The clinical characteristics and outcomes of patients with diabetes and secondary hyperglycaemia with coronavirus disease 2019: A single-centre, retrospective, observational study in Wuhan

Abstract: AIM: To explore whether coronavirus disease 2019 (COVID-19) patients with diabetes and secondary hyperglycaemia have different clinical characteristics and prognoses than those without significantly abnormal glucose metabolism. MATERIALS AND METHODS: We retrospectively analysed 166 COVID-19 patients at Tongji Hospital (Wuhan) from 8 February to 21 March 2020. Clinical characteristics and outcomes (as of 4 April 2020) were compared among control (group 1), secondary hyperglycaemia (group 2: no diabetes history, fasting plasma glucose levels of ≥7.0 mmol/L once and HbA1c values <6.5%) and patients with diabetes (group 3). RESULTS: Compared with group 1, groups 2 and 3 had higher rates of leukocytosis, neutrophilia, lymphocytopenia, eosinopenia and levels of hypersensitive C-reactive protein, ferritin and d-dimer (P < .05 for all). Group 2 patients had higher levels of lactate dehydrogenase, prevalence of liver dysfunction and increased interleukin-8 (IL-8) than those in group 1, and a higher prevalence of increased IL-8 was found in group 2 than in group 3 (P < .05 for all). The proportions of critical patients in groups 2 and 3 were significantly higher compared with group 1 (38.1%, 32.8% vs. 9.5%, P < .05 for both). Groups 2 and 3 had significantly longer hospital stays than group 1, which was nearly 1 week longer. The composite outcomes risks were 5.47 (1.56-19.82) and 2.61 (0.86-7.88) times greater in groups 2 and 3 than in group 1. CONCLUSIONS: Hyperglycaemia in both diabetes and secondary hyperglycaemia patients with COVID-19 may indicate poor prognoses. There were differences between patients with secondary hyperglycaemia and those with diabetes. We recommend that clinicians pay more attention to the blood glucose status of COVID-19 patients, even those not diagnosed with diabetes before admission.


COVID-19 and diabetes: What does the clinician need to know?

Abstract: COVID-19 and diabetes are currently two global pandemics. Epidemiological studies indicate that diabetes is the second most common comorbidity in COVID-19. This review aims to summarize currently available data about prevalence, possible pathophysiological mechanisms and management of patients with diabetes and COVID-19.


Assessment of risk, severity, mortality, glycemic control and antidiabetic agents in patients with diabetes and COVID-19: A narrative review

Abstract: AIMS: Rising prevalence of non-communicable diseases world-wide has made diabetes an important comorbidity in patients with coronavirus disease-19 (COVID-19). We sought to review the risk, severity and mortality in COVID-19 and its relation to the glycemic control, and role of anti-diabetic agents in patients with diabetes. METHODS: A Boolean search was made in PubMed, MedRxiv and Google Scholar database until May 10, 2020 and full articles with supplementary appendix were retrieved using the specific key words related to the topic. RESULTS: There is a high prevalence of diabetes in patients with COVID-19. Patients with diabetes had a significantly more severe variety of COVID-19 and increased mortality, compared to the groups without diabetes. Moreover, poor glycemic control is associated with a significantly higher severe COVID-19 and increased mortality, compared to the well-controlled glycemic groups. No data currently available for or against any anti-diabetic agents in COVID-19. CONCLUSIONS: Diabetes, in particular poorly-controlled group is associated with a significantly higher risk of severe COVID-19 and mortality. This calls for an optimal glycemic control and an increased emphasis on future preventative therapies including the vaccination programs for these groups in addition to the traditional risk prevention such as social distancing and self-isolation.


COVID-19: Impact of and on Diabetes

Abstract: Diabetes has been identified as a pre-existing health condition linked with worse outcomes following coronavirus disease 2019 infection. Here we explore the association between hyperglycaemia and more severe illness, the impact of the pandemic on diabetes service delivery, and the resultant opportunities for innovation.


COVID-19 and diabetes management: What should be considered?


Clinical characteristics and outcomes of patients with severe covid-19 with diabetes

Abstract: OBJECTIVE: This study explores the clinical characteristics of patients with diabetes with severe covid-19, and the association of diabetes with survival duration in patients with severe covid-19. RESEARCH DESIGN AND METHODS: In this single-center, retrospective, observational study, the clinical and laboratory characteristics of 193 patients with severe covid-19 were collected. 48 patients with severe covid-19 had diabetes, and 145 patients (ie, the controls) did not have diabetes. A severe case was defined as including at least one of the following criteria: (1) Respiratory rate >30/min. (2) Oxygen saturation ≤93%. (3) PaO2/FiO2≤300 mm Hg. (4) Patients, either with shock or respiratory failure, requiring mechanical ventilation, or combined with other organ failure, requiring admission to intensive care unit (ICU). RESULTS: Of 193 patients with severe covid-19, 48 (24.9%) had diabetes. Compared with patients with severe covid-19 without diabetes, patients with diabetes were older, susceptible to receiving mechanical ventilation and admission to ICU, and had higher mortality. In addition, patients with severe covid-19 with diabetes had higher levels of leukocyte count, neutrophil count, high-sensitivity C reaction protein, procalcitonin, ferritin, interleukin (IL) 2 receptor, IL-6, IL-8, tumor necrosis factor α, D-dimer, fibrinogen, lactic dehydrogenase and N-terminal pro-brain natriuretic peptide. Among patients with severe covid-19 with diabetes, more non-survivors were men (30 (76.9%) vs 9 (23.1%)). Non-survivors had severe inflammatory response, and cardiac, hepatic, renal and coagulation impairment. Finally, the Kaplan-Meier survival curve showed a trend towards poorer survival in patients with severe covid-19 with diabetes than patients without diabetes. The HR was 1.53 (95% CI 1.02 to 2.30; p=0.041) after adjustment for age, sex, hypertension, cardiovascular disease and cerebrovascular disease by Cox regression. The median survival durations from hospital admission in patients with severe covid-19 with and without diabetes were 10 days and 18 days, respectively. CONCLUSION: The mortality rate in patients with severe covid-19 with diabetes is considerable. Diabetes may lead to an increase in the risk of death.


Covid-19 and diabetes mellitus: unveiling the interaction of two pandemics

Abstract: A novel RNA betacoronavirus causing coronavirus disease 2019 (Covid-19) has now been declared pandemic disease by WHO. Guo et al published the first report of biochemical features in patients with diabetes and the further risk that this disease can determine to the progression of Covid-19. Among different cytokines found significantly higher in patients with diabetes compared to those without, Interleukin-6 (IL-6), which is already increased in conditions of chronic inflammation, may play a more deleterious role in Covid-19 infection. Targeting the overexpression of Il-6 effects with a monoclonal antibody against IL-6 receptor or using Janus Kinase inhibitors may be particularly helpful for treatment of Covid-19 pneumonia in diabetes.


Recommendations for management of diabetic foot ulcers during COVID-19 outbreak

Abstract: COVID-19 pandemia began in Wuhan, China, in December 2019. A total of 1 878 489 people were infected and 119 044 people were lost because of the disease and its complications by 15 April. Severe morbidity and mortality complications are mostly seen in elderly and patients having comorbidities. Diabetic foot ulcers (DFUs) are one of severe complications of diabetes mellitus and it may require urgent surgical interventions. In this paper, we aimed to create a management algorithm to prevent the unexpected complications that may occur in the patients and health care workers during the evaluation of COVID-19 in DFU patients who require urgent surgical intervention. We advise the use of thorax computerised tomography for preoperative screening in all DFU patients with severe signs of infection and especially those requiring urgent surgery for both the detection of the possible undiagnosed COVID-19 in the patient for the need for close follow-up and protection of the surgical and anaesthesiology team.


Coronavirus Infections and Type 2 Diabetes-Shared Pathways with Therapeutic Implications

Abstract: Individuals with diabetes are at increased risk for bacterial, mycotic, parasitic, and viral infections. The severe acute respiratory syndrome (SARS)-CoV-2 (also referred to as COVID-19) coronavirus pandemic highlights the importance of understanding shared disease pathophysiology potentially informing therapeutic choices in individuals with type 2 diabetes (T2D). Two coronavirus receptor proteins, angiotensin-converting enzyme 2 (ACE2) and dipeptidyl peptidase-4 (DPP4) are also established transducers of metabolic signals and pathways regulating inflammation, renal and cardiovascular physiology, and glucose homeostasis. Moreover, glucose-lowering agents such as the DPP4 inhibitors, widely used in subjects with T2D, are known to modify the biological activities of multiple immunomodulatory substrates. Here, we review the basic and clinical science spanning the intersections of diabetes, coronavirus infections, ACE2, and DPP4 biology, highlighting clinical relevance and evolving areas of uncertainty underlying the pathophysiology and treatment of T2D in the context of coronavirus infection.


Phenotypic characteristics and prognosis of inpatients with COVID-19 and diabetes: the CORONADO study

Abstract: AIMS/HYPOTHESIS: Coronavirus disease-2019 (COVID-19) is a life-threatening infection caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus. Diabetes has rapidly emerged as a major comorbidity for COVID-19 severity. However, the phenotypic characteristics of diabetes in COVID-19 patients are unknown. METHODS: We conducted a nationwide multicentre observational study in people with diabetes hospitalised for COVID-19 in 53 French centres in the period 10-31 March 2020. The primary outcome combined tracheal intubation for mechanical ventilation and/or death within 7 days of admission. Age- and sex-adjusted multivariable logistic regressions were performed to assess the prognostic value of clinical and biological features with the endpoint. ORs are reported for a 1 SD increase after standardisation. RESULTS: The current analysis focused on 1317 participants: 64.9% men, mean age 69.8 ± 13.0 years, median BMI 28.4 (25th-75th percentile: 25.0-32.7) kg/m2; with a predominance of type 2 diabetes (88.5%). Microvascular and macrovascular diabetic complications were found in 46.8% and 40.8% of cases, respectively. The primary outcome was encountered in 29.0% (95% CI 26.6, 31.5) of participants, while 10.6% (9.0, 12.4) died and 18.0% (16.0, 20.2) were discharged on day 7. In univariate analysis, characteristics prior to admission significantly associated with the primary outcome were sex, BMI and previous treatment with renin-angiotensin-aldosterone system (RAAS) blockers, but not age, type of diabetes, HbA1c, diabetic complications or glucose-lowering therapies. In multivariable analyses with covariates prior to admission, only BMI remained positively associated with the primary outcome (OR 1.28 [1.10, 1.47]). On admission, dyspnoea (OR 2.10 [1.31, 3.35]), as well as lymphocyte count (OR 0.67 [0.50, 0.88]), C-reactive protein (OR 1.93 [1.43, 2.59]) and AST (OR 2.23 [1.70, 2.93]) levels were independent predictors of the primary outcome. Finally, age (OR 2.48 [1.74, 3.53]), treated obstructive sleep apnoea (OR 2.80 [1.46, 5.38]), and microvascular (OR 2.14 [1.16, 3.94]) and macrovascular complications (OR 2.54 [1.44, 4.50]) were independently associated with the risk of death on day 7. CONCLUSIONS/INTERPRETATIONS: In people with diabetes hospitalised for COVID-19, BMI, but not long-term glucose control, was positively and independently associated with tracheal intubation and/or death within 7 days. TRIAL REGISTRATION: clinicaltrials.gov NCT04324736.


The Relationship between Diabetes Mellitus and COVID-19 Prognosis: A Retrospective Cohort Study in Wuhan, China

Abstract: BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease, first appeared in Wuhan, China, and quickly spread throughout the world. We aimed to understand the relationship between diabetes mellitus and the prognosis of COVID-19. METHODS: Demographic, clinical, laboratory, radiologic, treatments, complications, and clinical outcomes data were extracted from electronic medical records and compared between diabetes (n=84) and non-diabetes (n=500) groups. Kaplan-Meier method and multivariate Cox analysis were applied to determine the risk factors for the prognosis of COVID-19. RESULTS: Compared to non-diabetic patients, diabetic patients had higher levels of neutrophils (pâ¯=â¯0.014), c-reactive protein (pâ¯=â¯0.008), procalcitonin (p < 0.01), and D-dimer (pâ¯=â¯0.033), and lower levels of lymphocytes (pâ¯=â¯0.032) and albumin (pâ¯=â¯0.035). Furthermore, diabetic patients had a significant higher incidence of bilateral pneumonia (86.9%, pâ¯=â¯0.020). In terms of complications and clinical outcomes, the incidence of respiratory failure (36.9% vs. 24.2%, pâ¯=â¯0.022), acute cardiac injury (47.4% vs. 21.2%, p < 0.01) and death (20.2% vs. 8.0%, pâ¯=â¯0.001) in the diabetes group was significantly higher than that in non-diabetes group. Kaplan-Meier survival curve showed that COVID-19 patients with diabetes had a shorter overall survival time. Multivariate Cox analysis indicated that diabetes (HR 2.180, pâ¯=â¯0.031) was an independent risk factor for COVID-19 prognosis. In subgroup analysis, we divided diabetic patients into insulin required and non-insulin required groups according to whether they needed insulin, and found that diabetic patients requiring insulin may have a higher risk of disease progression and worse prognosis after the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). CONCLUSIONS: Diabetes is an independent risk factor for the prognosis of COVID-19. More attention should be paid to the prevention and treatment for diabetic patients, especially those who require insulin therapy.


Letter to the Editor: Mechanisms of increased morbidity and mortality of SARS-CoV-2 infection in individuals with diabetes: what this means for an effective management strategy


Letter to the editor in response to article: "Clinical considerations for patients with diabetes in times of COVID-19 epidemic (Gupta et al.)


Challenges of diabetes care management in developing countries with a high incidence of COVID-19: A brief report

Abstract: BACKGROUND AND AIMS: Diabetes mellitus (DM) is one of the most critical risk factors for complications and death in COVID-19 patients. The present study aims to highlight challenges in the management of diabetic patients during the COVID-19 outbreak in developing countries. METHODS: We reviewed the literature to obtain information about diabetic care during the Covid-19 crisis. We also seek opinions of clinicians working in undeveloped countries. RESULTS: Current challenges faced by clinicians in the management of diabetic patients in developing countries are as follows: lack of preventive measures, inadequate number of visits, loss of the traditional method of communication with the patient, shortage of medications, impaired routine diabetic care, and absence of telehealth services. CONCLUSIONS: Developing countries are faced with many challenges in diabetes management due to a lack of resources.


Newly diagnosed diabetes is associated with a higher risk of mortality than known diabetes in hospitalized patients with COVID-19

Abstract: AIM: To evaluate the association between different degrees of hyperglycaemia and the risk of all-cause mortality among hospitalized patients with COVID-19. MATERIALS AND METHODS: In a retrospective study conducted from 22 January to 17 March 2020, 453 patients were admitted to Union Hospital in Wuhan, China, with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection. Patients were classified into four categories: normal glucose, hyperglycaemia (fasting glucose 5.6-6.9 mmol/L and/or HbA1c 5.7%-6.4%), newly diagnosed diabetes (fasting glucose ≥7 mmol/L and/or HbA1c ≥6.5%) and known diabetes. The major outcomes included in-hospital mortality, intensive care unit (ICU) admission and invasive mechanical ventilation (IMV). RESULTS: Patients with newly diagnosed diabetes constituted the highest percentage to be admitted to the ICU (11.7%) and require IMV (11.7%), followed by patients with known diabetes (4.1%; 9.2%) and patients with hyperglycaemia (6.2%; 4.7%), compared with patients with normal glucose (1.5%; 2.3%), respectively. The multivariable-adjusted hazard ratios of mortality among COVID-19 patients with normal glucose, hyperglycaemia, newly diagnosed diabetes and known diabetes were 1.00, 3.29 (95% confidence interval [CI] 0.65-16.6), 9.42 (95% CI 2.18-40.7) and 4.63 (95% CI 1.02-21.0), respectively. CONCLUSION: We showed that COVID-19 patients with newly diagnosed diabetes had the highest risk of all-cause mortality compared with COVID-19 patients with known diabetes, hyperglycaemia and normal glucose. Patients with COVID-19 need to be kept under surveillance for blood glucose screening.


Impact of diabetes mellitus on clinical outcomes in patients affected by Covid-19

Abstract: A possible association could exist between type 2 diabetes mellitus (T2DM) and Coronavirus-19 (Covid-19) infection. Indeed, patients with T2DM show high prevalence, severity of disease and mortality during Covid-19 infection. However, the rates of severe disease are significantly higher in patients with diabetes compared with non-diabetes (34.6% vs. 14.2%; p < 0.001). Similarly, T2DM patients have higher rates of need for Intensive Care Unit (ICU, 37.0% vs. 26.7%; p = 0.028). Thus, about the pneumonia of Covid-19, we might speculate that the complicated alveolar-capillary network of lungs could be targeted by T2DM micro-vascular damage. Therefore, T2DM patients frequently report respiratory symptoms and are at increased risk of several pulmonary diseases. In addition, pro-inflammatory pathways as that involving interleukin 6 (IL-6), could be a severity predictor of lung diseases. Therefore, it looks intuitive to speculate that this condition could explain the growing trend of cases, hospitalization and mortality for patients with T2DM during Covid-19 infection. To date, an ongoing experimental therapy with monoclonal antibody against the IL-6 receptor in Italy seems to have beneficial effects on severe lung disease and prognosis in patients with Covid-19 infection. Therefore, should patients with T2DM be treated with more attention to glycemic control and monoclonal antibody against the IL-6 receptor during the Covid-19 infection?


Diabetes and covid-19: a global health challenge


Coping with diabetes during the COVID - 19 lockdown in India: Results of an online pilot survey

Abstract: AIM: The management of diabetes has become a challenge due to the COVID 19 lockdown. An online-based pilot survey was conducted to study how people with diabetes were coping with their Diabetes during the COVID - 19 lockdown. METHOD: The questions were designed in an online survey, Survey Monkey, to conduct this cross-sectional study. The link was generated and sent to 100 registered patients of the MV Hospital for Diabetes Royapuram who had not contacted the hospital after the lockdown announcement. The survey was done between April 1 and April 15, 2020.Oral consent was obtained through telephone before the link was sent by Whatsapp to them.The questionnaire consisted of questions on home blood glucose monitoring, regularity in doing their physical activity and dietary compliance and anxiety about the viral infection. RESULTS: 92% of the participants had Type 2 diabetes. Only 28% of the participants were checking their blood glucose levels regularly. 80% of the participants mentioned that they were following regular exercise and diet control during the lockdown period. 40% of the participants were anxious about the Covid infection. CONCLUSION: SMBG needs to be practiced on regular basis, especially among the patients with diabetes on insulin therapy. Most of the people surveyed were coping well with their Diabetes. Patients have reported that they were able to maintain proper dietary compliance and be more physically active at home during this lockdown. These findings need to be ascertained in larger sample of patients.


COVID-19 in diabetic patients: Related risks and specifics of management

Abstract: Diabetes is among the most frequently reported comorbidities in patients infected with COVID-19. According to current data, diabetic patients do not appear to be at increased risk of contracting SARS-CoV-2 compared to the general population. On the other hand, diabetes is a risk factor for developing severe and critical forms of COVID-19, the latter requiring admission to an intensive care unit and/or use of invasive mechanical ventilation, with high mortality rates. The characteristics of diabetic patients at risk for developing severe and critical forms of COVID-19, as well as the prognostic impact of diabetes on the course of COVID-19, are under current investigation. Obesity, the main risk factor for incident type 2 diabetes, is more common in patients with critical forms of COVID-19 requiring invasive mechanical ventilation. On the other hand, COVID-19 is usually associated with poor glycemic control and a higher risk of ketoacidosis in diabetic patients. There are currently no recommendations in favour of discontinuing antihypertensive medications that interact with the renin-angiotensin-aldosterone system. Metformin and SGLT2 inhibitors should be discontinued in patients with severe forms of COVID-19 owing to the risks of lactic acidosis and ketoacidosis. Finally, we advise for systematic screening for (pre)diabetes in patients with proven COVID-19 infection.


Practical recommendations for the management of diabetes in patients with COVID-19

Abstract: Diabetes is one of the most important comorbidities linked to the severity of all three known human pathogenic coronavirus infections, including severe acute respiratory syndrome coronavirus 2. Patients with diabetes have an increased risk of severe complications including Adult Respiratory Distress Syndrome and multi-organ failure. Depending on the global region, 20-50% of patients in the coronavirus disease 2019 (COVID-19) pandemic had diabetes. Given the importance of the link between COVID-19 and diabetes, we have formed an international panel of experts in the field of diabetes and endocrinology to provide some guidance and practical recommendations for the management of diabetes during the pandemic. We aim to briefly provide insight into potential mechanistic links between the novel coronavirus infection and diabetes, present practical management recommendations, and elaborate on the differential needs of several patient groups.


Letter to the Editor in Response to article: "Clinical considerations for patients with diabetes in times of COVID-19 epidemic (Gupta et al.)"


Infección por coronavirus en pacientes con diabetes

Abstract: Diabetes mellitus is a complex, multifactorial, chronic disease characterized by impaired metabolism of glucose, fats and proteins Patients who suffer from it frequently have hyperglycemia and coronary artery disease is the leading cause of death The comorbidities associated with diabetes are overweight and obesity, systemic arterial hypertension, atherogenic dyslipidemia and in some patients peripheral vascular disease, kidney damage, neuropathy and retinopathy Chronic lack of control of the disease is associated with increased susceptibility to infections, which generally have few symptoms, but hyperglycemia is generally magnified, which worsens the course of infections Since December 2019, when the disease caused by one of the coronaviruses (coronavirus 2 of severe acute respiratory syndrome, SARS-CoV-2) was identified and has been called coronavirus disease 2019 (COVID-19), there have been some reports that associate the presence of diabetes with an increased risk of mortality In this review article we have focused on four specific points: 1) epidemiology of the prevalence and mortality of COVID 19 in the general population and in the population with type 2 diabetes mellitus;2) pathophysiology related to the binding of SARS-CoV-2 to receptors in subjects with diabetes;3) the immune response induced by SARS-CoV-2, and 4) the outpatient and hospital treatment recommended in patients with diabetes who become infected with SARS-CoV-2


Characteristics and outcomes of COVID-19 positive patients with diabetes managed as outpatients

Abstract: We analyzed disease outcomes for patients with diabetes and laboratory-confirmed COVID-19 who were managed outpatient and followed by the Emory COVID-19 Virtual Outpatient Management Clinic (ECVOMC). The rate of hospitalization for patients with diabetes was double the overall rate of hospitalization for patients in the ECVOMC.


Influence of diabetes mellitus on the severity and fatality of SARS-CoV-2 (COVID-19) infection

Abstract: AIM: To evaluate the influence of diabetes on the severity and fatality of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. MATERIALS AND METHODS: The medical records of 66 hospitalized coronavirus disease 2019 (COVID-19) patients were collected and classified into non-severe (mild/moderate cases) and severe (severe/critical cases) groups. Logistic regression analysis was used to estimate the risk of severe COVID-19 (severe/critical infection). In addition, a meta-analysis including published studies reported the impact of diabetes on the severity and fatality of COVID-19. The current study was conducted using fixed effects models. RESULTS: There were 22 diabetes and 44 non-diabetes cases among the 66 hospitalized COVID-19 patients. Seven patients with diabetes (31.82%) were diagnosed as severe COVID-19 cases, which was significantly higher than that in the non-diabetes group (4/44, 9.09%, P = .033). After adjustment for age and gender, diabetes was significantly associated with COVID-19 severity (OR: 5.29, 95% CI: 1.07-26.02). A meta-analysis further confirmed the positive association between diabetes and COVID-19 severity (pooled OR = 2.58, 95% CI: 1.93-3.45). Moreover, the patients with diabetes infected with SARS-CoV-2 had a 2.95-fold higher risk of fatality compared with those patients without diabetes (95% CI: 1.93-4.53). CONCLUSIONS: Our findings provide new evidence that diabetes is associated with a higher risk of severity and fatality of COVID-19. Therefore, intensive monitoring and antidiabetic therapy should be considered in patients with diabetes with SARS-CoV-2 infection.


The Silver Lining to COVID-19: Avoiding Diabetic Ketoacidosis Admissions with Telehealth

Abstract: Background: The Stay at Home order in Colorado and The Stay Safe at Home order in California during COVID-19 pandemic have forced a majority of the endocrinologists/diabetologists to adapt to providing diabetes care remotely through telehealth. This may provide increased access to diabetes health care in certain settings. However, health care disparities continue to challenge availability of diabetes technologies for underprivileged communities. We report our experience with two patients providing diabetes care effectively and preventing hospital admissions by using telehealth. Methods: Two adult patients with type 1 diabetes (T1D): one new onset and the other one with established T1D are presented where telehealth facilitated by Clarity Software and the "Share" feature with the use of Dexcom G6 continuous glucose monitoring (CGM) for management of diabetic ketosis and hyperglycemia. Results: Both patients were managed effectively virtually despite higher risk of diabetic ketoacidosis (DKA). Shared glucose data through CGM facilitated frequent insulin dose adjustments, increased fluid and carbohydrate intake, and prevented hospital admissions in both cases. In the case of new onset patient with T1D, most of the education was done remotely by certified diabetes care and education specialists. Conclusion: Acute diabetes complication like DKA increases morbidity and mortality in addition to adding cost to the health care system. The current pandemic of COVID-19 has allowed newer ways (with the help of newer technologies) to manage high-risk patients with T1D and DKA through telehealth and may result in lasting benefits to people with T1D.


Dissecting the Interaction between Coronavirus Disease 2019 and Diabetes Mellitus

Abstract: Coronavirus disease 2019 (COVID-19) is a global pandemic that is caused by a novel coronavirus, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Data from several countries have demonstrated higher morbidity and mortality among individuals with chronic metabolic diseases such as diabetes mellitus (DM). In this review, we explore the contributing factors for poorer prognosis in these individuals. As a significant proportion of patients with COVID-19 also have DM, this adds another layer of complexity to their management. We explore potential interactions between anti-diabetic medications and renin-angiotensin-aldosterone-system inhibitors with COVID-19. Suggested recommendations for the use of anti-diabetic medications in COVID-19 patients with DM are provided. We also review pertinent clinical considerations in the management of diabetic ketoacidosis in the COVID-19 patient. In addition, we aim to increase the awareness of clinicians to the metabolic effects of promising drug therapies for COVID-19. Finally, we highlight the importance of timely vaccinations for patients with DM.


Management of diabetic persons with foot ulceration during COVID-19 health care emergency: Effectiveness of a new triage pathway

Abstract: AIM: To define the outcomes of persons with diabetes and foot ulcers (DFUs) managed through a specific triage pathway during the COVID-19 crisis. METHODS: Patients who had an active DFU during the COVID-19 emergency were included. All participants were managed using a specific triage system driven both by ulcer'severity and concomitant co-diseases. Subjects with severely complicated DFUs were urgently referred to hospital regardless of the concomitant comorbidities. Subjects with complicated DFUs received outpatient evaluation (within 48-72 h) and were admitted to hospital if required (revascularization, surgical intervention, intravenous antibiotic therapy); after the first outpatient visit or hospitalization, patients were followed according to the number of comorbidities (in the case of 3 or more comorbidities patients were followed up by telemedicine). Patients with uncomplicated DFUs were managed by telemedicine after outpatient evaluation. Healing, major amputation, death and rate of COVID-19 infection were evaluated. The minimum follow-up was 1 month. RESULTS: The study group included 151 patients. The mean age was 69.9 ± 14.2 years, 58.9% were male and 91.4% had type 2 diabetes; 58.7% had severely complicated, 21% complicated and 20.3% uncomplicated DFUs. Among those, 78.8% presented with 3 or more comorbidities. One hundred and six patients had regular clinical follow-ups, while 45 were managed through telemedicine. Forty-one (27.1%) patients healed, 3 (1.9%) had major amputations and 3 (1.9%) died. One patient (0.6%) reported COVID-19 positivity due to infection acquired at home. CONCLUSION: The triage pathway adopted during the COVID-19 pandemic showed adequate management of DFUs and no cases of hospital virus exposure.


Diabetic ketoacidosis precipitated by Covid-19 in a patient with newly diagnosed diabetes mellitus


Saving the Diabetic Foot During the COVID-19 Pandemic: A Tale of Two Cities

Abstract: Of all the late complications of diabetes, those involving the foot have traditionally required more face-to-face patient visits to clinics to treat wounds by debridement, offloading, and many other treatment modalities. The advent of the coronavirus disease 2019 (COVID-19) pandemic has resulted not only in the closing of most outpatient clinics for face-to-face consultations but also in the inability to perform most laboratory and imaging investigations. This has resulted in a paradigm shift in the delivery of care for those with diabetic foot ulcers. The approaches to this challenge in two centers with an interest in diabetic foot disease, including virtual consultations using physician-to-patient and physician-to-home nurse telemedicine as well as home podiatry visits, are described in this review and are illustrated by several case vignettes. The outcomes from these two centers suggest that we may be witnessing new possibilities in models of care for the diabetic foot.


Diabetes or endocrinopathy admitted in the COVID-19 ward

Abstract: The Covid-19 pandemic confronted us with unknown clinical pictures, also in diabetology and endocrinology. Sharing clinical experiences is therefore of enormous importance. Actually, information about the care given in the Covid-19 ward (in contrast to that provided in the Emergency Room/ICU) is still sparse. The last weeks we built experience and gathered knowledge while giving hospital care to patients who had a pre-existent endocrine disease (and diabetes; most patients suffered from a type two diabetes). In our contribution we presented our insights obtained from this intensive period obtained in the Covid-19 ward.


Prognostic value of Cardiac Biomarkers in COVID-19 Infection: A Meta-analysis

Abstract: Background Multiple Biomarkers have recently been shown to be elevated in COVID-19, a respiratory infection with multi-organ dysfunction; however, information regarding the prognostic value of cardiac biomarkers as it relates to disease severity and cardiac injury are inconsistent. Research Question The goal of this meta-analysis was to summarize the evidence regarding the prognostic relevance of cardiac biomarkers from data available in published reports. Study Design and Methods PubMed was searched from inception through April 2020 for studies comparing median values of cardiac biomarkers in critically ill versus non-critically ill COVID-19 patients, or patients who died versus those who survived. The weighted mean differences (WMD) and 95% confidence interval (CI) between the groups were calculated for each study and combined using a random effects meta-analysis model. The odds ratio (OR) for mortality based on cardiac injury was combined from studies reporting it. Results Troponin levels were significantly higher in COVID-19 patients who died or were critically ill versus those who were alive or not critically ill (WMD 0.58, 95% CI 0.42-0.71, p<0.001). Cardiac injury was independently associated with significantly increased odds of mortality (OR 6.641, 95% CI 1.26 - 35.1, p=0.03). No difference in BNP was seen between the two groups. A significant difference in levels of D-dimer was seen in those who died or were critically ill. CK levels were only significantly higher in those who died versus those who were alive (WMD 0.47 95% CI 0.09-0.84, p=0.014). Interpretation Cardiac biomarkers add prognostic value to the determination of the severity of COVID-19 and can predict mortality.


A comprehensive appraisal of laboratory biochemistry tests as major predictors of COVID-19 severity.

Abstract: Context: A relevant portion of COVID-19 patients develop severe disease with negative outcomes. Several biomarkers have been proposed to predict COVID-19 severity, but no definite interpretative criteria have been established to date for stratifying risk. Objective: To evaluate six serum biomarkers (C-reactive protein, lactate dehydrogenase, D-dimer, albumin, ferritin and cardiac troponin T) for predicting COVID-19 severity and to define related cut-offs able to aid clinicians in risk stratification of hospitalized patients. Design: A retrospective study of 427 COVID-19 patients was performed. Patients were divided into groups based on their clinical outcome: non-survivors vs. survivors and patients admitted to intensive care unit vs. others. ROC curves and likelihood ratios were employed to define predictive cut-offs for evaluated markers. Results: Marker concentrations at peak were significantly different between groups for both selected outcomes. At univariate logistic regression analysis, all parameters were significantly associated with higher odds of death and intensive care. At the multivariate analysis, high concentrations of lactate dehydrogenase and low concentrations of albumin in serum remained significantly associated with higher odds of death, while only low lactate dehydrogenase activities remained associated with lower odds of intensive care admission. The best cut-offs for death prediction were >731 U/L for lactate dehydrogenase and ≤18 g/L for albumin, while a lactate dehydrogenase activity <425 U/L was associated with a negative likelihood ratio of 0.10 for intensive treatment. Conclusions: Our study identifies which biochemistry tests represent major predictors of COVID-19 severity and defines the best cut-offs for their use.


Prediction of the severity of Corona Virus Disease 2019 and its adverse clinical outcomes.

Abstract: This study aims to investigate blood and biochemical laboratory findings in patients with severe Corona Virus Disease 2019 (COVID-19) and to develop a joint predictor for predicting the likelihood of severe COVID-19 and its adverse clinical outcomes, to provide more information for treatment. We collected the data of 88 patients with laboratory-confirmed COVID-19. Then patients were divided into a non-severe group and a critical group (including critically ill cases). Univariate analysis showed that the absolute lymphocyte count, albumin level, albumin/globulin (A/G) ratio, lactate dehydrogenase (LDH) level, interleukin-6 (IL-6) level, erythrocyte count, globulin level, blood glucose level, and age were significantly correlated with the severity of COVID-19. The multivariate binary logistic regression model revealed that Age, absolute lymphocyte count, and IL-6 level were independent risk factors in patients with COVID-19. The receiver operating characteristic (ROC) curve revealed that the combination of IL-6 level, absolute lymphocyte count and age is superior to a single factor as predictors for predicting severe COVID-19, regardless of whether it is the area under curve (AUC) or the prediction sensitivity and specificity. Early application is beneficial to early identification of critically ill patients and timing individual treatments to reduce mortality.


[Value of neutrophil-to-lymphocyte ratio in the classification diagnosis of coronavirus disease 2019].

Abstract: OBJECTIVE To investigate the clinical significance of neutrophil-to-lymphocyte ratio (NLR) in classification of patients with coronavirus disease 2019 (COVID-19). METHODS A retrospective analysis was performed on 72 patients with COVID-19 admitted to the critical ward of Cancer Center of Union Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology in Wuhan from February to March in 2020. The patients were divided into two groups: moderate type (non-severe group) and severe/critical type (severe group). The results of white blood cell count (WBC), neutrophil count (NEU), lymphocyte count (LYM), interleukin-6 (IL-6) and D-dimer were collected at the 2nd day after admission from the two groups, and the NLR was calculated. The diagnostic value of WBC, NEU, LYM, IL-6, D-dimer and NLR on COVID-19 classification was evaluated by the receiver operating characteristic (ROC) curve. RESULTS A total of 72 COVID-19 patients were enrolled, among whom 52 were moderate, 17 were severe, and 3 were critical. The most common clinical manifestations of patients were fever (70.8%), cough (36.1%), chest tightness and breathlessness (37.5%), diarrhea (15.3%), fatigue (15.3%), vomiting and nausea (11.1%), occasionally accompanied by acute dyspnea (2.8%), and only one patient had no clinical symptom (1.4%). The levels of WBC, NEU, IL-6, D-dimer and NLR in the severe group were significantly higher than those in the non-severe group [WBC (×109/L): 7.81±3.65 vs. 5.34±1.69, NEU (×109/L): 5.83±3.13 vs. 3.24±1.53, IL-6 (ng/L): 133.63 (71.09, 249.61) vs. 28.05 (6.41, 101.24), D-dimer (mg/L): 0.86 (0.31, 2.56) vs. 0.33 (0.20, 0.71), NLR: 6.14±4.75 vs. 2.66±1.93, all P < 0.05], and the level of LYM was significantly lower than that in the non-severe group (×109/L: 1.09±0.56 vs. 1.49±0.74, P < 0.05). The results of ROC curve analysis showed that the areas under ROC curve (AUC) of WBC, NEU, LYM, IL-6, D-dimer and NLR for COVID-19 classification were 0.790 [95% confidence interval (95%CI) was 0.684-0.897), 0.869 (95%CI was 0.789-0.949), 0.719 (95%CI was 0.592-0.847), 0.790 (95%CI was 0.682-0.898), 0.676 (95%CI was 0.526-0.827), and 0.888 (95%CI was 0.814-0.963) respectively. The AUC of NLR was the highest, which was of high diagnostic value; when the optimum cut-off value of NLR was 3.00, the sensitivity was 100%, and the specificity was 73.1%. CONCLUSIONS NLR can be used as a biomarker to predict classification of COVID-19 patients independently, which can provide a theoretical basis for the classification management of COVID-19 patients.


[Analysis of clinical features of 29 patients with 2019 novel coronavirus pneumonia].

Abstract: Objective: To analyze the clinical characteristics of 2019 novel coronavirus (2019-nCoV) pneumonia and to investigate the correlation between serum inflammatory cytokines and severity of the disease. Methods: 29 patients with 2019-ncov admitted to the isolation ward of Tongji hospital affiliated to Tongji medical college of Huazhong University of Science and Technology in January 2020 were selected as the study subjects. Clinical data were collected and the general information, clinical symptoms, blood test and CT imaging characteristics were analyzed. According to the relevant diagnostic criteria, the patients were divided into three groups: mild (15 cases), severe (9 cases) and critical (5 cases). The expression levels of inflammatory cytokines and other markers in the serum of each group were detected, and the changes of these indicators of the three groups were compared and analyzed, as well as their relationship with the clinical classification of the disease. Results: (1) The main symptoms of 2019-nCoV pneumonia was fever (28/29) with or without respiratory and other systemic symptoms. Two patients died with underlying disease and co-bacterial infection, respectively. (2) The blood test of the patients showed normal or decreased white blood cell count (23/29), decreased lymphocyte count (20/29), increased hypersensitive C reactive protein (hs-CRP) (27/29), and normal procalcitonin. In most patients, serum lactate dehydrogenase (LDH) was significantly increased (20/29), while albumin was decreased (15/29). Alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (Tbil), serum creatinine (Scr) and other items showed no significant changes. (3) CT findings of typical cases were single or multiple patchy ground glass shadows accompanied by septal thickening. When the disease progresses, the lesion increases and the scope expands, and the ground glass shadow coexists with the solid shadow or the stripe shadow. (4) There were statistically significant differences in the expression levels of interleukin-2 receptor (IL-2R) and IL-6 in the serum of the three groups (P<0.05), among which the critical group was higher than the severe group and the severe group was higher than the mild group. However, there were no statistically significant differences in serum levels of tumor necrosis factor-alpha (TNF-α), IL-1, IL-8, IL-10, hs-CRP, lymphocyte count and LDH among the three groups (P>0.05). Conclusion: The clinical characteristics of 2019-nCoV pneumonia are similar to those of common viral pneumonia. High resolution CT is of great value in the differential diagnosis of this disease. The increased expression of IL-2R and IL-6 in serum is expected to predict the severity of the 2019-nCoV pneumonia and the prognosis of patients.


The Association Between Biomarkers and Clinical Outcomes in Novel Coronavirus (COVID-19) Pneumonia in a U.S. Cohort

Abstract: Background: The global pandemic caused by COVID-19 remains poorly understood by clinicians. Identifying biologic markers associated with prognosis can help clinicians recognize disease severity. Objective: To describe the association between D-dimer, CRP, IL-6, ferritin, LDH, and clinical outcomes in a cohort of COVID-19 patients treated on the inpatient medical service at a university hospital in Washington, DC. Design: In this retrospective study, we included all adults admitted to the inpatient medicine service at George Washington University Hospital between March 12, 2020 and May 9, 2020 with laboratory confirmed COVID-19. Clinical and laboratory data were extracted from electronic medical records and compared between survivors not requiring ICU transfer, survivors requiring ICU transfer, survivors requiring intubation, and non-survivors. Key Results: 299 patients were included in our study, of whom 69 required transfer to the ICU, 39 required intubation, and 71 died. Threshold values for IL-6 (>50 pg/mL), D-dimer (>3 mcg/mL), ferritin (>450 ng/mL), CRP (>100 mg/L), and LDH (1,200 u/L) were found to be statistically significant and independently associated with higher odd of clinical deterioration and death. Hypertension, CVA and heart disease independently had an increased risk of all three outcomes, while CKD had only an increased risk of death. Patient co-morbidities had no effect on the different biomarkers' significant association with poor patient clinical outcomes, except cancer. Conclusion: Laboratory markers of inflammation and coagulopathy can help clinicians identify patients who are at high risk for clinical deterioration, independent of clinically significant medical comorbidities


The role of comorbidities and clinical predictors of severe disease in COVID-19: a systematic review and meta-analysis

Abstract: Background COVID_19 is unpredictable due to non-specific symptoms and clinical course diversity in different individuals. We analyzed studies regarding the factors associated with severe status of the disease to identify unique findings in severely affected patients. Methods We systematically searched the electronic databases, including PubMed, Scopus, EMBASE, Web of Science, and Google Scholar from inception to 12th of March 2020. Cochranes Q and I-square statistics were used to assess the existence of heterogeneity between the included studies. We used the random-effects model to pool the odds ratios (ORs) at 95% confidence intervals (CIs). Results Seventeen articles out of 3009 citations were included. These contained 3189 patients, of whom 732 were severely affected (severe group) and 3189 were in non-severe group. Using the random-effects model, our meta-analyses showed that the odds of comorbidities, including COPD, DM, HTN, CVD, CKD, and symptoms, including dyspnea, dizziness, anorexia, and cough, were significantly higher among the severe group compared with the non-severe group. There were no significant changes in odds of CVA, liver disease, immunodeficiency/immunosuppression, fever, fatigue, myalgia, headache, diarrhea, sore throat, nasal congestion, sputum, nausea, vomiting, chest pain between the two groups. Conclusions Early recognition and intervention can be critical in management, and might stop progression to severe disease. Predictive symptoms and comorbidities can be used as a predictor in patients who are at risk of severe disease.


Blood biomarker score identifies individuals at high risk for severe COVID-19 a decade prior to diagnosis: metabolic profiling of 105,000 adults in the UK Biobank

Abstract: Background: Identification of healthy people at high risk for severe COVID-19 is a global health priority. We investigated whether blood biomarkers measured by high-throughput metabolomics could be predictive of severe pneumonia and COVID-19 hospitalisation years after the blood sampling. Methods: Nuclear magnetic resonance metabolomics was used to quantify a comprehensive biomarker profile in 105,146 plasma samples collected in the UK Biobank during 2007-2010 (age range 39-70). The biomarkers were tested for association with severe pneumonia (2507 cases, defined as diagnosis in hospital or death record occurring during a median of 8.1-year follow-up) and with severe COVID-19 (195 cases, defined as diagnosis in hospital between mid-March to mid-June 2020). A multi-biomarker score was derived for prediction of severe pneumonia based on half of the study population and validated in the other half. We explored how this biomarker score relates to the risk of severe COVID-19. Findings: The biomarker associations with risk of severe COVID-19 followed an overall pattern similar to associations with risk of severe pneumonia (correlation 0.83). The multi-biomarker score, comprised of 25 blood biomarkers including inflammatory proteins, fatty acids, amino acids and advanced lipid measures, was strongly associated with risk of severe pneumonia (odds ratio 1.67 per standard deviation [95% confidence interval 1.59-1.76]; 3.8-fold risk increase for individuals in upper vs lower quintile). The multi-biomarker score was also associated with risk of severe COVID-19 (odds ratio 1.33 [1.17-1.53]; 2.5-fold risk for upper vs lower quintile) and remained significant when adjusting for body mass index, smoking, and existing respiratory and cardiometabolic diseases. Mimicking the decade lag from blood sampling to COVID-19, severe pneumonia events occurring after 7-11 years associated with the multi-biomarker score to a similar magnitude (odds ratio 1.43 [1.29-1.59]; 2.6-fold risk for upper vs lower quintile) as for severe COVID-19. However, the short-term risk of severe pneumonia events associated to the multi-biomarker score at even 3 times higher magnitude (odds ratio 2.21 [1.95-2.50]; 8.0-fold risk for upper vs lower quintile in analysis of the first 2 years after blood sampling). Interpretation: In decade-old blood samples from the UK Biobank, a biomarker score measured by high-throughput metabolomics is indicative of the risk for severe COVID-19. The molecular signature of biomarker changes reflective of risk for severe COVID-19 is similar to that for severe pneumonia, in particular when accounting for the time lag to the COVID-19 pandemic. The even stronger association of the biomarker score with 2-year risk for severe pneumonia lends support to promising screening possibilities for identifying people at high risk for severe COVID-19.


Plasma levels of soluble ACE2 are associated with sex, Metabolic Syndrome, and its biomarkers in a large cohort, pointing to a possible mechanism for increased severity in COVID-19

Abstract: We examined the associations between plasma concentrations of soluble ACE2 and biomarkers of Metabolic Syndrome in a large (N=2,051) sample of individuals who participated in a commercial wellness program and who underwent deep molecular phenotyping. sACE2 levels were significantly higher in men, compared to women, and in individuals with Metabolic Syndrome, compared to controls. sACE2 levels showed reliable associations with all individuals components of Metabolic Syndrome, including obesity, hypertension, insulin resistance, hyperlipidemia, and as well as markers of liver damage. This profile of associations was statistically significantly stronger in men, compared to women, and suggests that preexisting cardiometabolic conditions might confer increased severity of symptoms in some COVID-19 patients through increased expression of ACE2 in the liver.


Diagnostic and prognostic value of hematological and immunological markers in COVID-19 infection: A meta-analysis of 6320 patients

Abstract: Objective Evidence-based characterization of the diagnostic and prognostic value of the hematological and immunological markers related to the epidemic of Coronavirus Disease 2019 (COVID-19) is critical to understand the clinical course of the infection and to assess in development and validation of biomarkers. Methods Based on systematic search in Web of Science, PubMed, Scopus, and Science Direct up to April 22, 2020, a total of 52 eligible articles with 6,320 laboratory-confirmed COVID-19 cohorts were included. Pairwise comparison between severe versus mild disease, Intensive Care Unit (ICU) versus general ward admission, and expired versus survivors were performed for 36 laboratory parameters. The pooled standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated using the DerSimonian Laird method/random effects model and converted to Odds ratio (OR). The decision tree algorithm was employed to identify the key risk factor(s) attributed to severe COVID-19 disease. Results Cohorts with elevated levels of white blood cells (WBCs) (OR=1.75), neutrophil count (OR=2.62), D-dimer (OR=3.97), prolonged prothrombin time (PT) (OR=1.82), fibrinogen (OR=3.14), erythrocyte sedimentation rate (OR=1.60), procalcitonin (OR=4.76), IL-6 (OR=2.10), and IL-10 (OR=4.93) had higher odds of progression to severe phenotype. Decision tree model (sensitivity=100%, specificity=81%) showed the high performance of neutrophil count at a cut-off value of more than 3.74 x109/L for identifying patients at high risk of severe COVID-19. Likewise, ICU admission was associated with higher levels of WBCs (OR=5.21), neutrophils (OR=6.25), D-dimer (OR=4.19), and prolonged PT (OR=2.18). Patients with high IL-6 (OR=13.87), CRP (OR=7.09), D-dimer (OR=6.36), and neutrophils (OR=6.25) had the highest likelihood of mortality. Conclusions Several hematological and immunological markers, in particular neutrophilic count, could be helpful to be included within the routine panel for COVID-19 infection evaluation to ensure risk stratification and effective management.


A descriptive study of the impact of diseases control and prevention on the epidemics dynamics and clinical features of SARS-CoV-2 outbreak in Shanghai, lessons learned for metropolis epidemics prevention

Abstract: Objective: To describe and evaluate the impact of diseases control and prevention on epidemics dynamics and clinical features of SARS-CoV-2 outbreak in Shanghai. Design: A retrospective descriptive study Setting: China Participants: Epidemiology information was collected from publicly accessible database. 265 patients admitted to Shanghai Public Health Center with confirmed COVID-19 were enrolled for clinical features analysis. Main outcome measure: Prevention and control measures taken by Shanghai government, epidemiological, demographic, clinical, laboratory and radiology data were collected. Weibull distribution, Chi-square test, Fisher's exact test, t test or Mann-Whitney U test were used in statistical analysis. Results: COVID-19 transmission rate within Shanghai had reduced over 99% than previous speculated, and the exponential growth has been stopped so far. Epidemic was characterized by the first stage mainly composed of imported cases and the second stage where >50% of cases were local. The incubation period was 6.4 (95% CI 5.3 to 7.6) days and the mean onset-admission interval was 5.5 days (95% CI, 5.1 to 5.9). Median time for COVID-19 progressed to severe diseases were 8.5 days (IQR: 4.8-11.0 days). By February 11th, proportion of patients being mild, moderate, severe and critically ill were 1.9%(5/265), 89.8%(238/265), 3.8%(10/265), 4.5%(12/265), respectively; 47 people in our cohort were discharged, and 1 patient died. Conclusion: Strict controlling of the transmission rate at the early stage of an epidemic in metropolis can quickly prohibit the spread of the diseases. Controlling local clusters is the key to prevent outbreaks from imported cases. Most COVID-19 severe cases progressed within 14 days of disease onset. Multiple systemic laboratory abnormalities had been observed before significant respiratory dysfunction. Keyword: COVID-19, SARS-CoV-2, epidemics dynamics, diseases control, clinical features


A link between inflammatory biomarkers and lung ultrasound observations in patients with SARS-CoV-2 infection

Abstract: ABSTRACT: Lung ultrasound (LUS) has shown to correlate well with the findings obtained by chest computed tomography (CT) in acute-phase COVID-19. Although there is a significant correlation between blood biomarkers and CT radiological findings, a potential correlation between biochemical parameters and LUS images is still unknown. Our purpose was to evaluate a potential association between lung lesions visualised by LUS and blood biomarkers as well as the ability to predict mortality from two different lung ultrasound scoring systems (LUSS). We performed a retrospective observational study on 45 patients aged >70 years with SARS-CoV-2 infection who required hospitalisation. LUS was carried out at admission and on day 7, when the clinical course was favourable or earlier in case of worsening. Disease severity was scored by means of LUSS in 8 (LUSS8) and in 12 (LUSS12) quadrants. LUS and blood draw for inflammatory marker analysis were performed at the same time. The correlation between biochemical parameters and either LUSS score was significant for ferritin levels. It was 0.486 (p=0.001) for LUSS8 and 0.458 (p=0.002) for LUSS12. Using a threshold score of 15 with LUSS12 predicted mortality in 86.7% of cases (ORcrude 31, CI 95% 4.79-200.51). Applying a threshold of 10 with LUSS8 predicted mortality in 88.9% (ORcrude 69.75, CI 95% 6.90-705.20). There is a correlation between ferritin levels and LUSS. The prognostic capacity of LUSS12 does not surpass that of LUSS8.


Characteristics of lymphocyte subsets and their predicting values for the severity of COVID-19 patients

Abstract: Severe COVID-19 patients showed worse clinical outcomes compared to mild and moderate patients. However, effective indicators are still lacking to predict the severity of the disease. In the present study, we retrospectively analyzed the clinical and laboratory data of 16 COVID-19 patients and found that the absolute counts of three T-cells (CD3+, CD4+, and CD8+) were significantly lower in the moderate and severe patients than those in mild patients and were significantly lower in severe patients than in moderate patients on admission. With the recovery of the COVID-19, serum levels of inflammatory biomarkers (CRP, PCT, and IL6) of moderate and severe patients gradually decreased. In contrast, the counts of lymphocytes and their subsets including CD3+, CD4+, and CD8+ T cells gradually increased in severe patients, and eventually showed comparable levels with moderate patients. ROC analysis showed that the counts of CD3+, CD4+, and CD8+ T-cells with AUC > 0.9 have potential values for predicting the severity of COVID-19 patients. In conclusion, the reduction of CD3+, CD4+, and CD8+ T-cells is related to the severity of COVID-19 and dynamic detection of these T-lymphocyte subsets may help predict the outcome of the patients.


From Community Acquired Pneumonia to COVID-19: A Deep Learning Based Method for Quantitative Analysis of COVID-19 on thick-section CT Scans

Abstract: Background: Thick-section CT scanners are more affordable for the developing countries. Considering the widely spread COVID-19, it is of great benefit to develop an automated and accurate system for quantification of COVID-19 associated lung abnormalities using thick-section chest CT images. Purpose: To develop a fully automated AI system to quantitatively assess the disease severity and disease progression using thick-section chest CT images. Materials and Methods: In this retrospective study, a deep learning based system was developed to automatically segment and quantify the COVID-19 infected lung regions on thick-section chest CT images. 531 thick-section CT scans from 204 patients diagnosed with COVID-19 were collected from one appointed COVID-19 hospital from 23 January 2020 to 12 February 2020. The lung abnormalities were first segmented by a deep learning model. To assess the disease severity (non-severe or severe) and the progression, two imaging bio-markers were automatically computed, i.e., the portion of infection (POI) and the average infection HU (iHU). The performance of lung abnormality segmentation was examined using Dice coefficient, while the assessment of disease severity and the disease progression were evaluated using the area under the receiver operating characteristic curve (AUC) and the Cohen's kappa statistic, respectively. Results: Dice coefficient between the segmentation of the AI system and the manual delineations of two experienced radiologists for the COVID-19 infected lung abnormalities were 0.74 {+/-} 0.28 and 0.76 {+/-} 0.29, respectively, which were close to the inter-observer agreement, i.e., 0.79 {+/-} 0.25. The computed two imaging bio-markers can distinguish between the severe and non-severe stages with an AUC of 0.9680 (p-value < 0.001). Very good agreement ({kappa} = 0.8220) between the AI system and the radiologists were achieved on evaluating the changes of infection volumes. Conclusions: A deep learning based AI system built on the thick-section CT imaging can accurately quantify the COVID-19 associated lung abnormalities, assess the disease severity and its progressions.


Systemic hypoferraemia and severity of hypoxaemic respiratory failure in COVID-19

Abstract: Coronavirus disease 2019 (COVID-19) mortality is associated with hypoxaemia, multiorgan failure, and thromboinflammation. However severity of disease varies considerably and understanding physiological changes that may link to poor outcomes is important. Although increased serum ferritin has been observed in COVID-19 patients consistent with inflammation, other iron parameters have not been examined to our knowledge. Because iron is required for immunity and oxygen utilisation, and dysregulated iron homeostasis has been observed in COPD, we investigated serum iron concentrations in 30 patients with COVID-19 requiring ICU admission. All patients had low serum iron but patients with severe hypoxemic respiratory failure had more profound hypoferraemia. The area under the curve for receiver operating characteristic curves for serum iron to identify severe hypoxemia was 0.95; the optimal Youden Index for distinguishing between severe and non-severe hypoxemia was a serum iron concentration of 2.9 micromol/L. By linear regression, serum iron was associated with lymphocyte count and PaO2/FiO2. In conclusion, profound hypoferraemia identifies COVID-19 patients with severe hypoxaemia. Serum iron is a simple biomarker that could be usefully employed to stratify patients and monitor disease. Severe hypoferraemia may plausibly impair critical iron-dependent processes such as lymphocyte responses and hypoxia sensing, contributing to pathology, and is potentially treatable.


Validation of reported risk factors for disease classification and prognosis in COVID-19: a descriptive and retrospective study

Abstract: Risk indicators viral load (ORF1ab Ct), lymphocyte percentage (LYM%), C-reactive protein (CRP), interleukin-6 (IL-6), procalcitonin (PCT) and lactic acid (LA) in COVID-19 patients have been proposed in recent studies. However, the predictive effects of those indicators on disease classification and prognosis remains largely unknown. We dynamically measured those reported indicators in 132 cases of COVID-19 patients including the moderate-cured (moderated and cured), severe-cured (severe and cured) and critically ill (died). Our data showed that CRP, PCT, IL-6, LYM%, lactic acid and viral load could predict prognosis and guide classification of COVID-19 patients in different degrees. CRP, IL-6 and LYM% were more effective than other three factors in predicting prognosis. For disease classification, CRP and LYM% were sensitive in identifying the types between critically ill and severe (or moderate). Notably, among the investigated factors, LYM% was the only one that could distinguish between the severe and moderate types. Collectively, we concluded that LYM% was the most sensitive and reliable predictor for disease typing and prognosis. During the COVID-19 pandemic, the precise classification and prognosis prediction are critical for saving the insufficient medical resources, stratified treatment and improving the survival rate of critically ill patients. We recommend that LYM% be used independently or in combination with other indicators in the management of COVID-19.


Time-series plasma cell-free DNA analysis reveals disease severity of COVID-19 patients

Abstract: Symptoms of coronavirus disease 2019 (COVID-19) range from asymptomatic to severe pneumonia and death. Detection of individuals at high risk for critical condition is crucial for control of the disease. Herein, for the first time, we profiled and analyzed plasma cell-free DNA (cfDNA) of mild and severe COVID-19 patients. We found that in comparison between mild and severe COVID-19 patients, Interleukin-37 signaling was one of the most relevant pathways; top significantly altered genes included POTEH, FAM27C, SPATA48, which were mostly expressed in prostate and testis; adrenal glands, small intestines and liver were tissues presenting most differentially expressed genes. Our data thus revealed potential tissue involvement, provided insights into mechanism on COVID-19 progression, and highlighted utility of cfDNA as a noninvasive biomarker for disease severity inspections.


Elevated interleukin-6, interleukin-10 and neutrophil : lymphocyte ratio as identifiers of severe coronavirus disease 2019


The value of clinical parameters in predicting the severity of COVID-19

Abstract: To study the relationship between clinical indexes and the severity of coronavirus disease 2019 (COVID-19), and to explore its role in predicting the severity of COVID-19. Clinical data of 443 patients with COVID-19 admitted to our hospital were retrospectively analyzed, which were divided into nonsevere group (n = 304) and severe group (n = 139) according to their condition. Clinical indicators were compared between different groups. The differences in sex, age, the proportion of patients with combined heart disease, leukocyte, neutrophil-to-lymphocyte ratio (NLR), neutrophil, lymphocyte, platelet, D-dimer, C-reactive protein (CRP), procalcitonin, lactate dehydrogenase, and albumin on admission between the two groups were statistically significant (P < .05). Multivariate logistic regression analysis showed NLR and CRP were independent risk factors for severe COVID-19. Platelets were independent protective factors for severe COVID-19. The receiver operating characteristic (ROC) curve analysis demonstrated area under the curve of NLR, platelet, CRP, and combination was 0.737, 0.634, 0.734, and 0.774, respectively. NLR, CRP, and platelets can effectively assess the severity of COVID-19, among which NLR is the best predictor of severe COVID-19, and the combination of three clinical indicators can further predict severe COVID-19.


Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: A meta-analysis

Abstract: BACKGROUND: Coronavirus disease 2019 (COVID-19) is a novel infectious disease with lack of established laboratory markers available to evaluate illness severity. In this study, we investigate whether platelet count could differentiate between COVID-19 patients with or without severe disease. Additionally, we evaluate if thrombocytopenia is associated with severe COVID-19. METHODS: An electronic search in Medline, Scopus and Web of Science was performed to identify studies reporting data on platelet count in COVID-19 patients. A meta-analysis was performed, with calculation of weighted mean difference (WMD) of platelet number in COVID-19 patients with or without severe disease and odds ratio (OR) of thrombocytopenia for severe form of COVID-19. RESULTS: Nine studies with 1779 COVID-19 patients, 399 (22.4%) with severe disease, were included in the meta-analysis. The pooled analysis revealed that platelet count was significantly lower in patients with more severe COVID-19 (WMD -31 × 109/L; 95% CI, from -35 to -29 × 109/L). A subgroup analysis comparing patients by survival, found an even lower platelet count was observed with mortality (WMD, -48 × 109/L; 95% CI, -57 to -39 × 109/L. In the four studies (n = 1427) which reported data on rate of thrombocytopenia, a low platelet count was associated with over fivefold enhanced risk of severe COVID-19 (OR, 5.1; 95% CI, 1.8-14.6). CONCLUSIONS: Low platelet count is associated with increased risk of severe disease and mortality in patients with COVID-19, and thus should serve as clinical indicator of worsening illness during hospitalization.


Neutrophil to CD4+ lymphocyte ratio as a potential biomarker in predicting virus negative conversion time in COVID-19

Abstract: BACKGROUND: Since December 2019, novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) occurred in Wuhan, and rapidly spread throughout China. Our study aimed to evaluate the robustness of neutrophil to CD4+ lymphocyte ratio (NCD4LR) in predicting the negative conversion time (NCT) of SARS-CoV-2 in COVID-19 patients. METHODS: Univariate and multivariate analysis were conducted to evaluate the independency of NCD4LR in predicting NCT. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) were used to assess the diagnostic accuracy. RESULTS: Compared with low NCD4LR patients, patients with high NCD4LR had an older age; higher incidence of fever, fatigue, chest distress/breath shortness, severer disease assessment on admission; higher levels of inflammatory indicators; low levels of lymphocyte subsets, and a longer NCT. Multivariate analysis also identified NCD4LR as an independent risk factor for delayed NCT. ROC analysis showed that NCD4LR had a better performance than neutrophil to lymphocyte ratio in predicting the virus negative conversion within 2 weeks (AUC = 0.772), 3 weeks (AUC = 0.710), 4 weeks (AUC = 0.728), or 5 weeks (AUC = 0.815). CONCLUSION: This study suggests that NCD4LR is a potential and useful biomarker for predicting the virus negative conversion time in COVID-19 patients. Furthermore, due to the NCDLR value is easily calculated, it can be widely used as a clinical biomarker for disease progression and clinical outcomes in COVID-19 patients.


Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count

Abstract: Concomitant coagulation disorder can occur in severe patients withCOVID-19, but in-depth studies are limited. This study aimed to describe the parameters of coagulation function of patients with COVID-19 and reveal the risk factors of developing severe disease. This study retrospectively analyzed 113patients with SARS-CoV-2 infection in Taizhou Public Health Center. Clinical characteristics and indexes of coagulation function were collected. A multivariate Cox analysis was performed to identify potential biomarkers for predicting disease progression. Based on the results of multivariate Cox analysis, a Nomogram was built and the predictive accuracy was evaluated through the calibration curve, decision curve, clinical impact curve, and Kaplan-Meier analysis. Sensitivity, specificity, predictive values were calculated to assess the clinical value. The data showed that Fibrinogen, FAR, and D-dimer were higher in the severe patients, while PLTcount, Alb were much lower. Multivariate Cox analysis revealed that FAR and PLT count were independent risk factors for disease progression. The optimal cutoff values for FAR and PLT count were 0.0883 and 135*109/L, respectively. The C-index [0.712 (95% CI = 0.610-0.814)], decision curve, clinical impact curve showed that Nomogram could be used to predict the disease progression. In addition, the Kaplan-Meier analysis revealed that potential risk decreased in patients with FAR<0.0883 and PLT count>135*109/L.The model showed a good negative predictive value [(0.9474 (95%CI = 0.845-0.986)].This study revealed that FAR and PLT count were independent risk factors for severe illness and the severity of COVID-19 might be excluded when FAR<0.0883 and PLT count>135*109/L.


Correlation between the variables collected at admission and progression to severe cases during hospitalization among patients with COVID-19 in Chongqing

Abstract: Mortality is high among severe patients with 2019 novel coronavirus-infected disease (COVID-19). Early prediction of progression to severe cases is needed. We retrospectively collected patients with COVID-19 in two hospital of Chongqing from 1st January to 29th February 2020. At admission, we collected the demographics and laboratory tests to predict whether the patient would progress to severe cases in hospitalization. Severe case was confirmed when one of the following criteria occurred: (a) dyspnea, respiratory rate ≥30 breaths/min, (b) blood oxygen saturation ≤93%, and (c) PaO2 /FiO2 ≤ 300 mm Hg. At admission, 348 mild cases were enrolled in this study. Of them, 20 (5.7%) patients progressed to severe cases after median 4.0 days (interquartile range: 2.3-6.0). Pulmonary inflammation index, platelet counts, sodium, C-reactive protein, prealbumin, and PaCO2 showed good distinguishing power to predict progression to severe cases (each area under the curve of receiver operating characteristics [AUC] ≥ 0.8). Age, heart rate, chlorine, alanine aminotransferase, aspartate aminotransferase, procalcitonin, creatine kinase, pH, CD3 counts, and CD4 counts showed moderate distinguishing power (each AUC between 0.7-0.8). And potassium, creatinine, temperature, and D-dimer showed mild distinguishing power (each AUC between 0.6-0.7). In addition, higher C-reactive protein was associated with shorter time to progress to severe cases (r = -0.62). Several easily obtained variables at admission are associated with progression to severe cases during hospitalization. These variables provide a reference for the medical staffs when they manage the patients with COVID-19.


Plasma albumin levels predict risk for nonsurvivors in critically ill patients with COVID-19

Abstract: Aim: We aimed to explore the biomarkers for disease progression or the risk of nonsurvivors. Materials & methods: This study included 134 hospitalized patients with confirmed COVID-19 infection. The outcome of moderate versus severe versus critically ill patients and survivors versus nonsurvivors were compared. Results: An increase in the severity of COVID-19 pneumonia was positively associated with lower levels of platelets and albumin (all p < 0.05). In the critical group, the plasma levels of albumin continued to have a significant association for the risk of nonsurvivors (p < 0.05), even after adjusting for confounding factors. Conclusion: Albumin levels could be used as an independent predictor of the risk of nonsurvivors in critically ill patients with COVID-19.


Clinical analysis of risk factors for severe patients with novel coronavirus pneumonia/ 中华传染病杂志

Abstract: Objective To analyze the clinical features of patients with coronavirus disease 2019 (COVID-19) in Shanghai and to investigate the risk factors for disease progression to severe cases. Methods The clinical data of 292 adult patients with COVID-19 hospitalized in Shanghai Public Health Clinical Center from January 20, 2020 to February 10, 2020 were retrospectively analyzed, including 21 severe patients and 271 mild patients. The demographic characteristics, epidemiological history, history of underlying diseases and laboratory examinations were compared between the two groups. Measurement data were compared using t test or Mann-Whitney U test. The count data were compared using hi-square test. The binary logistic regression equation was used to analyze the risk factors for the progression of patients to severe cases. Results Among the 292 patients, 21 were severe cases with the rate of 7.2% (21/292). One patient died, and the mortality rate was 4.8% in severe patients. The severe patients aged (65.0±15.7) years old, 19 (90.5%) were male, 11 (52.4%) had underlying diseases, 7 (33.3%) had close relatives diagnosed with COVID-19. The mild patients aged (48.7±15.7) years old, 135 (49.8%) were male, 74 (27.3%) had underlying diseases, 36 (13.3%) had close relatives diagnosed with COVID-19. The differences between two groups were all significant statistically ( t =-4.730, χ 2 =12.930, 5.938 and 4.744, respectively, all P <0.05). Compared with the mild patients, the levels of absolute numbers of neutrophils, alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, creatinine, serum cystatin C, C reactive protein (CRP), procalcitonin , D -dimer, pro-B-type natriuretic peptide (proBNP), serum myoglobin, creatine kinase (CK), creatine kinase isoenzyme (CK-MB), serum troponin I (cTnI) in severe patients were all significantly higher ( U =2 091.5, 1 928.0, 1 215.5, 729.0, 1 580.5, 1 375.5, 917.5, 789.5, 1 209.0, 1 434.0, 638.0, 964.5, 1 258.0 and 1 747.5, respectively, all P <0.05), while the levels of lymphocyte count, albumin, transferrin, CD3 + T lymphocyte count, CD8 + T lymphocyte count and CD4 + T lymphocyte count in severe patients were all significantly lower ( U =1 263.5, t =4.716, U =1 214.0, 962.0, 1 167.5 and 988.0, respectively, all P <0.05). Further logistic regression analysis showed that the albumin (odds ratio ( OR )=0.806, 95% CI 0.675-0.961), CRP ( OR =1.016, 95% CI 1.000-1.032), serum myoglobin ( OR =1.010, 95% CI 1.004-1.016), CD3 + T lymphocyte count ( OR =0.996, 95% CI 0.991-1.000) and CD8 + T lymphocyte count ( OR =1.006, 95% CI 1.001-1.010) at admission were independent risk factors for the progression of COVID-19 patients to severe illness (all P <0.05). Conclusions Severe cases of patients with COVID-19 in Shanghai are predominantly elderly men with underlying diseases. Albumin, CRP, serum myoglobin, CD3 + T lymphocyte count and CD8 + T lymphocyte count could be used as early warning indicators for severe cases, which deserve more clinical attention.


Identification and validation of a novel clinical signature to predict the prognosis in confirmed COVID-19 patients

Abstract: BACKGROUND: This study aims to identify a prognostic biomarker to predict the disease prognosis and reduce the mortality rate of COVID-19, which has caused a worldwide pandemic. METHODS: COVID-19 patients were randomly divided into training and test groups. Univariate and multivariate Cox regression analyses were performed to identify the disease prognosis signature, which was selected to establish a risk model in the training group. Furthermore, the disease prognosis signature of COVID-19 was validated in the test group. RESULTS: The signature of COVID-19 was combined with five indicators, namely neutrophil count, lymphocyte count, procalcitonin, older age, and C-reactive protein. The signature stratified patients into high- and low-risk groups with significantly relevant disease prognosis (log-rank test, P<0.001) in the training group. The survival analysis indicated that the high-risk group displayed substantially lower survival probability than the low-risk group (log-rank test P<0.001). The area under ROC curve (AUC) showed that the signature of COVID-19 displayed the highest predictive accuracy regarding disease prognosis, which was 0.955 in the training group and 0.945 in the test group. The ROC analysis of both groups demonstrated that the predictive ability of the signature surpassed the use of each of the five indicators alone. CONCLUSION: The signature of COVID-19 presents a novel predictor and prognostic biomarker for closely monitoring patients and providing timely treatment for those who are severely or critically ill.


The clinical study on the relationship between serum albumin concentration and lymphocyte levels in patients with 2019-novel coronavirus pneumonia/ 中华急诊医学杂志

Abstract: Objective@#To explore the relationship between different serum albumin and lymphocyte levels in patients with 2019-novel coronavirus (2019-nCoV) pneumonia (COVID-19).@*Methods@#A retrospective study was performed to identify the characteristics of the clinical data of 205 COVID-19 patients who were hospitalized in the Happy Street of Hanchuan People's Hospital, Xiaogan, Hubei Province from January 24 to February 12, 2020, including their general information, serum albumin (ALB) levels, lymphocyte counts (LYM), percentage of lymphocytes (LYM%) and other laboratory parameter levels. Low ALB group and normal ALB group were demarcated by the concentration of 35g/L, further to identify the differences of LYM and LYM% levels and the incidence of LYM and LYM% decline at different ALB levels between groups,as well as the correlation between ALB and LYM, LYM% levels in hypoalbuminemia conditions .@*Results@#17.5% of COVID-19 patients were associated with hypoalbuminemia. The levels of LYM and LYM% in the low ALB group were significantly lower than those in the normal ALB group (P <0.001). The incidence of LYM and LYM% decline in the low ALB group was significantly higher than those in the normal ALB group (P <0.001). The levels of LYM and LYM% in the low ALB group were significantly positively correlated with serum ALB concentrations (P <0.05).@*Conclusions@#The decrease of lymphocyte levels in COVID-19 patients may be correlated to hypoalbuminemia. COVID-19 patients complicated by hypoalbuminemia should be actively intervened to maintain serum albumin in the normal range.


IL-6 may be a good biomarker for earlier detection of COVID-19 progression


Infection with SARS-CoV-2 causes abnormal laboratory results of multiple organs in patients

Abstract: AIM: To evaluate the clinical value of abnormal laboratory results of multiple organs in patients with coronavirus disease 2019 (COVID-2019) and to help clinicians perform correct treatment. RESULTS: Elevated neutrophil-to-LYM ratio (NLR), D-dimer(D-D), interleukin (IL)-6, IL-10, IL-2, interferon-Y, and age were significantly associated with the severity of illness. However, significant and sustained decreases were observed in the LYM subset (p<0.05). D-D, T cell counts, and cytokine levels in severe COVID-19 patients who survived the disease gradually recovered at later time points to levels that were comparable to those of mild cases. Second, D-D increased from 0.5 to 8, and the risk ratio increased from 2.75 to 55, eventually leading to disseminated intravascular coagulation. Moreover, the acute renal function damage occurred earlier than abnormal heart and liver functions (p<0.05). CONCLUSIONS: The degrees of lymphopenia and proinflammatory cytokine storm were higher in severe COVID-19 patients than in mild cases. The degree was associated with the disease severity. Advanced age, NLR, D-D, and cytokine levels may serve as useful prognostic factors for the early identification of severe COVID-19 cases. METHODS: Peripheral blood samples were collected from 93 confirmed COVID-19 patients. The samples were examined for lymphocyte (LYM) subsets by flow cytometry and cytokine profiles by specific immunoassays. The receiver operating characteristic curve was applied to determine the best diagnostic thresholds for laboratory results, and principal component analysis was used to screen the major risk factors. The prognostic values were assessed using the Kaplan-Meier curve and univariate and multivariate COX regression models.


Prediction of the severity of Corona Virus Disease 2019 and its adverse clinical outcomes

Abstract: This study aims to investigate blood and biochemical laboratory findings in patients with severe Corona Virus Disease 2019 (COVID-19) and to develop a joint predictor for predicting the likelihood of severe COVID-19 and its adverse clinical outcomes, to provide more information for treatment. We collected the data of 88 patients with laboratory-confirmed COVID-19. Then patients were divided into a non-severe group and a critical group (including critically ill cases). Univariate analysis showed that the absolute lymphocyte count, albumin level, albumin/globulin (A/G) ratio, lactate dehydrogenase (LDH) level, interleukin-6 (IL-6) level, erythrocyte count, globulin level, blood glucose level, and age were significantly correlated with the severity of COVID-19. The multivariate binary logistic regression model revealed that Age, absolute lymphocyte count, and IL-6 level were independent risk factors in patients with COVID-19. The receiver operating characteristic (ROC) curve revealed that the combination of IL-6 level, absolute lymphocyte count and age is superior to a single factor as predictors for predicting severe COVID-19, regardless of whether it is the area under curve (AUC) or the prediction sensitivity and specificity. Early application is beneficial to early identification of critically ill patients and timing individual treatments to reduce mortality.


Plasma IP-10 and MCP-3 levels are highly associated with disease severity and predict the progression of COVID-19

Abstract: BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 was first reported in Wuhan, December 2019, and continuously poses a serious threat to public health, highlighting the urgent need of identifying biomarkers for disease severity and progression. OBJECTIVE: We sought to identify biomarkers for disease severity and progression of COVID-19. METHODS: Forty-eight cytokines in the plasma samples from 50 COVID-19 cases including 11 critically ill, 25 severe, and 14 moderate patients were measured and analyzed in combination with clinical data. RESULTS: Levels of 14 cytokines were found to be significantly elevated in COVID-19 cases and showed different expression profiles in patients with different disease severity. Moreover, expression levels of IFN-Î³-induced protein 10, monocyte chemotactic protein-3, hepatocyte growth factor, monokine-induced gamma IFN, and macrophage inflammatory protein 1 alpha, which were shown to be highly associated with disease severity during disease progression, were remarkably higher in critically ill patients, followed by severe and then the moderate patients. Serial detection of the 5 cytokines in 16 cases showed that continuously high levels were associated with deteriorated progression of disease and fatal outcome. Furthermore, IFN-Î³-induced protein 10 and monocyte chemotactic protein-3 were excellent predictors for the progression of COVID-19, and the combination of the 2 cytokines showed the biggest area under the curve of the receiver-operating characteristics calculations with a value of 0.99. CONCLUSIONS: In this study, we report biomarkers that are highly associated with disease severity and progression of COVID-19. These findings add to our understanding of the immunopathologic mechanisms of severe acute respiratory syndrome coronavirus 2 infection, and provide potential therapeutic targets and strategies.


Prompt Predicting of Early Clinical Deterioration of Moderate-to-Severe COVID-19 Patients: Usefulness of a Combined Score Using IL-6 in a Preliminary Study

Abstract: BACKGROUND: The early identification of patients at risk of clinical deterioration is of interest considering the timeline of COVID-19 after the onset of symptoms. OBJECTIVE: The aim of our study was to evaluate the usefulness of testing serum IL-6 and other serological and clinical biomarkers, to predict a short-term negative clinical course of patients with noncritical COVID-19. METHODS: A total of 208 patients with noncritical COVID-19 pneumonia at admission were consecutively enrolled. Clinical and laboratory findings obtained on admission were analyzed by using survival analysis and stepwise logistic regression for variable selection. Three-day worsening as outcome in a logistic model to generate a prognostic score was used. RESULTS: Clinical worsening occurred in 63 patients (16 = died; 39 = transferred to intensive care unit; 8 worsening of respiratory failure). Forty-five of them worsened within 3 days after admission. The risk of clinical worsening was progressively enhanced along with increasing quartiles of IL-6 levels. Multivariate analysis showed that IL-6 (P = .005), C-reactive protein (CRP) (P = .003), and SaO2/FiO2 (P = .014) were the best predictors for clinical deterioration in the first 3 days after admission. The combined score yielded an area under the curve = 0.88 (95% confidence interval: 0.83-0.93). A nomogram predicting the probability of 3-day worsening was generated. The score also showed good performance for 7-day and 14- or 21-day worsening and in predicting death occurring during all the follow-up. CONCLUSIONS: Combining IL-6, CRP, and SaO2/FiO2 in a score may help clinicians to identify on admission those patients with COVID-19 who are at high risk for a further 3-day clinical deterioration.


The role of biomarkers in diagnosis of COVID-19 - A systematic review

Abstract: AIMS: As of the 28th April 2020, the COVID-19 pandemic has infiltrated over 200 countries and affected over three million confirmed people. We review different biomarkers to evaluate if they are able to predict clinical outcomes and correlate with the severity of COVID-19 disease. METHODS: A systematic review of the literature was carried out to identify relevant articles using six different databases. Keywords to refine the search included 'COVID-19', 'SARS-CoV2', 'Biomarkers', among others. Only studies which reported data on pre-defined outcomes were included. KEY FINDINGS: Thirty-four relevant articles were identified which reviewed the following biomarkers: C-reactive protein, serum amyloid A, interleukin-6, lactate dehydrogenase, neutrophil-to-lymphocyte ratio, D-dimer, cardiac troponin, renal biomarkers, lymphocytes and platelet count. Of these, all but two, showed significantly higher levels in patients with severe complications of COVID-19 infection compared to their non-severe counterparts. Lymphocytes and platelet count showed significantly lower levels in severe patients compared to non-severe patients. SIGNIFICANCE: Although research is still in its early stages, the discovery of how different biomarkers behave during the course of the disease could help clinicians in identifying severe disease earlier and subsequently improve prognosis. Nevertheless, we urge for more research across the globe to corroborate these findings.


The profile of peripheral blood lymphocyte subsets and serum cytokines in children with 2019 novel coronavirus pneumonia

Abstract: OBJECTIVES: The study was aimed at investigating the characteristics of peripheral blood lymphocyte subsets and serum cytokines in children with 2019 novel coronavirus (2019-nCoV) pneumonia. METHODS: Children with 2019-nCoV pneumonia or with respiratory syncytial virus (RSV) pneumonia were included. Data including lymphocyte subsets and serum cytokines were collected and analyzed. RESULTS: 56 patients were included in the study, 40 children with 2019-nCoV pneumonia and 16 children with RSV pneumonia. Compared with children with RSV pneumonia, patients with 2019-nCoV pneumonia had higher count of CD3+8+ lymphocyte, higher percentages of CD3+, CD3+8+ lymphocytes and a lower percentage of CD19+ lymphocyte. The serum IL-10 level was significantly higher in children with RSV pneumonia. One 2019-nCoV pneumonia child who was with an obvious increase of IL-10 developed severe pneumonia. CONCLUSIONS: Immune response played a very important role in the development of 2019-nCoV pneumonia. The effective CD8+ T cell response might influence the severity of 2019-nCoV pneumonia. The adaptable change in IL-10 level might contribute to the relatively mild pneumonia symptoms in children with 2019-nCoV pneumonia and bacterial co-infection might be a risk factor of severe 2019-nCoV pneumonia.


Tumor biomarkers predict clinical outcome of COVID-19 patients


C-reactive protein correlates with computed tomographic findings and predicts severe COVID-19 early

Abstract: COVID-19 has developed into a worldwide pandemic; early identification of severe illness is critical for controlling it and improving the prognosis of patients with limited medical resources. The present study aimed to analyze the characteristics of severe COVID-19 and identify biomarkers for differential diagnosis and prognosis prediction. In total, 27 consecutive patients with COVID-19 and 75 patients with flu were retrospectively enrolled. Clinical parameters were collected from electronic medical records. The disease course was divided into four stages: initial, progression, peak, and recovery stages, according to computed tomography (CT) progress. to mild COVID-19, the lymphocytes in the severe COVID-19 progressively decreased at the progression and the peak stages, but rebound in the recovery stage. The levels of C-reactive protein (CRP) in the severe group at the initial and progression stages were higher than those in the mild group. Correlation analysis showed that CRP (R = .62; P < .01), erythrocyte sedimentation rate (R = .55; P < .01) and granulocyte/lymphocyte ratio (R = .49; P < .01) were positively associated with the CT severity scores. In contrast, the number of lymphocytes (R = -.37; P < .01) was negatively correlated with the CT severity scores. The receiver-operating characteristic analysis demonstrated that area under the curve of CRP on the first visit for predicting severe COVID-19 was 0.87 (95% CI 0.10-1.00) at 20.42 mg/L cut-off, with sensitivity and specificity 83% and 91%, respectively. CRP in severe COVID-19 patients increased significantly at the initial stage, before CT findings. Importantly, CRP, which was associated with disease development, predicted early severe COVID-19.


AI-Driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia

Abstract: Chest computed tomography (CT) is widely used for the management of Coronavirus disease 2019 (COVID-19) pneumonia because of its availability and rapidity. The standard of reference for confirming COVID-19 relies on microbiological tests but these tests might not be available in an emergency setting and their results are not immediately available, contrary to CT. In addition to its role for early diagnosis, CT has a prognostic role by allowing visually evaluating the extent of COVID-19 lung abnormalities. The objective of this study is to address prediction of short-term outcomes, especially need for mechanical ventilation. In this multi-centric study, we propose an end-to-end artificial intelligence solution for automatic quantification and prognosis assessment by combining automatic CT delineation of lung disease meeting performance of experts and data-driven identification of biomarkers for its prognosis. AI-driven combination of variables with CT-based biomarkers offers perspectives for optimal patient management given the shortage of intensive care beds and ventilators.


Presepsin as a predictive biomarker of severity in COVID-19: A case series


Correlation between Heart fatty acid binding protein and severe COVID-19: A case-control study

Abstract: BACKGROUND: Heart-fatty acid binding protein (HFABP) has been recognized as a highly heart-specific marker. However, it is currently unknown that its HFABP is also closely related to the severity of COVID-19. METHODS: We retrospectively screened 46 patients who met our inclusion criteria within 4 weeks. They were tested for HFABP after the diagnosis of COVID-19, and monitored for HFABP during their hospital stay. We tracked the patients during their hospital stay to determine if they had severe COVID-19 or mild-to-severe transition features. We calculated the chi-square test values found for HFABP to predict the correlation between HFABP levels and the severity of the COVID-19. RESULTS: Of these 46 cases, 16 cases with confirmed COVID-19 were tested for HFABP> 7 ng / mL upon admission; among them, 14 cases were diagnosed with severe COVID-19 within the hospitalization. The Odds ratio of the measured HFABP elevation was 6.81(95% confidence interval [CI] 5.23-8.40), and 3 patients with severe COVID-19 progressed in 5 patients with mild HFABP> 7 ng/mL. CONCLUSION: These data indicate that the elevation of HFABP is closely related to the severity of COVID-19 in the patients, and the elevated HFABP may cause rapid development of patients with mild COVID-19 into severe COVID-19. But serum HFABP negative maybe make patients with mild COVID-19 safer, the current data show no effect on the all-cause mortality. TRIAL REGISTRATION: Our study has been registered with the Chinese Clinical Trial Registry, the registration number: ChiCTR2000029829.


Serum Amyloid A is a biomarker of severe Coronavirus Disease and poor prognosis

Abstract: BACKGROUND: To explore the significance of SAA in evaluating the severity and prognosis of COVID-19. METHODS: A total of 132 patients with confirmed COVID-19 who were admitted to a designated COVID-19 hospital in Wuhan, China from January 18, 2020 to February 26, 2020 were collected. The dynamic changes of blood SAA, CRP, PCT, WBC, Lymphocyte (L), PLT, CT imaging, and disease progression were studied. All patients completed at least twice laboratory data collection and clinical condition assessment at three time points indicated for this study; The length of hospital stay was longer than 14 days prior to February 26, 2020. RESULTS: COVID-19 patients had significantly increased SAA and CRP levels, while L count decreased, and PCT, WBC, and PLT were in the normal range. As disease progressed from mild to critically severe, SAA and CRP gradually increased, while L decreased, and PLT, WBC, and PCT had no significant changes; ROC curve analysis suggests that SAA/L, CRP, SAA, and L count are valuable in evaluating the severity of COVID-19 and distinguishing critically ill patients from mild ones; Patients with SAA consistently trending down during the course of disease have better prognosis, compared with the patients with SAA continuously rising; The initial SAA level is positively correlated with the dynamic changes of the serial CT scans. Patient with higher initial SAA level are more likely to have poor CT imaging. CONCLUSIONS: SAA and L are sensitive indicators in evaluating the severity and prognosis of COVID-19. Monitoring dynamic changes of SAA, combined with CT imaging could be valuable in diagnosis and treatment of COVID-19.