Prognostic Value of C-Reactive Protein in Patients With Coronavirus 2019

Hematological and Biochemical Parameters at Admission as Predictors for Mortality in Patients with Moderate to Severe COVID-19

Background

Timely diagnosis and effective use of available resources are urgent to avoid the loss of time, medical, and technological resources, particularly in COVID-19 pandemic. This study aimed to identify the most dominant predicting factor for mortality in moderate-severe COVID-19 patients.

Methods

This retrospective cohort study included a total of 253 patients diagnosed with moderate-severe COVID-19. The primary outcome measure was mortality during hospitalization. The receiver operating characteristic (ROC) curve was used to determine cut-off points. The data were categorized according to the cut-off points in ROC curve and analyzed using Chi-square and by binary logistic regression test to identify the independent predictors associated with mortality.

Results

The mean number of leukocytes (/µL), neutrophils (%), neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), C-reactive protein (CRP, mg/L), and D-dimer (mg/L) in the non-survived group was significantly higher than those of the survived group. Meanwhile, the mean number of platelet count/µL, absolute lymphocyte count (ALC), in the non-survived group was significantly lower than those of the survived group. CRP level predicted mortality with a cut-off point of ≥8.41 mg/L, sensitivity of 98.1%, and specificity of 72.0% (P = .000).

Conclusions

High leukocyte count, low platelet count, high NLR, high CRP level, and high D-dimer on admission predicted mortality of COVID-19 patients. In addition, CRP was found to be the most dominant predicting factor of mortality in moderate-severe COVID-19 patients.

The use of prognostic nutritional index (PNI) and selected inflammatory indicators for predicting malnutrition in COVID-19 patients: A retrospective study

BACKGROUND

Malnutrition causes diverse alterations in the immune system, and COVID-19 is an infection affecting the immune system, consequently leading to malnutrition.

AIMS

This study aimed to investigate the use of prognostic nutritional index (PNI) and selected inflammatory indices for malnutrition screening among COVID-19 hospitalized patients.

MATERIAL AND METHODOLOGY

This is a single-center retrospective study that enrolled 289 hospitalized COVID-19 patients between 1st January to 30th April 2021, their median age was 59 years. Demographic and biochemical data were collected from patients' records. The PNI, platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and an early warning score to predict mortality risk (ANDC) were calculated. Univariate and multivariate logistic regression analyses were performed. A P-value of < 0.05 was considered statistically significant.

RESULTS

about 30 % of patients were admitted to the intensive care unit (ICU), and ICU patients had significantly higher levels of white blood cell (WBCs) count, neutrophils, C-reactive protein (C-RP), and D-dimer (P < 0.05). On the other hand, they had significantly lower levels of lymphocytes and serum albumin (P < 0.001; for both). Those with high ANDC scores were more likely to develop severe conditions affecting nutritional status compared to non-ICU (OR = 1.04, 95 % CI:1.014-1.057; P < 0.001). ANDC showed good discrimination ability with an AUC of 0.784 (cut-off value > 68.19 score).

CONCLUSION

It is suggested that ANDC could be used as a predictor for nutritional status and severity in COVID-19 hospitalized patients.

Inflammation as Prognostic Hallmark of Clinical Outcome in Patients with SARS-CoV-2 Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is often characterized by a life-threatening interstitial pneumonia requiring hospitalization. The aim of this retrospective cohort study is to identify hallmarks of in-hospital mortality in patients affected by Coronavirus Disease 19 (COVID-19). A total of 150 patients admitted for COVID-19 from March to June 2021 to "F. Perinei" Murgia Hospital in Altamura, Italy, were divided into survivors (n = 100) and non-survivors groups (n = 50). Blood counts, inflammation-related biomarkers and lymphocyte subsets were analyzed into two groups in the first 24 h after admission and compared by Student's t-test. A multivariable logistic analysis was performed to identify independent risk factors associated with in-hospital mortality. Total lymphocyte count and CD3⁺ and CD4⁺ CD8⁺ T lymphocyte subsets were significantly lower in non-survivors. Serum levels of interleukin-6 (IL-6), lactate dehydrogenase (LDH), C-reactive protein (CRP) and procalcitonin (PCT) were significantly higher in non-survivors. Age > 65 years and presence of comorbidities were identified as independent risk factors associated with in-hospital mortality, while IL-6 and LDH showed a borderline significance. According to our results, markers of inflammation and lymphocytopenia predict in-hospital mortality in COVID-19.

Race and Remdesivir: Examination of Clinical Outcomes in a Racially and Ethnically Diverse Cohort in New York City

Objective

To compare clinical characteristics and examine in-hospital length of stay (LOS) differences for COVID-19 patients who received remdesivir, by race or ethnicity.

Design

Retrospective descriptive analysis comparing cumulative LOS as a proxy of recovery time.

Setting

A large academic medical center serving a minoritized community in Northern Manhattan, New York City.

Participants

Inpatients (N=1024) who received remdesivir from March 30, 2020-April 20, 2021.

Methods

We conducted descriptive analyses among patients who received remdesivir. Patients were described by proxies of social determinants of health (SDOH): race and ethnicity, residence, insurance coverage, and clinical characteristics. We calculated median hospital LOS as the cumulative incidence of hospitalized patients who were discharged alive, and tested differences between groups by using the Gray test. Patients who died or were discharged to hospice were censored at 29 days.

Main Outcome Measures

The primary outcome was hospital LOS. The secondary outcome was in-hospital mortality.

Results

Median LOS was 11.9 days (95% CI, 10.8-13.2) overall, with Black patients having the shortest (10.0 days, 95% CI, 8.0-13.2) and Asian patients having the longest (16.2 days, 95% CI, 8.3-27.2) LOS. A total of 214 patients (21%) died or were discharged to hospice, ranging from 16.5% to 23.7% of patients who identified as Black and Other (multiracial, biracial, declined), respectively.

Conclusions

COVID-19 has disproportionately burdened communities of color. We observed no difference in median LOS between racial or ethnic groups, which supports the notion that the heterogeneous effect of remdesivir in the literature may be explained in part by underrecruitment or participation of Black, Hispanic, and Asian patients in clinical trials.

Factors Affecting Duration of Hospital Stay in Deceased COVID-19 Patients

Objective

Extensive research has been conducted to identify the predictive criteria for COVID-19 disease. White blood cell, C-reactive protein, CRP/albumin ratio, neutrophil-to-lymphocyte ratio and ferritin are among the indicators of increased inflammatory response; hence, they could be used to determine the prognosis of COVID-19 cases. Within the scope of this study, we aimed to elucidate the predictivity of NLR, CAR and other laboratory parameters on the duration of hospital stay and mortality in patients with COVID-19.

Materials and Method

The data of 1516 COVID-19 patients who were hospitalized in our institution have been analyzed retrospectively. Patients were divided into two groups those who deceased within the first 10 days of hospitalization (Group I, ≤10 days) and those who deceased in the later period (Group II, >10 days). Age, gender, time to mortality after hospitalization, neutrophil count, CRP, neutrophil-to-lymphocyte ratio (NLR), CRP/albumin ratio (CAR), and d-dimer values were obtained from blood samples taken during hospitalization.

Results

NLR and CAR values were significantly higher in those who died in the first 10 days compared to the other group (p<0.02 and p<0.001, respectively). In addition, WBC, neutrophil, CRP and d-dimer levels were statistically significantly higher than the other group (p<0.05). Logistic regression analysis results for NLR and CAR were significant. The cut-off values were calculated (5.74 and 4.27, respectively) for both parameters. Among the most common comorbid diseases were hypertension (HT) in 41%, coronary artery disease (CAD) in 41.7%, asthma-chronic obstructive pulmonary disease (COPD) in 36.7%, diabetes mellitus (DM) in 36.1%.

Conclusion

NLR and CAR may have a decisive influence in determining the length of stay in hospital for patients who die in hospital due to COVID-19. In addition, it is recommended that COVID-19 cases with diabetes be followed closely.

C-reactive protein to lymphocyte ratio is a significant predictive factor for poor short-term clinical outcomes of SARS-CoV-2 BA.2.2 patients

Objective

The aim of the present study is to assess the utility of C-reactive protein to Lymphocyte Ratio (CLR) in predicting short-term clinical outcomes of patients infected by SARS-CoV-2 BA.2.2.

Methods

This retrospective study was performed on 1,219 patients with laboratory-confirmed SARS-CoV-2 BA.2.2 to determine the association of CLR with short-term clinical outcomes. Independent Chi square test, Rank sum test, and binary logistic regression analysis were performed to calculate mean differences and adjusted odds ratios (aORs) with their 95% CI, respectively.

Results

Over 8% of patients admitted due to SARS-CoV-2 BA.2.2. were critically ill. The best cut-off value of CLR was 21.25 in the ROC with a sensitivity of 72.3% and a specificity of 86%. After adjusting age, gender, and comorbidities, binary logistic regression analysis showed that elevated CLR was an independent risk factor for poor short-term clinical outcomes of COVID-19 patients.

Conclusion

C-reactive protein to Lymphocyte Ratio is a significant predictive factor for poor short-term clinical outcomes of SARS-CoV-2 BA.2.2 inflicted patients.

Persistence of neutrophil extracellular traps and anticardiolipin auto-antibodies in post-acute phase COVID-19 patients

In the early phase of the pandemic, we were among the first to postulate that neutrophil extracellular traps (NETs) play a key role in COVID-19 pathogenesis. This exploratory prospective study based on 279 individuals showed that plasma levels of neutrophil elastase, myeloperoxidase and circulating DNA of nuclear and mitochondrial origins in nonsevere (NS), severe (S) and postacute phase (PAP) COVID-19 patients were statistically different as compared to the levels in healthy individuals, and revealed the high diagnostic power of these NETs markers in respect to the disease severity. The diagnostic power of NE, MPO, and cir-nDNA as determined by the Area Under Receiver Operating Curves (AUROC) was 0.95, 097, and 0.64; 0.99, 1.0, and 0.82; and 0.94, 1.0, and 0.93, in NS, S, and PAP patient subgroups, respectively. In addition, a significant fraction of NS, S as well as of PAP patients exhibited aCL IgM/IgG and anti-B2GP IgM/IgG positivity. We first demonstrate persistence of these NETs markers in PAP patients and consequently of sustained innate immune response imbalance, and a prolonged low-level pro-thrombotic potential activity highlighting the need to monitor these markers in all COVID-19 PAP individuals, to investigate postacute COVID-19 pathogenesis following intensive care, and to better identify which medical resources will ensure complete patient recovery.

Galectins can serve as biomarkers in COVID-19: A comprehensive systematic review and meta-analysis

Background

Galectins are an eleven-member class of lectins in humans that function as immune response mediators and aberrancies in their expression are commonly associated with immunological diseases. Several studies have focused on galectins as they may represent an important biomarker and a therapeutic target in the fight against COVID-19. This systematic review and meta-analysis examined the usefulness of clinical assessment of circulating galectin levels in patients with COVID-19.

Methods

International databases including PubMed, Scopus, Web of Science, and Embase were systematically used as data sources for our analyses. The random-effect model was implemented to calculate the standardized mean difference (SMD) and a 95% confidence interval (CI).

Results

A total of 18 studies, comprising 2,765 individuals, were identified and used in our analyses. We found that Gal-3 is the most widely investigated galectin in COVID-19. Three studies reported significantly higher Gal-1 levels in COVID-19 patients. Meta-analysis revealed that patients with COVID-19 had statistically higher levels of Gal-3 compared with healthy controls (SMD 0.53, 95% CI 0.10 to 0.96, P=0.02). However, there was no significant difference between severe and non-severe cases (SMD 0.45, 95% CI -0.17 to 1.07, P=0.15). While one study supports lower levels of Gal-8 in COVID-19, Gal-9 was measured to be higher in patients and more severe cases.

Conclusion

Our study supports Gal-3 as a valuable non-invasive biomarker for the diagnosis and/or prognosis of COVID-19. Moreover, based on the evidence provided here, more studies are needed to confirm a similar diagnostic and prognostic role for Gal-1, -8, and -9.

Astegolimab or Efmarodocokin Alfa in Patients With Severe COVID-19 Pneumonia: A Randomized, Phase 2 Trial

OBJECTIVES

Severe cases of COVID-19 pneumonia can lead to acute respiratory distress syndrome (ARDS). Release of interleukin (IL)-33, an epithelial-derived alarmin, and IL-33/ST2 pathway activation are linked with ARDS development in other viral infections. IL-22, a cytokine that modulates innate immunity through multiple regenerative and protective mechanisms in lung epithelial cells, is reduced in patients with ARDS. This study aimed to evaluate safety and efficacy of astegolimab, a human immunoglobulin G2 monoclonal antibody that selectively inhibits the IL-33 receptor, ST2, or efmarodocokin alfa, a human IL-22 fusion protein that activates IL-22 signaling, for treatment of severe COVID-19 pneumonia.

DESIGN

Phase 2, double-blind, placebo-controlled study (COVID-astegolimab-IL).

SETTING

Hospitals.

PATIENTS

Hospitalized adults with severe COVID-19 pneumonia.

INTERVENTIONS

Patients were randomized to receive IV astegolimab, efmarodocokin alfa, or placebo, plus standard of care. The primary endpoint was time to recovery, defined as time to a score of 1 or 2 on a 7-category ordinal scale by day 28.

MEASUREMENTS AND MAIN RESULTS

The study randomized 396 patients. Median time to recovery was 11 days (hazard ratio [HR], 1.01 d; p = 0.93) and 10 days (HR, 1.15 d; p = 0.38) for astegolimab and efmarodocokin alfa, respectively, versus 10 days for placebo. Key secondary endpoints (improved recovery, mortality, or prevention of worsening) showed no treatment benefits. No new safety signals were observed and adverse events were similar across treatment arms. Biomarkers demonstrated that both drugs were pharmacologically active.

CONCLUSIONS

Treatment with astegolimab or efmarodocokin alfa did not improve time to recovery in patients with severe COVID-19 pneumonia.

The presence of SARS-CoV-2 in multiple clinical specimens of a fatal case of COVID-19: a case report

BACKGROUND

The risk of developing severe and even fatal coronavirus disease 2019 (COVID-19) increases with various factors such as advanced age and chronic diseases, especially those treated with immunosuppressive drugs. Viral ribonucleic acid (RNA) and viral load detection in extra-pulmonary specimens have been proposed to indicate disease severity.

CASE PRESENTATION

Here we describe a fatal COVID-19 case of an 83-year-old Caucasian male patient with various underlying comorbidities, including cardiovascular and autoimmune disorders, as well as immunosuppression due to lymphoma treatment. Upon admission, the patient was radiologically diagnosed with severe COVID-19. The patient was febrile and presented with diarrhea, continued dyspnea, tachypnea, and low blood oxygen saturation, treated with high-concentration oxygen supplementation and antibacterial therapy. Overall the patient was treated for COVID-19 for 19 days. Blood tests were performed upon admission, on the fifth, 10th, 13th, and 19th day. In addition, nasopharyngeal swab, blood, urine, and fecal samples were collected from the patient on the 14th day for virological and immunological investigations. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detectable in all samples collected from this patient, including blood plasma and peripheral blood mononuclear cells (PBMC), with very high viral loads. However, neither virus-specific IgA, IgM, nor IgG antibodies were detectable.

CONCLUSIONS

The various cardiovascular, autoimmune, and oncological disorders, advanced age, and the high levels of inflammatory markers predisposed the patient to severe COVID-19 and determined the fatal outcome of the disease. We believe that the multiple specimen SARS-CoV-2 positivity and extremely high viral loads in nasopharyngeal swab and fecal samples to be the result of COVID-19 severity, the inability of viral clearance and weakened immune response due to advanced age, comorbidities, and the presence of non-Hodgkin's lymphoma and the immunosuppressive treatment for it, highlighting the risks of COVID-19 in such patients.

Global Hemostasis Potential in COVID-19 Positive Patients Performed on St-Genesia Show Hypercoagulable State

BACKGROUND

At the dawn of the pandemic, severe forms of COVID-19 were often complicated by thromboembolisms. However, routine laboratory tests cannot be used to predict thromboembolic events. The objective of this study was to investigate the potential value of the thrombin generation test (TGT) in predicting hypercoagulability and thrombotic risk in the aforementioned set of patients.

METHODS

The study panel comprised 52 patients divided into two groups (26 COVID-19 positive and 26 COVID-19 negative); COVID-19-positive patients were further grouped in "severe" (n = 11) and "non-severe" (n = 15) categories based on clinical criteria. The routine blood tests and TGT of these patients were retrospectively analyzed.

RESULTS

All 26 COVID-19-positive patients showed decreased lymphocyte, monocyte and basophil counts and increased lactate dehydrogenase (LDH), aspartate aminotransferase (AST), and alanine transaminase (ALT) compared with control patients. Conversely, we did not observe statistically significant differences between severe and non-severe patients despite anecdotal variations in the distribution patterns. TGT without thrombomodulin (TM) addition showed statistically significant differences in the thrombin peak heights between COVID-19-positive and negative patients. After addition of TM, peak height, Endogenous Thrombin Potential (ETP) and velocity index were increased in all COVID-19-positive patients while the percentage of inhibition of ETP was reduced. These trends correlated with the severity of disease, showing a greater increase in peak height, ETP, velocity index and a drastic reduction in the percentage of ETP inhibition in more severely affected patients.

CONCLUSIONS

Our data suggest that all COVID-19 patients harbor a hypercoagulable TGT profile and that this is further pronounced in severely affected patients.

Chest x-ray imaging score is associated with severity of COVID-19 pneumonia: the MBrixia score

Spatial resolution in existing chest x-ray (CXR)-based scoring systems for coronavirus disease 2019 (COVID-19) pneumonia is low, and should be increased for better representation of anatomy, and severity of lung involvement. An existing CXR-based system, the Brixia score, was modified to increase the spatial resolution, creating the MBrixia score. The MBrixia score is the sum, of a rule-based quantification of CXR severity on a scale of 0 to 3 in 12 anatomical zones in the lungs. The MBrixia score was applied to CXR images from COVID-19 patients at a single tertiary hospital in the period May 4th-June 5th, 2020. The relationship between MBrixia score, and level of respiratory support at the time of performed CXR imaging was investigated. 37 hospitalized COVID-19 patients with 290 CXRs were identified, 22 (59.5%) were admitted to the intensive care unit and 10 (27%) died during follow-up. In a Poisson regression using all 290 MBrixia scored CXRs, a higher MBrixia score was associated with a higher level of respiratory support at the time of performed CXR. The MBrixia score could potentially be valuable as a quantitative surrogate measurement of COVID-19 pneumonia severity, and future studies should investigate the score's validity and capabilities of predicting clinical outcomes.

Assessment of inflammatory markers and their association with disease mortality in severe COVID-19 patients of tertiary care hospital in South India

Background

COVID-19 infection involves a complex interplay of the immunological and inflammatory responses. Low blood-oxygen levels have been a hallmark in COVID-19 patients. The lung tissue damage infiltered by the viral-mediated inflammation decreases oxygen saturation to cause silent hypoxia and cell death. This study aimed to evaluate the association of inflammatory biomarkers with oxygen saturation (SpO₂) and mortality in severe COVID-19 patients.

Methods

A total of 190 severe COVID-19 patients were included in this study after confirmed by the RT-PCR assay. The laboratory tests were performed for biochemical assessment. Serum levels of C-reactive protein (CRP), lactate dehydrogenase (LDH), and ferritin were determined and compared between survivors and nonsurvivors using independent sample t-test. The correlation of these inflammatory markers was studied using Spearman’s correlation, and their association with mortality was studied using logistic regression.

Results

All the COVID-19 patients were severe with SpO₂< 90% and respiratory rate > 30/min. While the serum levels of CRP, LDH, ferritin, aspartate transaminase (AST), urea, and random blood sugar (RBS) were elevated, hemoglobin (Hb) and SpO₂ levels were reduced in COVID-19 patients. LDH and ferritin levels were significantly higher in nonsurvivors compared to survivors with p values of 0.001 and 0.022 respectively. Spearman’s correlation showed a significant correlation of the inflammatory markers with SpO₂, serum electrolytes (potassium, chloride), liver enzymes (AST and alanine transaminase (ALT)), and markers of kidney damage (urea, creatinine).

Conclusion

Inflammatory markers could effectively discriminate the risk of mortality in severe COVID-19 patients. As CRP, LDH, and ferritin levels determine the tissue oxygen availability, they seem to be valuable biomarkers in the prognosis of COVID-19.

Evaluation of emerging inflammatory markers for predicting oxygen support requirement in COVID-19 patients

Coronavirus disease 2019 (COVID-19), a highly contagious pathogenic viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly and remains a challenge to global public health. COVID-19 patients manifest various symptoms from mild to severe cases with poor clinical outcomes. Prognostic values of novel markers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and C-reactive protein to lymphocyte ratio (CLR) calculated from routine laboratory parameters have recently been reported to predict severe cases; however, whether this investigation can guide oxygen therapy in COVID-19 patients remains unclear. In this study, we assessed the ability of these markers in screening and predicting types of oxygen therapy in COVID-19 patients. The retrospective data of 474 COVID-19 patients were categorized into mild and severe cases and grouped according to the types of oxygen therapy requirement, including noninvasive oxygen support, high-flow nasal cannula and invasive mechanical ventilator. Among the novel markers, the ROC curve analysis indicated a screening cutoff of CRP ≥ 30.0 mg/L, NLR ≥ 3.0 and CLR ≥ 25 in predicting the requirement of any type of oxygen support. The NLR and CLR with increasing cut-off values have discriminative power with high accuracy and specificity for more effective oxygen therapy with a high-flow nasal cannula (NLR ≥ 6.0 and CLR ≥ 60) and mechanical ventilator (NLR ≥ 8.0 and CLR ≥ 80). Our study thus identifies potential markers to differentiate the suitable management of oxygen therapy in COVID-19 patients at an earlier time for improving disease outcomes with limited respiratory support resources.

The role of IL-6 in coronavirus, especially in COVID-19

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infects both people and animals and may cause significant respiratory problems, including lung illness: Corona Virus Disease 2019 (COVID-19). Swabs taken from the throat and nose of people who have the illness or are suspected of having it have shown this pathogenic virus. When SARS-CoV-2 infects the upper and lower respiratory tracts, it may induce moderate to severe respiratory symptoms, as well as the release of pro-inflammatory cytokines including interleukin 6 (IL-6). COVID-19-induced reduction of IL-6 in an inflammatory state may have a hitherto undiscovered therapeutic impact. Many inflammatory disorders, including viral infections, has been found to be regulated by IL-6. In individuals with COVID-19, one of the primary inflammatory agents that causes inflammatory storm is IL-6. It promotes the inflammatory response of virus infection, including the virus infection caused by SARS-CoV-2, and provides a new diagnostic and therapeutic strategy. In this review article, we highlighted the functions of IL-6 in the coronavirus, especially in COVID-19, showing that IL-6 activation plays an important function in the progression of coronavirus and is a rational therapeutic goal for inflammation aimed at coronavirus.

Clinical and laboratory predictors for disease progression in patients with COVID-19: A multi-center cohort study

BACKGROUND

Reliable clinical and laboratory predictors of coronavirus disease 2019 (COVID-19) disease progression could help to identify the subset of patients who are susceptible to severe symptoms. This study sought to identify the predictors for disease progression in patients with COVID-19.

METHODS

This study recruited consecutive patients from four hospitals between March 1, 2020, and July 31, 2021. Demographic characteristics, laboratory results, and clinical outcomes were collected.

RESULTS

Among the 239 enrolled patients, 39.3% (94/239) experienced in-hospital disease progression. Multivariate logistic regression revealed that coronary arterial disease (CAD) (OR, 4.15; 95% C.I., 1.47-11.66), cerebrovascular attack (CVA) (OR, 12.98; 95% C.I., 1.30-129.51), platelet count < median value (OR, 3.23; 95% C.I., 1.65-6.32), and C-reactive protein (CRP) levels > median value of (OR, 2.25; 95% C.I., 1.02-4.99) were independent factors associated with COVID-19 progression. Patients who underwent disease progression at days 1, 4, and 7 presented lower lymphocyte counts and higher CRP levels, compared to patients without disease progression.

CONCLUSIONS

The study revealed that in hospitalized COVID-19 patients, comorbidity with CAD and CVA, low platelet count, and elevated CRP levels were independently associated with disease progression. Compared with patients without disease progression, those with disease progression presented persistently low lymphocyte counts and elevated CRP levels.

C-Reactive Protein (CRP): A poor prognostic biomarker in COVID-19

Introduction

The COVID-19 pandemic continues to be rampant with considerable morbidity and mortality worldwide since its emergence in December 2019. Several studies have focused on identifying different predictive factors of poor prognosis, including biological markers, such as C Reactive Protein among others. The objective of our work was to determine whether the CRP levels on admission to the intensive care unit are predictive of an unfavorable evolution of patients with COVID-19 through the experience of the Anesthesia and Intensive Care Unit of the University Hospital of Oujda and to compare our results with those reported in the literature.

Methods

We conducted a retrospective, monocentric, descriptive and analytical study in the Department of Anesthesia and Intensive Care of the Mohammed VI University Hospital of Oujda, Morocco, between March 2020 and October 2021, including all critically ill patients admitted to the department during this period and meeting the inclusion criteria. The baseline admission CRP value was arbitrarily set at 100mg/d, thus conditioning the division of our patients into two groups (group 1: CRP < 100mg/L, group 2: CRP ≥ 100mg/L).

Results

Among our 1035 included patients, 291 patients with had a CRP<100mlg/L (group 1) and 744 presented a CRP level equal or superior to 100mg/L (group 2). Lung parenchymal involvement was more severe or even critical (CT involvement > 75%) in group 2 (60.8%) compared to group 1 (39.2%). In group 2, 79.8% of patients were mechanically ventilated, compared to 20.2% of patients in group 1. Finally, the mortality rate in patients with a CRP ≥ 100mg/l was 77.4%, compared with 22.6% for patients with a CRP < 100mg/l. These findings are all statistically highly significant (p<0.001).

Conclusion

Given the high contagiousness of the virus and the emergence of several variants, the management of the COVID-19 pandemic has focused more on prevention through vaccination against the virus, but also on an early identification of patients likely to evolve unfavorably for a personalized management.

Prognostic peripheral blood biomarkers at ICU admission predict COVID-19 clinical outcomes

The COVID-19 pandemic continues to challenge the capacities of hospital ICUs which currently lack the ability to identify prospectively those patients who may require extended management. In this study of 90 ICU COVID-19 patients, we evaluated serum levels of four cytokines (IL-1β, IL-6, IL-10 and TNFα) as well as standard clinical and laboratory measurements. On 42 of these patients (binned into Initial and Replication Cohorts), we further performed CyTOF-based deep immunophenotyping of peripheral blood mononuclear cells with a panel of 38 antibodies. All measurements and patient samples were taken at time of ICU admission and retrospectively linked to patient clinical outcomes through statistical approaches. These analyses resulted in the definition of a new measure of patient clinical outcome: patients who will recover after short ICU stays (&lt; 6 days) and those who will subsequently die or recover after long ICU stays (≥6 days). Based on these clinical outcome categories, we identified blood prognostic biomarkers that, at time of ICU admission, prospectively distinguish, with 91% sensitivity and 91% specificity (positive likelihood ratio 10.1), patients in the two clinical outcome groups. This is achieved through a tiered evaluation of serum IL-10 and targeted immunophenotyping of monocyte subsets, specifically, CD11clow classical monocytes. Both immune biomarkers were consistently elevated ( ≥15 pg/ml and ≥2.7 x107/L for serum IL-10 and CD11clow classical monocytes, respectively) in those patients who will subsequently die or recover after long ICU stays. This highly sensitive and specific prognostic test could prove useful in guiding clinical resource allocation.

Comparison of the characteristics, morbidity and mortality of COVID-19 between first and second/third wave in a hospital setting in Lombardy: a retrospective cohort study

Coronavirus disease 2019 (COVID-19) represents a major health problem in terms of deaths and long-term sequelae. We conducted a retrospective cohort study at Montichiari Hospital (Brescia, Italy) to better understand the determinants of outcome in two different COVID-19 outbreaks. A total of 634 unvaccinated patients admitted from local emergency room to the Internal Medicine ward with a confirmed diagnosis of SARS-CoV-2 infection and a moderate-to-severe COVID-19 were included in the study. A group of 260 consecutive patients during SARS-CoV-2 first wave (from February to May 2020) and 374 consecutive patients during SARS-CoV-2 2nd/3rd wave (from October 2020 to May 2021) were considered. Demographic data were not significantly different between waves, except a lower prevalence of female sex during first wave. Mortality was significantly higher during the 1st wave than in the following periods (24.2% vs. 11%; p < 0.001). Time from symptoms onset to hospital admission was longer during first wave (8 ± 6 vs. 6 ± 4 days; p < 0.001), while in-hospital staying was significantly shorter (10 ± 14 vs. 15 ± 11 days; p < 0.001). Other significant differences were a larger use of corticosteroids and low-molecular weight heparin as well less antibiotic prescription during the second wave. Respiratory, bio-humoral and X-ray scores were significantly poorer at the time of admission in first-wave patients. After a multivariate regression analysis, C-reactive protein and procalcitonin values, % fraction of inspired oxygen on admission to the Internal Medicine ward and length of hospital stay and duration of symptoms were the strongest predictors of outcome. Concomitant anti-hypertensive treatment (including ACE-inhibitors and angiotensin-receptor blockers) did not affect the outcome. In conclusion, our data suggest that earlier diagnosis, timely hospital admission and rational use of the therapeutic options reduced the systemic inflammatory response and were associated to a better outcome during the 2nd/3rd wave.

Predictive models for COVID-19 detection using routine blood tests and machine learning

The problem of accurate, fast, and inexpensive COVID-19 tests has been urgent till now. Standard COVID-19 tests need high-cost reagents and specialized laboratories with high safety requirements, are time-consuming. Data of routine blood tests as a base of SARS-CoV-2 invasion detection allows using the most practical medicine facilities. But blood tests give general information about a patient's state, which is not directly associated with COVID-19. COVID-19-specific features should be selected from the list of standard blood characteristics, and decision-making software based on appropriate clinical data should be created. This review describes the abilities to develop predictive models for COVID-19 detection using routine blood tests and machine learning.

The Usefulness of the COVID-GRAM Score in Predicting the Outcomes of Study Population with COVID-19

BACKGROUND

The COVID-GRAM is a clinical risk rating score for predicting the prognosis of hospitalized COVID-19 infected patients.

AIM

Our study aimed to evaluate the use of the COVID-GRAM score in patients with COVID-19 based on the data from the COronavirus in the LOwer Silesia (COLOS) registry.

MATERIAL AND METHODS

The study group (834 patients of Caucasian patients) was retrospectively divided into three arms according to the risk achieved on the COVID-GRAM score calculated at the time of hospital admission (between February 2020 and July 2021): low, medium, and high risk. The Omnibus chi-square test, Fisher test, and Welch ANOVA were used in the statistical analysis. Post-hoc analysis for continuous variables was performed using Tukey's correction with the Games-Howell test. Additionally, the ROC analysis was performed over time using inverse probability of censorship (IPCW) estimation. The GRAM-COVID score was estimated from the time-dependent area under the curve (AUC).

RESULTS

Most patients (65%) had a low risk of complications on the COVID-GRAM scale. There were 113 patients in the high-risk group (13%). In the medium- and high-risk groups, comorbidities occurred statistically significantly more often, e.g., hypertension, diabetes, atrial fibrillation and flutter, heart failure, valvular disease, chronic kidney disease, and obstructive pulmonary disease (COPD), compared to low-risk tier subjects. These individuals were also patients with a higher incidence of neurological and cardiac complications in the past. Low saturation of oxygen values on admission, changes in C-reactive protein, leukocytosis, hyperglycemia, and procalcitonin level were associated with an increased risk of death during hospitalization. The troponin level was an independent mortality factor. A change from low to medium category reduced the overall survival probability by more than 8 times and from low to high by 25 times. The factor with the strongest impact on survival was the absence of other diseases. The medium-risk patient group was more likely to require dialysis during hospitalization. The need for antibiotics was more significant in the high-risk group on the GRAM score.

CONCLUSION

The COVID-GRAM score corresponds well with total mortality. The factor with the strongest impact on survival was the absence of other diseases. The worst prognosis was for patients who were unconscious during admission. Patients with higher COVID-GRAM score were significantly less likely to return to full health during follow-up. There is a continuing need to develop reliable, easy-to-adopt tools for stratifying the course of SARS-CoV-2 infection.

Lymphocyte–C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission

In this study, we aimed to explore whether lymphocyte–C-reactive protein ratio (LCR) can differentiate disease severity of coronavirus disease 2019 (COVID-19) patients and its value as an assistant screening tool for admission to hospital and intensive care unit (ICU). A total of 184 adult COVID-19 patients from the COVID-19 Treatment Center in Heilongjiang Province at the First Affiliated Hospital of Harbin Medical University between January 2020 and March 2021 were included in this study. Patients were divided into asymptomatic infection group, mild group, moderate group, severe group, and critical group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (ninth edition). Demographic and clinical data including gender, age, comorbidities, severity of COVID-19, white blood cell count (WBC), neutrophil proportion (NEUT%), lymphocyte count (LYMPH), lymphocyte percentage (LYM%), red blood cell distribution width (RDW), platelet (PLT), C-reactive protein (CRP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum creatinine (SCr), albumin (ALB), total bilirubin (TB), direct bilirubin (DBIL), indirect bilirubin (IBIL), and D-dimer were obtained and collated from medical records at admission, from which sequential organ failure assessment (SOFA) score and LCR were calculated, and all the above indicators were compared among the groups. Multiple clinical parameters, including LYMPH, CRP, and LCR, showed significant differences among the groups. The related factors to classify COVID-19 patients into moderate, severe, and critical groups included age, number of comorbidities, WBC, LCR, and AST. Among these factors, the number of comorbidities showed the greatest effect, and only WBC and LCR were protective factors. The area under the receiver operating characteristic (ROC) curve of LCR to classify COVID-19 patients into moderate, severe, and critical groups was 0.176. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 1,780.7050 and 84.6% and 66.2%, respectively. The related factors to classify COVID-19 patients into severe and critical groups included the number of comorbidities, PLT, LCR, and SOFA score. Among these factors, SOFA score showed the greatest effect, and LCR was the only protective factor. The area under the ROC curve of LCR to classify COVID-19 patients into severe and critical groups was 0.106. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 571.2200 and 81.3% and 90.0%, respectively. In summary, LCR can differentiate disease severity of COVID-19 patients and serve as a simple and objective assistant screening tool for hospital and ICU admission.

Bidirectional causal associations between type 2 diabetes and COVID-19

Observational studies have reported high comorbidity between type 2 diabetes (T2D) and severe COVID-19. However, the causality between T2D and COVID-19 has yet to be validated. We performed genetic correlation and Mendelian randomization (MR) analyses to assess genetic relationships and potential causal associations between T2D and three COVID-19 outcomes (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] infection, COVID-19 hospitalization, and critical COVID-19). Molecular pathways connecting SARS-CoV-2 and COVID-19 were reconstructed to extract insights into the potential mechanisms underlying the connection. We identified a high genetic overlap between T2D and each COVID-19 outcome (genetic correlations 0.21-0.28). The MR analyses indicated that genetic liability to T2D confers a causal effect on hospitalized COVID-19 (odds ratio 1.08, 95% confidence interval [CI] 1.04-1.12) and critical COVID-19 (1.09, 1.03-1.16), while genetic liability to SARS-CoV-2 infection exerts a causal effect on T2D (1.25, 1.00-1.56). There was suggestive evidence that T2D was associated with an increased risk for SARS-CoV-2 infection (1.02, 1.00-1.03), while critical COVID-19 (1.06, 1.00-1.13) and hospitalized COVID-19 (1.09, 0.99-1.19) were associated with an increased risk for T2D. Pathway analysis identified a panel of immunity-related genes that may mediate the links between T2D and COVID-19 at the molecular level. Our study provides robust support for the bidirectional causal associations between T2D and COVID-19. T2D may contribute to amplifying the severity of COVID-19, while the liability to COVID-19 may increase the risk for T2D.

Prognostic Model of ICU Admission Risk in Patients with COVID-19 Infection Using Machine Learning

With the onset of the COVID-19 pandemic, the number of critically sick patients in intensive care units (ICUs) has increased worldwide, putting a burden on ICUs. Early prediction of ICU requirement is crucial for efficient resource management and distribution. Early-prediction scoring systems for critically ill patients using mathematical models are available, but are not generalized for COVID-19 and Non-COVID patients. This study aims to develop a generalized and reliable prognostic model for ICU admission for both COVID-19 and non-COVID-19 patients using best feature combination from the patient data at admission. A retrospective cohort study was conducted on a dataset collected from the pulmonology department of Moscow City State Hospital between 20 April 2020 and 5 June 2020. The dataset contains ten clinical features for 231 patients, of whom 100 patients were transferred to ICU and 131 were stable (non-ICU) patients. There were 156 COVID positive patients and 75 non-COVID patients. Different feature selection techniques were investigated, and a stacking machine learning model was proposed and compared with eight different classification algorithms to detect risk of need for ICU admission for both COVID-19 and non-COVID patients combined and COVID patients alone. C-reactive protein (CRP), chest computed tomography (CT), lung tissue affected (%), age, admission to hospital, and fibrinogen parameters at hospital admission were found to be important features for ICU-requirement risk prediction. The best performance was produced by the stacking approach, with weighted precision, sensitivity, F1-score, specificity, and overall accuracy of 84.45%, 84.48%, 83.64%, 84.47%, and 84.48%, respectively, for both types of patients, and 85.34%, 85.35%, 85.11%, 85.34%, and 85.35%, respectively, for COVID-19 patients only. The proposed work can help doctors to improve management through early prediction of the risk of need for ICU admission of patients during the COVID-19 pandemic, as the model can be used for both types of patients.

Dysregulated naïve B cells and de novo autoreactivity in severe COVID-19

Severe SARS-CoV-2 infection¹ has been associated with highly inflammatory immune activation since the earliest days of the COVID-19 pandemic^2–5. More recently, these responses have been associated with the emergence of self-reactive antibodies with pathologic potential^6–10, although their origins and resolution have remained unclear¹¹. Previously, we and others have identified extrafollicular B cell activation, a pathway associated with the formation of new autoreactive antibodies in chronic autoimmunity^12,13, as a dominant feature of severe and critical COVID-19 (refs. ^14–18). Here, using single-cell B cell repertoire analysis of patients with mild and severe disease, we identify the expansion of a naive-derived, low-mutation IgG1 population of antibody-secreting cells (ASCs) reflecting features of low selective pressure. These features correlate with progressive, broad, clinically relevant autoreactivity, particularly directed against nuclear antigens and carbamylated proteins, emerging 10–15 days after the onset of symptoms. Detailed analysis of the low-selection compartment shows a high frequency of clonotypes specific for both SARS-CoV-2 and autoantigens, including pathogenic autoantibodies against the glomerular basement membrane. We further identify the contraction of this pathway on recovery, re-establishment of tolerance standards and concomitant loss of acute-derived ASCs irrespective of antigen specificity. However, serological autoreactivity persists in a subset of patients with postacute sequelae, raising important questions as to the contribution of emerging autoreactivity to continuing symptomology on recovery. In summary, this study demonstrates the origins, breadth and resolution of autoreactivity in severe COVID-19, with implications for early intervention and the treatment of patients with post-COVID sequelae.

Single-cell B cell repertoire analysis identifies the expansion of a naive-derived population of antibody-secreting cells contributing to de novo autoreactivity in patients with severe COVID-19 and those with post-COVID symptoms.

Facilitating Safe Discharge Through Predicting Disease Progression in Moderate Coronavirus Disease 2019 (COVID-19): A Prospective Cohort Study to Develop and Validate a Clinical Prediction Model in Resource-Limited Settings

BACKGROUND

In locations where few people have received coronavirus disease 2019 (COVID-19) vaccines, health systems remain vulnerable to surges in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Tools to identify patients suitable for community-based management are urgently needed.

METHODS

We prospectively recruited adults presenting to 2 hospitals in India with moderate symptoms of laboratory-confirmed COVID-19 to develop and validate a clinical prediction model to rule out progression to supplemental oxygen requirement. The primary outcome was defined as any of the following: SpO2 < 94%; respiratory rate > 30 BPM; SpO2/FiO2 < 400; or death. We specified a priori that each model would contain three clinical parameters (age, sex, and SpO2) and 1 of 7 shortlisted biochemical biomarkers measurable using commercially available rapid tests (C-reactive protein [CRP], D-dimer, interleukin 6 [IL-6], neutrophil-to-lymphocyte ratio [NLR], procalcitonin [PCT], soluble triggering receptor expressed on myeloid cell-1 [sTREM-1], or soluble urokinase plasminogen activator receptor [suPAR]), to ensure the models would be suitable for resource-limited settings. We evaluated discrimination, calibration, and clinical utility of the models in a held-out temporal external validation cohort.

RESULTS

In total, 426 participants were recruited, of whom 89 (21.0%) met the primary outcome; 257 participants comprised the development cohort, and 166 comprised the validation cohort. The 3 models containing NLR, suPAR, or IL-6 demonstrated promising discrimination (c-statistics: 0.72-0.74) and calibration (calibration slopes: 1.01-1.05) in the validation cohort and provided greater utility than a model containing the clinical parameters alone.

CONCLUSIONS

We present 3 clinical prediction models that could help clinicians identify patients with moderate COVID-19 suitable for community-based management. The models are readily implementable and of particular relevance for locations with limited resources.

Factors Affecting the Self-Isolation Monitoring Program for COVID-19 Patients at the Universitas Indonesia Hospital

When the outbreak of the COVID-19 delta variant occurred in June 2021, there was a marked increase in Indonesia's number of self-isolated patients. The Universitas Indonesia Hospital provided a One-Stop Service (OSS) to monitor COVID-19 patients on self-isolation. This study was conducted to determine the effectiveness of the self-isolation monitoring performed by hospitals and the factors that determined the outcomes of patients on self-isolation. This study was conducted using a cross-sectional method based on secondary data from electronic medical records. Data analysis was performed by determining the relationship of patient risk factors and characteristics with COVID-19 outcomes. The study found that poorer symptoms, administration of antibiotics, absence of shortness of breath, and normal ALT levels significantly improved the outcome of OSS patients. The study also suggested that during monitoring of patients on COVID-19 self-isolation, chest/thorax radiography is necessary. The self-isolation monitoring program is essential to observe the patient's condition and evaluate the possibility of deteriorating conditions that could lead to admission decisions in the early or middle stages of the program. This will be beneficial during pandemic emergencies.

Predictors of intensive care unit admission and mortality in SARS-CoV-2 infection: A cross sectional study at a tertiary care hospital

Background

The transmissibility and associated morbidity and mortality of severe acute respiratory syndrome-related coronavirus (SARS-Cov-2), have overwhelmed worldwide healthcare systems, resulting in an urgent need to understand this virus and its associated effects. The aim of our study was to identify patient symptoms, clinical characteristics, laboratory, and radiology findings that are associated with serious morbidity and mortality in COVID-19 patients.

Methods

A cross sectional study was conducted in Jaber Al Ahmad Hospital, the designated COVID-19 center in Kuwait between August 1st, 2020 and January 31st, 2021. The main outcomes measured in this study were to identify variables associated with intensive care unit (ICU) admission, as proxy for serious morbidity, and in hospital mortality.

Results

Two hundred and seventy-six patients were included in the study. Thirty-six (13%) patients were admitted to intensive care unit (ICU) and 33 (12%) patients expired. On multivariate analysis we found having elevated fibrinogen [OR 1.39, 95% CI 1.08–1.64, P = 0.04], low estimated glomerular filtration rate (eGFR) [OR 0.89, 95% CI 0.81–0.95, P = 0.02], and having bilateral patchy lung shadowing [OR 6.68, 95% CI 1.85–15.28, P < 0.01] to be significantly associated with increase odds of ICU admission. Elevated CRP [OR 1.25, 95% CI 1.10–1.98, P < 0.01], low eGFR [OR 0.95, 95% CI 0.90–0.99, P = 0.05] and having ischemic heart disease [OR 7.03, 95% CI 1.60–46.42, P = 0.04] were independently associated with increased odds of mortality.

Conclusion

Certain inflammatory and coagulopathy markers, and having certain lung radiological features, in addition to having medical comorbidities, specifically, ischemic heart disease and renal impairment are key predictors for serious morbidity and mortality in patients infected with COVID-19. These should be incorporated into medical institutes risk assessment tools used by physicians and policy makers to instigate, prioritize, and reprioritize care in patients with COVID-19 and instigate preventative strategy to reduce the impact of future outbreak.

•

Understanding risk factors associated with worse outcomes when infected with COVID-19 infection is important.

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A multifactorial model incorporating certain laboratory blood tests and patient clinical characteristics seems to be the best way to predict morbidity and mortality.

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Obesity, Cardiovascular and renal deficiencies are predictors of worse outcomes and so should be prioritized in managing COVID-19 patients.

Effect of Molnupiravir on Biomarkers, Respiratory Interventions, and Medical Services in COVID-19 : A Randomized, Placebo-Controlled Trial

BACKGROUND

In the MOVe-OUT trial, molnupiravir showed a clinically meaningful reduction in the risk for hospitalization or death in adults with mild to moderate COVID-19 and risk factors for progression to severe disease.

OBJECTIVE

To identify other potential clinical benefits of molnupiravir versus placebo.

DESIGN

Secondary analysis of the randomized, double-blind, placebo-controlled phase 3 component of MOVe-OUT. (ClinicalTrials.gov: NCT04575597).

SETTING

107 sites globally.

PARTICIPANTS

1433 nonhospitalized adults aged 18 years or older with mild to moderate COVID-19.

INTERVENTION

Molnupiravir, 800 mg, or placebo every 12 hours for 5 days.

MEASUREMENTS

Changes from baseline in C-reactive protein (CRP) concentration and oxygen saturation (Spo 2), need for respiratory interventions (including invasive mechanical ventilation), and need for medical services in all randomly assigned participants through day 29, and need for respiratory interventions and time to discharge in the subgroup of participants who were hospitalized after randomization.

RESULTS

Participants receiving molnupiravir showed faster normalization of CRP and Spo 2, with improvements observed on day 3 of therapy, compared with placebo. Molnupiravir-treated participants had a decreased need for respiratory interventions versus placebo-treated participants (relative risk reduction [RRR], 34.3% [95% CI, 4.3% to 54.9%]), with similar findings in participants who were hospitalized after randomization (RRR, 21.3% [CI, 0.2% to 38.0%]). Hospitalized participants who received molnupiravir were discharged a median of 3 days before those who received placebo. Acute care visits (7.2% vs. 10.6%; RRR, 32.1% [CI, 4.4% to 51.7%]) and COVID-19-related acute care visits (6.6% vs. 10.0%; RRR, 33.8% [CI, 5.6% to 53.6%]) were less frequent in molnupiravir- versus placebo-treated participants.

LIMITATIONS

Some analyses were performed post hoc. Longer-term benefits of molnupiravir therapy were not evaluated. Participants were not immunized against SARS-CoV-2.

CONCLUSION

The findings suggest there are additional important clinical benefits of molnupiravir beyond reduction in hospitalization or death.

PRIMARY FUNDING SOURCE

Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc.

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.

COVID-19 Severity and Mortality in Two Pandemic Waves in Poland and Predictors of Poor Outcomes of SARS-CoV-2 Infection in Hospitalized Young Adults

SARS-CoV-2 variants pose a significant threat to global public health. However, their influence on disease severity, especially among young adults who may exhibit different clinical characteristics, is debatable. In this retrospective study of 229 young adults hospitalized with COVID-19, we investigated the differences between Poland's second and third waves of the pandemic. To identify potential predictors of severe COVID-19 in young adults, we analyzed patient characteristics and laboratory findings between survivors and non-survivors and we performed logistic regression to assess the risk of death, mechanical ventilation, and intensive care unit treatment. We found no increase in COVID-19 severity comparing the third and second waves of the pandemic, indicating that the alpha variant had no influence on disease severity. In addition, we found that factors, such as obesity, comorbidities, lung involvement, leukocytosis, neutrophilia, lymphopenia, higher IG count, the neutrophil-to-lymphocyte ratio, C-reactive protein, procalcitonin, interleukin-6, D-Dimer, lactate dehydrogenase, high-sensitive troponin I, creatine kinase-myocardial band, myoglobin, N-terminal-pro-B-type natriuretic peptide, creatinine, urea and gamma-glutamyl transferase, lower estimated glomerular filtration rate, albumin, calcium and vitamin D3, possibly a decrease in red blood cell counts, hemoglobin and hematocrit, and an increase in creatine kinase during hospitalization may be associated with poor outcomes of COVID-19.

C-Reactive Protein Velocity (CRPv) as a New Biomarker for the Early Detection of Acute Infection/Inflammation

C-reactive protein (CRP) is considered a biomarker of infection/inflammation. It is a commonly used tool for early detection of infection in the emergency room or as a point-of-care test and especially for differentiating between bacterial and viral infections, affecting decisions of admission and initiation of antibiotic treatments. As C-reactive protein is part of a dynamic and continuous inflammatory process, a single CRP measurement, especially at low concentrations, may erroneously lead to a wrong classification of an infection as viral over bacterial and delay appropriate antibiotic treatment. In the present review, we introduce the concept of C-reactive protein dynamics, measuring the velocity of C-reactive protein elevation, as a tool to increase this biomarker’s diagnostic ability. We review the studies that helped define new metrics such as estimated C-reactive protein velocity (velocity of C-reactive protein elevation from symptoms’ onset to first C-reactive protein measurement) and the measured C-reactive protein velocity (velocity between sequential C-reactive protein measurements) and the use of these metrics in different clinical scenarios. We also discuss future research directions for this novel metric.

A Real Pandora's Box in Pandemic Times: A Narrative Review on the Acute Cardiac Injury Due to COVID-19

The intricate relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the cardiovascular system is an extensively studied pandemic topic, as there is an ever-increasing amount of evidence that reports a high prevalence of acute cardiac injury in the context of viral infection. In patients with Coronavirus disease 2019, COVID-19, a significant increase in serum levels of cardiac troponin or other various biomarkers was observed, suggesting acute cardiac injury, thus predicting both a severe course of the disease and a poor outcome. Pathogenesis of acute cardiac injury is not yet completely elucidated, though several mechanisms are allegedly involved, such as a direct cardiomyocyte injury, oxygen supply-demand inequity caused by hypoxia, several active myocardial depressant factors during sepsis, and endothelial dysfunction due to the hyperinflammatory status. Moreover, the increased levels of plasma cytokines and catecholamines and a significantly enhanced prothrombotic environment may lead to the destabilization and rupture of atheroma plaques, subsequently triggering an acute coronary syndrome. In the present review, we focus on describing the epidemiology, pathogenesis, and role of biomarkers in the diagnosis and prognosis of patients with acute cardiac injury in the setting of the COVID-19 pandemic. We also explore some novel therapeutic strategies involving immunomodulatory therapy, as well as their role in preventing a severe form of the disease, with both the short-term outcome and the long-term cardiovascular sequelae being equally important in patients with SARS-CoV-2 induced acute cardiac injury.

Biomarkers of Inflammation among Patients with COVID-19: A Single-Centre Prospective Study from Prishtina, Kosovo

SARS-CoV-2 infection involves the phase of viral replication and inflammatory response predicting the severity of COVID-19. The aim of the study was to analyze the association between IL-6 and hematological and inflammatory parameters and outcomes of patients with COVID-19. Plasma interleukin 6 (IL-6) levels and other inflammatory and hematological parameters were analyzed in 86 adult patients diagnosed with SARS-CoV-2 infection in Kosovo. The median age of patients was 61.50 (49.75–67.25) years. Over half of patients were categorised as severe (58%) and had comorbidities (69%) with hypertension being the most common. The overall mortality rate was 4.7%. The distribution of biochemical parameters across disease severity groups was significantly different for C-reactive protein (CRP), lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), white blood cells (WBC), and granulocytes with higher median values in more severe and critically ill patients whereas lower percentage of lymphocytes, monocytes, and platelet count in severe and critically ill patients. IL-6 levels were increased in 63% of patients with significant differences in the distribution across the following groups; age, disease severity, hospitalisation status, pulmonary infiltrates, oxygen therapy, and hypertension status. IL-6 significantly correlated with CRP, LDH, CK, ESR, and percentages of granulocytes. IL-6 and other inflammatory and hematological parameters were strongly associated with disease severity and may predict the outcome of the SARS-CoV-2 infection.

[Value of autotaxin in predicting refractory Mycoplasma pneumoniae pneumonia in children and its correlation with inflammatory cytokines]

OBJECTIVES

To study the value of autotaxin (an autocrine motility factor) level in serum and bronchoalveolar lavage fluid (BALF) in predicting refractory Mycoplasma pneumoniae pneumonia (RMPP) in children and its correlation with interleukin-6 (IL-6), interleukin-8 (IL-8), and C-reactive protein (CRP).

METHODS

A retrospective analysis was performed on 238 children with Mycoplasma pneumoniae pneumonia who were admitted from January 2019 to December 2021. According to disease severity, they were divided into two groups: RMPP (n=82) and general Mycoplasma pneumoniae pneumonia (GMPP; n=156). The two groups were compared in terms of the levels of autotaxin, IL-6, IL-8, and CRP in serum and BALF to study the value of autotaxin level in serum and BALF in predicting RMPP in children, as well as the correlation of autotaxin level with IL-6, IL-8, and CRP in children with RMPP.

RESULTS

Compared with the GMPP group, the RMPP group had significantly higher levels of autotaxin, IL-6, IL-8, and CRP in serum and BALF (P<0.05). For the children with RMPP, the levels of autotaxin, IL-6, IL-8, and CRP in serum and BALF in the acute stage were significantly higher than those in the convalescent stage (P<0.05). The receiver operating characteristic (ROC) curve showed that the level of autotaxin in serum and BALF had a good value in predicting RMPP in children, with an area under the curve of 0.874 (95%CI: 0.816-0.935) and 0.862 (95%CI: 0.802-0.924), respectively. The correlation analysis showed that the level of autotaxin in serum and BALF was positively correlated with IL-6, IL-8, and CRP levels (P<0.001).

CONCLUSIONS

The level of autotaxin in serum and BALF increases and is correlated with the degree of disease recovery and inflammatory cytokines in children with RMPP. Autotaxin can be used as a predictive indicator for RMPP in children.

The lung ultrasound "Rule of 7" in the prognosis of COVID-19 patients: Results from a prospective multicentric study

Purpose

There is growing evidence regarding the imaging findings of coronavirus disease 2019 (COVID-19) in lung ultrasound (LUS), however the use of a combined prognostic and triage tool has yet to be explored.To determine the impact of the LUS in the prediction of the mortality of patients with highly suspected or confirmed COVID-19.The secondary outcome was to calculate a score with LUS findings with other variables to predict hospital admission and emergency department (ED) discharge.

Material and methods

Prospective study performed in the ED of three academic hospitals. Patients with highly suspected or confirmed COVID-19 underwent a LUS examination and laboratory tests.

Results

A total of 228 patients were enrolled between March and September 2020. The mean age was 61.9 years (Standard Deviation - SD 21.1). The most common findings in LUS was a right posteroinferior isolated irregular pleural line (53.9%, 123 patients). A logistic regression model was calculated, including age over 70 years, C-reactive protein (CRP) over 70 mg/L and a lung score over 7 to predict mortality, hospital admission and discharge from the ED. We obtained a predictive model with a sensitivity of 56.8% and a specificity of 87.6%, with an AUC of 0.813 [p < 0.001].

Conclusions

The combination of LUS, clinical and laboratory findings in this easy to apply "rule of 7" showed excellent performance to predict hospital admission and mortality.

A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection

The emergence of the novel SARS-CoV-2 virus is the most important public-health issue of our time. Understanding the diverse clinical presentations of the ensuing disease, COVID-19, remains a critical unmet need. Here we present a comprehensive listing of the diverse clinical indications associated with COVID-19. We explore the theory that anti-SARS-CoV-2 antibodies could cross-react with endogenous human proteins driving some of the pathologies associated with COVID-19. We describe a novel computational approach to estimate structural homology between SARS-CoV-2 proteins and human proteins. Antibodies are more likely to interrogate 3D-structural epitopes than continuous linear epitopes. This computational workflow identified 346 human proteins containing a domain with high structural homology to a SARS-CoV-2 Wuhan strain protein. Of these, 102 proteins exhibit functions that could contribute to COVID-19 clinical pathologies. We present a testable hypothesis to delineate unexplained clinical observations vis-à-vis COVID-19 and a tool to evaluate the safety-risk profile of potential COVID-19 therapies.

Prognostic assessment of C‑reactive protein and neutrophil to lymphocyte ratio in patients with non-small cell lung cancer

OBJECTIVE

To investigate the prognostic assessment of inflammatory factor serum C‑reactive protein CRP and neutrophil to lymphocyte ratio NLR value in patients with non-small cell lung cancer NSCLC.

METHODS

A retrospective analysis was conducted for 475 patients with NSCLC who visited our hospital with complete follow-up data from January 2017 to 1 January 2019. The changes of serum CRP, NLR levels in patients with NSCLC of different stages, as well as the changes in the levels of the two indexes before and after chemotherapy in patients with advanced stage were compared using t tests with SPSS19.0 software. Serum CRP and NLR were divided into low and high groups with median intercept values and the relationship between inflammation score index and tumor progression-free survival time (PFS) was analyzed retrospectively. Clinical factors that may affect disease prognosis were included in the proportional hazards (COX) regression model for multifactorial prognostic analysis.

RESULTS

Pretreatment serum levels of NLR and CRP were significantly higher in non-operated patients relative to preoperative levels in surgical patients. Advanced patients had higher levels of both indexes than locally advanced patients. After chemotherapy, the levels of the two indexes reaching remission were significantly lower than those before chemotherapy. The levels of the two indexes in patients with stable disease after chemotherapy were not statistically significant compared with those before chemotherapy, and the levels of the two indexes in the group with progressive disease after chemotherapy were significantly higher than those before chemotherapy. The results of PFS survival analyses showed that PFS was prolonged in the low score CRP and the low score NLR group, compared with the high score group. Multifactorial prognostic analysis showed that smoking, CRP and NLR were risk factors for PFS prognosis in patients with NSCLC.

CONCLUSION

Serum CRP and NLR are effective predictors of poor prognosis in patients with NSCLC.

The Impact of Neutrophil-Lymphocyte Count Ratio in COVID-19: A Systematic Review and Meta-Analysis

Background: The neutrophil-lymphocyte count ratio (NLR) has emerged as a potential prognostic tool for different diseases. In the current coronavirus disease (COVID-19) pandemic, the NLR may be a useful tool for risk scarification and the optimal utilization of limited healthcare resources. However, there is no consensus regarding the optimal value of NLR, and the association with disease severity and mortality. Thus, this study aims to systematically analyze the current evidence of the utility of baseline NLR as a predictive tool for mortality, disease severity in COVID-19 patients. Methods: A compendious screening of electronic databases up to June 15, 2021, was done after enlisting the protocol in PROSPERO (CRD42020202659). Studies evaluating the utility of baseline NLR in COVID-19 are included for this review as per the PRISMA statement. Results: We retrieved a total of 13112 and 12986 COVID-19 patients for survivability and severity over 90 studies. The expired and critically sick patients had elevated baseline NLR on admission, in comparison to survivors and noncritical patients. (SMD = 3.82; 95% CI: 2.79-4.85; I2 = 100% and SMD = 1.42; 95% CI: 1.22-1.63; I2 = 95%, respectively). The summary receiver operating curve analysis for mortality (AUC = 0.87; 95% CI: 0.86-0.87; I2 = 94.7%), and severity (AUC = 0.82; 95% CI: 0.80-0.84; I2 = 79.7%) were also suggestive of its significant predictive value. Conclusions: The elevated NLR on admission in COVID-19 patients is associated with poor outcomes.

COVID-19 and the injured patient: A multicenter review

Introduction

Coronavirus disease 2019 (COVID-19) has been shown to affect outcomes among surgical patients. We hypothesized that COVID-19 would be linked to higher mortality and longer length of stay of trauma patients regardless of the injury severity score (ISS).

Methods

We performed a retrospective analysis of trauma registries from two level 1 trauma centers (suburban and urban) from March 1, 2019, to June 30, 2019, and March 1, 2020, to June 30, 2020, comparing baseline characteristics and cumulative adverse events. Data collected included ISS, demographics, and comorbidities. The primary outcome was time from hospitalization to in-hospital death. Outcomes during the height of the first New York COVID-19 wave were also compared with the same time frame in the prior year. Kaplan–Meier method with log-rank test and Cox proportional hazard models were used to compare outcomes.

Results

There were 1180 trauma patients admitted during the study period from March 2020 to June 2020. Of these, 596 were never tested for COVID-19 and were excluded from the analysis. A total of 148 COVID+ patients and 436 COVID− patients composed the 2020 cohort for analysis. Compared with the 2019 cohort, the 2020 cohort was older with more associated comorbidities, more adverse events, but lower ISS. Higher rates of historical hypertension, diabetes, neurologic events, and coagulopathy were found among COVID+ patients compared with COVID− patients. D-dimer and ferritin were unreliable indicators of COVID-19 severity; however, C-reactive protein levels were higher in COVID+ relative to COVID− patients. Patients who were COVID+ had a lower median ISS compared with COVID− patients, and COVID+ patients had higher rates of mortality and longer length of stay.

Conclusions

COVID+ trauma patients admitted to our two level 1 trauma centers had increased morbidity and mortality compared with admitted COVID− trauma patients despite age and lower ISS. C-reactive protein may play a role in monitoring COVID-19 activity in trauma patients. A better understanding of the physiological impact of COVID-19 on injured patients warrants further investigation.

Inflammatory and thrombotic parameters associated with the COVID-19 course in Poland (SARSTer study)

Purpose

The aim of the study was to assess the coagulation and inflammatory markers connected with severe course of COVID-19 and no clinical improvement.

Material and methods

The study population included 2590 adult patients, diagnosed with COVID-19, selected from the SARSTer national database - an ongoing project led by the Polish Association of Epidemiologists and Infectiologists and supported by the Medical Research Agency. Clinical and laboratory parameters, such as C-reactive protein (CRP), white blood cells (WBCs), neutrophil and lymphocyte count, procalcitonin, ferritin, interleukin-6 (IL-6), D-dimer concentration and platelet (PLT) count were analyzed before and after treatment (remdesivir, tocilizumab, dexamethasone, anticoagulants).

Results

Significant differences between patients with mild and severe course of the disease were observed in all examined parameters before treatment (p ​< ​0.05). After treatment only ferritin concentration did not differ significantly. In patients with pulmonary embolism, CRP concentration, neutrophil count, D-dimer and IL-6 concentration were significantly higher than in patients without embolism (p ​< ​0.05). The significant differences between the groups with and without fatal outcome were observed within all analyzed parameters. Significant differences in all examined parameters before treatment were observed between patients with and without clinical improvement (p ​< ​0.05).

Multivariate logistic regression showed that no clinical improvement was associated with: IL-6>100 ​pg/ml (OR-2.14), D-dimer concentration over 1000 ​ng/ml (OR-1.62) and PLT count below 150,000/μl (OR-1.57).

Conclusions

Severe course of the disease is associated with lower PLT and lymphocyte count, higher D-dimer, CRP, neutrophil count and IL-6 concentration. The best predictors of no clinical improvement in COVID-19 are: IL-6>100 ​pg/ml, D-dimer>1000 ​ng/ml and PLT<150,000/μl.

Predictors of Occurrence and 30-Day Mortality for Co-Infection of Carbapenem-Resistant Klebsiella pneumoniae and Carbapenem-Resistant Acinetobacter baumannii

Background

The phenomenon of co-infection with multiple carbapenem-resistant bacteria is growing, which pose a great challenge for infection control and treatment. This study aimed to analyze predictors of occurrence and 30-day mortality for carbapenem-resistant Klebsiella pneumoniae and carbapenem-resistant Acinetobacter baumannii co-infection.

Methods

From June 2018 to June 2021, clinical data of 103 patients co-infected with carbapenem-resistant Acinetobacter baumannii (CRAB) and carbapenem-resistant Klebsiella pneumoniae (CRKP) were collected from a tertiary teaching hospital in Anhui Province, China. The clinical characteristics and predictors of mortality were analyzed. Meanwhile, the bacterial isolates were characterized for drug susceptibility, multi-locus sequence typing, and drug resistance genes.

Results

The multivariate analysis revealed that fiberoptic bronchoscopy (p = 0.005, OR=2.72), repeat transfusions (p = 0.008, OR= 2.23) and exposure to tigecycline (p = 0.002, OR = 6.58) were independent risk factors for CRKP and CRAB co-infection. Neutrophil ≥11.9*109 (p = 0.035, adjusted HR = 3.12) and C-reactive protein ≥ 149 mg/L (p = 0.009, adjusted HR = 4.41) were found associated with 30-day mortality. Combined neutrophil with C-reactive protein could predict 30-day mortality, of which AUC value was 0.791 (95%CI: 0.661-0.921). KPC (46/51, 90.2%) was the most common carbapenemase in CRKP. 33 isolates of CRKP belong to ST11 (33/51, 64.7%), and three new ST types ST5882, ST5883, ST5885 were detected.

Conclusions

Invasive operations and antibiotics exposure can lead to CRKP and CRAB co-infection. Combined neutrophil with C-reactive protein could predict 30-day mortality.

A Pilot Study on COVID-19 Positive Subjects: An Excerpt of Post-Infection-Pro-Diabetic Disposition & Related Consequences in Correlation to Hepato-Pancreatic Bio-Markers, Pro-Inflammatory Cytokines and Other Risk Factors

COVID-19, a global pandemic that led to increased morbidity and mortality worldwide since its outcome at the end of the year 2019. A newly discovered variant of severe acute respiratory distress syndrome coronavirus-2 (SARS-CoV-2) was the arbitrator for spreading the syndrome by droplet transmission causing multi-organ failure in many occasions. A post-infection-pro-diabetic disposition was found evident in this study with the persistence of hepato-pancreatic aberrations in respect of reference range of tissue specific bio-markers in hospital admitted COVID-19 cases. The results of this study show that hyperglycemia is a risk factor in precipitating disease oriented complications to the patients with COVID-19 disease. A post-infection follow- up on glycemic-index and related complexities is a vital need to the COVID-19 infected convalescent subjects. Implementation of guidelines on social measure and awareness of anti-viral interventions may be the only way to prevent COVID-19 transmission.

Diagnostic Accuracy of Liquid Biomarkers in Airway Diseases: Toward Point-of-Care Applications

Background

Liquid biomarkers have shown increasing utility in the clinical management of airway diseases. Salivary and blood samples are particularly amenable to point-of-care (POC) testing due to simple specimen collection and processing. However, very few POC tests have successfully progressed to clinical application due to the uncertainty and unpredictability surrounding their diagnostic accuracy.

Objective

To review liquid biomarkers of airway diseases with well-established diagnostic accuracies and discuss their prospects for future POC applications.

Methodology

A literature review of publications indexed in Medline or Embase was performed to evaluate the diagnostic accuracy of liquid biomarkers for chronic obstructive pulmonary disease (COPD), asthma, laryngopharyngeal reflux (LPR), and COVID-19.

Results

Of 3,628 studies, 71 fulfilled the inclusion criteria. Sputum and blood eosinophils were the most frequently investigated biomarkers for the management of asthma and COPD. Salivary pepsin was the only biomarker with a well-documented accuracy for the diagnosis of LPR. Inflammatory blood biomarkers (e.g., CRP, D-dimers, ferritin) were found to be useful to predict the severity, complications, and mortality related to COVID-19 infection.

Conclusion

Multiple liquid biomarkers have well-established diagnostic accuracies and are thus amenable to POC testing in clinical settings.

Clinical Characteristics and Prognosis of COVID-19 patients in Syria: A cross-sectional multicenter study

Background

Materials and methods

Results

Conclusion

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The Syrian civil war negatively affects the healthcare systems.

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The highest risks for mortality are males over 60 years with multiple comorbidities.

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WBC, lymphocyte, INR, LDH, AST, ALT, and Glu values are a prognostic biomarkers.

Clinical utility of inflammatory biomarkers in COVID-19 in direct comparison to other respiratory infections-A prospective cohort study

Background

Inflammatory biomarkers are associated with severity of coronavirus disease 2019 (COVID-19). However, direct comparisons of their utility in COVID-19 versus other respiratory infections are largely missing.

Objective

We aimed to investigate the prognostic utility of various inflammatory biomarkers in COVID-19 compared to patients with other respiratory infections.

Materials and methods

Patients presenting to the emergency department with symptoms suggestive of COVID-19 were prospectively enrolled. Levels of Interleukin-6 (IL-6), c-reactive protein (CRP), procalcitonin, ferritin, and leukocytes were compared between COVID-19, other viral respiratory infections, and bacterial pneumonia. Primary outcome was the need for hospitalisation, secondary outcome was the composite of intensive care unit (ICU) admission or death at 30 days.

Results

Among 514 patients with confirmed respiratory infections, 191 (37%) were diagnosed with COVID-19, 227 (44%) with another viral respiratory infection (viral controls), and 96 (19%) with bacterial pneumonia (bacterial controls). All inflammatory biomarkers differed significantly between diagnoses and were numerically higher in hospitalized patients, regardless of diagnoses. Discriminative accuracy for hospitalisation was highest for IL-6 and CRP in all three diagnoses (in COVID-19, area under the curve (AUC) for IL-6 0.899 [95%CI 0.850–0.948]; AUC for CRP 0.922 [95%CI 0.879–0.964]). Similarly, IL-6 and CRP ranged among the strongest predictors for ICU admission or death at 30 days in COVID-19 (AUC for IL-6 0.794 [95%CI 0.694–0.894]; AUC for CRP 0.807 [95%CI 0.721–0.893]) and both controls. Predictive values of inflammatory biomarkers were generally higher in COVID-19 than in controls.

Conclusion

In patients with COVID-19 and other respiratory infections, inflammatory biomarkers harbour strong prognostic information, particularly IL-6 and CRP. Their routine use may support early management decisions.