Clinical characteristics, laboratory outcome characteristics, comorbidities, and complications of related COVID-19 deceased: a systematic review and meta-analysis

An IoT Framework for Screening of COVID-19 Using Real-Time Data from Wearable Sensors

Experts have predicted that COVID-19 may prevail for many months or even years before it can be completely eliminated. A major problem in its cure is its early screening and detection, which will decide on its treatment. Due to the fast contactless spreading of the virus, its screening is unusually difficult. Moreover, the results of COVID-19 tests may take up to 48 h. That is enough time for the virus to worsen the health of the affected person. The health community needs effective means for identification of the virus in the shortest possible time. In this study, we invent a medical device utilized consisting of composable sensors to monitor remotely and in real-time the health status of those who have symptoms of the coronavirus or those infected with it. The device comprises wearable medical sensors integrated using the Arduino hardware interfacing and a smartphone application. An IoT framework is deployed at the backend through which various devices can communicate in real-time. The medical device is applied to determine the patient's critical status of the effects of the coronavirus or its symptoms using heartbeat, cough, temperature and Oxygen concentration (SpO2) that are evaluated using our custom algorithm. Until now, it has been found that many coronavirus patients remain asymptomatic, but in case of known symptoms, a person can be quickly identified with our device. It also allows doctors to examine their patients without the need for physical direct contact with them to reduce the possibility of infection. Our solution uses rule-based decision-making based on the physiological data of a person obtained through sensors. These rules allow to classify a person as healthy or having a possibility of infection by the coronavirus. The advantage of using rules for patient's classification is that the rules can be updated as new findings emerge from time to time. In this article, we explain the details of the sensors, the smartphone application, and the associated IoT framework for real-time, remote screening of COVID-19.

Potential COVID-19 Therapeutic Agents and Vaccines: An Evidence-Based Review

Since the early days of 2020, the severe acute respiratory syndrome coronavirus 2 pandemic has become a global health concern. Currently, some therapies and vaccines have received US Food and Drug Administration approval or emergency use authorization for the management of coronavirus disease 2019. According to the pathophysiology of the disease, several medications have been evaluated in different clinical conditions of the disease. Evidence-based reviewing and categorizing these medications can guide the clinicians to select the proper medications according to each patient's condition. Therefore, we performed this review to categorize the coronavirus disease 2019 potential therapeutics and vaccines.

COVID-19 in People Living with HIV: A Systematic Review and Meta-Analysis

COVID-19 is a global health emergency. People living with human immunodeficiency virus (PLHIV) have concerns about whether they have a higher risk of getting the infection and suffer worse COVID-19 outcomes. Findings from studies on these questions have largely been inconsistent. We aimed to determine the epidemiological characteristics, clinical signs and symptoms, blood parameters, and clinical outcomes among PLHIV who contracted COVID-19. Relevant studies were identified through Medline, Cinahl, and PubMed databases. A random-effects model was used in meta-analyses with a 95% confidence interval. Eighty-two studies were included in the systematic review and sixty-seven studies for the meta-analysis. The pooled incidence proportion of COVID-19 among PLHIV was 0.9% (95% CI 0.6%, 1.1%) based on the data from seven cohort studies. Overall, 28.4% were hospitalised, of whom, 2.5% was severe-critical cases and 3.5% needed intensive care. The overall mortality rate was 5.3%. Hypertension was the most commonly reported comorbidity (24.0%). Fever (71.1%) was the most common symptom. Chest imaging demonstrated a wide range of abnormal findings encompassing common changes such as ground glass opacities and consolidation as well as a spectrum of less common abnormalities. Laboratory testing of inflammation markers showed that C-reactive protein, ferritin, and interleukin-6 were frequently elevated, albeit to different extents. Clinical features as well as the results of chest imaging and laboratory testing were similar in highly active antiretroviral therapy (HAART)-treated and non-treated patients. PLHIV were not found to be at higher risk for adverse outcomes of COVID-19. Hence, in COVID-19 management, it appears that they can be treated the same way as HIV negative individuals. Nevertheless, as the pandemic situation is rapidly evolving, more evidence may be needed to arrive at definitive recommendations.

Predictive Biomarkers of COVID-19 Severity in SARS-CoV-2 Infected Patients with Obesity and Metabolic Syndrome

In SARS-CoV-2-infected patients, obesity, hypertension, and diabetes are dangerous factors that may result in death. Priority in detection and specific therapies for these patients are necessary. We wanted to investigate the impact of obesity and metabolic syndrome (MS) on the clinical course of COVID-19 and whether prognostic biomarkers described are useful to predict the evolution of COVID-19 in patients with obesity or MS. This prospective cohort study included 303 patients hospitalized for COVID-19. Participants were first classified according to the presence of obesity; then, they were classified according to the presence of MS. Clinical, radiologic, and analytical parameters were collected. We reported that patients with obesity presented moderate COVID-19 symptoms and pneumonia, bilateral pulmonary infiltrates, and needed tocilizumab more frequently. Meanwhile, patients with MS presented severe pneumonia and respiratory failure more frequently, they have a higher mortality rate, and they also showed higher creatinine and troponin levels. The main findings of this study are that IL-6 is a potential predictor of COVID-19 severity in patients with obesity, while troponin and LDH can be used as predictive biomarkers of COVID-19 severity in MS patients. Therefore, treatment for COVID-19 in patients with obesity or MS should probably be intensified and personalized.

Unexpected high frequency of early mortality in COVID-19: a single-centre experience during the first wave of the pandemic

We report the high frequency of early mortality in COVID‐19 patients (48.6% of 72 deaths). Early deaths were not explained by differences in age, sex and comorbidities, but they had a more severe disease at hospital admission compared with late deaths. These data highlight the importance of outpatient monitoring for the early identification of COVID‐19 patients who require hospital admission.

Detecting COVID-19 patients based on fuzzy inference engine and Deep Neural Network

COVID-19, as an infectious disease, has shocked the world and still threatens the lives of billions of people. Recently, the detection of coronavirus (COVID-19) is a critical task for the medical practitioner. Unfortunately, COVID-19 spreads so quickly between people and approaches millions of people worldwide in few months. It is very much essential to quickly and accurately identify the infected people so that prevention of spread can be taken. Although several medical tests have been used to detect certain injuries, the hopefully detection efficiency has not been accomplished yet. In this paper, a new Hybrid Diagnose Strategy (HDS) has been introduced. HDS relies on a novel technique for ranking selected features by projecting them into a proposed Patient Space (PS). A Feature Connectivity Graph (FCG) is constructed which indicates both the weight of each feature as well as the binding degree to other features. The rank of a feature is determined based on two factors; the first is the feature weight, while the second is its binding degree to its neighbors in PS. Then, the ranked features are used to derive the classification model that can classify new persons to decide whether they are infected or not. The classification model is a hybrid model that consists of two classifiers; fuzzy inference engine and Deep Neural Network (DNN). The proposed HDS has been compared against recent techniques. Experimental results have shown that the proposed HDS outperforms the other competitors in terms of the average value of accuracy, precision, recall, and F-measure in which it provides about of 97.658%, 96.756%, 96.55%, and 96.615% respectively. Additionally, HDS provides the lowest error value of 2.342%. Further, the results were validated statistically using Wilcoxon Signed Rank Test and Friedman Test.

The clinical characteristics and prognosis of COVID-19 patients with comorbidities: a retrospective analysis of the infection peak in Wuhan

Background

This study aims to determine the clinical characteristics and prognosis of COVID-19 patients with comorbidities and to identify survival factors.

Methods

A retrospective study was conducted in Wuhan, China, between February 8, 2020, and March 9, 2020. Based on underlying diseases, patients were assigned to either the comorbidity group or the non-comorbidity group. The clinical characteristics and outcomes of COVID-19 were analyzed and a Kaplan-Meier survival analysis was used to evaluate the prognosis predictive value of each comorbidity.

Results

During the study period, 278 COVID-19 patients were enrolled, 175 (62.95%) were assigned to the comorbidity group, and 103 (37.05%) to the non-comorbidity group. Of the patients in the comorbidity group, 34.86% were classified as critical. Further, patients in the comorbidity group had lower lymphocyte cell counts, and higher concentrations of D-dimer, high sensitivity C-reactive protein, interleukin 6, and serum ferritin as well as higher critical illness severity scores than patients in the non-comorbidity group (P<0.05). Patients in the comorbidity group also had higher mortality, acute respiratory distress syndrome, and ventilation treatment rates than patients in the non-comorbidity group (P<0.05). The length of hospital stay was longer in the comorbidity group than in the non-comorbidity group (P<0.05). The most common underlying diseases included hypertension (40.65%), diabetes mellitus (20.5%), and cardiovascular disease (19.42%). Patients with comorbidities were more likely to develop cardiovascular sequelae associated with COVID-19, shock, acute kidney injury, and multiple organ dysfunction syndrome (30.86% vs. 12.62%, P=0.001; 18.86% vs. 8.74%, P=0.023; 24.57% vs. 11.65%, P=0.009; 33.71% vs. 14.56%, P=0.000, respectively). In the Kaplan-Meier survival analysis, older patients (¡Ý65 years) (log-rank test: χ²=4.202, P=0.040) and patients with chronic obstructive pulmonary disease (COPD) (log-rank test: χ²=4.839, P=0.028) or diabetes mellitus (log-rank test: χ²=4.377, P=0.036) had shorter survival than those without comorbidities.

Conclusions

Patients with comorbidities were more severely affected and had a higher mortality rate. Age, COPD and diabetes mellitus were the main factors affecting the survival of patients.

Acute respiratory distress syndrome (ARDS) as an adverse event following immunization: Case definition & guidelines for data collection, analysis, and presentation of immunization safety data

This is a Brighton Collaboration Case Definition of the term “Acute Respiratory Distress Syndrome – ARDS” to be utilized in the evaluation of adverse events following immunization. The Case Definition was developed by a group of experts convened by the Coalition for Epidemic Preparedness Innovations (CEPI) in the context of active development of vaccines for SARS-CoV-2 vaccines and other emerging pathogens. The case definition format of the Brighton Collaboration was followed to develop a consensus definition and defined levels of certainty, after an exhaustive review of the literature and expert consultation. The document underwent peer review by the Brighton Collaboration Network and by selected Expert Reviewers prior to submission. The comments of the reviewers were taken into consideration and edits incorporated in this final manuscript.

Patterns of COVID-19 related excess mortality in the municipalities of Northern Italy during the first wave of the pandemic

The impact of Coronavirus Disease 2019 (COVID-19) on mortality in Italy has been described at the regional level, while less is known about mortality in municipalities, although the spatial distribution of COVID-19 in its first wave has been uneven. We aimed to describe the excess mortality due to COVID-19 from February 23rd to April 30th, 2020 in the three most affected Italian regions, in age and gender subgroups within each municipality. Excess mortality varied widely among municipalities even within the same region; it was higher among the elderly and higher in males except in the ≥75 age group. Thus, nearby municipalities may show a different mortality burden despite being under common regional health policies, possibly as a result of local reinforcements of regional policies. Identifying the municipalities where mortality was higher and the pathways used by the virus to spread may help to concentrate efforts in understanding the reasons why this happened and to identify the frailest areas in light of recurrences of the epidemic.

Clinical Characteristics of COVID-19 Patients in a Regional Population With Diabetes Mellitus: The ACCREDIT Study

OBJECTIVE

To identify clinical and biochemical characteristics associated with 7- & 30-day mortality and intensive care admission amongst diabetes patients admitted with COVID-19.

RESEARCH DESIGN AND METHODS

We conducted a cohort study collecting data from medical notes of hospitalised people with diabetes and COVID-19 in 7 hospitals within the Mersey-Cheshire region from 1 January to 30 June 2020. We also explored the impact on inpatient diabetes team resources. Univariate and multivariate logistic regression analyses were performed and optimised by splitting the dataset into a training, test, and validation sets, developing a robust predictive model for the primary outcome.

RESULTS

We analyzed data from 1004 diabetes patients (mean age 74.1 (± 12.6) years, predominantly men 60.7%). 45% belonged to the most deprived population quintile in the UK. Median BMI was 27.6 (IQR 23.9-32.4) kg/m². The primary outcome (7-day mortality) occurred in 24%, increasing to 33% by day 30. Approximately one in ten patients required insulin infusion (9.8%). In univariate analyses, patients with type 2 diabetes had a higher risk of 7-day mortality [p < 0.05, OR 2.52 (1.06, 5.98)]. Patients requiring insulin infusion had a lower risk of death [p = 0.02, OR 0.5 (0.28, 0.9)]. CKD in younger patients (<70 years) had a greater risk of death [OR 2.74 (1.31-5.76)]. BMI, microvascular and macrovascular complications, HbA1c, and random non-fasting blood glucose on admission were not associated with mortality. On multivariate analysis, CRP and age remained associated with the primary outcome [OR 3.44 (2.17, 5.44)] allowing for a validated predictive model for death by day 7.

CONCLUSIONS

Higher CRP and advanced age were associated with and predictive of death by day 7. However, BMI, presence of diabetes complications, and glycaemic control were not. A high proportion of these patients required insulin infusion warranting increased input from the inpatient diabetes teams.

Clinical Characteristics of 47 Death Cases With COVID-19: A Retrospective Study at a Tertiary Center in Lahore

Introduction Coronavirus disease 2019 (COVID-19) presents with a wide spectrum of symptoms, ranging from patients being asymptomatic to having life-threatening acute respiratory distress syndrome (ARDS). COVID-19 emerged as a pandemic and has led to multiple causalities worldwide. A better understanding of the clinical characteristics of the COVID-19 patients and their disease course will aid in better management of these patients and hence may positively impact their outcomes as well. Methodology This was a retrospective observational study conducted from April 15, 2020, to August 31, 2020, after gaining institutional review board approval at the University of Lahore Teaching Hospital, Lahore, Pakistan. A total of 47 patients with severe disease who had died due to COVID-19 during this period were enrolled by the consecutive method. Patients were evaluated for their epidemiological, biochemical, clinical, and radiological features. The modified Radiographic Assessment of Lung Edema (mRALE) score was used to calculate the extent of alveolar opacities and percentages of lung involvement in chest radiographs. Furthermore, patients' management plans were also evaluated. Data were analyzed using SPSS Statistics version 23 (IBM, Armonk, NY). Results The mean age of the patients was 61.53 ±13.35 years. The male-to-female ratio was 2:1, and the mean BMI was 28.05 ±3.52 kg/m2. Diabetes was the most prevalent comorbidity among the patients (32, 68.1%), followed by hypertension (six, 12.8%), ischemic heart disease (five, 10.6%), and chronic kidney disease (four, 8.5%) respectively. The predominant symptom observed among patients was cough (95%), followed by shortness of breath (93%), fever (63%), sputum (23%), and gastrointestinal symptoms (6.4%). The mean D-dimer was 1,567.13 ±1,903.77 ng/mL, mean ferritin was 1,730.34 ±1,382.35 ng/mL, mean C-reactive protein (CRP) was 202.59 ±104.97 mg/dl, and the mean neutrophil-to-lymphocyte ratio was 10.50 ±9.58. Bilateral lung involvement was seen among 40 (85.11%) patients whereas unilateral right lung involvement was reported in three (6.38%) and unilateral left lung involvement in four (8.51%) respectively. The mean mRALE score for bilateral lung involvement was 18.78 ±4.89. The mean area radiologically involved in bilateral lung fields was 72.12 ±18.45%, followed by unilateral right lung involvement of 67.87 ±15.97%, and unilateral left lung involvement of 61.38 ±17.95% in the cohort respectively. The most common type of radiological pathology was diffuse ground-glass opacities, which was observed in 18 (38%) patients. Most patients received antibiotics (39, 63.83%), while nine (19%) received tocilizumab, four (8.5%) had antiviral therapy, and three (6.4%) were given plasma treatment. All patients received glucocorticoids and anticoagulation. The most common cause of death was ARDS, which was observed in 12 (25.5%) patients. Conclusion This study significantly demonstrated that most cases were males above 50 years of age with chronic medical comorbidities of diabetes, hypertension, and ischemic heart disease. COVID-19 has a predilection for multisystem involvement leading to mortality. In addition, elevated D-dimer and neutrophil-to-lymphocyte ratio may be indicative of a poor prognosis. A combination of antimicrobials had no positive impact on the outcomes in this cohort. It is difficult to predict the efficacy of tocilizumab and remdesivir as only a few patients in the cohort received these drugs.

Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions

OBJECTIVE

Risk factors for in-hospital mortality in confirmed COVID-19 patients have been summarized in numerous meta-analyses, but it is still unclear whether they vary according to the age, sex and health conditions of the studied populations. This study explored these variables as potential mortality predictors.

METHODS

A systematic review was conducted by searching the MEDLINE, Scopus, and Web of Science databases of studies available through July 27, 2020. The pooled risk was estimated with the odds ratio (p-OR) or effect size (p-ES) obtained through random-effects meta-analyses. Subgroup analyses and meta-regression were applied to explore differences by age, sex and health conditions. The MOOSE guidelines were strictly followed.

RESULTS

The meta-analysis included 60 studies, with a total of 51,225 patients (12,458 [24.3%] deaths) from hospitals in 13 countries. A higher in-hospital mortality risk was found for dyspnoea (p-OR = 2.5), smoking (p-OR = 1.6) and several comorbidities (p-OR range: 1.8 to 4.7) and laboratory parameters (p-ES range: 0.3 to -2.6). Age was the main source of heterogeneity, followed by sex and health condition. The following predictors were more markedly associated with mortality in studies with patients with a mean age ≤60 years: dyspnoea (p-OR = 4.3), smoking (p-OR = 2.8), kidney disease (p-OR = 3.8), hypertension (p-OR = 3.7), malignancy (p-OR = 3.7), diabetes (p-OR = 3.2), pulmonary disease (p-OR = 3.1), decreased platelet count (p-ES = -1.7), decreased haemoglobin concentration (p-ES = -0.6), increased creatinine (p-ES = 2.4), increased interleukin-6 (p-ES = 2.4) and increased cardiac troponin I (p-ES = 0.7). On the other hand, in addition to comorbidities, the most important mortality predictors in studies with older patients were albumin (p-ES = -3.1), total bilirubin (p-ES = 0.7), AST (p-ES = 1.8), ALT (p-ES = 0.4), urea nitrogen (p-ES), C-reactive protein (p-ES = 2.7), LDH (p-ES = 2.4) and ferritin (p-ES = 1.7). Obesity was associated with increased mortality only in studies with fewer chronic or critical patients (p-OR = 1.8).

CONCLUSION

The prognostic effect of clinical conditions on COVID-19 mortality vary substantially according to the mean age of patients.

PROSPERO REGISTRATION NUMBER

CRD42020176595.

Clinical and epidemiological features of COVID-19 deaths in Nepal

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has taken more than 1 million lives globally. This study, based on the official media releases of the Government of Nepal, analyses the clinical and epidemiological features of the individuals who died as a result of COVID-19 in Nepal from 23 January to 10 August 2020. We found that nearly half of the deaths were among people less than 50 years of age and being female increased the risk of death. The majority of deaths were associated with co-morbidities, the most common being cardiovascular diseases and diabetes followed by respiratory diseases. With the approaching festive season and relaxed lockdown, both government and citizens need to be more cautious about the severity of COVID-19 and take appropriate action.

Risk factors for severe disease in patients admitted with COVID-19 to a hospital in London, England: a retrospective cohort study

COVID-19 has caused a major global pandemic and necessitated unprecedented public health restrictions in almost every country. Understanding risk factors for severe disease in hospitalised patients is critical as the pandemic progresses. This observational cohort study aimed to characterise the independent associations between the clinical outcomes of hospitalised patients and their demographics, comorbidities, blood tests and bedside observations. All patients admitted to Northwick Park Hospital, London, UK between 12 March and 15 April 2020 with COVID-19 were retrospectively identified. The primary outcome was death. Associations were explored using Cox proportional hazards modelling. The study included 981 patients. The mortality rate was 36.0%. Age (adjusted hazard ratio (aHR) 1.53), respiratory disease (aHR 1.37), immunosuppression (aHR 2.23), respiratory rate (aHR 1.28), hypoxia (aHR 1.36), Glasgow Coma Scale <15 (aHR 1.92), urea (aHR 2.67), alkaline phosphatase (aHR 2.53), C-reactive protein (aHR 1.15), lactate (aHR 2.67), platelet count (aHR 0.77) and infiltrates on chest radiograph (aHR 1.89) were all associated with mortality. These important data will aid clinical risk stratification and provide direction for further research.

COVID-19 and the World with Co-Morbidities of Heart Disease, Hypertension and Diabetes

Newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) pandemic has now spread across the globe in past few months while affecting 26 million people and leading to more than 0.85 million deaths as on 2nd September, 2020. Severity of SARS-CoV-2 infection increases in COVID-19 patients due to pre-existing health co-morbidities. This mini-review has focused on the three significant co-morbidities viz., heart disease, hypertension, and diabetes, which are posing high health concerns and increased mortality during this ongoing pandemic. The observed co-morbidities have been found to be associated with the increasing risk factors for SARS-CoV-2 infection and COVID-19 critical illness as well as to be associated positively with the worsening of the health condition of COVID-19 suffering individuals resulting in the high risk for mortality. SARS-CoV-2 enters host cell via angiotensin-converting enzyme 2 receptors. Regulation of crucial cardiovascular functions and metabolisms like blood pressure and sugar levels are being carried out by ACE2. This might be one of the reasons that contribute to the higher mortality in COVID-19 patients having co-morbidities. Clinical investigations have identified higher levels of creatinine, cardiac troponin I, alanine aminotransferase, NT-proBNP, creatine kinase, D-dimer, aspartate aminotransferase and lactate dehydrogenase in patients who have succumbed to death from COVID-19 as compared to recovered individuals. More investigations are required to identify the modes behind increased mortality in COVID-19 patients having co-morbidities of heart disease, hypertension, and diabetes. This will enable us to design and develop suitable therapeutic strategies for reducing the mortality. More attention and critical care need to be paid to such high risk patients suffering from co-morbidities during COVID-19 pandemic.

Treatment of Multi-Drug Resistant Gram-Negative Bacterial Pathogenic Infections

The multidrug-resistant Gram-negative bacteria (MDR-GNB) infections in severely infected patients present numerous difficulties in terms of treatment failure where antibiotics cannot arrest such drug resistant bacteria. Based on the patient’s medical history and updated microbiological epidemiology data, an effective empirical treatment remains critical for optimal results to safeguard human health. The aim of this manuscript is to review management of MDR-Gram negative pathogenic bacterial infections. Quick diagnosis and narrow antimicrobial spectrum require rapid and timely diagnosis and effective laboratories in accordance with antimicrobial stewardship (AS) principles. Worldwide, there is an increased emergence of Carbapenem-resistant Enterobacteriaceae (CRE), Pseudomonas aeruginosa, and Acinetobacter baumannii. Recently, novel therapeutic options, such as meropenem/vaborbactam, ceftazidime/avibactam, ceftolozane/tazobactam, eravacycline and plazomicin became accessible to effectively counteract severe infections. Optimally using these delays the emergence of resistance to novel therapeutic agents. Further study is required, however, due to uncertainties in pharmacokinetic/pharmacodynamics optimization of dosages and therapeutic duration in severely ill patients. The novel agents should be verified for (i) action on carbapenem resistant Acinetobacter baumannii; (ii) action on CRE of β-lactam/β-lactamase inhibitors dependence on type of carbapenemase; (iii) emergence of resistance to novel antibacterials and dismiss selective pressure promoting development of resistance. Alternative treatments should be approached alike phage therapy or antibacterial peptides. The choice of empirical therapy is complicated by antibiotic resistance and can be combated by accurate antibiotic and their combinations usage, which is critical to patient survival. Noteworthy are local epidemiology, effective teamwork and antibiotic stewardship to guarantee that medications are utilized properly to counter the resistance.

Targeting Host Defense System and Rescuing Compromised Mitochondria to Increase Tolerance against Pathogens by Melatonin May Impact Outcome of Deadly Virus Infection Pertinent to COVID-19

Fighting infectious diseases, particularly viral infections, is a demanding task for human health. Targeting the pathogens or targeting the host are different strategies, but with an identical purpose, i.e., to curb the pathogen's spreading and cure the illness. It appears that targeting a host to increase tolerance against pathogens can be of substantial advantage and is a strategy used in evolution. Practically, it has a broader protective spectrum than that of only targeting the specific pathogens, which differ in terms of susceptibility. Methods for host targeting applied in one pandemic can even be effective for upcoming pandemics with different pathogens. This is even more urgent if we consider the possible concomitance of two respiratory diseases with potential multi-organ afflictions such as Coronavirus disease 2019 (COVID-19) and seasonal flu. Melatonin is a molecule that can enhance the host's tolerance against pathogen invasions. Due to its antioxidant, anti-inflammatory, and immunoregulatory activities, melatonin has the capacity to reduce the severity and mortality of deadly virus infections including COVID-19. Melatonin is synthesized and functions in mitochondria, which play a critical role in viral infections. Not surprisingly, melatonin synthesis can become a target of viral strategies that manipulate the mitochondrial status. For example, a viral infection can switch energy metabolism from respiration to widely anaerobic glycolysis even if plenty of oxygen is available (the Warburg effect) when the host cell cannot generate acetyl-coenzyme A, a metabolite required for melatonin biosynthesis. Under some conditions, including aging, gender, predisposed health conditions, already compromised mitochondria, when exposed to further viral challenges, lose their capacity for producing sufficient amounts of melatonin. This leads to a reduced support of mitochondrial functions and makes these individuals more vulnerable to infectious diseases. Thus, the maintenance of mitochondrial function by melatonin supplementation can be expected to generate beneficial effects on the outcome of viral infectious diseases, particularly COVID-19.

A Telemedicine Approach to Covid-19 Assessment and Triage

Covid-19 is a new highly contagious RNA viral disease that has caused a global pandemic. Human-to-human transmission occurs primarily through oral and nasal droplets and possibly through the airborne route. The disease may be asymptomatic or the course may be mild with upper respiratory symptoms, moderate with non-life-threatening pneumonia, or severe with pneumonia and acute respiratory distress syndrome. The severe form is associated with significant morbidity and mortality. While patients who are unstable and in acute distress need immediate in-person attention, many patients can be evaluated at home by telemedicine or videoconferencing. The more benign manifestations of Covid-19 may be managed from home to maintain quarantine, thus avoiding spread to other patients and health care workers. This document provides an overview of the clinical presentation of Covid-19, emphasizing telemedicine strategies for assessment and triage of patients. Advantages of the virtual visit during this time of social distancing are highlighted.