Health professionals are the base of the healthcare systems in all societies. Their daily contact with the patient in a context of demanding and difficult working conditions affect their general health. This research was carried out to describe the levels of general health among health professionals and their perceived levels of fatigue and social support. Additionally, the purpose of this study was to examine the above three variables in relation to demographic (education, gender) and employment factors (working hours, department). The research was conducted in 165 health professionals working in hospitals in the region of Eastern Macedonia-Thrace and in the urban centers of Athens and Thessaloniki. The General Health Questionnaire (GHQ-28), the Fatigue Assessment Scale (FAS) as well as the Multidimensional Scale of Perceived Social Support (MSPSS) were used to measure the research variables. The processing and statistical analysis of the data was done using IBM SPSS. The majority of health professionals presented a high score in GHQ-28 subscales indicating low general health (avg 8.59≥5). One hundred thirty nine out of 165 health professionals (84%) were tired and 15 out of 165 (9%) were too tired. The perceived social support was at high levels (avg 5.57). Health professionals exhibit high fatigue and low levels of general health and quality of life. Instead, they receive high social support. Existence of circular hours and work in heavy part worsens the levels of fatigue and quality of life. Measures are needed to increase the number of health professionals and organizational and structural measures to improve their working conditions and strengthen their social work.Full article

Parental anxiety and depression are factors that significantly affect the practice of parental role and have an impact on the upbringing of children and their quality of life. The purpose of this study is to investigate whether the counseling intervention that parents received during their participation in parent school programs reduced stress and depressive symptoms and improved their quality of life. A sample of 160 parents was collected from two independent groups: the experimental group consisting of 80 parents who participated in the program and the control group consisting of parents who after being informed about the implementation of the programs in their schools decided not to participate. The psychometric tools have been used are: The Spielberger Stress Trait Anxiety Inventory (STAI), the Beck depression Inventory (BDI), and the Health and well-being Questionnaire (The RAND 36-Item Healthy Survey, SF-36, Version 1.0). The results of the research confirmed the research hypothesis according to which the effect of the counseling intervention on the parents who participated in the parent schools affected the reduction of the stress index, state anxiety (Ζ=-2,882, p=0,004) and trait anxiety (Ζ=-3,776, p<0,001), the reduction of the depression index (Ζ=-6,876, p<0,001) and the improvement of their quality of life(Ζ=-5,364, p<0,001) ) especially of physical health (Ζ=-4,529, p<0,001) and emotional health (Ζ=-4,529, p<0,001).Full article

The deleterious health effects of ethanol abuse are widely known and a diversity of medical conditions appear with excessive consumption. Acute and chronic abuse have different clinical characteristics, although severe intoxications are rare among alcoholics of a long career, where the systemic complications will dominate the symptomatology. While the medical focus acutely will mostly stay on the nervous and circulatory effects, gastrointestinal complications that will come up chronically (liver, pancreas, bowel dysfunction) need proper consideration. Ethanol will affect gastrointestinal functionality through a triple action, directly on the epithelial cell and the secretory activity, by altering the motility and in the long-term scope, through promoting carcinogenesis. Medical teams dealing with acute and chronic ethanol intoxication or abuse must be aware of the multiple effects it shows, and perform a prompt diagnosis as well as appropriate intervention.Full article

We reviewed the influence of coronavirus disease 2019 (COVID-19) on the central nervous system reported in the literature since its prevalence. Common neurological symptoms of COVID-19 include altered or impaired consciousness, headache, dizziness, cerebrovascular accidents, and seizures, etc. Encephalopathy caused by or related to COVID-19 includes stroke, acute encephalitis, and Guillain-Barre syndrome. Concomitant COVID-19 in patients with vascular risk factors increased the risk of stroke; the hypercoagulable state and vascular dysfunction caused by COVID-19 also led to stroke. Acute encephalitis was usually accompanied by a history of headache, fever, and altered mental status, and shown hemorrhagic lesions or high signal on MRI. In Guillain-Barre syndrome, there was a time lag between infection with the primary pathogen and the onset of neurological symptoms, which generally manifest as limb paralysis and various sensory abnormalities. The review illustrated that COVID-19 lead to serious consequences of brain and brought difficulties to the treatment. Exploring the neural mechanisms of COVID-19 to better understand the activity of the virus in the brain and to prevent further viral damage to the brain is an urgent issue.Full article

Objectives: There remains no consensus management for isolated distal deep vein thrombosis (IDDVT), with current data inconclusive and dating back to the warfarin era. In the current direct oral anticoagulant (DOAC) era, optimal management of IDDVT needs to be re-assessed. Methods: A retrospective evaluation of patients treated with therapeutic anticoagulation for IDDVT in the DOAC era (2013-2016) was compared with historically published data from the warfarin era (2011-2012). Results: 247 patients were evaluated, 103 from the DOAC era and 122 from the warfarin era. There were less provoked events in the DOAC cohort (45.6% vs 66.7%, p=<0.01). Overall rate of major bleeding was 1.6% with 1.0% in the DOAC era and 2.1% in the warfarin era (p=0.50). There was no difference in rates of VTE progression on treatment 5.8% vs 4.9% respectively (p=0.91). Overall risk of VTE recurrence post cessation was 5.3% (1.86 per 100 person years) with no difference between groups (5.8% vs 4.9%, p=0.74). Conclusions: Our data shows IDDVT is not always benign, with risk of extension despite treatment and long-term risk of VTE-recurrence. Therapeutic anticoagulation with DOAC in these patients was associated with a major bleeding rate of 1.0% in the DOAC cohort. Further clinical trials into the optimal IDDVT management in the DOAC era are necessary.Full article

This work details how the integration of cloud computing and advanced data engineering can innovate and reshape patient care and digital infrastructure. In the healthcare sector, cloud services offer the necessary support to generate digitally-oriented services and service kits. These services can contain high levels of availability, low levels of latency, and on-demand scaling capabilities, while following the strictest data protection laws and regulations. On the other hand, these services can be combined with data engineering techniques to construct an ecosystem that enhances and adds an optimized data layer on any cloud environment. This ecosystem includes technologies to acquire, process, and manage healthcare data while respecting all regulatory obligations and institutions and can be part of a comprehensive digitalization strategy. The objective is to augment the healthcare services that the industry offers by leveraging healthcare data and AI technologies. Designed services, processes, and technologies can be described either as industry-agnostic services or healthcare-specific services that process and manage electronic healthcare records (EHR). Industry-agnostic services offer a set of tools and methodologies to conduct optimized data experiments. The goal is to exploit any variety, velocity, volume, and veracity of medical data. Healthcare-specific services offer a set of tools and methodologies to connect to any common EHR vendor in a privacy-preserving manner. Participating companies are thus able to hold, share, and make use of healthcare data in real-time. The proposed architecture can be transformative for the healthcare industry, opening up and facilitating experimentation on new and scalable service models. The transition to a more digital health approach would help overcome the limits encountered in traditional settings. Limitations in the availability of healthcare facilities and healthcare professionals have underpinned the increasing share of telemedicine in the care process. However, the record-keeping of the patients that undergo care outside of traditional healthcare facilities is often missing and can severely influence the continuity of treatment. Identifying new methods to implement disease prevention and early intervention processes is crucial to avoid more extensive treatment and to support those on multiple line therapies. For chronic patients, having a service available that monitors the state of health and intervenes when parameters go off the wanted range is crucial. However, the same patients are the most under the influence of the decision of care providers; a second opinion might be given remotely which the patient can access at any time on-demand. To address these different kinds of services, an ecosystem composed of a dictionary's worth data layer is outlined, able to live and operate seamlessly in any cloud environment. This future work's envisioned outcome is the rapid evolution and re-definition of the European healthcare landscape.Full article

Scalable architecture principles for data warehousing are introduced to support population health management and predictive analytics. These principles are validated through the design of an accompanying Data Pipeline that allows the integration of non-traditional data sources, the use of real-time data for descriptive analytics dashboards, and support for the generation of supervised Machine Learning models. Several analytical capabilities have been implemented to exemplify the practical application of the principles, including predictive models for Risk Stratification in health care. Optimal cost-effectiveness and performance considerations ensure the practical relevance of the architectural principles and associated Data Pipeline. In recent years, the availability of Low-Cost Data Storage services and the increasing popularity of Streaming technologies opened new possibilities for the storage and processing of Streaming data on a near-real-time basis. These technologies can help Developing Countries in tackling many relevant issues such as Urban Planning, Environmental Management, Migration Policies, etc. A multi-tier approach combining Cloud-based Storage with Data Warehousing and Data Mining technologies can offer an interesting architecture to exploit Big Data related to populations.Full article

Healthcare is increasingly recognized as a data-intensive industry. Multi-hospital networks, among other organizations, face mounting operational and governance challenges because of rigid data-integration pipelines that support all data sources and destinations in the network. These pipelines have become difficult to modify, causing them to lag behind the changing needs of the clinical operation. Scalable data-pipeline architectures better support clinical decision making, optimize hospital operations, ease data quality and compliance concerns, and contribute to improved patient outcomes. Meeting scalability goals requires breaking up monolithic data-integration pipelines into smaller decoupled components and aligning service-level agreements of pipeline components and source systems. Parallelization and adoption of distributed data-warehouse technology mitigate the burden of ingesting data into a multi-hospital network. However, latency requirements still warrant the construction of separate pipelines for data ingress from clinical devices, electronic health records, and external laboratory-information systems. Healthcare associations recommend near real-time data availability for a growing list of clinical and operational applications. Mishandling the real-time ingestion of data from clinical devices, in particular, compromises availability and performance. Scalable architectural patterns for real-time streaming Ingestion from heterogeneous data sources, transport processes, and back-end processing structures are detailed.Full article