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The international incidence associated with key despression symptoms (MDD) among the aging adults: A systematic assessment as well as meta-analysis.
The data produced during a research project are too often collected for the sole purpose of the study, therefore hindering profitable reuse in similar contexts. The growing need to counteract this trend has recently led to the formalization of the FAIR principles that aim to make (meta)data Findable, Accessible, Interoperable and Reusable, for humans and machines. Since their introduction, efforts are ongoing to encourage FAIR principles adoption and to implement solutions based on them. This paper reports on the FAIR-compliant registry we developed to collect and serve metadata describing clinical trials. The design of the registry is based on the FAIR Data Point (FDP) specifications, the state-of-the-art reference for FAIRified metadata sharing. To map the metadata relevant to our use case, we have extended the DCAT-based semantic model of the FDP adopting well-established ontologies in the biomedical and clinical domain, like the Semanticscience Integrated Ontology (SIO). Current implementation is based on the Molgenis software and provides both a user interface and a REST API for metadata discovering. At present the registry is being loaded with the metadata of the 18 clinical studies included in the 'I FAIR Program', a project finalised to the dissemination of FAIR best practices among the clinical researchers in Sardinia (Italy). After a testing phase, the registry will be publicly available, while the new model and the source code will be released open source.Bacterial meningitis is one of the harmful and deadly infectious diseases, and any delay in its treatment will lead to death. In this paper, a prognostic model was developed to predict the risk of death amongst probable cases of bacterial meningitis. Our prognostic model was developed using a decision tree algorithm on the national meningitis registry of the Iranian Center for Disease and Prevention (ICDCP) containing 3,923 records of meningitis suspected cases in 2018-2019. The most important features have been selected for the model construction. This model can predict the mortality risk for the meningitis probable cases with 78% accuracy, 84% sensitivity, and 73% specificity. The identified variables in prognosis the death included age and CSF protein level. CSF protein level (mg/dl) 137 (mg/dl), the mortality risk was 60%. The prognostic factors identified in the present study draw the attention of clinicians to provide early specific measures, such as the admission of patients with a higher risk of death to intensive care units (ICU). It could also provide a helpful risk score tool in decision-making in the early phases of admission in pandemics, decrease mortality rate and improve public health operations efficiently in infectious diseases.The main challenge in the pathway analysis of cancer treatments is the complexity of the process. Process mining is one of the approaches that can be used to visualize and analyze these complex pathways. In this study, our purpose was to use process mining to explore variations in the treatment pathways of endometrial cancer. We extracted patient data from a hospital information system, created the process model, and analyzed the variations of the 62-day pathway from a General Practitioner referral to the first treatment in the hospital. We also analyzed the variations based on three different criteria the type of the first treatment, the age at diagnosis, and the year of diagnosis. This approach should be of interest to others dealing with complex medical and healthcare processes.In response to epidemics and pandemics, access to authentic sources of information plays a critical role in informing public health practices. However, infodemic, i.e., an overabundance of health information, misinformation, and disinformation, impede implementing best public health policies during a public health crisis such as COVID-19. In this bibliometric study, we aim to report on concept mapping of infodemic literature, and in line with the World Health Organization (WHO)'s repeated calls for actions in managing infodemic, we highlight fruitful avenues for future directions. Through a visualization approach on a set of 414 records, a concept mapping was carried out. This map revealed 42 infodemic-related nodes in five clusters. We also propose an infodemic research platform in which a combination of the research nodes (e.g., COVID, pandemic, disinformation, fake news, post-truth, fact-checking, social networks, Facebook, WhatsApp, and lockdown) with impactful questions suggest future directions.The effect of the 2020 pandemic, and of the national measures introduced to control it, is not yet fully understood. The aim of this study was to investigate how different types of primary care data can help quantify the effect of the coronavirus disease (COVID-19) crisis on mental health. A retrospective cohort study investigated changes in weekly counts of mental health consultations and prescriptions. The data were extracted from one the UK's largest primary care databases between January 1st 2015 and October 31st 2020 (end of follow-up). The 2020 trends were compared to the 2015-19 average with 95% confidence intervals using longitudinal plots and analysis of covariance (ANCOVA). A total number of 504 practices (7,057,447 patients) contributed data. During the period of national restrictions, on average, there were 31% (3957 ± 269, p less then 0.001) fewer events and 6% (4878 ± 1108, p less then 0.001) more prescriptions per week as compared to the 2015-19 average. The number of events was recovering, increasing by 75 (± 29, p = 0.012) per week. Prescriptions returned to the 2015-19 levels by the end of the study (p = 0.854). The significant reduction in the number of consultations represents part of the crisis. selleck kinase inhibitor Future service planning and quality improvements are needed to reduce the negative effect on health and healthcare.The term e-health refers to all areas where information and communication technologies (ICT) are used for health. E-health appears more and more as a relevant solution to meet the challenges health systems are facing. However, despite its interest, e-health has long remained underexploited in Burkina Faso even if many softwares have been the subject of investments in hospitals as part of a modernization of administrative operations, which does not directly contribute to the quality of care. Hospital information systems (HIS) are the foundation on which e-health is based. They organize, at the IT level, the exchange of information between departments within the same hospital. It is on those systems that the shared medical record (SMR) is based. In this paper, we present an inventory of the implementation of e-health in Burkina Faso. We collected data on hospital information systems deployed in major hospitals in Burkina Faso. Then we analyzed the level of interoperability of those hospital information systems and we finally proposed an interoperability approach adapted to Burkina Faso.3D printing is applicable in various fields. The purpose of this study was to explore the knowledge and perceptions of undergraduate and postgraduate nursing students in relation to the use of 3D printing. A questionnaire was developed including questions about demographics, the students' knowledge about, and the student's attitude towards the 3D printing technology. Descriptive statistics and correlations were examined. link2 The average knowledge score was 2.6 out of 6 and the perception score was 7.7 out of 10. Only gender was found to be related with 3D printing knowledge. Gender, age, and educational level were related with students' attitude towards 3D printing.Citizens of the Netherlands receive excellent care, when they need it, insurance based funded according to the solidarity principle. Maintaining this system is a huge challenge, as we live longer and the demand for care is growing. With an increasing percentage of multi-morbidity in all age groups the need for integrated network organized care is growing at equal pace. Gradually the need to shift focus to prevention is increasingly understood, but a challenging business model is still lacking. The involvement of citizens in maintaining their health requires a focus on managing the social determinants of health. The concept of the holistic problem list and the overarching care plan provides a unique way to combine both health and disease management. Our vision is to bring control to the patient and promote coordination of all active problems across the health and social care network.Medical emergencies involving children are rare events. The experience of emergency physicians is therefore low and the results are correspondingly poor. Assistance services to help in emergencies are regularly requested. The use case is thus very complicated, a complex system consisting of multiple devices is necessary to provide the most efficient and effective service. This short paper presents prototypically tested ideas on how such a ubiquitous approach can be designed and how communication between devices can be simplified and ensured.This paper presents the results of a new approach to discover related health and social factors during the COVID-19 pandemic. The approach leverages a knowledge graph of related concepts mined from a corpus of published evidence (PubMed) prior to the pandemic. Population trends from online searches were used to identify social determinants of health (SDoH) concepts that trended high at the outset of the pandemic from a list of SDoH topics from the World Health Organization (WHO). The trending concepts were then mapped to the knowledge graph and a subsequent analysis of the derived insights, spanning two years, was conducted. This paper suggests an approach to derive new related health and social factors that may have either played a role in, or been affected by, the onset of the global COVID-19 pandemic. In particular, our results show how, from a list of SDoH topics, Food Security, Unemployment trended the highest at the start of the pandemic. Further work is needed to continue to ascertain the validity of the derived relations in a population health context and to improve mining insights from published evidence.In Finland, it is possible to quickly produce medical symptom self-assessment tools within the existing infrastructure. The Finnish Omaolo Covid-19 web-based symptom self-assessment tool (symptom checker) was launched on March 16, 2020 after a 6-day development period. By using the web-based Omaolo Covid-19 symptom checker during the second wave of the epidemic, some 1.72 million questionnaires were recorded, out of which 1.55 million from symptomatic persons. Some 15% of the responses (245,500) were directed to seek emergency medical care based on the online screening by respondent response profiles.The paper analyzes the evolution of COVID-19 cases in Romanian counties over a period of 10 months, to highlight possible similarities that may contribute to a better understanding of the spreading pattern. The study uses the numbers of active cases for each county in Romania, as well as Bucharest and the whole country, reported daily by the Romanian Ministry of Health (https//datelazi.ro) between April 2nd, 2020 and January 25th, 2021. We compared the disease's evolution in Suceava county (the first outbreak of spread) with other counties in Romania in order to highlight the gaps between them. We calculated the cross-correlations between counties, interpreted as time series. link3 The recorded lags varied between 1-15 days, the most counties having a lag of 6-7 days compared with Suceava. Therefore, on long term there are no important discrepancies between the regions in Romania regarding the evolution of the disease, which shows that the intervention efforts of the medical staff were uniform in efficiency. The existence of a lag of only one day between Suceava and the whole country shows that on long term, even in this county the situation is not very discrepant, belonging to the general evolution.
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