health communities can contribute to users’ mental health positively and negatively. Yet the measurement of outcomes and impact relating to digital mental health communities is difficult to capture. In this paper we demonstrate the development of an online experience measure for a specific children and young people’s community inside a digital mental health service. The development is informed by three phases: (i) item reduction through Estimate-Talk-Estimate modified Delphi methods, (ii) user testing with participatory action research and (iii) a pilot within the digital service community to explore its use. Rounds of experts talks help to reduce the items. User experience workshops helped to inform the usability and appearance, wording, and purpose of the measure. Finally, the pilot results highlight completion rates, difference in scores for age and community roles and a preference to ‘relate to others’; as a mechanism of support. Outcomes frequently selected in the measure show the importance of certain aspects of the community, such as safety, connection, and non-judgment previously highlighted in the literature. Self-reported helpfulness scales like this one could be used as indicators of meaningful engagement within the community and its content but further research is required to ascertain its acceptability and validity. Phased approaches involving stakeholders and participatory action research enhances the development of digitally enabled measurement tools.

Background: The CoBaTrICE initiative standardized intensive care training throughout Europe. Pericardiocentesis, an important yet infrequent operation, poses unique training challenges often unmet by conventional methods. This study evaluates the efficacy of virtual reality (VR) simulations and 3D-printed mannequins in pericardiocentesis training, both crafted from scratch using highly affordable materials and free software. Methods: Thirty-five final-year medical students participated in this prospective, quasi-experimental study. Initially, students underwent VR simulation training, followed by training using 3D-printed self-made mannequins. Learning outcomes were assessed using the Objective and Structured Clinical Examination (OSCE) questionnaire. Heart rate variability (HRV) analysis was employed to monitor stress responses, while the NASA Task Load Index (NASA-TLX) was used to gauge self-perceived difficulty. Results: Although the mannequin model induced more stress reactions, it excelled in tasks requiring fine motor skills, such as correct placement and asepsis maintenance. In contrast, lower NASA-TLX scores indicated that the VR model imposed less mental demand and effort, reflecting a reduced cognitive load. Conclusion: Both VR simulations and 3D-printed mannequins effectively taught pericardiocentesis skills, each offering distinct advantages. Mannequins enhanced fine motor skills, whereas VR reduced cognitive load and increased engagement. The combination of both approaches could maximize training outcomes, particularly in resource-constrained environments, thus broadening access to advanced simulation education.

Background/Objectives: Hematopoietic stem cell transplantation (HSCT) in pediatric and young adult (YA) patients can lead to endotheliopathy, such as thrombotic microangiopathy (TMA), sinusoidal obstruction syndrome (SOS), and diffuse alveolar hemorrhage (DAH). Natriuretic peptides have been studied as markers of endotheliopathy and critical illness. We hypothesized that elevation in NT-proBNP was associated with development of endotheliopathy (DAH, SOS, or TMA) in the first 100 days following HSCT in pediatric and YA patients. Methods: IRB exempt status was obtained. This retrospective case-control study reviewed HSCT at our institution from 2016-2020. Cases were selected based on an endotheliopathy diagnosis in the first 100 days after HSCT. Cases were matched with controls. Baseline and near-event NT-proBNP levels were compared between cases and matched controls. Effect of NT-proBNP levels on developing endotheliopathy was estimated using conditional logistic regression. Results: Sixty-two patients were included (31 cases, 31 controls). Near-event NT-proBNP was significantly higher in cases compared to controls (Median: 473 vs. 187 pg/mL, p = 0.03, Wilcoxon rank-sum test), in contrast to comparison in baseline NT-proBNP (Median: 86 vs. 86 pg/mL, p = 0.51). After adjusting for co-variates, association between near-event NT-proBNP and odds of developing endotheliopathy did not achieve statistical significance. However, trends from most common transplant indications suggested an association between elevated near-event NT-proBNP level and endotheliopathy, particularly in acute lymphoblastic leukemia (ALL) patients. Conclusions: NT-proBNP should be studied further as a biomarker for endotheliopathy in pediatric and YA patients undergoing HSCT. This may be particularly relevant for patients undergoing HSCT for ALL.

In the following article, we estimate the Renunciation of Healthcare Services-RHS in Italian regions in the context of the Environmental, Social and Governance-ESG model during the period 2004-2022. The data were acquired from the ISTAT-BES dataset. The data were analyzed using the following econometric techniques: Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled Ordinary Least Squares-OLS, Weighted Least Square-WLS,. Results show that RHS tends to growth with the E-Component, is negatively associated to the S-Component, and positively associate with the G-Component within the ESG model. Furthermore, a clusterization with the unsupervised k-Means algorithm is presented and the results are discussed with a confrontation between optimal and suboptimal k values optimized with the Silhouette Coefficient. Finally, a confrontation among eight different machine-learning algorithms is performed to predict the future value of RHS. Outcomes show that the Simple Regression Tree is the best predictive algorithm and that the level of RHS is predicted to growth on average of 4.4% for the Italian regions. Results are critically discussed.

Heel pain in the “funnel-shaped” space between the calcaneus, talus, and talocalcaneonavicular and subtalar joints may be representative of Sinus Tarsi syndrome. The pain is often characterized by a burning, numbness, or tingling sensation that can stem from strains and tears on the ligaments in that area. Injury treatment typically includes balance training, muscle exercises, bracing, foot orthosis, and non-steroidal anti-inflammatory drugs (NSAIDs). This study presents Wharton Jelly (WJ) tissue allografts as an alternative intervention for patients who fail standard-care treatments. WJ targets tissue defects, unlike other therapies, which aim to reduce swelling and symptomatic pain. This study includes five female patients who have previously failed standard-of-care treatment. Each received extracorporeal pulse-activated therapy (EPAT), WJ, laser therapy, and an orthotic. After an average of 80 days, the cohort had an overall 85.29% improvement in pain. The study's limitations include a small cohort size and a non-blinded design. Given the significant improvement in pain, WJ tissue allograft, combined with other techniques, presents an optimal patient care plan for tissue defects associated with Sinus Tarsi syndrome when standard-of-care treatments fail. These results provide evidence for a more extensive, randomized study to define dosage protocols further and confirm safety and efficacy.

In this article, we analyse the ESG determinants of the “Elderly People Treated in Integrated Home Care”-EPIHC in the Italian regions between 2004 and 2022. We used data from the ISTAT-BES database. We used different econometric techniques i.e.: Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS and Weighted Least Squares-WLS. The results show that the EPIHC is positively associated with “Nurses, midwives, and Soil sealing by artificial cover" and negatively associated with "Museum heritage density and relevance" and "Trust in law enforcement agencies and firefighters fire". Furthermore, we have applied a k-Means algorithm with the Silhouette Coefficient and we find the presence of two clusters. Finally, we propose a confrontation among eight different machine-learning algorithms and we find that Linear Regression is the best predictive algorithm.

In the following article, it is presented an investigation of the determinants of Beds for High-Care Specialties-BHCS in the Italian regions in the context of Environmental, Social and Governance-ESG approach. Data from ISTAT-BES for 20 countries in the period 2004-2021 are been used. Different econometric techniques have been applied i.e.: Pooled Ordinary Least Squares, Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel at 1 stage. Furthermore, a cluster analysis performed with a k-Means algorithm optimized with the Silhouette Coefficient indicated the presence of three clusters. Finally, eight different machine-learning algorithms are analysed to predict the future value of BHCS. The results show that the Artificial Neural Network-ANN algorithm is the best algorithm. The future value of BHSC is expected to growth on average of 4.88% for the analysed regions.

The following article presents an analysis of the impact of the Environmental, Social and Governance-ESG determinants on Hospital Emigration to Another Region-HEAR in the Italian regions in the period 2004-2021. The data are analysed using Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS, Weighted Least Squares-WLS, and Dynamic Panel at 1 Stage. Results show that HEAR is negatively associated to E, positively to S and negatively associated to the G within the ESG model. The data were subjected to clustering with a k-Means algorithm optimized with the Silhouette coefficient. The optimal clustering with k=2 is compared to the sub-optimal cluster with k=3. The results suggest a negative relationship between the resident population and hospital emigration at regional level. Finally, a prediction is proposed with machine learning algorithms classified based on statistical performance. The results show that the Artificial Neural Network-ANN algorithm is the best predictor. The ANN predictions are critically analyzed in light of health economic policy directions.

In the following article, we analyse the determinants of the number of physicians in the context of ISTAT BES-Benessere Equo Sostenibile data among twenty Italian regions in the period 2004-2022. We apply Panel Data with Random Effects, Panel Data with Fixed Effects, and Pooled OLS-Ordinary Least Squares. We found that the number of Physicians among Italian regions is positively associated, among others, to “Trust in the Police and Firefighters”, “Net Income Inequality”, and negatively associated, among others, to “Research and Development Intensity” and “Soil waterproofing by artificial cover”. Furthermore, we apply the k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of two clusters. Finally, we confront eight different machine-learning algorithms to predict the future value of physicians and we find that the PNN-Probabilistic Neural Network is the best predictive algorithm.

Abstract: Background: This research aims to investigate the oral health status and needs of individuals with disabilities, a vulnerable population that is facing barriers in accessing and maintaining oral care. Methods: Data for this study were obtained through self-administered questionnaires distributed to individuals with disabilities who were receiving assistance from Helping Restore Ability and Neuro Assistance Foundation. The data were analyzed using statistical methods using SPSS and Microsoft Excel to identify patterns and associations related to oral health maintenance among individuals with disabilities. Results: The findings of this research indicate a high prevalence of poor oral hygiene, periodontal diseases, and untreated dental caries, risk factors of oral cancer among individuals with disabilities. Social determinants were found to have a significant influence on the oral health status of this population. The study also highlights the crucial role of caregivers in ensuring oral health maintenance. Conclusion: The results of this study underscore the urgent need for targeted interventions and improved caregiver awareness to address the oral health needs of individuals with disabilities. By addressing the disparities and barriers faced by people with disabilities in accessing dental care, we can mitigate the health, social, and economic burdens associated with poor oral health in this vulnerable population.

Background: Globally, women’s responsibility for unpaid care work (UCW) remains a barrier to gender equality and women’s empowerment. Rwanda, a low-income country, has a legal and policy framework for promoting gender equality but remains a patriarchal society with women responsible for UCW. Reseaux des Femmes, a local NGO, has been delivering a programme targeted at reducing and redistributing the UCW of women with the objective of gender transformational change. However, there has been no impact evaluation of their intervention to date. Methods/Design: The impact evaluation will be a proof-of-concept critical realist cluster control trial (CRcCT) to evaluate for which women, how and under what circumstances the intervention reduces and redistributes women’s UCW, promote gender equality and women’s empowerment, and improves women’s quality of life. Four clusters of villages in each of five districts in Rwanda will be randomly allocated to the intervention or control arms, and all eligible households, those headed by a couple with at least one child under 12 years, will be recruited. This will yield a sample of around 550 intervention households and 550 control. Discussion: This protocol describes the design of mixed-methods research to evaluate an intervention in Rwanda aimed at reducing and redistributing the time women spend on UCW, thereby promoting gender equality and women’s empowerment. This paper will contribute to our understanding of interventions for transforming gender relations from a scholarly perspective. From a policy perspective, it will act as a proof of concept of Reseaux des Femmes’ Programme.

In Kenya, millions of children have limited access to nurturing care. With the COVID-19 pandemic, it is anticipated that vulnerable children will bear the biggest brunt of the direct and indirect impacts of the pandemic. This review aimed to deepen understanding of the effects of COVID-19 on nurturing care from conception to four years of age, a period where the care of children is often delivered through caregivers or other informal platforms. The review has drawn upon the empirical evidence from previous pandemics and epidemics, and anecdotal and emerging evidence from the ongoing COVID-19 crisis. Multifactorial impacts fall into five key domains: direct health; health and nutrition systems, economic, social and child protection, and child development and early learning. The review proposes program and policy strategies to guide the re-orientation of nurturing care, prevent the detrimental effects associated with deteriorating nurturing care environments, and support the optimal development of the youngest and most vulnerable children. These include the provision of cash transfers and essential supplies for vulnerable households, and strengthening of community-based platforms for nurturing care. Further research on COVID-19 and the ability of children’s ecology to provide nurturing care is needed, as is further testing of new ideas.

Explainable AI (XAI) has emerged as a pivotal tool in healthcare diagnostics, offering much-needed transparency and interpretability in complex AI models. XAI techniques, such as SHAP, Grad-CAM, and LIME, enable clinicians to understand AI-driven decisions, fostering greater trust and collaboration between human and machine in clinical settings. This review explores the key benefits of XAI in enhancing diagnostic accuracy, personalizing patient care, and ensuring compliance with regulatory standards. However, despite its advantages, XAI faces significant challenges, including balancing model accuracy with interpretability, scaling for real-time clinical use, and mitigating biases inherent in medical data. Ethical concerns, particularly surrounding fairness and accountability, are also discussed in relation to AI's growing role in healthcare. The review emphasizes the importance of developing hybrid models that combine high accuracy with improved interpretability and suggests that future research should focus on explainable-by-design systems, reducing computational costs, and addressing ethical issues. As AI continues to integrate into healthcare, XAI will play an essential role in ensuring that AI systems are transparent, accountable, and aligned with the ethical standards required in clinical practice.

This paper introduces the AltumView Sentinare smart activity sensor for senior care and patient monitoring. The sensor uses an AI chip and deep learning algorithms to monitor the activity of people, collect activity statistics, and notify caregivers when emergencies such as falls are detected. To protect privacy, only skeleton (stick figure) animations are transmitted instead of videos. The sensor is highly affordable, accessible, and versatile. It was a CES 2021 Innovation Award Honoree, and has been selected by Amazon as one of only three fall detection devices integrated into its Alexa Together urgent response service, and has received very positive reviews from Amazon customers. It has also been used in different senior care settings in about ten different countries. The paper presents the main features of the system, the evidences and lessons learned from its practical applications, and future directions.

Quality of life (QOL) is based on their perception of their position in life in respect to their goals, expectations, standards, and concerns, as well as their culture and value systems, their workflow and workplace situations while it influences quality of services. In this study we aim to report on dental and nursing academians’ QOL and well-being at the end of the third year of the COVID-19 pandemic. The World Health Organization Quality of Life-BREF Scale (WHOQOL-BREF) tool, recording Physical, Psychological, Social and Environmental dimensions of QOL, was used. The WHOQOL-BREF was modified on a spiritual, coaching/mentoring approach in a two-step designing and validated procedure. The modified SHQOL-BREF (Spiritual Healthcare version) designed for this study, was uploaded, and filled in online during April-June 2023. Staff (N=120, 75% female) of both departments of Dentistry (44.2%) and Nursing (55.8%) of the National and Kapodistrian university of Athens, participated in anonymity. QOL in terms of physical health was reported at a higher level (M=72.2 points) compared to social relationships (M=69 points), psychological health (M=65 points) and environment (M=59 points) (scores reported in 0-100 score). Overall QOL was rated at 66 points while satisfaction from health at 72 points. Job satisfaction (M1=3.2) and spirituality (M2=3.0) were reported at a medium level in a 5-point scale, while personal beliefs and values were reported at a high level (M3=4.0). Participants age presented a significant, moderate to strong effect on physical health [F(3,97)=2.89, p<.05, η2p=.08] and on environment [F(3,97)=2.80, p<.05, η2p=.08] and marital status on social relationships [F(1,97)=9.66, p<.05, η2p=.09]. Married participants reported consistently higher levels of QOL compared to single participants, for all age groups. Department had a significant moderate effect on social relationships (F(1,97)=5.10, p<.05, η2p=.05) and education a significant moderate to strong effect on psychological health (F(2,97)=3.74, p<.05, η2p=.07). PhD level participants in both departments presented higher levels of psychological health compared to lower educational levels. Also, participants from the department of Dentistry reported higher levels of social relationships QOL in all educational groups, compared to the department of Nursing. Strategic planning on sustainability and QOL initiatives should be introduced after the COVID-19 pandemic for dental and nursing academic personnel to promote resilience and QOL scores.

Our primary objectives were a) to determine the need for, and the availability of point-of-care testing (POCT) for infectious diseases and b) to recommend point-of-care testing strategies and spatial care paths (SCPs) that enhance public health preparedness in regional districts of Thua Thien Hue Province (TTHP), Central Vietnam, where we conducted field surveys. Medical professionals in 7 community health centers (CHCs), 7 district hospitals (DHs) and 1 provincial hospital (PH) participated. Survey questions (English and Vietnamese) determined the status of diagnostic testing capabilities for infectious diseases and other acute medical challenges in TTHP. Infectious disease testing was limited: 6 of 7 CHCs (86%) lacked infectious disease tests. One CHC (14%, 1/7) had two forms of diagnostic tests available for the detection of Malaria. All CHCs lacked adequate microbiology laboratories. District hospitals had few diagnostic tests for infectious diseases (Tuberculosis, Syphilis), blood culture (29%, 2/7), and pathogen culture (57%, 4/7) available. The PH had broader diagnostic testing capabilities but lacked preparedness for highly infectious disease threats (e.g., Ebola, MERS-CoV, SARS, Zika, and Monkeypox). All sites reported having COVID-19 rapid antigen tests; COVID-19 RT-PCR tests were limited to higher tier hospitals. We conclude that infectious disease diagnostic testing should be improved and POC tests must be supplied near patients’ homes and in primary care settings for the early detection of infected individuals and mitigation of the spread of new COVID-19 variants and other highly infectious diseases.

Determination of the presence in the blood of antibodies specific to the causative agent of a particular disease (serodiagnosis) is an effective approach in medical analytical chemistry. Serodiagnostics performed in the lateral flow immunoassay format (immunochromatography) meet the modern requirements for point-of-care testing and are supported by existing technologies of large-scale diagnostic tests production—thus raising increased attention in a tense epidemiological situation. For traditional lateral flow serodiagnostics formats, a large number of nonspecific immunoglobulins in the sample significantly reduces the degree of detectable binding. To overcome these limitations, an assay based on the formation of immobilized antigen— specific antibody—labeled antigen complexes detection was proposed. However, the requirements for its implementation, providing maximum sensitivity, have not been established. This article describes the mathematical model for the above assay. The influence of the ratio of reagent concentrations on the analysis results is considered. It is noted that the formation of specific antibody complexes with several labeled antigens is the main limiting factor in reducing the detection limit, and methods are proposed to minimize this factor. Recommendations for the choice of the assay conditions, following from the analysis of the model, are confirmed experimentally.

Individuals with low health literacy (HL) are known to have poorer health outcomes and to have higher mortality rates compared to individuals with higher HL: hence, the improvement of HL is a key outcome in modern healthcare systems. Healthcare providers are therefore asked to support patients’ literacy skills by encouraging the implementation of autonomy-supportive patient centered communication (PCC), which in turn requires the enhancement of patient engagement. Our main hypothesis is that the well-known relationship between autonomy-supportive PCC and HL is mediated by patient engagement which is known to play a role in HL promotion and that is related to PCC as well. The purpose of this study was to formulate a hypothetical structural equation model (SEM) linking PCC to patient engagement and HL. A cross-sectional survey design was employed involving 1007 Italian chronic patients. The hypothetical model was tested using SEM to verify the hypothesized mediation of patient engagement between PCC and HL. Results show that the theoretical model has a good fit indexes and that patient engagement fully mediates the relationship between PCC and HL. This finding suggests healthcare systems to implement a new paradigm where patients are supported to play an autonomous role in their own healthcare.

Despite available global efforts and funding, Tuberculosis (TB) continues to affect a considerable number of patients worldwide. Policy makers and stakeholders set clear goals to reduce TB incidence and mortality, but the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) complicate the reach of these goals. Drug-resistance TB needs to be diagnosed rapidly and accurately to effectively treat patients, prevent the transmission of MDR-TB, minimise mortality, reduce treatment costs and avoid unnecessary hospitalisations. In this narrative review, we provide a comprehensive overview of laboratory methods for detecting drug resistance in MTB, focusing on phenotypic, molecular and other drug susceptibility testing (DST) techniques. We found a large variety of methods used, with the BACTEC MGIT 960 being the most common phenotypic DST and the Xpert MTB/RIF being the most common molecular DST. We emphasise the importance of integrating phenotypic and molecular DST to address issues like resistance to new drugs, heteroresistance, mixed infections and low-level resistance mutations. Notably, most of the analysed studies adhered to the outdated definition of XDR-TB and did not consider the pre-XDR definition, thus posing challenges in aligning diagnostic methods with the current landscape of TB resistance.

There is significant need for development of a new environmentally friendly, extraction-free sample collection medium that can effectively preserve and protect genetic material for point-of-care, and/or self-collection, home-collection, and mail-back testing. Systematic Evolution of Ligands by Exponential Enrichment (SELEX) was used to create anti-ribonuclease (RNase) Deoxyribonucleic acid (DNA) aptamers against purified RNase A conjugated to paramagnetic carboxylated beads. Following 8 rounds of SELEX carried out under various stringency conditions, e.g., selection using Xtract-Free™ (XF) specimen collection medium, and elevated ambient temperature of 28 ºC, a panel of 5 aptamers was chosen following bioinformatic analysis using next-generation sequencing. The efficacy of aptamer inactivation of RNase was assessed by monitoring Ribonucleic acid (RNA) integrity by fluorometric and real-time RT-PCR analysis. Inclusion of aptamers in reaction incubations resulted in an 8,800 to 11,200-fold reduction of RNase activity, i.e., digestion of viral RNA compared to control. Thus, anti-RNase aptamers integrated into XF collection medium as well as other commercial reagents and kits have great potential for ensuring quality intact RNA for subsequent genomic analysis.

Goals: To use visual logistics for interpreting COVID-19 molecular and rapid antigen test (RAgT) performance, determine prevalence boundaries where risk exceeds expectations, and evaluate benefits of recursive testing along home, community, and emergency spatial care paths. Methods: Mathematica/open access software helped graph relationships, compare performance patterns, and perform recursive computations. Results: Tiered sensitivity/specificity comprise: T1) 90%/95%; T2) 95%/97.5%; and T3) 100%/≥99%, respectively. In emergency medicine, median RAgT performance peaks at 13.2% prevalence, then falls below T1, generating risky prevalence boundaries. RAgTs in pediatric ERs/EDs parallel this pattern with asymptomatic worse than symptomatic performance. In communities, RAgTs display large uncertainty with median prevalence boundary of 14.8% for 1/20 missed diagnoses, and at prevalence >33.3-36.9% risk 10% false omissions for symptomatic subjects. Recursive testing improves home RAgT performance. Home molecular tests elevate performance above T1, but lack adequate validation. Conclusions: Widespread RAgT availability encourages self-testing. Asymptomatic RAgT and PCR-based saliva testing present the highest chance of missed diagnoses. Home testing twice, once just before mingling, and molecular-based self-testing help avoid false omissions. Community and ER/ED RAgTs can identify contagiousness in low prevalence (<22%). Real-world trials of performance, cost-effectiveness, and public health impact could identify home molecular diagnostics as the optimal diagnostic portal.

Haematopoietic stem cell transplantation (HSCT) is a curative approach for blood cancers, yet its efficacy is undermined by a range of acute and chronic complications. In light of mounting evidence to suggest that these complications are linked to a dysbiotic gut microbiome, we aimed to evaluate the feasibility of faecal microbiota transplantation (FMT) delivered during the acute phase after HSCT. Of note, this trial opted for FMT prepared using the individual’s own stool (autologous FMT) to mitigate risks of disease transmission from donor stool. Adults (>18 years) with multiple myeloma were recruited from a single centre. Stool was collected prior to starting first-line therapy. Patients that progressed to HSCT were offered FMT via 3 x re-tention enemas before day +5 (HSCT = day 0). Feasibility was determined by recruitment rate, number and volume of enemas administered, and retention time. Longitudinally collected stool samples were also col-lected to explore the influence of auto-FMT using 16S rRNA gene sequencing. N=4 (2F:2M) participants received auto-FMT in 12 months. Participants received an average of 2.25(1-3) enemas (43.67(25-50)mL total, retained for an average of 60.78(10-145)minutes). No AEs, attributed to the FMT, were identified. Although minimum requirements were met for the volume and retention of auto-FMT, recruitment was significantly impacted by the logistical challenges of pre-therapy stool collection. This ultimately under-mined the feasibility of this trial and suggests that third party (donor) FMT should be prioritised.

Background: Recently, the management of musculoskeletal disorders with the patients' own stem cells, isolated from the walls of small blood vessels, which can be found in great numbers in the adipose tissue, has received considerable attention. On the other hand, there are still misconceptions about these adipose-derived regenerative cells (ADRCs) that contain vascular-associated pluripotent stem cells (vaPS cells) in regenerative medicine. Methods: Based on our previous publications on this topic, we have developed a concept to describe the significance of the ADRCs/vaPS cells in the field of orthobiologics as briefly as possible and at the same time as precisely as possible. Results: The ADRCs/vaPS cells belong to the group of orthobiologics that are based on autologous cells. Because the latter can both stimulate a patient’s body's localized self-healing power and provide new cells that can integrate into the host tissue during the healing response when the localized self-healing power is exhausted, this group of orthobiologics appears more advantageous than cell-free orthobiologics and orthobiologics that are based on allogeneic cells. Within the group of orthobiologics that are based on autologous cells, enzymatically isolated, uncultured ADRCs/vaPS cells have several advantages over non-enzymatically isolated cells/microfragmented fat as well as over uncultured bone marrow aspirate concentrate and cultured cells (adipose-derived stem cells, bone marrow-derived mesenchymal stem cells). Conclusions: The use of ADRCs/vaPS cells can be seamlessly integrated into modern orthopedic treatment concepts, which can be understood as the optimization of a process which - albeit less efficiently - also takes place physiologically. Accordingly, this new safe and effective type of treatment is attractive in terms of holistic thinking and personalized medicine.

The survival analysis of the Cancer Genome Atlas (TCGA) dataset is a well-known method to discover the gene expression-based prognostic biomarkers of head and neck squamous cell carcinoma (HNSCC). A cutoff point is usually used in survival analysis for the patients' dichotomization in the continuous gene expression. There is some optimization software for cutoff determination. However, the software's predetermined cutoffs are usually set at the median or quantiles of gene expression value to perform the analyses. There are also few clinicopathological features available on their pre-processed data sets. We applied an in-house workflow, including data retrieving and pre-processing, feature selection, sliding-window cutoff selection, Kaplan-Meier survival analysis, and Cox proportional hazard modeling for biomarker discovery. In our approach for the TCGA HNSCC cohort, we scanned human protein-coding genes to find optimal cutoff values. After adjustment with confounders, the clinical tumor stage and the surgical margin involvement are independent risk factors for patients' prognosis. According to the resulting tables with Bonferroni-adjusted P value under the optimal cutoff and the hazard ratio, three biomarker candidates, CAMK2N1, CALML5, and FCGBP, are significantly associated with the patients' overall survival. We validated this discovery by using the other independent HNSCC dataset (GSE65858). Thus, we suggest the transcriptomic analysis could help for biomarker discovery.

Abstract: A prevalence boundary (PB) marks the point in prevalence where the false omission rate, RFO=FN/(TN+FN), exceeds the tolerance limit for missed diagnoses. Objectives were to mathematically analyze rapid antigen test (RAgT) performance, determine why PBs are breeched, and evaluate the merits of testing three times over five days, now required by the US Food and Drug Administration for asymptomatic persons. Equations were derived to compare test performance patterns, calculate PBs, and perform recursive computations. An independent July 2023 FDA-university-commercial evaluation of RAgTs provided performance data used in theoretical calculations. Tiered sensitivity/specificity comprise: Tier-1) 90%, 95%; Tier-2) 95%, 97.5%; and Tier-3) 100%, ≥99%, respectively. Repeating a T2 test improves the PB from 44.6% to 95.2% (RFO 5%). In the FDA-university-commercial evaluation, RAgTs generated sensitivity of 34.4%, which improved to 55.3% when repeated, then 68.5% with the third test. With RFO=5%, PBs were 7.37/10.46/14.22%, respectively. PB analysis suggests RAgTs should achieve clinically proven sensitivity of 91.0-91.4%. When prevalence exceeds PBs, missed diagnoses can perpetuate virus transmission. Repeating low-sensitivity RAgTs delays diagnosis. In homes, high-risk settings, and hotspots, PB breaches may prolong contagion, defeat mitigation, facilitate new variants, and transform outbreaks into endemic disease. Molecular diagnostics can help avoid these potential vicious cycles

Type 1 diabetes affects millions of people globally and requires careful management to avoid serious long-term complications, including heart and kidney disease, stroke, and loss of sight. The present standard-of-care for type 1 diabetes is exogenic insulin substitutional therapy. The most advanced stretegies in this area is the development of hybrid-closed loop system and the producing of long-acting insulins. Progresses in stem cell therapies have started to revolutionize the care of patients with type 1 diabetes; however, significant challenges remain including the limited islets availability, difficulties in maintaining the viability, the heterogeneity within a complex pathology and in patients’ responses to treatment. On the way, a considerable amount of efforts in maximizing the islet transplantation effectiveness by controlling the advantageous of different stem cell approaches. With the availability and the use of big data, the concept of precision medicine is gaining wide attention worldwide and could bring the dream of “presonlaized” therapies as a reality in the near future. Here we review the current range of treatments available as well as recent pre-clinical breakthroughs in the field of personlaized medicine for type 1 diabetes.

This article describes the use of the PI ProcessBook software tool for visualization and indirect monitoring of occupancy of SHC rooms from the measured operational and technical quantities for monitoring of daily living activities for support of independent life of elderly persons. The proposed method for data processing (predicting the CO₂ course using neural networks from the measured temperature indoor T_i (°C), temperature outdoor T_o (°C) and the relative humidity indoor rHi (%)) was implemented, verified and compared in MATLAB SW tool and IBM SPSS SW tool with IoT platform connectivity. Within the proposed method, the Stationary Wavelet Transform de noising algorithm was used to remove the noise of the resulting predicted course. In order to verify the method, two long-term experiments were performed, (specifically from February 8 to February 15, 2015, from June 8 to June 15, 2015) and two short-term experiments (from February 8, 2015 and from June 8, 2015). For the best results of the trained ANN BRM within the prediction of CO₂, the correlation coefficient R for the proposed method was up to 90%. The verification of the proposed method confirmed the possibility to use the presence of persons of the monitored SHC premises for rooms ADL monitoring.

The SARS-CoV-2 virus that causes the COVID-19 disease has wreaked havoc on the world community in terms of every imaginable parameter. The research output on COVID-19 has been nothing short of phenomenal, especially in the medical and biomedical sciences, where the search for a potential vaccine is being conducted in earnest. Much of the advanced research has been distributed in the leading medical journals, including the Journal of the American Medical Association (JAMA), where the latest research is distributed on a daily basis. The purpose of this paper is to provide some perspectives on 44 interesting and highly topical research papers that have been published in JAMA, at the time of writing, within the past two weeks. The diverse topics include public health, general medicine, internal medicine, oncology, paediatrics, geriatrics, and biostatistics.