Clinical features and potential risk factors for discerning the critical cases and predicting the outcome of patients with COVID-19

Clinical and immunological comparison of COVID-19 disease between critical and non-critical courses: a systematic review and meta-analysis

Introduction

Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which appeared in 2019, has been classified as critical and non-critical according to clinical signs and symptoms. Critical patients require mechanical ventilation and intensive care unit (ICU) admission, whereas non-critical patients require neither mechanical ventilation nor ICU admission. Several factors have been recently identified as effective factors, including blood cell count, enzymes, blood markers, and underlying diseases. By comparing blood markers, comorbidities, co-infections, and their relationship with mortality, we sought to determine differences between critical and non-critical groups.

Method

We used Scopus, PubMed, and Web of Science databases for our systematic search. Inclusion criteria include any report describing the clinical course of COVID-19 patients and showing the association of the COVID-19 clinical courses with blood cells, blood markers, and bacterial co-infection changes. Twenty-one publications were eligible for full-text examination between 2019 to 2021.

Result

The standard difference in WBC, lymphocyte, and platelet between the two clinical groups was 0.538, -0.670, and -0.421, respectively. Also, the standard difference between the two clinical groups of CRP, ALT, and AST was 0.482, 0.402, and 0.463, respectively. The odds ratios for hypertension and diabetes were significantly different between the two groups. The prevalence of co-infection also in the critical group is higher.

Conclusion

In conclusion, our data suggest that critical patients suffer from a suppressed immune system, and the inflammation level, the risk of organ damage, and co-infections are significantly high in the critical group and suggests the use of bacteriostatic instead of bactericides to treat co-infections.

The Role of Platelet Parameters in Predicting the Disease Severity of COVID-19 Patients: A Hospital-Based Study

Background and objective Globally, a large number of people have been impacted by the extremely contagious coronavirus disease 2019 (COVID-19) infection, and several pieces of literature were published on hematological parameter changes in this infection, particularly focusing on leucocytes. In this study, we have analyzed the platelet parameters and platelet-leucocyte ratios in COVID-19 patients and correlated them with the disease severity. Methods The COVID-19 patients who were hospitalized during the second peak of the pandemic were assessed. The platelet count and indices, platelet to lymphocyte ratio (PLR), neutrophil to platelet ratio (NPR), and clinical severity of each patient were analyzed. The significance of parameters and clinical severity was evaluated using analysis of variance (ANOVA) and the Kruskal Wallis test. A bivariate analysis was performed to assess the strength of the association. Receiver operating characteristic (ROC) curves were plotted to detect the predictive value of parameters for disease severity. Results The data of 132 COVID-19 patients has been evaluated. The average mean age was 45.60 ± 15.76 years with slight female predominance. Thrombocytopenia was found in 33% of cases with the majority of them being mild. Age, platelet distribution width (PDW), and PLR and NPR parameters were significantly (p-value <0.05) associated with disease severity. ROC curves showed age, PDW, PLR, NPR, absolute neutrophil count (ANC), and absolute lymphocyte count (ALC) had significant prediction values for clinical severity. Conclusions Platelet parameters may not accurately reflect the severity of the disease, but when combined with leucocyte parameters and their ratios (PLR and NPR), they offer important information about disease severity.

Neurological complications and effects of COVID-19: Symptoms and conceivable mechanisms

A novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in December 2019 in Wuhan, China. The new coronavirus disease (COVID-19) was declared a global pandemic by the World Health Organization (WHO) in March 2020. SARS-CoV-2 can invade the nervous system aside from infecting the respiratory system as its primary target. The most common nervous system symptoms of COVID-19 are stated as headache, myalgia, fatigue, nausea, vomiting, sudden and unexplained anosmia, and ageusia. More severe conditions such as encephalomyelitis, acute myelitis, thromboembolic events, ischemic stroke, intracerebral hemorrhage, Guillain-Barré-syndrome, Bell's palsy, rhabdomyolysis, and even coma have also been reported. Cohort studies revealed that neurological findings are associated with higher morbidity and mortality. The neurological symptoms and manifestations caused by SARS-CoV-2 and COVID-19 are examined and summarized in this article.

Associations of the neutrophil/lymphocyte ratio, monocyte/ lymphocyte ratio, and platelet/lymphocyte ratio with COVID-19 disease severity in patients with neurological symptoms: A cross-sectional monocentric study

Objectives

Data are limited regarding the relationship of neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), and platelet/ lymphocyte ratio (PLR) with neurological symptoms (NS) in COVID-19 patients. This study is the first to assess the utility of the NLR, MLR, and PLR for predicting COVID-19 severity in infected patients with NS.

Materials and Methods

Consecutive 192 PCR-positive COVID-19 patients with NS were included in this cross-sectional and prospective study. The patients were classified into the non-severe and severe groups. We analyzed routinely complete blood count in these groups in terms of COVID-19 disease severity.

Results

Advanced age, a higher body mass index, and comorbidities were significantly more common in the severe group (P < 0.001). Among the NS, anosmia (P = 0.001) and memory loss (P = 0.041) were significantly more common in the non-severe group. In the severe group, the lymphocytes and monocyte counts and the hemoglobin level were significantly lower, while the neutrophil count, NLR, and PLR were significantly higher (all P < 0.001). In the multivariate model, advanced age and a higher neutrophil count were independently associated with severe disease (both P < 0.001) but the NLR and PLR were not (both P > 0.05).

Conclusion

We found positive associations of COVID-19 severity with the NLR and PLR in infected patients with NS. Further research is required to shed more light on the role of neurological involvement in disease prognosis and outcomes.

Platelet-to-Lymphocyte Ratio (PLR) Is Not a Predicting Marker of Severity but of Mortality in COVID-19 Patients Admitted to the Emergency Department: A Retrospective Multicenter Study

(1) Introduction: In the present study, we investigate the prognostic value of platelet-to-lymphocyte ratio (PLR) as a marker of severity and mortality in COVID-19 infection. (2) Methods: Between 1 March and 30 April 2020, we conducted a multicenter, retrospective cohort study of patients with moderate to severe coronavirus 19 (COVID-19), all of whom were hospitalized after being admitted to the emergency department (ED). (3) Results: A total of 1035 patients were included in our study. Neither lymphocytes, platelets or PLR were associated with disease severity. Lymphocyte count was significantly lower and PLR values were significantly higher in the group of patients who died, and both were associated with mortality in the univariate analysis (OR: 0.524, 95% CI: (0.336−0.815), p = 0.004) and (OR: 1.001, 95% CI: (1.000−1.001), p = 0.042), respectively. However, the only biological parameter significantly associated with mortality in the multivariate analysis was platelet count (OR: 0.996, 95% CI: (0.996−1.000), p = 0.027). The best PLR value for predicting mortality in COVID-19 was 356.6 (OR: 3.793, 95% CI: (1.946−7.394), p < 0.001). (4) Conclusion: A high PLR value is however associated with excess mortality.

The Role of Neutrophil-to-Lymphocyte Ratio in Risk Stratification and Prognostication of COVID-19: A Systematic Review and Meta-Analysis

Several studies have proposed that the neutrophil−lymphocyte ratio (NLR) is one of the various biomarkers that can be useful in assessing COVID-19 disease-related outcomes. Our systematic review analyzes the relationship between on-admission NLR values and COVID-19 severity and mortality. Six different severity criteria were used. A search of the literature in various databases was conducted from 1 January 2020 to 1 May 2021. We calculated the pooled standardized mean difference (SMD) for the collected NLR values. A meta-regression analysis was performed, looking at the length of hospitalization and other probable confounders, such as age, gender, and comorbidities. A total of sixty-four studies were considered, which included a total of 15,683 patients. The meta-analysis showed an SMD of 3.12 (95% CI: 2.64−3.59) in NLR values between severe and non-severe patients. A difference of 3.93 (95% CI: 2.35−5.50) was found between survivors and non-survivors of the disease. Upon summary receiver operating characteristics analysis, NLR showed 80.2% (95% CI: 74.0−85.2%) sensitivity and 75.8% (95% CI: 71.3−79.9%) specificity for the prediction of severity and 78.8% (95% CI: 73.5−83.2%) sensitivity and 73.0% (95% CI: 68.4−77.1%) specificity for mortality, and was not influenced by age, gender, or co-morbid conditions. Conclusion: On admission, NLR predicts both severity and mortality in COVID-19 patients, and an NLR > 6.5 is associated with significantly greater the odds of mortality.

Immunologic features of asymptomatic postvaccination infections with the Delta variant of SARS-CoV-2 in adults

Background

Asymptomatic infections may play an important role in severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) Delta variant transmissions. However, the immunologic features of asymptomatic postvaccination infections with the Delta variant of SARS‐CoV‐2 in adults remain to be defined.

Methods

A retrospective study involving 36 vaccinated adults infected with the SARS‐CoV‐2 Delta variant was performed. Their demographic and laboratory data were collected and analyzed in The First People's Hospital of Jingmen from August 4 to 20, 2021.

Results

Of the 36 adults, 6 persons had an asymptomatic infection. The severity of the SARS‐CoV‐2 infections was highly correlated with the doses of vaccinations (p = 0.019). The symptomatic and asymptomatic infected SARS‐CoV‐2 adults showed normal levels of leukocytes and lymphocytes. The C‐reactive protein (CRP) and interleukin‐6 (IL‐6) levels were elevated in the symptomatic groups. The period between the last vaccination to the time of infection in the asymptomatic group was longer than that in the mild and moderate groups (73 vs. 61 vs. 50 days; p = 0.047). The percentage of suppressor T‐cells in the asymptomatic group was the highest (32.2 ± 4.0% vs. 22.0 ± 7.2% vs. 29.3 ± 8.0%; p = 0.004). The signal‐to‐cutoff ratio value of total antibody against SARS‐CoV‐2 in the asymptomatic group was lower than that in the other two groups (383 vs. 703 vs. 1792; p < 0.001) and much lower than that in the moderate group. The multivariate ordinal logistic analysis after adjusting for gender, vaccination date, and vaccination dose indicated that CRP at Days 4−7 and 8−14, IL‐6 on Days 4−7, and total antibody were risk factors for coronavirus disease 2019 severity.

Conclusions

Asymptomatic postvaccination infections with the Delta variant of SARS‐CoV‐2 in adults tend to infect persons vaccinated twice. The immunophenotype profile for asymptomatic postvaccination infections is less inflammatory and accompanied by relatively lower antibody titers.

Associations between Serum Interleukins (IL-1β, IL-2, IL-4, IL-6, IL-8, and IL-10) and Disease Severity of COVID-19: A Systematic Review and Meta-Analysis

Background. To investigate the association between interleukins (IL-1β, IL-2, IL-4, IL-6, IL-8, and IL-10) and the disease severity of coronavirus disease 2019 (COVID-19). Materials and Methods. We systematically searched records investigating the role of interleukins (IL-1β, IL-2, IL-4, IL-6, IL-8, and IL-10) in COVID-19 patients in Web of Science, Pubmed, and Embase through December 2020. Data were extracted and pooled, and the weighted mean difference (WMD) and its 95% confidence interval (CI) were calculated. The funnel plot and the nonparametric trim and fill method were used to visualize and adjust the publication bias. Results. In total, 61 studies enrolled 14,136 subjects (14,041 patients and 95 healthy subjects) were enrolled in this meta-analysis. Our results showed that serum IL-2, IL-4, IL-6, and IL-10 levels were elevated in COVID-19 patients compared to healthy controls, and IL-6, IL-8, and IL-10 levels were increased in severe COVID-19 cases compared to nonsevere patients. Additionally, the levels of IL-1β, IL-6, and IL-8 were elevated in nonsurvivor patients compared to survivors. For patients in the intensive care unit (ICU), IL-6 and IL-8 levels were increased than that in non-ICU patients. Conclusions. Elevated levels of IL-6, IL-8, and IL-10 were associated with the disease severity of COVID-19, and elevated levels of IL-1β, IL-6, and IL-8 were related to the prognosis of COVID-19 patients, which could be used to evaluate COVID-19 patients’ disease severity and prognosis.

Prognostic factors for predicting severity and mortality in hospitalized COVID‐19 patients

Background

Coronavirus disease 2019, COVID‐19, has reached all the corners of the world and was declared by the WHO as a global pandemic and public health emergency of international concern on the January 31, 2020. Allocating quick and specific biomarkers to predict the disease severity upon admission to hospital became a crucial need. This study, therefore, aimed at exploring the relationship between laboratory results in COVID‐19 patients admitted to hospital and the final outcome in these patients.

Methods

Retrospective analysis was performed on the medical records of 310 COVID‐19‐positive patients admitted to Uhod Hospital, the referral hospital in the area of Madinah, Kingdom of Saudi Arabia, between the April 13 and the July 29, 2020. The association of laboratory results with the survival/mortality outcomes was studied.

Results

It was demonstrated that lymphopenia, prolonged aPTT, high INR, high D. dimer and high CK are valuable prognostic predictors of the severity of the disease at early stages that can determine the outcome. Based on the results of the multiple logistic regression, the variables that are associated with death outcome are aPTT, HR, RR, ALT and CK level

Conclusion

It is proposed to perform these tests on admission to hospital for moderate to severe COVID‐19 patients to improve the management of those cases and reduce mortality.

Value of the Neutrophil-Lymphocyte Ratio in Predicting COVID-19 Severity: A Meta-analysis

Background

Coronavirus disease 2019 (COVID-19) is highly contagious and continues to spread rapidly. However, there are no simple and timely laboratory techniques to determine the severity of COVID-19. In this meta-analysis, we assessed the potential of the neutrophil-lymphocyte ratio (NLR) as an indicator of severe versus nonsevere COVID-19 cases.

Methods

A search for studies on the NLR in severe and nonsevere COVID-19 cases published from January 1, 2020, to July 1, 2021, was conducted on the PubMed, EMBASE, and Cochrane Library databases. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and area under the curve (AUC) analyses were done on Stata 14.0 and Meta-disc 1.4 to assess the performance of the NLR.

Results

Thirty studies, including 5570 patients, were analyzed. Of these, 1603 and 3967 patients had severe and nonsevere COVID-19, respectively. The overall sensitivity and specificity were 0.82 (95% confidence interval (CI), 0.77-0.87) and 0.77 (95% CI, 0.70-0.83), respectively; positive and negative correlation ratios were 3.6 (95% CI, 2.7-4.7) and 0.23 (95% CI, 0.17-0.30), respectively; DOR was 16 (95% CI, 10-24), and the AUC was 0.87 (95% CI, 0.84-0.90).

Conclusion

The NLR could accurately determine the severity of COVID-19 and can be used to identify patients with severe disease to guide clinical decision-making.

Risk factors for prolonged virus shedding of respiratory tract and fecal in adults with severe acute respiratory syndrome coronavirus-2 infection

BACKGROUND

The dynamic alteration and comparative study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA shedding pattern during treatment are limited. This study explores the potential risk factors influencing prolonged viral shedding in COVID-19.

METHODS

A total of 126 COVID-19 patients were enrolled in this retrospective longitudinal study. A multivariate logistic regression analysis was carried out to estimate the potential risk factors.

RESULTS

38.1% (48/126) cases presented prolonged respiratory tract viral shedding, and 30 (23.8%) cases presented prolonged rectal swab viral shedding. Obesity (OR, 3.31; 95% CI, 1.08-10.09), positive rectal swab (OR, 3.43; 95% CI, 1.53-7.7), treatment by lopinavir/ritonavir with chloroquine phosphate (OR, 2.5; 95% CI, 1.04-6.03), the interval from onset to antiviral treatment more than 7 days (OR, 2.26; 95% CI, 1.04-4.93), lower CD4+ T cell (OR, 0.92; 95% CI, 0.86-0.99) and higher NK cells (OR, 1.11; 95% CI, 1.02-1.20) were significantly associated with prolonged respiratory tract viral shedding. CD3-CD56+ NK cells (OR, 0.87; 95% CI, 0.76-0.99) were related with prolonged fecal shedding.

CONCLUSIONS

Obesity, delayed antiviral treatment, and positive SARS-CoV-2 for stool were independent risk factors for prolonged SARS-CoV-2 RNA shedding of the respiratory tract. A combination of LPV/r and abidol as the initial antiviral regimen was effective in shortening the duration of viral shedding compared with LPV/r combined with chloroquine phosphate. CD4+ T cell and NK cells were significantly associated with prolonged viral shedding, and further studies are to be warranted to determine the mechanism of immunomodulatory response in virus clearance.

Role of platelet-to-lymphocyte count ratio (PLR), as a prognostic indicator in COVID-19: A systematic review and meta-analysis

Prognostic predictors are of paramount interest for prompt intervention and optimal utilization of the healthcare system in the ongoing context of the COVID-19 pandemic. The platelet-to-lymphocyte count ratio (PLR), has emerged as a potential tool for risk stratification of critically ill patients with sepsis. The current systematic review explores the utility of PLR as a prognostic predictor of COVID-19 patients. We screened the electronic databases until May 15, 2021 after enrolling in PROSPERO (CRD42021220269). Studies evaluating the association between PLR on admission and outcomes in terms of mortality and severity among COVID-19 patients were included. We retrieved 32 studies, with a total of 2768 and 3262 COVID-19 patients for mortality and disease severity outcomes. Deceased and critically ill patients had higher PLR levels on admission in comparison to survivors and non-severe patients (mean differences [MD] = 66.10; 95% confidence interval [CI]: 47.75-84.44; p < 0.00001 and MD = 86.74; 95% CI: 67.7-105.7; p < 0.00001, respectively). A higher level of PLR on admission in COVID-19 patients is associated with increased morbidity and mortality. However, the evidence is of low quality and further studies regarding the cut-off value of PLR are the need of the hour.

Neurological Manifestations in COVID-19 Patients: A Meta-Analysis

Common symptoms such as dizziness, headache, olfactory dysfunction, nausea, vomiting, etc. in COVID-19 patients have indicated the involvement of the nervous system. However, the exact association of the nervous system with COVID-19 infection is still unclear. Thus, we have conducted a meta-analysis of clinical studies associated with neurological problems in COVID-19 patients. We have searched for electronic databases with MeSH terms, and the studies for analysis were selected based on inclusion and exclusion criteria and quality assessment. The Stats Direct (version 3) was used for the analysis. The pooled prevalence with 95% confidence interval of various neurological manifestations reported in the COVID-19 patients was found to be headache 14.6% (12.2-17.2), fatigue 33.6% (29.5-37.8), olfactory dysfunction 26.4% (21.8-31.3), gustatory dysfunction 27.2% (22.3-32.3), vomiting 6.7% (5.5-8.0), nausea 9.8% (8.1-11.7), dizziness 6.7% (4.7-9.1), myalgia 21.4% (18.8-24.1), seizure 4.05% (2.5-5.8), cerebrovascular diseases 9.9% (6.8-13.4), sleep disorders 14.9% (1.9-36.8), altered mental status 17.1% (12.3-22.5), neuralgia 2.4% (0.8-4.7), arthralgia 19.9% (15.3-25.0), encephalopathy 23.5% (14.3-34.1), encephalitis 0.6% (0.2-1.3), malaise 38.3% (24.7-52.9), confusion 14.2% (6.9-23.5), movement disorders 5.2% (1.7-10.4), and Guillain-Barre syndrome 6.9% (2.3-13.7). However, the heterogeneity among studies was found to be high. Various neurological manifestations related to the central nervous system (CNS) and peripheral nervous system (PNS) are associated with COVID-19 patients.

Low serum level of apolipoprotein A1 may predict the severity of COVID-19: A retrospective study

BACKGROUND

Dyslipidemia has been observed in patients with coronavirus disease 2019 (COVID-19). This study aimed to investigate blood lipid profiles in patients with COVID-19 and to explore their predictive values for COVID-19 severity.

METHODS

A total of 142 consecutive patients with COVID-19 were included in this single-center retrospective study. Blood lipid profile characteristics were investigated in patients with COVID-19 in comparison with 77 age- and gender-matched healthy subjects, their predictive values for COVID-19 severity were analyzed by using multivariable logistic regression analysis, and their prediction efficiencies were evaluated by using receiver operator characteristic (ROC) curves.

RESULTS

There were 125 and 17 cases in the non-severe and severe groups, respectively. Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein A1 (ApoA1) gradually decreased across the groups in the following order: healthy controls, non-severe group, and severe group. ApoA1 was identified as an independent risk factor for COVID-19 severity (adjusted odds ratio [OR]: 0.865, 95% confidence interval [CI]: 0.800-0.935, p < 0.001), along with interleukin-6 (IL-6) (adjusted OR: 1.097, 95% CI: 1.034-1.165, p = 0.002). ApoA1 exhibited the highest area under the ROC curve (AUC) among all single markers (AUC: 0.896, 95% CI: 0.834-0.941); moreover, the risk model established using ApoA1 and IL-6 enhanced prediction efficiency (AUC: 0.977, 95% CI: 0.932-0.995).

CONCLUSION

Blood lipid profiles in patients with COVID-19 are quite abnormal compared with those in healthy subjects, especially in severe cases. Serum ApoA1 may represent a good indicator for predicting the severity of COVID-19.

Nutrition risk prevalence and nutrition care recommendations for hospitalized and critically-ill patients with COVID-19

Nutritional status is an often-overlooked component in infectious disease severity. Hospitalized or critically ill patients are at higher risk of malnutrition, and rapid assessment and treatment of poor nutritional status can impact clinical outcomes. As it relates to the COVID-19 pandemic, an estimated 5% of these patients require admission to an ICU. Per clinical practice guidelines, nutrition therapy should be a core component of treatment regimens. On account of the urgent need for information relating to the nutritional support of these patients, clinical practice guidance was published based on current critical care guidelines. However, a growing body of literature is now available that may provide further direction for the nutritional status and support in COVID-19 patients. This review, intended for the health care community, provides a heretofore lacking in-depth discussion and summary of the current data on nutrition risk and assessment and clinical practice guidelines for medical nutrition therapy for hospitalized and critically ill patients with COVID-19.

Asthma in patients with coronavirus disease 2019: A systematic review and meta-analysis

BACKGROUND

It is unclear whether asthma has an influence on contracting coronavirus disease 2019 (COVID-19) or having worse outcomes from COVID-19 disease.

OBJECTIVE

To explore the prevalence of asthma in patients with COVID-19 and the relationship between asthma and patients with COVID-19 with poor outcomes.

METHODS

The pooled prevalence of asthma in patients with COVID-19 and corresponding 95% confidence interval (CI) were estimated. The pooled effect size (ES) was used to evaluate the association between asthma and patients with COVID-19 with poor outcomes.

RESULTS

The pooled prevalence of asthma in patients with COVID-19 worldwide was 8.3% (95% CI, 7.6-9.0) based on 116 articles (119 studies) with 403,392 cases. The pooled ES based on unadjusted effect estimates revealed that asthma was not associated with reduced risk of poor outcomes in patients with COVID-19 (ES, 0.91; 95% CI, 0.78-1.06). Similarly, the pooled ES based on unadjusted effect estimates revealed that asthma was not associated with the reduced risk of mortality in patients with COVID-19 (ES, 0.88; 95% CI, 0.73-1.05). However, the pooled ES based on adjusted effect estimates indicated that asthma was significantly associated with reduced risk of mortality in patients with COVID-19 (ES 0.80, 95% CI 0.74-0.86).

CONCLUSION

The pooled prevalence of asthma in patients with COVID-19 was similar to that in the general population, and asthma might be an independent protective factor for the death of patients with COVID-19, which suggests that we should pay high attention to patients co-infected asthma and COVID-19 and take locally tailored interventions and treatment. Further well-designed studies with large sample sizes are required to verify our findings.

Asthma in Adult Patients with COVID-19. Prevalence and Risk of Severe Disease

Rationale: Health outcomes of people with coronavirus disease (COVID-19) range from no symptoms to severe illness and death. Asthma, a common chronic lung disease, has been considered likely to increase the severity of COVID-19, although data addressing this hypothesis have been scarce until very recently.Objectives: To review the epidemiologic literature related to asthma's potential role in COVID-19 severity.Methods: Studies were identified through the PubMed (MEDLINE) and medRxiv (preprint) databases using the search terms "asthma," "SARS-CoV-2" (severe acute respiratory syndrome coronavirus 2), and "COVID-19," and by cross-referencing citations in identified studies that were available in print or online before December 22, 2020.Measurements and Main Results: Asthma prevalence data were obtained from studies of people with COVID-19 and regional health statistics. We identified 150 studies worldwide that allowed us to compare the prevalence of asthma in patients with COVID-19 by region, disease severity, and mortality. The results of our analyses do not provide clear evidence of increased risk of COVID-19 diagnosis, hospitalization, severity, or mortality due to asthma.Conclusions: These findings could provide some reassurance to people with asthma regarding its potential to increase their risk of severe morbidity from COVID-19.

The Surviving Sepsis Campaign: Research Priorities for Coronavirus Disease 2019 in Critical Illness

OBJECTIVES

To identify research priorities in the management, pathophysiology, and host response of coronavirus disease 2019 in critically ill patients.

DESIGN

The Surviving Sepsis Research Committee, a multiprofessional group of 17 international experts representing the European Society of Intensive Care Medicine and Society of Critical Care Medicine, was virtually convened during the coronavirus disease 2019 pandemic. The committee iteratively developed the recommendations and subsequent document.

METHODS

Each committee member submitted a list of what they believed were the most important priorities for coronavirus disease 2019 research. The entire committee voted on 58 submitted questions to determine top priorities for coronavirus disease 2019 research.

RESULTS

The Surviving Sepsis Research Committee provides 13 priorities for coronavirus disease 2019. Of these, the top six priorities were identified and include the following questions: 1) Should the approach to ventilator management differ from the standard approach in patients with acute hypoxic respiratory failure?, 2) Can the host response be modulated for therapeutic benefit?, 3) What specific cells are directly targeted by severe acute respiratory syndrome coronavirus 2, and how do these cells respond?, 4) Can early data be used to predict outcomes of coronavirus disease 2019 and, by extension, to guide therapies?, 5) What is the role of prone positioning and noninvasive ventilation in nonventilated patients with coronavirus disease?, and 6) Which interventions are best to use for viral load modulation and when should they be given?

CONCLUSIONS

Although knowledge of both biology and treatment has increased exponentially in the first year of the coronavirus disease 2019 pandemic, significant knowledge gaps remain. The research priorities identified represent a roadmap for investigation in coronavirus disease 2019.

Nervous system diseases are associated with the severity and mortality of patients with COVID-19: a systematic review and meta-analysis

Coronavirus disease 2019 (COVID-19) has become a global pandemic. Previous studies showed that comorbidities in patients with COVID-19 are risk factors for adverse outcomes. This study aimed to clarify the association between nervous system diseases and severity or mortality in patients with COVID-19. We performed a systematic literature search of four electronic databases and included studies reporting the prevalence of nervous system diseases in COVID-19 patients with severe and non-severe disease or among survivors and non-survivors. The included studies were pooled into a meta-analysis to calculate the odds ratio (OR) with 95% confidence intervals (95%CI). We included 69 studies involving 17 879 patients. The nervous system diseases were associated with COVID-19 severity (OR = 3.19, 95%CI: 2.37 to 4.30, P < 0.001) and mortality (OR = 3.75, 95%CI: 2.68 to 5.25, P < 0.001). Specifically, compared with the patients without cerebrovascular disease, patients with cerebrovascular disease infected with COVID-19 had a higher risk of severity (OR = 3.10, 95%CI: 2.21 to 4.36, P < 0.001) and mortality (OR = 3.45, 95% CI: 2.46 to 4.84, P < 0.001). Stroke was associated with severe COVID-19 disease (OR = 1.95, 95%CI: 1.11 to 3.42, P = 0.020). No significant differences were found for the prevalence of epilepsy (OR = 1.00, 95%CI: 0.42 to 2.35, P = 0.994) and dementia (OR = 2.39, 95%CI: 0.55 to 10.48, P = 0.247) between non-severe and severe COVID-19 patients. There was no significant association between stroke (OR = 1.79, 95%CI: 0.76 to 4.23, P = 0.185), epilepsy (OR = 2.08, 95%CI: 0.08 to 50.91, P = 0.654) and COVID-19 mortality. In conclusion, nervous system diseases and cerebrovascular disease were associated with severity and mortality of patients with COVID-19. There might be confounding factors that influence the relationship between nervous system diseases and COVID-19 severity as well as mortality.

Immune Response to SARS-CoV-2 Infection in Obesity and T2D: Literature Review

In December 2019, a novel coronavirus known as SARS-CoV-2 was first detected in Wuhan, China, causing outbreaks of the coronavirus disease COVID-19 that has now spread globally. For this reason, The World Health Organization (WHO) declared COVID-19 a public health emergency in March 2020. People living with pre-existing conditions such as obesity, cardiovascular diseases, type 2 diabetes (T2D), and chronic kidney and lung diseases, are prone to develop severe forms of disease with fatal outcomes. Metabolic diseases such as obesity and T2D alter the balance of innate and adaptive responses. Both diseases share common features characterized by augmented adiposity associated with a chronic systemic low-grade inflammation, senescence, immunoglobulin glycation, and abnormalities in the number and function of adaptive immune cells. In obese and T2D patients infected by SARS-CoV-2, where immune cells are already hampered, this response appears to be stronger. In this review, we describe the abnormalities of the immune system, and summarize clinical findings of COVID-19 patients with pre-existing conditions such as obesity and T2D as this group is at greater risk of suffering severe and fatal clinical outcomes.

Clinical Utility of a Nomogram for Predicting 30-Days Poor Outcome in Hospitalized Patients With COVID-19: Multicenter External Validation and Decision Curve Analysis

Aim: Early detection of coronavirus disease 2019 (COVID-19) patients who are likely to develop worse outcomes is of great importance, which may help select patients at risk of rapid deterioration who should require high-level monitoring and more aggressive treatment. We aimed to develop and validate a nomogram for predicting 30-days poor outcome of patients with COVID-19.

Methods: The prediction model was developed in a primary cohort consisting of 233 patients with laboratory-confirmed COVID-19, and data were collected from January 3 to March 20, 2020. We identified and integrated significant prognostic factors for 30-days poor outcome to construct a nomogram. The model was subjected to internal validation and to external validation with two separate cohorts of 110 and 118 cases, respectively. The performance of the nomogram was assessed with respect to its predictive accuracy, discriminative ability, and clinical usefulness.

Results: In the primary cohort, the mean age of patients was 55.4 years and 129 (55.4%) were male. Prognostic factors contained in the clinical nomogram were age, lactic dehydrogenase, aspartate aminotransferase, prothrombin time, serum creatinine, serum sodium, fasting blood glucose, and D-dimer. The model was externally validated in two cohorts achieving an AUC of 0.946 and 0.878, sensitivity of 100 and 79%, and specificity of 76.5 and 83.8%, respectively. Although adding CT score to the clinical nomogram (clinical-CT nomogram) did not yield better predictive performance, decision curve analysis showed that the clinical-CT nomogram provided better clinical utility than the clinical nomogram.

Conclusions: We established and validated a nomogram that can provide an individual prediction of 30-days poor outcome for COVID-19 patients. This practical prognostic model may help clinicians in decision making and reduce mortality.

Laboratory markers associated with COVID-19 progression in patients with or without comorbidity: A retrospective study

OBJECTIVES

To investigate laboratory markers for COVID-19 progression in patients with different medical conditions.

METHODS

We performed a multicenter retrospective study of 836 cases in Hubei. To avoid the collinearity among the indicators, principal component analysis (PCA) followed by partial least squares discriminant analysis (PLS-DA) was performed to obtain an overview of laboratory assessments. Multivariable logistic regression analysis and multivariable Cox proportional hazards regression analysis were respectively used to explore risk factors associated with disease severity and mortality. Survival analysis was performed in patients with the most common comorbidities.

RESULTS

Lactate dehydrogenase (LDH) and prealbumin were associated with disease severity in patients with or without comorbidities, indicated by both PCA/PLS-DA and multivariable logistic regression analysis. The mortality risk was associated with age, LDH, C-reactive protein (CRP), D-dimer, and lymphopenia in patients with comorbidities. CRP was a risk factor associated with short-term mortality in patients with hypertension, but not liver diseases; additionally, D-dimer was a risk factor for death in patients with liver diseases.

CONCLUSIONS

Lactate dehydrogenase was a reliable predictor associated with COVID-19 severity and mortality in patients with different medical conditions. Laboratory biomarkers for mortality risk were not identical in patients with comorbidities, suggesting multiple pathophysiological mechanisms following COVID-19 infection.

Clinical features and potential risk factors for discerning the critical cases and predicting the outcome of patients with COVID-19

Objective

To investigate the clinical features and risk factors for discerning the critical and predicting the outcome of patients with COVID‐19.

Methods

Patients who were admitted to the intensive care unit (ICU) department and general infection department of TaiKang Tongji (Wuhan) Hospital from February 10 to March 27, 2020, were included. Data on clinical features, complications, laboratory parameters, chest CT, nutrient requirement, and electrolyte imbalance were analyzed retrospectively.

Results

A total of 123 (50 critical and 73 non‐critical) patients were enrolled. 65% of patients with comorbidities, hypertension (45.5%), diabetes (21.9%), 36.5% of patients had more than one comorbidity. The proportion of lymphocytes in critical patients was significantly lower than that of non‐critical patients. The proportion of patients with increased NLR, PLR, IL‐6, CRP levels, and chest CT score was significantly higher in the critical than that of non‐critical patients. The logistic regression analysis identified low lymphocyte count, high NLR, PLR, IL‐6, CRP levels, and CT score as independent factors for discerning critical cases and high NLR, PLR, IL‐6, and CT score could predict poor clinical outcome. Furthermore, we identified patients who needed nutrition support (HR 16.99) and with correction of electrolyte imbalance (HR 18.24) via intravenous injection were more likely to have a poor outcome.

Conclusions

The potential risk factors of lower lymphocyte count, high levels of NLR, PLR, IL‐6, CRP, chest CT score, and the statue of nutrient requirement or electrolyte imbalance could assist clinicians in discerning critical cases and predict the poor outcome in patients with COVID‐19.