Introduction: The spread of SARS-CoV-2 cases grew exponentially. In Mexico, it focused mainly on containing the disease and adopting activities and actions to mitigate it. Hospital reconversion was a fundamental strategy in the management of care for patients with COVID-19.Objective: To know the clinical characteristics of patients admitted with respiratory disease and probable COVID-19 in the Zacatecas General Hospital “Luz González Cosío” México.Material and methods: Descriptive, cross-sectional, and analytical study, at the General Hospital, from March 2019 to September 2021; using data from the Respiratory Disease Surveillance System. Data from patients admitted with a diagnosis of some pathology of respiratory disease and probable COVID-19 were analyzed.Results: We included 2,678 diagnosed with respiratory disease and a mean age; of 47.6 ± 21.6 gender distribution was almost equal; women 1,344 (51.0%). positive result to COVID-19 by PCR; 1,654 negatives; 900 and 124 without result. 193 (7.0%) required mechanical ventilation. The presence of comorbidities was evaluated; type 2 diabetes mellitus, systemic arterial hypertension, obesity, alone and together. Also the association of the age factor, as well as the lethality index; was 531 (19.6%).Discussion: What has been published in other studies about comorbidities and their influence on the severity of COVID-19 is confirmed, disagreeing on the case fatality rate; 20.7% against what was reported; 17.6% in other countries for COVID-19 hospitalized. An age variable was used as a risk factor with a cut-off point > 45 years; (FRE), obtaining; RR 3.42 (95% CI 2.79 to 4.19) and an odds ratio of 4.015 in binary logistic regression analysis. Reported male mortality (OR = 1.45; 95% CI: 1.41–1.51) according to our OR results; 1,45.Conclusion: The present study shows how certain chronic diseases influenced respiratory disease to present a serious state, regardless of the positive or negative result of COVID-19.

Introduction: Severe cases of COVID-19 presented a high incidence of multi-organ dysfunction syndrome (MODS) during their evolution. This was attributed to a theoretical cytokine storm, where microcirculatory disorders would play a fundamental role, causing these patients to present a sepsis-like pattern as observed in sublingual microcirculation studies. The evidence in this regard is controversial. The Peripheral Perfusion Index is a reliable method to continuously and non-invasively assess the microcirculatory bed, which assesses the pulsatile (PPI) component of the plethysmographic pulse curve.Methods: We conducted a prospective observational study to evaluate the behavior of the PPI in patients with severe respiratory failure due to SARS-CoV-2 and its association with SDOM.Results: We evaluated 60 patients with APACHE II 14.6 ± 4.4 and SOFA 4.7 ± 2.1. 55% of the patients presented SDOM. Perfusion monitoring showed IP values of 5.32 ± 1.87 that were associated with normal lactate levels of 1.49 mmol/L (min 0.89/ max 2.20 mmol/L). The PPI values between the living and the dead did not show a significant difference (p = 0.854) or the presence of SDOM.The PPI values between the patients who presented renal failure, hemodynamics, or perfusion disorders were determined by the presence of hyperlactatemia, and for those who did not present these characteristics, no statistical difference was found; neither when stratified by PaFiO2 ratio. Mortality was 55%.Conclusion: In our series of patients with severe pneumonia due to COVID-19, we found high PPI values, which would correspond to a pattern of capillary recruitment, and the associated organ injury could not be substantiated by this phenomenon.

Introduction: Infection and the accompanying inflammation of the upper and lower respiratory tract, influenza and COVID-19, are among the deadliest diseases in human life in the world. Due to the high emergence of bacterial resistance to antibiotics, we strive to find alternatives to contribute to the treatment by using a new formulation of a mixture of six essential oils in the form of a drop called Respira drops for a therapeutic approach to the upper or lower parts of the respiratory system infection, either by inhalation or sniffing, or by touching it with the body in the form of a skin patch on the head, neck, or chest. The present study suggested that natural essential oils may act as a prophylactic and therapeutic agent in respiratory tract hypoxia, inflammation, and bacterial and viral infection (influenza and COVID-19).Case presentation: A 62-year-old Yemeni man was suffering from acute pneumonia and had used antibiotics his condition improved, but he was suffering from difficulty breathing and stayed on the use of oxygen at home for more than three months, and his SpO2 ranged between 75 to 85 and he also suffered from an abdominal hernia, and he went for a procedure Surgery, and when the SpO2 was measured at 86, the surgery was not completed as a result, so he used Respira drops by inhalation and by steam for twenty-four hours and the next day he went to the hospital and the SpO2 was measured 96 and the operation was performed and he continued using Respira for two weeks three times per day and his condition improved completely.Conclusion: The present case study shows the excellent therapeutic response for Respira drops as inhalation and smiling three times per day increased SpO2 levels which reflect the anti-inflammatory, antimicrobial and anti-viral effects (influenza and COVID-19).

Originating from China in 2019, the novel Coronavirus Disease 2019 (COVID-19) pandemic had badly affected most of the world causing immense morbidity and mortality. The disease in moderate to severe cases was characterized by intense inflammation leading to ARDS and hypercoagulable states leading to thrombo-embolism and mortality.Aim: This study aimed to explore the association of inflammatory biomarkers with COVID-19 disease severity in our hospital which became a dedicated COVID hospital during the pandemic.

Coronavirus disease (COVID-19) is a viral pneumonia that is found in China and has spread globally. Early diagnosis is important for effective and timely treatment. Thus, many ongoing studies attempt to solve key COVID-19 problems such as workload classification, detection, and differentiation from other pneumonia and healthy lungs using different imaging modalities. Researchers have identified some limitations in the deployment of deep learning methods to detect COVID-19, but there are still unmet challenges to be addressed. The use of binary classifiers or building classifiers based on only a few classes is some of the limitations that most of the existing research on the COVID-19 classification problem suffers from. Additionally, most prior studies have focused on model or ensemble models that depend on a flat single-feature imaging modality without using any clinical information or benefiting from the hierarchical structure of pneumonia, which leads to clinical challenges, and evaluated their systems using a small public dataset. Additionally, reliance on diagnostic processes based on CT as the main imaging modality, ignoring chest X-rays. Radiologists, computer scientists, and physicians all need to come to an understanding of these interdisciplinary issues. This article first highlights the challenges of deep learning deployment for COVID-19 detection using a literature review and document analysis. Second, it provides six key recommendations that could assist future researchers in this field in improving the diagnostic process for COVID-19. However, there is a need for a collective effort from all of them to consider the provided recommendations to effectively solve these issues.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appeared in December 2019 in China and has rapidly become a major global health concern. Patients with end-stage renal disease receiving dialysis treatment are very exposed to the SARS-CoV-2 during their frequent visits to healthcare facilities and immune induced by uremia. The aim of our work was to describe the particularity of COVID-19 infection in hemodialysis patients in sub-Saharan Africa and in Ziguinchor, south of Senegal, particularly. To do this, we conducted a monocentric prospective study over a period of 16 months at the Ziguinchor hemodialysis center and compared our results to a study that focuses on the seroprevalence of SARS-CoV-2 in chronic hemodialysis patients. We found a low prevalence of COVID-19 infection while the majority of our patients were in contact with the virus.

Introduction: Child Protection Services (CPSs) are dedicated to providing protection and responding to any threats a child could face as children worldwide could be abused. Recently, the COVID-19 pandemic affected all aspects of life. Procedures implemented to restrict the spread of the disease (such as reduced access to services, school closure, and social distancing measures) had an impact on child life and maltreatment. Therefore, it is important to know the impact of this pandemic on child abuse and protection. Aim and rationales: This study aimed to assess the impact of COVID-19 on CPSs in Oman by studying the change in the number of reported cases of child abuse and the change in the reporting procedure at the Ministry of Social Development (MOSD). In addition, know the impact of the restriction measures on child rights and risk factors of child maltreatment based on CPSs workers’ opinions and experience. To understand the adaptation of the CPSs to the change in work and life environment imposed by COVID-19. Method: A cross-section study was conducted using a semi-structured questionnaire, that was distributed to the workers involved in the CPSs at the MOSD in Oman. Data also were collected from the statistical bulletins on the Ministry’s website. Results: COVID-19 pandemic was not found associated with a significant change in the number and type of child abuse cases reported to the MOSD. The reporting procedures also did not change. In addition, the pattern of child abuse types did not change before and during the pandemic, as neglect cases were the most. The participants judged the restriction measures affecting family life through separation, cyber abuse, and reduced educational support. With regard to intervention and follow-up procedures, the main difference was in the communication processes by using online communication methods and reducing the fieldwork for mild cases.Conclusion: CPSs in Oman were not much affected by the COVID-19 pandemic, which may reflect the success of this system in dealing with the restriction measures. However, more solutions should be developed to adapt to these circumstances in the future altogether.

Background: In light of the COVID-19 pandemic and the health crisis left in its wake, our goal is to develop extensive machine-learning techniques to provide a clear picture of the treatment, and possible mistreatment, of specific patient demographics during hospital triaging.Objective: We aim to reveal whether a patient’s treatment and hospital disposition is related to the following attributes - Emergency Severity Index (ESI), gender, employment status, insurance status, race, or ethnicity which our 100 MB dataset included.Materials and methods: Our work is separated into two parts - the classification task and data analysis. As part of the classification task, we used the k-Nearest-Neighbor classifier, the F1-score, and a random forest. We then analyze the data using SHapley Additive exPlanations (SHAP) values to determine the importance of each attribute.Results: Our findings show that significance varies for each attribute. Notably, we found that patients with private insurance programs receive better treatment compared to patients with federal-run healthcare programs (e.g. Medicaid, Medicare). Furthermore, a patient’s ethnicity has a greater impact on treatment for patients under 40 years of age for any given ESI level. Surprisingly, our findings show language is not a barrier during treatment.Discussion and conclusion: We, therefore, conclude that although hospitals may not be doing so intentionally, there is a systemic bias in hospital triaging for specific patient demographics. For future works, we hope to aggregate additional patient data from hospitals to find whether specific demographics of patients receive better healthcare in different parts of the United States.

The well-documented therapeutic potential of group singing for patients living with Alzheimer’s disease (PLAD) has been hindered by COVID-19 restrictions, exacerbating loneliness and cognitive decline among seniors in residential and long-term care centers (CHSLDs). Addressing this challenge, the multidisciplinary study aims to develop a patient-oriented virtual reality (XR) interaction system facilitating group singing for mental health support during confinement and enhancing the understanding of the links between Alzheimer’s disease, social interaction, and singing. The researchers also propose to establish an early AD detection system using voice, facial, and non-invasive biometric measurements and validate the efficacy of selected intervention practices. The methodology involves co-designing an intelligent environment with caregivers to support PLAD mental health through online group singing, addressing existing constraints in CHSLDs. The researchers will engage volunteers in remote singing interactions and validate the impact of voice stimulation for PLADs using a control group. The primary expected outcome is the development of an “Intelligent Learning Health Environment,” fostering interactions while adapting to individual PLAD situations and incrementally accumulating knowledge on AD signs. This environment will facilitate the transfer of knowledge and technologies to promote non-verbal interactions via singing, enabling intervention at the first symptoms. Additionally, the research will contribute to transforming CHSLDs’ living environments, informed by neuroscience insights, and potentially extend the “collaborative self-care” approach to support seniors in aging safely and healthily at home.

The 2019 COVID-19 pandemic caused by SARS-CoV-2 has resulted in many fatalities worldwide. Despite various types of supportive care, mortality rates for patients with comorbidities remain high. To explore alternative treatment options, interferons (IFNs) have emerged as promising therapeutic drugs for SARS-CoV-2. This review aims to investigate the potential of IFNs as a drug with details on their mechanisms of action, and available data on their use with ongoing clinical trials, results, potential limitations, and challenges.  Recently published research articles, which are systematically searched through online databases, have been selected and found that IFNs have colossal potential in treating SARS-CoV-2 infection by modulating the host’s immune response and inhibiting viral replication and decreasing the severity of disease and hospitalization (p = 0.03, ± 0.05) and (p = 0.04, ± 0.05) respectively. However, due to less available data, more controlled and randomized trials are needed to confirm the efficacy and safety of IFN therapy.  The optimal dosing and duration of IFN therapy also remain to be determined. Although further research is needed the wait for ongoing clinical trial results under investigation is also important for a better understanding of IFN therapy.