Inflammatory and hematologic markers as predictors of severe outcomes in COVID-19 infection: A systematic review and meta-analysis

Predictive Value and Diagnostic Potential of IL-10, IL-17A, IL1-β, IL-6, CXCL, and MCP for Severe COVID-19 and COVID-19 Mortality

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) necessitates advanced prognostic tools to anticipate disease progression and optimize patient outcomes. This study evaluates the predictive value and diagnostic potential of interleukins interleukin (IL) IL-10, IL-17A, IL1-β, IL-6, chemokine ligand (CXCL), and Monocyte Chemotactic Protein (MCP) for severe coronavirus disease 2019 (COVID-19) and COVID-19 mortality, aiming to correlate cytokine levels with disease severity. Conducted from January 2023 to January 2024, this prospective cohort study involved patients hospitalized with moderate and severe COVID-19 from Romania. This study analyzed statistically significant predictors of severe COVID-19 outcomes. IL-6 and MCP emerged as significant, with hazard ratios (HRs) of 2.35 (95% confidence interval (CI): 1.54-3.59, p = 0.014) and 2.05 (95% CI: 1.22-3.45, p = 0.007), respectively. Compound scores integrating multiple inflammatory markers also demonstrated predictive value; Compound Score 2 had an HR of 2.23 (95% CI: 1.35-3.68, p = 0.002), surpassing most single markers in association with severe disease. Notably, interleukins IL-10 and IL-1β did not show significant associations with disease severity. This study underscores the importance of IL-6 and MCP as robust predictors of severe COVID-19, substantiating their role in clinical assessments to foresee patient deterioration. The utility of compound scores in enhancing predictive accuracy suggests a composite approach may be more effective in clinical settings.

Prognosis of COVID-19 severity using DERGA, a novel machine learning algorithm

It is important to determine the risk for admission to the intensive care unit (ICU) in patients with COVID-19 presenting at the emergency department. Using artificial neural networks, we propose a new Data Ensemble Refinement Greedy Algorithm (DERGA) based on 15 easily accessible hematological indices. A database of 1596 patients with COVID-19 was used; it was divided into 1257 training datasets (80 % of the database) for training the algorithms and 339 testing datasets (20 % of the database) to check the reliability of the algorithms. The optimal combination of hematological indicators that gives the best prediction consists of only four hematological indicators as follows: neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase, ferritin, and albumin. The best prediction corresponds to a particularly high accuracy of 97.12 %. In conclusion, our novel approach provides a robust model based only on basic hematological parameters for predicting the risk for ICU admission and optimize COVID-19 patient management in the clinical practice.

Combined coagulation and inflammation markers as predictors of venous thrombo-embolism and death in COVID-19

Background

The COVID-19 pandemic related to SARS-CoV-2 virus was responsible for global pandemic. The severe form of the disease was linked to excessive activation of immune pathways together with a systemic cytokine storm response and thrombotic venous or arterial complications. Factors predicting severe outcomes including venous and/or pulmonary thrombosis (VT) and death were identified, but the prognostic role of their combination was not addressed extensively.

Objectives

We investigated the role of prognostic factors from the coagulation or inflammatory pathways to better understand the outcome of the disease.

Methods

For this, we prospectively studied 167 SARS-CoV-2-positive patients from admission in intensive care units (ICU) or emergency departments from four academic hospitals over a 14-month period. Besides standard biology, we assessed serum concentrations of inflammatory markers, coagulation factors and peripheral blood cells immunophenotyping.

Results

Thirty-nine patients (23.3%) developed VT and 30 patients (18%) died. By univariate analysis, C-reactive protein (CRP) level > 150 mg/L, interleukin-6 (IL-6) ≥ 20 pg/mL, D-dimers > 1,500 μg/L, ADAMTS13 activity ≤ 50%, Von.

Conclusion

A combination of coagulation and inflammatory markers can refine the prognostication of severe outcome in COVID-19, and could be useful for the initial evaluation of other types of viral infection.

Cytokine expression and mortality risk among COVID-19 hospitalized patients over 60 years of age in a referral hospital in Cartagena, Colombia

Background

Cytokine dysregulation in COVID-19 patients aged over 60 has been associated to adverse outcomes. While serum levels have been studied, cellular expression, particularly in Afro-Colombians, remains understudied. This research aims to describe cytokine expression in peripheral blood leukocytes and its association with adverse outcomes in COVID-19 patients aged over 60 at Cartagena's referral hospital.

Methods

A cohort study was conducted, encompassing severe and critical cases of COVID-19 between November 2021 and February 2022. At baseline, the cellular expression level of cytokines IL-2, IL-4, IL-6, IL-10, TNF-α and IFN-γ was assessed using flow cytometry. Additionally, various biochemical, hematological, and coagulation markers were evaluated. The main outcome was time to death.

Results

Among the 50 enrolled participants, the median age was 76.5 years, 60% were male, 60% were admitted to the ICU, and 42% died. Lactate dehydrogenase and hemoglobin were the only markers that differed between fatal and surviving cases. Regarding cytokines, the level of IL-6 expression was associated with an increased risk of death. Specifically, a one percent increase in the expression was associated with a 7.3% increase in the risk of death. Stratifying the analysis by death and ICU admission, the median expression level remained high in fatal cases who were admitted to the ICU.

Conclusions

Our findings revealed a significant association between high cellular expression levels of IL-6 and an increased risk of mortality. These results provide valuable scientific insights that could inform the prioritization of case management, providing especially advantageous for the vulnerable Afro-Colombian group.

Predictive Value of Nutrition and Inflammation-Related Indices on Prognosis in Type 2 Diabetes Mellitus Patients with Coronavirus Disease-2019

Objectives

This study aimed to demonstrate how the prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) help predict the severity and prognosis of patients with type 2 diabetes (T2DM) and coronavirus disease (COVID-19).

Methods

This retrospective cohort study included 501 T2DM patients (male, 42.1%; female, 57.9%) who were hospitalized due to COVID-19 between April 2020 and December 2020. The patients were divided into survivors and non-survivors. After comparing demographic and laboratory data between the groups, the correlation of PNI and SII with clinical and laboratory data was evaluated.

Results

The median (interquartile) ages of the non-survivor and survivor groups were 74 (15) and 69 (14) years, respectively, and the difference was significant (p<0.001). The PNI was significantly lower in the non-survivor group than in the survivor group (p<0.001). The SII was significantly higher in the non-survivor group than in the survivor group (p<0.001). PNI was negatively correlated with glucose levels (r=-0.115, p=0.011). If the cut-off PNI value of 29.1 was used, it had a sensitivity and specificity of 76.2% and 76.3%, respectively, in predicting the severity of the illness and the risk of death in T2DM patients.

Conclusion

Consequently, the PNI and SII levels are effective in predicting survival and disease severity in patients with COVID-19 and T2DM.

Specific and Non-specific Aspects and Future Challenges of ICU Care Among COVID-19 Patients with Obesity: A Narrative Review

PURPOSE OF REVIEW

Since the end of 2019, the coronavirus disease 2019 (COVID-19) pandemic has infected nearly 800 million people and caused almost seven million deaths. Obesity was quickly identified as a risk factor for severe COVID-19, ICU admission, acute respiratory distress syndrome, organ support including mechanical ventilation and prolonged length of stay. The relationship among obesity; COVID-19; and respiratory, thrombotic, and renal complications upon admission to the ICU is unclear.

RECENT FINDINGS

The predominant effect of a hyperinflammatory status or a cytokine storm has been suggested in patients with obesity, but more recent studies have challenged this hypothesis. Numerous studies have also shown increased mortality among critically ill patients with obesity and COVID-19, casting doubt on the obesity paradox, with survival advantages with overweight and mild obesity being reported in other ICU syndromes. Finally, it is now clear that the increase in the global prevalence of overweight and obesity is a major public health issue that must be accompanied by a transformation of our ICUs, both in terms of equipment and human resources. Research must also focus more on these patients to improve their care. In this review, we focused on the central role of obesity in critically ill patients during this pandemic, highlighting its specificities during their stay in the ICU, identifying the lessons we have learned, and identifying areas for future research as well as the future challenges for ICU activity.

Risk factors for acute kidney injury in patients hospitalized with COVID-19

INTRODUCTION

Acute kidney injury (AKI) occurs frequently in COVID-19 patients and is associated with greater morbidity and mortality. Knowing the risks of AKI allows for identification, prevention, and timely treatment. This study aimed to identify the risk factors associated with AKI in hospitalized patients.

METHODS

A descriptive, retrospective, cross-sectional, and analytical component study of adult patients hospitalized with COVID-19 from March 1 to December 31, 2020 was carried out. AKI was defined by the creatinine criteria of the KDIGO-AKI guidelines. Information, regarding risk factors, was obtained from electronic medical records.

RESULTS

Out of the 934 patients, 42.93% developed AKI, 60.59% KDIGO-1, and 9.9% required renal replacement therapy. Patients with AKI had longer hospital stay, higher mortality, and required more intensive care unit (ICU) admission, mechanical ventilation, and vasopressor support. Multivariate analysis showed that age (OR 1.03; 95% CI 1.02-1.04), male sex (OR 2.13; 95% CI 1.49-3.04), diabetes mellitus (DM) (OR 1.55; 95% CI 1.04-2.32), chronic kidney disease (CKD) (OR 2.07; 95% CI 1.06-4.04), C-reactive protein (CRP) (OR 1.02; 95% CI 1.00-1.03), ICU admission (OR 1.81; 95% CI 1.04-3.16), and vasopressor support (OR 7.46; 95% CI 3.34-16.64) were risk factors for AKI, and that bicarbonate (OR 0.89; 95% CI 0.84-0.94) and partial pressure arterial oxygen/inspired oxygen fraction index (OR 0.99; 95% CI 0.98-0.99) could be protective factors.

CONCLUSIONS

A high frequency of AKI was documented in COVID-19 patients, with several predictors: age, male sex, DM, CKD, CRP, ICU admission, and vasopressor support. AKI occurred more frequently in patients with higher disease severity and was associated with higher mortality and worse outcomes.

Association of PADI2 and PADI4 polymorphisms in COVID-19 host severity and non-survival

Background

Enzymes of the peptidylarginine deiminase family (PADs) play a relevant role in the pathogenesis of COVID-19. However, the association of single nucleotide polymorphisms (SNPs) in their genes with COVID-19 severity and death is unknown.

Methodology

We included 1045 patients who were diagnosed with COVID-19 between October 2020 and December 2021. All subjects were genotyped for PADI2 (rs1005753 and rs2235926) and PADI4 (rs11203366, rs11203367, and rs874881) SNPs by TaqMan assays and their associations with disease severity, death, and inflammatory biomarkers were evaluated.

Results

291 patients presented had severe COVID-19 according to PaO2/FiO2, and 393 had a non-survival outcome. Carriers of the rs1005753 G/G genotype in the PADI2 gene presented susceptibility for severe COVID-19, while the heterozygous carriers in rs11203366, rs11203367, and rs874881 of the PADI4 gene showed risk of death. The GTACC haplotype in PADI2-PADI4 was associated with susceptibility to severe COVID-19, while the GCACC haplotype was a protective factor. The GCGTG haplotype was associated with severe COVID-19 but as a protective haplotype for death. Finally, the GTACC haplotype was associated with platelet-to-lymphocyte ratio (PLR), the GCACC haplotype with neutrophil-to-hemoglobin and lymphocyte and the GCGTG haplotype as a protective factor for the elevation of procalcitonin, D-dimer, CRP, LCRP, NHL, SII, NLR, and PLR.

Conclusions

Our results suggest that the haplotypic combination of GTACC and some individual genotypes of PADI2 and PADI4 contribute to the subjects' susceptibility for severity and death by COVID-19.

Vaccination and Nutritional Outcomes of Hemodialysis Patients Infected With SARS-CoV-2

BACKGROUND

Patients on hemodialysis are particularly vulnerable to COVID-19 and may have a reduced response to vaccination because of a decreased immune response. The nutritional status before or during the infection could also impact on the clinical effectiveness of vaccination.

OBJECTIVES

We aim to describe the evolution of clinical and nutritional biomarkers of hemodialysis patients infected with SARS-CoV-2 and to assess their association with vaccination status.

METHODS

An observational, analytic, longitudinal, retrospective multicenter study was carried out in 82 patients on hemodialysis with SARS-CoV-2 infection. Nutritional status was assessed using the Geriatric Nutritional Risk Index (GNRI), anthropometry, and biochemical parameters. The association of the vaccine doses with clinical- and nutritional-related variables was also evaluated.

RESULTS

The percentage of vaccinated patients was similar to that of nonvaccinated patients. Before infection, most of the patients were malnourished. They presented lower albumin, creatinine, and urea levels than the well-nourished patients. Significant deterioration of nutritional status after infection was evidenced considering GNRI score, dry weight, and body mass index. Albumin and creatinine also decreased significantly after infection, whereas C-reactive protein increased in the acute phase. Significant inverse correlation was found between the variation of post-pre GNRI scores and basal albumin and C-reactive protein at 7 days. In addition, we observed the opposite trend between albumin at 30 days and basal cholesterol. A negative value in the GNRI variation was associated with bilateral pneumonia, need for hospitalization, and nutritional support. Vaccinated patients presented substantially less bilateral pneumonia and hospitalization. No significant effects were observed between vaccine doses and the variation in nutritional status, although a positive correlation was detected with the albumin at 7 days and C-reactive protein before infection and the number of vaccine doses received.

DISCUSSION

COVID-19 is associated with affectations in the nutritional status and biomarkers in hemodialysis patients. In this study, vaccines have shown a protective effect against the clinical consequences of COVID. However, they have shown limitations in preventing the deterioration of nutritional status after infection. The results highlight the importance of promoting the vaccination in these patients as well as incorporating nutritional assessment before, during, and after the infection.

Elevated lactate dehydrogenase predicts pneumonia in spontaneous intracerebral hemorrhage

Background

Although a variety of risk factors for pneumonia after spontaneous intracerebral hemorrhage have been established, an objective and easily obtainable predictor is still needed. Lactate dehydrogenase is a nonspecific inflammatory biomarker. In this study, we aimed to assess the association between lactate dehydrogenase and pneumonia in spontaneous intracerebral hemorrhage patients.

Methods

Our study was a retrospective, multicenter cohort study, undertaken in 7562 patients diagnosed with spontaneous intracerebral hemorrhage from 3 hospitals. All serum Lactate dehydrogenase was collected within 7 days from admission and divided into four groups as quartile(Q). We conducted a multivariable logistic regression analysis to assess the association of Lactate dehydrogenase with pneumonia.

Results

Among a total of 7562 patients, 2971 (39.3%) patients were diagnosed with pneumonia. All grades of elevated lactate dehydrogenase were associated with increased raw and risk-adjusted risk of pneumonia. Multiple logistic regression analysis showed odds ratios for Q2-Q4 compared with Q1 were 1.21 (95% CI, 1.04-1.42), 1.64(95% CI, 1.41-1.92), and 1.92 (95% CI, 1.63-2.25) respectively. The odds ratio after adjustment was 4.42 (95% CI, 2.94-6.64) when lactate dehydrogenase was a continuous variable after log-transformed.

Conclusions

Elevated lactate dehydrogenase is significantly associated with an increase in the odds of pneumonia and has a predictive value for severe pneumonia in patients with pneumonia. Lactate dehydrogenase may be used to predict pneumonia events in spontaneous intracerebral hemorrhage patients as a laboratory marker.

Novel COVID-19 biomarkers identified through multi-omics data analysis: N-acetyl-4-O-acetylneuraminic acid, N-acetyl-L-alanine, N-acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate

This study aims to apply machine learning models to identify new biomarkers associated with the early diagnosis and prognosis of SARS-CoV-2 infection.Plasma and serum samples from COVID-19 patients (mild, moderate, and severe), patients with other pneumonia (but with negative COVID-19 RT-PCR), and healthy volunteers (control) from hospitals in four different countries (China, Spain, France, and Italy) were analyzed by GC-MS, LC-MS, and NMR. Machine learning models (PCA and PLS-DA) were developed to predict the diagnosis and prognosis of COVID-19 and identify biomarkers associated with these outcomes.A total of 1410 patient samples were analyzed. The PLS-DA model presented a diagnostic and prognostic accuracy of around 95% of all analyzed data. A total of 23 biomarkers (e.g., spermidine, taurine, L-aspartic, L-glutamic, L-phenylalanine and xanthine, ornithine, and ribothimidine) have been identified as being associated with the diagnosis and prognosis of COVID-19. Additionally, we also identified for the first time five new biomarkers (N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate) that are also associated with the severity and diagnosis of COVID-19. These five new biomarkers were elevated in severe COVID-19 patients compared to patients with mild disease or healthy volunteers.The PLS-DA model was able to predict the diagnosis and prognosis of COVID-19 around 95%. Additionally, our investigation pinpointed five novel potential biomarkers linked to the diagnosis and prognosis of COVID-19: N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate. These biomarkers exhibited heightened levels in severe COVID-19 patients compared to those with mild COVID-19 or healthy volunteers.

Association of human leukocyte antigen class II alleles with epithelial cell apoptosis and extracellular matrix production in acute COVID-19

Introduction

Pathogenic mechanisms and long-term consequences of COVID-19 require attention in studies on SARS-CoV-2. The association of the severity of COVID-19 with genetic factors, such as human leukocyte antigen (HLA) genes, remains underexplored. Our study assessed the relationships between HLA class II alleles and COVID-19 severity and blood-based indicators of systemic inflammation and organ damage, serum markers of epithelial cell apoptosis such as caspase-cleaved CK18 fragment M30 (CK18-M30) and the extracellular matrix product hyaluronic acid (HA).

Material and methods

The study included 101 hospitalized COVID-19 patients (mean age 60 ±14 years). Clinical tests were performed at admission to the hospital. The levels of CK18-M30 and HA were detected in serum by enzyme-linked immunosorbent assay (ELISA). HLA typing was performed in HLA-DRB1, -DQA1, and -DQB1 loci by the polymerase chain reaction with low-resolution sequence-specific primers.

Results

Sixty-one patients had a non-severe and 40 had a severe or critical disease course (following the WHO definition). The severity was associated with older age, male gender, higher HA, CK18-M30, and some indicators of inflammation. Despite the lack of direct association between HLA alleles and the severity of COVID-19, the presence of HLA-DRB1*04 and 12 alleles in the genotype was associated with lowered or elevated HA, respectively. The HLA-DQB1*03:01 allele was associated with lowered CK18-M30, aspartate aminotransferase, and ferritin. In addition, HLA-DQB1*06:01 was associated with elevated alanine aminotransferase.

Conclusions

Associations of HLA class II alleles with markers of epithelial cell apoptosis and extracellular matrix production indirectly support the influence of HLA genes on acute COVID-19 severity.

'Immune-inflammatory markers & clinical characteristics for outcomes in hospitalized SARS-CoV-2 infected patients of Pakistan: a retrospective analysis'

OBJECTIVE

Accumulating evidence suggests the role of immune-inflammatory markers in early risk stratification and prognostication of COVID-19 patients. We aimed to evaluate their association with severity and the development of diagnostic scores with optimal thresholds in critical patients.

SETTING AND PARTICIPANTS

This retrospective case study includes hospitalized COVID-19 patients from March 2019 to March, 2022, in the developing area teaching hospital in Pakistan. Polymerase chain reaction (PCR) positive patients, n = 467 were investigated for clinical outcomes, comorbidities and disease prognosis. The plasma levels of Interleukin-6 (IL-6), Lactate dehydrogenase (LDH), C-reactive protein (CRP), Procalcitonin (PCT), ferritin and Complete blood count markers were measured.

RESULTS

Majority were males (58.8%) and patients with comorbidities had more severe disease. Hypertension and diabetes mellitus were the commonest comorbidities. Shortness of breath, myalgia and cough were the main symptoms. The hematological markers NLR, as well as the plasma levels of immune-inflammatory variables, IL-6, LDH, Procalcitonin, Erythrocyte sedimentation rate, Ferritin were markedly raised in severe and critical patients (p < 0.0001 for these markers). ROC analysis supports IL-6 as the most accurate marker with high prognostic relevance with proposed cut-off threshold (43 pg/ml), determining >90% of patients in terms of COVID-19 severity (AUC = 0.93, 91.7%, se; 90.3%sp). Furthermore, positive correlation with all other markers including NLR with cut-off = 2.99 (AUC = 0.87, se = 89.8%, sp = 88.4%), CRP with cut-offs at 42.9 mg/l, (AUC = 0.883, se = 89.3% and sp = 78.6%), LDH cut-off at 267μg/L, evidenced in >80% patients (AUC = 0.834 se = 84% and sp = 80%). Additionally, ESR and ferritin have the corresponding AUC 0.81 and 0.813 with cut-off at 55 mm/hr and 370, respectively.

CONCLUSION

Investigating the immune-inflammatory markers can assist physicians in providing prompt treatment and ICU admission in terms of COVID-19 severity. As a result, which may reduce the overall mortality of COVID-19 patients.

COVID-19 subphenotypes at hospital admission are associated with mortality: a cross-sectional study

BACKGROUND

We have an incomplete understanding of COVID-19 characteristics at hospital presentation and whether underlying subphenotypes are associated with clinical outcomes and therapeutic responses.

METHODS

For this cross-sectional study, we extracted electronic health data from adults hospitalized between 1 March and 30 August 2020 with a PCR-confirmed diagnosis of COVID-19 at five New York City Hospitals. We obtained clinical and laboratory data from the first 24 h of the patient's hospitalization. Treatment with tocilizumab and convalescent plasma was assessed over hospitalization. The primary outcome was mortality; secondary outcomes included intubation, intensive care unit (ICU) admission and length of stay (LOS). First, we employed latent class analysis (LCA) to identify COVID-19 subphenotypes on admission without consideration of outcomes and assigned each patient to a subphenotype. We then performed robust Poisson regression to examine associations between COVID-19 subphenotype assignment and outcome. We explored whether the COVID-19 subphenotypes had a differential response to tocilizumab and convalescent plasma therapies.

RESULTS

A total of 4620 patients were included. LCA identified six subphenotypes, which were distinct by level of inflammation, clinical and laboratory derangements and ranged from a hypoinflammatory subphenotype with the fewest derangements to a hyperinflammatory with multiorgan dysfunction subphenotypes. Multivariable regression analyses found differences in risk for mortality, intubation, ICU admission and LOS, as compared to the hypoinflammatory subphenotype. For example, in multivariable analyses the moderate inflammation with fever subphenotype had 3.29 times the risk of mortality (95% CI 2.05, 5.28), while the hyperinflammatory with multiorgan failure subphenotype had 17.87 times the risk of mortality (95% CI 11.56, 27.63), as compared to the hypoinflammatory subphenotype. Exploratory analyses suggested that subphenotypes may differential respond to convalescent plasma or tocilizumab therapy.

CONCLUSION

COVID-19 subphenotype at hospital admission may predict risk for mortality, ICU admission and intubation and differential response to treatment.KEY MESSAGEThis cross-sectional study of COVID patients admitted to the Mount Sinai Health System, identified six distinct COVID subphenotypes on admission. Subphenotypes correlated with ICU admission, intubation, mortality and differential response to treatment.

Hematological and Biochemical Laboratory Parameters in COVID-19 Patients: A Retrospective Modeling Study of Severity and Mortality Predictors

Background

It is well known that laboratory markers could help in identifying risk factors of severe illness and predicting outcomes of diseases. Here, we performed a retrospective modeling study of severity and mortality predictors of hematological and biochemical laboratory parameters in Iranian COVID-19 patients.

Methods

Data were obtained retrospectively from medical records of 564 confirmed Iranian COVID-19 cases. According to the disease severity, the patients were categorized into two groups (severe or nonsevere), and based on the outcome of the disease, patients were divided into two groups (recovered or deceased). Demographic and laboratory data were compared between groups, and statistical analyses were performed to define predictors of disease severity and mortality in the patients.

Results

The study identified a panel of hematological and biochemical markers associated with the severe outcome of COVID-19 and constructed different predictive models for severity and mortality. The disease severity and mortality rate were significantly higher in elderly inpatients, whereas gender was not a determining factor of the clinical outcome. Age-adjusted white blood cells (WBC), platelet cells (PLT), neutrophil-to-lymphocyte ratio (NLR), red blood cells (RBC), hemoglobin (HGB), hematocrit (HCT), erythrocyte sedimentation rate (ESR), mean corpuscular hemoglobin (MCHC), blood urea nitrogen (BUN), and creatinine (Cr) also showed high accuracy in predicting severe cases at the time of hospitalization, and logistic regression analysis suggested grouped hematological parameters (age, WBC, NLR, PLT, HGB, and international normalized ratio (INR)) and biochemical markers (age, BUN, and lactate dehydrogenase (LDH)) as the best models of combined laboratory predictors for severity and mortality.

Conclusion

The findings suggest that a panel of several routine laboratory parameters recorded on admission could be helpful for clinicians to predict and evaluate the risk of disease severity and mortality in COVID-19 patients.

Serological Biomarkers at Hospital Admission and Hospitalization Treatments Are Not Related to Sensitization-Associated Symptoms in Patients with Post-COVID Pain

Current evidence suggests that a group of patients who had survived coronavirus disease, 2019 (COVID-19) and developed post-COVID pain can exhibit altered nociceptive processing. The role of serological biomarkers and hospitalization treatments in post-COVID pain is unclear. This study aimed to investigate the association of serological biomarkers and treatments received during hospitalization with sensitization-associated symptoms in COVID-19 survivors with post-COVID pain. One hundred and eighty-three (n = 183) patients who had been hospitalized due to COVID-19 in one urban hospital of Madrid (Spain) during the first wave of the pandemic were assessed in a face-to-face interview 9.4 (SD 3.4) months after hospitalization. Levels of 19 serological biomarkers, hospitalization data, and treatments during hospitalization were obtained from hospital records. Sensitization-associated symptoms (Central Sensitization Inventory, CSI), sleep quality (Pittsburgh Sleep Quality Index, PSQI), pain catastrophism (Pain Catastrophizing Scale), and anxiety/depressive level (Hospital Anxiety and Depression Scale, HADS) were assessed. The prevalence of post-COVID pain was 40.9% (n = 75). Twenty-nine (38.6%) patients had sensitization-associated symptoms. Overall, no differences in hospitalization data and serological biomarkers were identified according to the presence of sensitization-associated symptoms. The analysis revealed that patients with sensitization-associated symptoms exhibited higher lymphocyte count and lower urea levels than those without sensitization-associated symptoms, but differences were small. Pain catastrophism and depressive levels, but not fatigue, dyspnea, brain fog, anxiety levels, or poor sleep, were higher in individuals with sensitization-associated symptoms. In conclusion, this study revealed that sensitization-associated post-COVID pain symptoms are not associated with serological biomarkers at hospital admission and hospitalization treatments received.

Leukopenia and leukocytosis as strong predictors of COVID-19 severity: A cross-sectional study of the hematologic abnormalities and COVID-19 severity in hospitalized patients

Background and Aims

Predicting severe disease is important in provocative decision-making for the management of patients with the coronavirus disease 2019 (COVID-19); However, there are still some controversies about the COVID-19's severity predicting factors. This study aimed to investigate the relationships between clinical and laboratory findings regarding COVID-19's severity in patients admitted to a tertiary hospital in Mashhad, Iran.

Methods

A cross-sectional study was conducted on patients with documented COVID-19 infection based on the reverse transcription-polymerase chain reaction test. Clinical symptoms, vital signs, and medical history of the patients were recorded from their medical records. Laboratory findings and computed tomography (CT) study findings were documented. Disease severity was defined based on CT scan findings.

Results

A total of 564 patients (58.8 ± 16.8 years old) were evaluated. The frequency of severe disease was 70.4%. There was a significant difference in heart rate (p = 0.0001), fever (p = 0.002), dyspnea (p = 0.0001), chest pain (p = 0.0001), diarrhea (p = 0.021), arthralgia (p = 0.0001), and chills (p = 0.044) as well as lymphopenia (p = 0.014), white blood cell count (p = 0.001), neutrophil count (p < 0.0001), lymphocyte count (p < 0.0001), and prothrombin time (p = 0.001) between disease severity groups. Predictors of severe COVID-19 were pulse rate (crude odds ratio [cOR] = 1.014, 95% confidence interval [CI] for cOR: 1.001, 1.027) and leukopenia (cOR = 3.910, 95% CI for cOR: 1.294, 11.809). Predictors for critical COVID-19 were pulse rate (cOR = 1.075, 95% CI for cOR: 1.046, 1.104), fever (cOR = 2.516, 95%CI for cOR: 1.020, 6.203), dyspnea (cOR = 4.190, 95% CI for cOR: 1.227, 14.306), and leukocytosis (cOR = 3.866, 95% CI for cOR: 1.815, 8.236).

Conclusions

Leukopenia and leukocytosis have the strongest correlation with the COVID-19 severity. These findings could be a valuable guild for clinicians in COVID-19 patient management in the inpatient setting.

Biochemical Analysis of Ferritin and D-dimer in COVID-19 Survivors and Non-survivors

Background COVID-19 is a major cause of illness and mortality. The management of COVID-19-related illnesses might change if variables connected to their severity and the requirement for ICU admission could be found. The severity of COVID-19 might be efficiently predicted with several laboratory measures, such as ferritin levels and D-dimer analysis. Objectives This study aimed to evaluate the association between serum D-dimer and ferritin levels and their effects on mortality in patients with COVID-19. Methods This retrospective observational study included all patients with positive real-time polymerase chain reaction (RT-PCR) results for COVID-19 who were hospitalized in the Ministry of Health South Al-Qunfudah General Hospital between March and September 30, 2020. Their laboratory parameters, serum D-dimer, and ferritin levels were evaluated. IBM SPSS Statistics for Windows, Version 26.0 (released 2019; IBM Corp., Armonk, New York, United States) was used to analyze the data. Results A total of 318 COVID-19 patients were analyzed; 56.9% (n=181) were male and 43.1% (n=137) were female. Of these, 78.6% (n=250) survived, including 58% of men and 42% of women. The mean D-dimer was 2.1 mcg/mL (SD=3.16) and the mean ferritin was 698.59 ng/mL (SD=603.11). Non-recovered patients were substantially older (66.16 years old) and had higher D-dimer (5.46) mcg/mL and ferritin levels (992.96) ng/mL. Intubation length and gender did not affect survival. Of the non-survivors, 95.6% (n=239) were admitted to the ICU, and 50% (n=34) required mechanical ventilation. Conclusions COVID-19 infection mortality dramatically increased with older age and increased mean ferritin and plasma D-dimer values, which were significantly higher in COVID-19 non-survivors than in survivors. Therefore, assessing and monitoring these laboratory markers in the early stages of the disease may have a significant impact on preventing disease progression and death.

Confounding role of comorbidities and COVID-19 vaccination uptake in clinical utility of hematological biomarkers in Cameroonian patients infected with SARS-CoV-2

Objectives

To analyze variations in blood profile, the extent of hematological disorders, and the impact of comorbidities and COVID-19 vaccination on blood profile parameters and their clinical value for prognostic of SARS-CoV-2 infection.

Methods

This cross-sectional study took place in Douala, Cameroon. A complete blood count and molecular detection of SARS-CoV-2 were performed on patients. Clinical value was appraised using area under the curve (AUC) analysis.

Results

In total, 420 participants were included. A significant reduction of hematological parameters such as lymphocytes (p < 0.0001), red blood cells (P = 0.0025), mean corpuscular hemoglobin count (P < 0.0001), and platelets (P = 0.02) was seen in SARS-CoV-2 (+) patients. Anisocytosis was the main hematological disorder (95.5%). Normocytic normochromic anemia was predominant in SARS-CoV-2 (+) (35.3%) while microcytic normochromic anemia was more frequently seen in SARS-CoV-2 (-) (16.5%). Neutrophil-to-lymphocyte (NLR) consistently showed statistically significant AUC ∼0.75 upon stratification for age, gender, and comorbidities, with the exception of COVID-19 vaccination uptake.

Conclusion

In a context where molecular detection methods are difficultly affordable in health facilities in developing countries such as Cameroon, NLR could be clinically interesting for identifying SARS-CoV-2 infected individuals, especially those with comorbidities.

C-reactive protein and clinical outcome in COVID-19 patients: the importance of harmonized measurements

C-reactive protein (CRP) is a cytokine-mediated acute phase reactant with a recognized role in inflammatory conditions and infectious disease. In coronavirus disease 2019 (COVID-19), elevated CRP concentrations in serum were frequently detected and significantly associated with poor outcome in terms of disease severity, need for intensive care, and in-hospital death. For these reasons, the marker was proposed as a powerful test for prognostic classification of COVID-19 patients. In most of available publications, there was however confounding information about how interpretative criteria for CRP in COVID-19 should be derived, including quality of employed assays and optimal cut-off definition. Assuring result harmonization and controlling measurement uncertainty in terms of performance specifications are fundamental to allow worldwide application of clinical information according to specific CRP thresholds and to avoid risk of patient misclassification.

Real-World Effectiveness of Nirmatrelvir/Ritonavir and Dexamethasone Among Hospitalized Patients with COVID-19: A Prospective Cohort Study

Purpose

Anti-viral and anti-inflammatory therapies were effective in altering virus repletion and immune dysregulation in Coronavirus Disease 2019 (COVID-19) patients. This study aimed to explore the effect of combination therapy on disease progression in a real-world setting.

Patients and Methods

A total of 836 patients confirmed with SARS-CoV-2 infection participated in the study from 15 November to 25 December 2022 at Beijing Youan Hospital, Capital Medical University. A prospective cohort study was implemented to investigate the prognostic effect of the combination therapy on virus shedding and clinical recovery.

Results

About 78% of patients used nirmatrelvir/ritonavir (N/R, Paxlovid®, Pfizer) negatively, 16% of patients were prescribed nirmatrelvir/ritonavir beyond five days of symptom onset, 4% of patients received N/R monotherapy within five days of symptom onset and 2% of patients received N/R combined with dexamethasone. Compared with untreated patients, N/R monotherapy reduced the median time to 10.0 days from 12.0 days according to the negative conversion of nucleic acid amplification test (NAAT), and combination therapy reduced the time to 7.0 days, and increased to a 1.99 (95% CI 0.92, 4.32) and 14.23-fold (95% CI 4.50, 44.95) probability of negative NAAT, respectively. N/R monotherapy reduced the clinical recovery time to 10.0 days from 13.0 days. Single-use and combined-use non-significantly increased the recovery probability by 61% and 69%, respectively. In mild and moderate patients, the HRs for clinical recovery increased to 1.69 (95% CI 0.73, 3.94) and 2.18 (95% CI 0.29, 16.62), respectively.

Conclusion

Combination therapy of N/R and dexamethasone increased negative conversion of NAAT and was associated with a non-significant improvement in clinical recovery. Further studies are warranted to confirm this efficacy.

Clinical profile of hospitalised moderate category COVID-19 patients: Short study from a Tertiary Care Centre in Delhi

Background

The clinical profile of hospitalized moderate-category COVID-19 patients has been understudied globally and in India.

Aim

The present study was conducted to study the clinical profile and assess the proportions of patients who progressed to severe disease and its predictors among moderate COVID-19 patients.

Materials and Methods

In this single-center observational study, 100 moderate-category COVID-19 patients as per Ministry of Health and Family Welfare (MoHFW) criteria of age ≥18 years of either sex, excluding pregnant females from February to November 2021, were studied by analyzing their clinical profiles and assessing Quick Sequential Organ Failure Assessment (qSOFA), National Early Warning Score 2 (NEWS-2), and chest computed-tomography severity score (CTSS) to predict progression to severe disease. Severe disease was defined as per MoHFW criteria.

Results

Out of 100 moderate-category COVID-19 patients, progression to severe disease was seen in 11 patients (11%), among which eight patients had expired, three patients were discharged, and the rest of the 89 patients (89%) who did not progress to severe disease were discharged. A higher age (62.2± 19.5 vs 54.8 ± 14.6 years), along with multivariate analysis revealing male sex (1.25 times), chronic kidney disease (2.86 times), leukocytosis (6.10 times), thrombocytopenia (1.04 times), anemia (9.3 times), a higher qSOFA score (3.6 times), and a higher NEWS-2 score on admission (1.56 times) had higher odds of progression to severe disease. A significant correlation (P < .05) of qSOFA score with serum LDH, ferritin, and hs-CRP levels; CT severity score with the serum ferritin, IL-6, and LDH levels; and NEWS-2 with serum LDH, hs-CRP, and ferritin levels were found. Moreover, the NEWS-2 score was found slightly better than qSOFA on receiver operating characteristic (ROC) curve analysis, with an area under the curve of 85.8% and 83.2%, respectively, predicting progression to severe disease.

Conclusion

Our study revealed male gender, chronic kidney disease, leukocytosis, anemia, thrombocytopenia, a higher qSOFA and NEWS-2 score on admission, and further, NEWS-2 score better than qSOFA on ROC curve analysis, with an area under the curve of 85.8% and 83.2%, respectively, in predicting severe disease among hospitalized moderate COVID-19 patients.

Hematological alterations associated with long COVID-19

Long COVID-19 is a condition characterized by persistent symptoms lasting beyond the acute phase of COVID-19. Long COVID-19 produces diverse symptomatology and can impact organs and systems, including the hematological system. Several studies have reported, in COVID-19 patients, hematological abnormalities. Most of these alterations are associated with a higher risk of severe disease and poor outcomes. This literature review identified studies reporting hematological parameters in individuals with Long COVID-19. Findings suggest that Long COVID-19 is associated with a range of sustained hematological alterations, including alterations in red blood cells, anemia, lymphopenia, and elevated levels of inflammatory markers such as ferritin, D-dimer, and IL-6. These alterations may contribute to a better understanding of the pathophysiology of Long COVID-19 and its associated symptoms. However, further research is needed to elucidate the underlying mechanisms and potential treatments for these hematological changes in individuals with Long COVID-19.

Effect of antiviral and immunomodulatory treatment on a cytokine profile in patients with COVID-19

Background

The severity of COVID-19 is associated with an elevated level of a variety of inflammatory mediators. Increasing evidence suggests that the Th17 response contributes to the severity of COVID-19 pneumonia, whereas Th22 response plays a regulatory role in SARS-CoV-2 infection. Two main types of available COVID-19 treatments are antivirals and immunomodulatory drugs; however, their effect on a cytokine profile is yet to be determined.

Methods

This study aim to analyse a cytokine profile in peripheral blood from patients with COVID-19 (n=44) undergoing antiviral or/and immunomodulatory treatment and healthy controls (n=20). Circulating CD4+ and CD8+ T cells and their intracellular expression of IL-17A and IL-22 were assessed by flow cytometry.

Results

Initial results showed an overexpression of IL-17F, IL-17A, CCL5/RANTES, GM-CSF, IL-4, IL-10, CXCL-10/IP-10 and IL-6 in COVID-19 patients compared to healthy controls. Treatment with remdesivir resulted in a significant decline in concentrations of IL-6, IL-10, IFN-alpha and CXCL10/IP-10. Immunomodulatory treatment contributed to a significant downregulation of IL-10, IFN-alpha, CXCL10/IP-10 and B7-H3 as well as upregulation of IL-22 and IL-1 beta. A combination of an antiviral and immunomodulatory treatment resulted in a significant decrease in IL-17F, IL-10, IFN-alpha, CXCL10/IP-10 and B7-H3 levels as well as an increase in IL-17A and IL-1 beta. We found significantly higher percentage of both CD4+ and CD8+ T cells producing IL-17A and CD4+ T cells producing IL-22 in patients with COVID-19.

Conclusion

Administration of antiviral or/and immunomodulatory treatment resulted in a significant downregulation of pro-inflammatory cytokine expression and an upregulation of T cell absolute counts in most cases, thus showing effectiveness of treatment in COVID-19. SARS-CoV-2 infection induced cytokine overexpression in hospitalized patients with COVID-19 as well as lymphopenia, particularly a decrease in CD4+ and CD8+ T cell counts. Moreover, despite the reduced counts of CD4+ and CD8+ T cells, both subsets showed overactivation and increased expression of IL-17A and IL-22, thus targeting Th17 response might alleviate inflammatory response in severe disease.

COVID-19 association with multidrug-resistant bacteria superinfections: Lessons for future challenges

The future waves of COVID 19 infections will continue to raise serious problems in patients with severe forms of the disease. Bacterial infections associated with SARS-CoV-2 disease may complicate the progress of hospitalized patients with COVID-19. The present study aimed to evaluate the etiological spectrum of superinfection in adult patients with COVID-19 and to investigate the correlation between superinfection with multidrug-resistant (MDR) bacteria and serum procalcitonin (PCT). A total of 82 COVID-19 hospitalized patients with COVID-19 and bacterial superinfection were included. The superinfections were classified into early infections (3-7 days from admission) and late infections (>7 days from admission). Bacterial superinfection etiological spectrum, MDR bacteria profile and levels of serum PCT were studied. The most frequently isolated bacteria were Klebsiella pneumoniae, Acinetobacter baumannii and Enterococcus spp. MDR bacteria were involved in 73.17% of COVID-19 patients with bacterial superinfections. Most MDR bacteria superinfections (73.52%) occurred in the late infection period. Klebsiella pneumoniae, Enterococcus spp. and Methicillin-resistant Staphylococcus aureus were the most common MDR bacteria identified in late infections after hospitalization in 20.43, 4.30 and 4.30% of all infections, respectively. Serum PCT values were significantly higher in patients with MDR bacteria superinfection compared with patients with sensitive bacteria superinfection (P=0.009). The principal findings of the present study were the high prevalence of superinfection with MDR bacteria among the COVID-19 patients with bacterial superinfections and the presence of a statistically significant association between serum PCT levels and the presence of superinfection with MDR bacteria. The most effective way to fight against microbial resistance to antibiotics, whether it occurs independently or overlaps with viral infections, is to pursue a national policy for the rational use of antibiotics.

Association of Monocyte Distribution Width with the Need for Respiratory Support in Hospitalized COVID-19 Patients

Background

The monocyte distribution width (MDW), a novel inflammatory biomarker reflecting morphological changes in response to inflammation, has been shown to be useful in identifying COVID-19 infection or predicting death. However, data on the association with predicting the need for respiratory support are still limited. The aim of this study was to determine the association of MDW with the need for respiratory support in patients with SARS-CoV-2 infection.

Patients and methods

This is a single-center retrospective cohort study. Consecutive hospitalized COVID-19 adult patients who presented at the outpatient department (OPD) or emergency department (ED) between May and August 2021 were enrolled. Respiratory support was defined as any one of the following: conventional oxygen therapy, high-flow oxygen nasal cannula, noninvasive, or invasive mechanical ventilation. The performance of MDW was measured using the area under the receiver operating characteristic (AuROC) curve.

Results

Of the 250 enrolled patients, 122 (48.8%) patients received respiratory support. The mean MDW was significantly higher in the respiratory support group: 27.2 ± 4.6 vs 23.6 ± 4.1 (p < 0.001). The MDW ≥ 25 had the best AuROC characteristics of 0.70 (95% CI: 0.65-0.76).

Conclusions

The MDW is a potential biomarker that may aid in identifying individuals at risk of requiring oxygen support in COVID-19 and can be easily implemented in clinical practice.

How to cite this article

Daorattanachai K, Hirunrut C, Pirompanich P, Weschawalit S, Srivilaithon W. Association of Monocyte Distribution Width with the Need for Respiratory Support in Hospitalized COVID-19 Patients. Indian J Crit Care Med 2023;27(5):352-357.

Common Prognostic Biomarkers and Outcomes in Patients with COVID-19 Infection in Saudi Arabia

Background: COVID-19 is a respiratory disease that eventually became a pandemic, with 300 million people infected around the world. Alongside the improvement in COVID-19 management and vaccine development, identifying biomarkers for COVID-19 has recently been reported to help in early prediction and managing severe cases, which might improve outcomes. Our study aimed to find out if there is any correlation between clinical severity and elevated hematological and biochemical markers in COVID-19 patients and its effect on the outcome. Methods: We have collected retrospective data on socio-demographics, medical history, biomarkers, and disease outcomes from five hospitals and health institutions in the Kingdom of Saudi Arabia. Results: Pneumonia was the most common presentation of COVID-19 in our cohort. The presence of abnormal inflammatory biomarkers (D-dimer, CRP, troponin, LDH, ferritin, and t white blood cells) was significantly associated with unstable COVID-19 disease. In addition, patients with evidence of severe respiratory disease, particularly those who required mechanical ventilation, had higher biomarkers when compared to those with stable respiratory conditions (p < 0.001). Conclusion: Identifying biomarkers predicts outcomes for COVID-19 patients and may significantly help in their management.

On-admission and dynamic trend of laboratory profiles as prognostic biomarkers in COVID-19 inpatients

This large-scale study aimed to investigate the trend of laboratory tests of patients with COVID-19. Hospitalized confirmed and probable COVID-19 patients in three general hospitals were examined from March 20, 2020, to June 18, 2021. The confirmed and probable COVID-19 patients with known outcomes and valid laboratory results were included. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to select admittance prognostic features. Parallel Pairwise Comparison of mortality versus survival was used to examine the trend of markers. In the final cohort, 11,944 patients were enrolled, with an in-hospital mortality rate of 21.8%, mean age of 59.4 ± 18.0, and a male-to-female ratio of 1.3. Abnormal admittance level of white blood cells, neutrophils, lymphocytes, mean cellular volume, urea, creatinine, bilirubin, creatine kinase-myoglobin binding, lactate dehydrogenase (LDH), Troponin, c-reactive protein (CRP), potassium, and creatinine phosphokinase reduced the survival of COVID-19 inpatients. Moreover, the trend analysis showed lymphocytes, platelet, urea, CRP, alanine transaminase (ALT), and LDH have a dissimilar trend in non-survivors compared to survived patients. This study proposed a novel approach to find serial laboratory markers. Serial examination of platelet count, creatinine, CRP, LDH, and ALT can guide healthcare professionals in finding patients at risk of deterioration.

Variant-Related Differences in Laboratory Biomarkers among Patients Affected with Alpha, Delta and Omicron: A Retrospective Whole Viral Genome Sequencing and Hospital-Setting Cohort Study

During the COVID-19 pandemic, different SARS-CoV-2 variants of concern (VOC) with specific characteristics have emerged and spread worldwide. At the same time, clinicians routinely evaluate the results of certain blood tests upon patient admission as well as during hospitalization to assess disease severity and the overall patient status. In the present study, we searched for significant cell blood count and biomarker differences among patients affected with the Alpha, Delta and Omicron VOCs at admission. Data from 330 patients were retrieved regarding age, gender, VOC, cell blood count results (WBC, Neut%, Lymph%, Ig%, PLT), common biomarkers (D-dimers, urea, creatinine, SGOT, SGPT, CRP, IL-6, suPAR), ICU admission and death. Statistical analyses were performed using ANOVA, the Kruskal-Wallis test, two-way ANOVA, Chi-square, T-test, the Mann-Whitney test and logistic regression was performed where appropriate using SPSS v.28 and STATA 14. Age and VOC were significantly associated with hospitalization, whereas significant differences among VOC groups were found for WBC, PLT, Neut%, IL-6, creatinine, CRP, D-dimers and suPAR. Our analyses showed that throughout the current pandemic, not only the SARS-CoV-2 VOCs but also the laboratory parameters that are used to evaluate the patient's status at admission are subject to changes.

Development and external validation of prediction models for critical outcomes of unvaccinated COVID-19 patients based on demographics, medical conditions and dental status

Background

Multiple prediction models were developed for critical outcomes of COVID-19. However, prediction models using predictors which can be easily obtained in clinical practice and on dental status are scarce.

Aim

The study aimed to develop and externally validate prediction models for critical outcomes of COVID-19 for unvaccinated adult patients in hospital settings based on demographics, medical conditions, and dental status.

Methods

A total of 285 and 352 patients from two hospitals in the Netherlands were retrospectively included as derivation and validation cohorts. Demographics, medical conditions, and dental status were considered potential predictors. The critical outcomes (death and ICU admission) were considered endpoints. Logistic regression analyses were used to develop two models: for death alone and for critical outcomes. The performance and clinical values of the models were determined in both cohorts.

Results

Age, number of teeth, chronic kidney disease, hypertension, diabetes, and chronic obstructive pulmonary diseases were the significant independent predictors. The models showed good to excellent calibration with observed: expected (O:E) ratios of 0.98 (95%CI: 0.76 to 1.25) and 1.00 (95%CI: 0.80 to 1.24), and discrimination with shrunken area under the curve (AUC) values of 0.85 and 0.79, based on the derivation cohort. In the validation cohort, the models showed good to excellent discrimination with AUC values of 0.85 (95%CI: 0.80 to 0.90) and 0.78 (95%CI: 0.73 to 0.83), but an overestimation in calibration with O:E ratios of 0.65 (95%CI: 0.49 to 0.85) and 0.67 (95%CI: 0.52 to 0.84).

Conclusion

The performance of the models was acceptable in both derivation and validation cohorts. Number of teeth was an additive important predictor of critical outcomes of COVID-19. It is an easy-to-apply tool in hospitals for risk stratification of COVID-19 prognosis.

Clinical and treatment factors associated with the mortality of COVID-19 patients admitted to a referral hospital in Indonesia

Background

Indonesia had the second-highest number of COVID-19 cases and deaths in South-East Asia. We aimed to determine the factors associated with this mortality and the effect of the recommended COVID-19 treatment regimen during the first 10 months of the epidemic.

Methods

This was a retrospective cohort study using secondary data from medical records. In total, 689 adult COVID-19 inpatients hospitalized between March and December 2020 were enrolled. Clinical characteristics, laboratory parameters, and treatments were analyzed by survival outcome. Kaplan-Meier statistics were used to estimate survival.

Findings

Of the 689 patients enrolled, 103 (14.9%) died. Disease severity was highly associated with mortality (hazard ratio [HR]: 7.69, p < 0.001). Other clinical factors associated with mortality were older age and comorbidities. Based on laboratory parameters, higher procalcitonin and C-reactive protein contents and a neutrophil-to-lymphocyte ratio >3.53 were also linked to mortality. Favipiravir was associated with lower mortality, with adjusted HRs of 0.24 (0.11-0.54) and 0.40 (0.17-0.98) among the mild/moderate and severe cases, respectively. Among patients with severe disease, steroids showed some beneficial effects in the early days of hospitalization.

Interpretation

Older age and comorbidities were associated with disease severity and, consequently, higher mortality. Higher mortality after the second week of hospitalization may be related to secondary bacterial infection. Favipiravir showed significant benefit for COVID-19 survival, while steroids showed benefit only in the early days of admission among patients with severe disease.

Funding

This research did not receive a specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

The association of clinically relevant variables with chest radiograph lung disease burden quantified in real-time by radiologists upon initial presentation in individuals hospitalized with COVID-19

Objectives

We aimed to correlate lung disease burden on presentation chest radiographs (CXR), quantified at the time of study interpretation, with clinical presentation in patients hospitalized with coronavirus disease 2019 (COVID-19).

Material and methods

This retrospective cross-sectional study included 5833 consecutive adult patients, aged 18 and older, hospitalized with a diagnosis of COVID-19 with a CXR quantified in real-time while hospitalized in 1 of 12 acute care hospitals across a multihospital integrated healthcare network between March 24, 2020, and May 22, 2020. Lung disease burden was quantified in real-time by 118 radiologists on 5833 CXR at the time of exam interpretation with each lung annotated by the degree of lung opacity as clear (0%), mild (1–33%), moderate (34–66%), or severe (67–100%). CXR findings were classified as (1) clear versus disease, (2) unilateral versus bilateral, (3) symmetric versus asymmetric, or (4) not severe versus severe. Lung disease burden was characterized on initial presentation by patient demographics, co-morbidities, vital signs, and lab results with chi-square used for univariate analysis and logistic regression for multivariable analysis.

Results

Patients with severe lung disease were more likely to have oxygen impairment, an elevated respiratory rate, low albumin, high lactate dehydrogenase, and high ferritin compared to non-severe lung disease. A lack of opacities in COVID-19 was associated with a low estimated glomerular filtration rate, hypernatremia, and hypoglycemia.

Conclusions

COVID-19 lung disease burden quantified in real-time on presentation CXR was characterized by demographics, comorbidities, emergency severity index, Charlson Comorbidity Index, vital signs, and lab results on 5833 patients. This novel approach to real-time quantified chest radiograph lung disease burden by radiologists needs further research to understand how this information can be incorporated to improve clinical care for pulmonary-related diseases.. An absence of opacities in COVID-19 may be associated with poor oral intake and a prerenal state as evidenced by the association of clear CXRs with a low eGFR, hypernatremia, and hypoglycemia.

COVID-19 infection during pregnancy: A retrospective study in a city in the Southeastern region of Turkey

OBJECTIVES

To evaluate the maternal and fetal clinical outcomes in SARS-CoV-2 infected pregnant women during the whole period of the pandemic in a single province in the southeast of Turkey.

METHODS

This retrospective study included patients who were screened from the medical registration system and found to be infected with SARS-CoV-2 virus during pregnancy. The demographic, clinical, laboratory, and radiological features of all the patients were obtained and compared between groups classified as severe-critical and mild-moderate disease severity.

RESULTS

The mean age of all the cases was 29.0±5.3 years in the mild-moderate cases, and 30.1±5.5 years in the severe-critical cases. The rates of 3rd trimester, cesarean and premature birth, high body mass index (BMI), symptoms of cough and dyspnea, the presence of comorbidities, and hypothyroidism were significantly higher in the severe-critical cases than in the mild-moderate group. In the univariate analyses, BMI, dyspnea, cough, maternal complication rate, the neutrophil/lymphocyte ratio, the values of white blood cells, procalcitonin, high-sensitive C-reactive protein, D-dimer, ferritin, aspartate aminotransferase, and alanine aminotransferase were detected as significant risk factors. In the multivariate analysis, only procalcitonin was a significant factor.

CONCLUSION

In the 3rd trimester of pregnancy, obesity and hypothyroidism were found to be risk factors for severe-critical cases of COVID-19 infection, and the clinical course was more severe with a higher rate of mortality in the recent period of the pandemic.

Efficacy of blood urea nitrogen-to-albumin ratio for predicting prognostic outcomes of inpatients with COVID-19: A meta-analysis

BACKGROUND

The associations between blood urea nitrogen (BUN)/albumin ratio and poor prognosis in patients with diagnosis of coronavirus disease 2019 (COVID-19) remain to be clarified.

METHODS

A search based on 4 electronic databases (i.e., EMBASE, Google scholar, MEDLINE, and Cochrane Library) was performed on June 23, 2022. The association of BUN/Albumin ratio with poor prognostic outcomes, defined as patients with mortality/severe illnesses, were analyzed.

RESULTS

Results from analysis of 7 cohort studies (3600 individuals with COVID-19) published between 2020 and 2022 showed a higher BUN/Albumin ratio in the poor-prognosis group (Mean difference:  = 2.838, 95% confidence interval: 2.015-3.66, P < .001, I2 = 92.5%) than the good-prognosis group. Additional investigation into the connection between BUN/Albumin ratio as a binary variable (i.e., high or low) and the risk of poor outcome also supported an association between a higher BUN/Albumin ratio and a poor prognostic risk (odd ratio = 3.009, 95% confidence interval: 1.565-5.783, P = .001, I2 = 93.7%, 5 studies). Merged analysis of poor prognosis produced a sensitivity of 0.76, specificity of 0.72, and area under curve of 0.81.

CONCLUSION

This meta-analysis demonstrated a positive correlation between BUN/albumin ratio and poor outcome in patients with COVID-19. Additional large-scale prospective studies are needed to verify our findings.

Hematological, Inflammatory, Coagulation, and Oxidative/Antioxidant Biomarkers as Predictors for Severity and Mortality in COVID-19: A Prospective Cohort-Study

Purpose

Oxidative stress (OS) and inflammation are pivotal points in the pathophysiology of coronavirus disease-2019 (COVID-19). This study aims to use routine laboratory and oxidative stress/antioxidative biomarkers as predictors for the mortality of the disease.

Patients and Methods

This prospective cohort study, made up of 120 COVID-19 patients from emergency units in Erbil, Duhok, Kirkuk, and Sulaymaniyah cities in Iraq, from May the 1^st to May the 30^th, 2021, and 60 healthy controls (HCs) (n = 60). The patients were re-categorized into mild (n = 54), severe (n = 40), and critical (n = 26) groups based on the clinical criteria. Following admission to the hospital, blood was directly collected for measuring routine laboratory biomarkers.

Results

Neutrophils and neutrophil/lymphocyte ratio (NLR) were higher in the critical group, while lymphocytes were lower in the severe and critical groups compared to the mild group. The CRP, ferritin, and D-dimer values were more elevated in severe and critical cases than in mild COVID-19 cases. The levels of malondialdehyde (MDA), nitric oxide (NO), and copper were elevated, while the superoxide dismutase (SOD) activity level and total antioxidant capacity (TAC) level were lower. However, vitamin C, glutathione peroxidase (GPx), and catalase activity levels were not changed in the COVID-19 groups compared to the HCs. NO and ferritin were predictors of ICU hospitalization; D-dimer, MDA, and NLR were predictors of mortality. NO, and NLR were predictors of SpO₂ depression. Moreover, NO, and copper have both good diagnostic values, their cutoffs were 39.01 and 11.93, respectively.

Conclusion

There is an association between immune dysregulation and oxidative imbalance. The biomarkers, that could be considered as predictors for the severity and mortality of COVID-19, are the NLR, NO, ferritin, and D-dimer. The age equal to and older than 50 has a poor prognosis in the Kurdish population.

Parameters to Predict the Outcome of Severe and Critical COVID-19 Patients when Admitted to the Hospital

Manifestations of COVID-19 are diverse and range from asymptomatic to severe, critical illness and death. Cases requiring hospital care (in severe and critical illnesses) are associated with comorbidities and hyperactivation of the immune system. Therefore, in this exploratory observational study, we analyzed which parameters are associated with mortality. We evaluated: demographic characteristics (age, sex and comorbidities), laboratory data (albumin, leukocytes, lymphocytes, platelets, ferritin), days of hospital stay, interleukins (IL-2, IL-6, IL-7, IL-10, IL-17) and sP-selectin in 40 Mexican patients admitted to medical emergencies with a confirmed diagnosis of COVID-19, a complete clinical record, and who signed the informed consent. Twenty severe (they required intermediate care with non-invasive ventilation) and twenty critically ill patients (they required mechanical ventilation) were classified, and these were subsequently compared with healthy and recovered subjects. A significant difference was found between the hospitalized groups in the parameters of age, ferritin, days of hospital stay and death with p values = 0.0145, p = 0.0441, p = 0.0001 and p = 0.0001, respectively. In the determination of cytokines and P-selectin, a significant difference was found between the following groups: recovered patients and healthy volunteers compared with hospitalized patients in severe and critical condition. Importantly, IL-7 remained elevated one year later in recovered patients. Taken together, these values determined at the time of hospital admission could be useful to monitor patients closely and evaluate in-hospital progress, hospital discharge, and out-of-hospital progress.

Serum Krebs von den Lungen-6 for Predicting the Severity of COVID-19: A Systematic Review, Meta-Analysis, and Trial Sequence Analysis

OBJECTIVE

This systematic review and meta-analysis aimed to find the association between serum Krebs von den Lungen-6 (KL-6) and the severity of Coronavirus disease 2019 (COVID-19) infection.

DATA SOURCES

Databases of Embase, PubMed, Web of Science, Science Direct, and Google Scholar were searched for studies reporting KL-6 levels in COVID-19 patients, published between January 2020 and September 30 2022.

DATA SYNTHESIS

For comparison between the groups, standard mean difference (SMD) and 95% confidence intervals (CI) were computed as the effect sizes. Sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were measured to assess the diagnostic power of KL-6. In addition, the summary receiver operating characteristics curve (sROC) was constructed to summarize the true positive (TP), and false positive (FP) rates. To validate the findings of meta-analysis, Trial Sequential Analysis (TSA) was conducted.

RESULTS

Altogether 497 severe COVID-19 patients and 934 non-severe (mild to moderate) COVID-19 patients were included. Pooling of 12 studies indicated that the serum KL-6 level had significant association with severity of COVID-19 infection: standard mean difference = 1.18 (95% CI: 0.93-1.43), p = 0.01; I²: 58.56%]. Pooled diagnostic parameters calculated from eight studies were: sensitivity 0.53 (95% CI: 0.47-0.59); specificity 0.90 (95% CI: 0.88-0.93); positive likelihood ratio 4.80 (95% CI: 3.53-6.53); negative likelihood ratio 0.46 (95% CI: 0.32-0.68); and area under curve: 0.8841. Additionally, TSA verified the adequacy of sample size and robustness of the meta-analysis.

CONCLUSION

Serum KL-6 level has a moderate degree of correlation with the severity of COVID-19 infection but has low sensitivity. So, it is not recommended as a screening test for severe COVID-19 infection.

Biochemical and hematological findings and risk factors associated with kidney impairment in patients with COVID-19

Background

COVID-19 is a new pandemic that has infected millions of people worldwide and caused a high morbidity and mortality rate. COVID-19 may have a harmful effect on organs, especially the kidneys. Aims: The main aim of our research is to study the association between the severity of COVID-19 disease and biochemical parameters related to kidney function and to investigate certain risk factors of COVID-19-associated kidney disease.

Methods

A total of 174 individuals, 121 COVID-19 positive and 53 COVID-19 negative, were enrolled in this study. The relation between COVID-19 infection, severity, kidney function test, and hematological indicators were examined.

Results

The most prominent symptoms among COVID-19 were fever (95% ) and fatigue (92%). Regarding biochemical parameters, median creatinine, MPV, and CRP were significantly higher in COVID-19 patients, whereas median eGFR, Na+, WBC, MCH, MCHC, and eosinophil percentages were significantly lower in this group. Severely infected patients were observed to have higher urea, creatinine, neutrophils, and NLR. However, median sodium, eGFR, hemoglobin, hematocrit, RBC, lymphocytes, and platelet count were significantly lower in the severe group. Urine examination of the severe group showed a significantly lower specific gravity, while urine pH, protein, and glucose were significantly higher.

Conclusions

Our analysis indicates that COVID-19 infection affects kidney function, mainly creatinine level, urea, eGFR, Na+ and urine protein. Additionally, comorbidities such as older age (>65), hypertension, taking medications, and CRP (>33.55 mg/L) are considered risk factors that are more likely to contribute to kidney impairment in COVID-19 positive patients.

Machine Learning Successfully Detects Patients with COVID-19 Prior to PCR Results and Predicts Their Survival Based on Standard Laboratory Parameters in an Observational Study

INTRODUCTION

In the current COVID-19 pandemic, clinicians require a manageable set of decisive parameters that can be used to (i) rapidly identify SARS-CoV-2 positive patients, (ii) identify patients with a high risk of a fatal outcome on hospital admission, and (iii) recognize longitudinal warning signs of a possible fatal outcome.

METHODS

This comparative study was performed in 515 patients in the Maria Skłodowska-Curie Specialty Voivodeship Hospital in Zgierz, Poland. The study groups comprised 314 patients with COVID-like symptoms who tested negative and 201 patients who tested positive for SARS-CoV-2 infection; of the latter, 72 patients with COVID-19 died and 129 were released from hospital. Data on which we trained several machine learning (ML) models included clinical findings on admission and during hospitalization, symptoms, epidemiological risk, and reported comorbidities and medications.

RESULTS

We identified a set of eight on-admission parameters: white blood cells, antibody-synthesizing lymphocytes, ratios of basophils/lymphocytes, platelets/neutrophils, and monocytes/lymphocytes, procalcitonin, creatinine, and C-reactive protein. The medical decision tree built using these parameters differentiated between SARS-CoV-2 positive and negative patients with up to 90-100% accuracy. Patients with COVID-19 who on hospital admission were older, had higher procalcitonin, C-reactive protein, and troponin I levels together with lower hemoglobin and platelets/neutrophils ratio were found to be at highest risk of death from COVID-19. Furthermore, we identified longitudinal patterns in C-reactive protein, white blood cells, and D dimer that predicted the disease outcome.

CONCLUSIONS

Our study provides sets of easily obtainable parameters that allow one to assess the status of a patient with SARS-CoV-2 infection, and the risk of a fatal disease outcome on hospital admission and during the course of the disease.

Association of SARS-CoV-2 nucleocapsid viral antigen and the receptor for advanced glycation end products with development of severe disease in patients presenting to the emergency department with COVID-19

Introduction

There remains a need to better identify patients at highest risk for developing severe Coronavirus Disease 2019 (COVID-19) as additional waves of the pandemic continue to impact hospital systems. We sought to characterize the association of receptor for advanced glycation end products (RAGE), SARS-CoV-2 nucleocapsid viral antigen, and a panel of thromboinflammatory biomarkers with development of severe disease in patients presenting to the emergency department with symptomatic COVID-19.

Methods

Blood samples were collected on arrival from 77 patients with symptomatic COVID-19, and plasma levels of thromboinflammatory biomarkers were measured.

Results

Differences in biomarkers between those who did and did not develop severe disease or death 7 days after presentation were analyzed. After adjustment for multiple comparisons, RAGE, SARS-CoV-2 nucleocapsid viral antigen, interleukin (IL)-6, IL-10 and tumor necrosis factor receptor (TNFR)-1 were significantly elevated in the group who developed severe disease (all p<0.05). In a multivariable regression model, RAGE and SARS-CoV-2 nucleocapsid viral antigen remained significant risk factors for development of severe disease (both p<0.05), and each had sensitivity and specificity >80% on cut-point analysis.

Discussion

Elevated RAGE and SARS-CoV-2 nucleocapsid viral antigen on emergency department presentation are strongly associated with development of severe disease at 7 days. These findings are of clinical relevance for patient prognostication and triage as hospital systems continue to be overwhelmed. Further studies are warranted to determine the feasibility and utility of point-of care measurements of these biomarkers in the emergency department setting to improve patient prognostication and triage.

MINIMAL LIVER ENZYMES ABNORMALITIES AT ADMISSION ARE RELATED TO SEVERE COVID-19 CLINICAL COURSE IN A LARGE BRAZILIAN COHORT

BACKGROUND

COVID-19 is a multisystemic disease, primarily affecting the respiratory system. Liver involvement is frequent, but the impact on the clinical course and outcomes are controversial.

OBJECTIVE

The aim was to assess liver function at the admission and evaluate its effects on severity and mortality in hospitalized patients with COVID-19.

METHODS

This is a retrospective study of hospitalized patients in a tertiary hospital in Brazil, with a PCR-confirmed SARS-CoV-2 infection between April and October 2020. 1080 out of 1229 patients had liver enzymes on admission and were divided in two cohorts, based on the presence or absence of abnormal liver enzymes (ALE). Demographic, clinical, laboratory, imaging, clinical severity, and mortality were evaluated. Patients were followed until discharge, death or transfer to another institution.

RESULTS

Median age was 60 years and 51.5% were male. The more frequent comorbidities were hypertension (51.2%), and diabetes (31.6%). Chronic liver disease and cirrhosis were present in 8.6% and 2.3%, respectively. ALE (aminotransferases higher than 40 IU/L) were present in 56.9% of patients [mild (1-2 times): 63.9%; moderate (2-5 times): 29.8%; severe (>5 times): 6.3%]. Male gender [RR 1.49, P=0.007], increased total bilirubin [RR 1.18, P<0.001] and chronic liver disease [RR 1.47, P=0.015] were predictors of abnormal aminotransferases on admission. Patients with ALE had a higher risk of disease severity [RR 1.19; P=0.004]. There was no association among ALE and mortality.

CONCLUSION

ALE is common in COVID-19 hospitalized patients and were independently correlated with severe COVID-19. Even mild ALE at admission may be a severity prognostic marker.

Intensive care unit burden is associated with increased mortality in critically ill COVID-19 patients

BACKGROUND

Traditional models to predict intensive care outcomes do not perform well in COVID-19. We undertook a comprehensive study of factors affecting mortality and functional outcome after severe COVID-19.

METHODS

In this prospective multicentre cohort study, we enrolled laboratory-confirmed, critically ill COVID-19 patients at six ICUs in the Skåne Region, Sweden, between May 11, 2020, and May 10, 2021. Demographics and clinical data were collected. ICU burden was defined as the total number of ICU-treated COVID-19 patients in the region on admission. Surviving patients had a follow-up at 90 days for assessment of functional outcome using the Glasgow Outcome Scale-Extended (GOSE), an ordinal scale (1-8) with GOSE ≥5 representing a favourable outcome. The primary outcome was 90-day mortality; the secondary outcome was functional outcome at 90 days.

RESULTS

Among 498 included patients, 74% were male with a median age of 66 years and a median body mass index (BMI) of 30 kg/m² . Invasive mechanical ventilation was employed in 72%. Mortality in the ICU, in-hospital and at 90 days was 30%, 38% and 39%, respectively. Mortality increased markedly at age 60 and older. Increasing ICU burden was independently associated with a two-fold increase in mortality. Higher BMI was not associated with increased mortality. Besides age and ICU burden, smoking status, cortisone use, P_a CO₂ >7 kPa, and inflammatory markers on admission were independent factors of 90-day mortality. Lower GOSE at 90 days was associated with a longer stay in the ICU.

CONCLUSION

In critically ill COVID-19 patients, the 90-day mortality was 39% and increased considerably at age 60 or older. The ICU burden was associated with mortality, whereas a high BMI was not. A longer stay in the ICU was associated with unfavourable functional outcomes at 90 days.

COVID19 biomarkers: What did we learn from systematic reviews?

The coronavirus disease 2019 (COVID19) pandemic continues to represent a substantial public health concern. It can rapidly progress to severe disease, with poor prognosis and a high mortality risk. An early diagnosis and specific prognostic tools can help healthcare providers to start interventions promptly, understand the likely prognosis and to identify and treat timely individuals likely to develop severe disease with enhanced mortality risk. Here we focused on an impressive set of systematic reviews and meta-analyses that were performed since the start of the COVID19 pandemic and summarized their results related to the levels of hematologic, inflammatory, immunologic biomarkers as well as markers of cardiac, respiratory, hepatic, gastrointestinal and renal systems and their association with the disease progression, severity and mortality. The evidence outlines the significance of specific biomarkers, including inflammatory and immunological parameters (C-reactive protein, procalcitonin, interleukin-6), hematological (lymphocytes count, neutrophil-to-lymphocyte ratio, D-dimer, ferritin, red blood cell distribution width), cardiac (troponin, CK-MB, myoglobin), liver (AST, ALT, total bilirubin, albumin) and lung injury (Krebs von den Lungen-6) that can be used as prognostic biomarkers to aid the identification of high-risk patients and the prediction of serious outcomes, including mortality, in COVID19. Thus, these parameters should be used as essential tools for an early risk stratification and adequate intervention in improving disease outcomes in COVID19 patients.

Association of follicular helper T and follicular regulatory T cells with severity and hyperglycemia in hospitalized COVID-19 patients

We aimed to determine the levels of follicular helper T (Tfh) and follicular regulatory T (Tfr) cells in COVID-19 patients and determine whether their levels correlated with disease severity and presence of hyperglycemia. This study was carried out in 34 hospitalized COVID-19 patients and 20 healthy controls. Levels of total circulating Tfh, inducible T-cell costimulator (ICOS)+ activated Tfh, and Tfr cells were assessed in all participants by flow cytometry. Total CD4+CXCR5+ Tfh cells and ICOS+Foxp3-activated Tfh cells increased and ICOS+Foxp3+ Tfr cells decreased in COVID-19 patients, especially in diabetic patients and those with severe disease. Activated ICOS+ Tfh cells were directly correlated with lactate dehydrogenase, D-dimer, ferritin, and respiratory rate and inversely correlated with the partial pressure of carbon dioxide. COVID-19 is associated with marked activation of Tfh cells and a profound drop in Tfr cells, especially in severe and diabetic patients. Future studies on expanded cohorts of patients are needed to clarify the relationship between SARS-CoV-2 and acute-onset diabetes.

Effect of colchicine on the outcomes of patients with COVID-19: a systematic review and meta-analysis of randomised controlled trials

AIM

This meta-analysis aimed to assess the usefulness of colchicine in patients with COVID-19.

METHODS

PubMed, Web of Science, Ovid MEDLINE, the Cochrane Library, Embase, and Clinicaltrials.gov were searched for relevant randomised controlled trials (RCTs) published between database inception and November 12, 2021. Only RCTs that compared the clinical efficacy and safety of colchicine with other alternative treatments or placebos in patients with COVID-19 were included.

RESULTS

Overall, 7 RCTs involving 16,024 patients were included; 7,794 patients were in the study group receiving colchicine and 8,230 were in the control group receiving placebo or standard treatment. The study and control groups had similar risk of mortality (odds ratio [OR], 1.00; 95% CI, 0.91-1.09; I² = 0%). No significant difference was observed between the study and control groups in terms of the need for non-invasive ventilation (OR, 0.92; 95% CI, 0.83-1.03; I² = 0%), the need for mechanical ventilation (OR, 0.64; 95% CI, 0.32-1.32; I² = 58%), and length of hospital stay (mean difference, -0.42 days; 95% CI, -1.95 to 1.11; I² = 62%). In addition, colchicine was associated with significantly higher risks of gastrointestinal adverse events (OR, 1.81; 95% CI, 1.56-2.11; I² = 0%) and diarrhoea (OR, 2.12; 95% CI, 1.75-2.56; I² = 9%).

CONCLUSIONS

Colchicine does not improve clinical outcomes in patients with COVID-19, so it did not support the additional use of colchicine in the treatment of patients with COVID-19.Key messageColchicine could not reduce the mortality of patients with COVID-19.No significant difference was observed between the colchicine and comparators in terms of the need for non-invasive ventilation, need for mechanical ventilation, and length of hospital stay.Colchicine was associated with a higher risk of gastrointestinal adverse events.

The COVID HOME study research protocol: Prospective cohort study of non-hospitalised COVID-19 patients

BACKGROUND

Guidelines on COVID-19 management are developed as we learn from this pandemic. However, most research has been done on hospitalised patients and the impact of the disease on non-hospitalised and their role in transmission are not yet well understood. The COVID HOME study conducts research among COVID-19 patients and their family members who were not hospitalised during acute disease, to guide patient care and inform public health guidelines for infection prevention and control in the community and household.

METHODS

An ongoing prospective longitudinal observational study of COVID-19 outpatients was established in March 2020 at the beginning of the COVID-19 pandemic in the Netherlands. Laboratory confirmed SARS-CoV-2 infected individuals of all ages that did not merit hospitalisation, and their household (HH) members, were enrolled after written informed consent. Enrolled participants were visited at home within 48 hours after initial diagnosis, and then weekly on days 7, 14 and 21 to obtain clinical data, a blood sample for biochemical parameters/cytokines and serological determination; and a nasopharyngeal/throat swab plus urine, stool and sperm or vaginal secretion (if consenting) to test for SARS-CoV-2 by RT-PCR (viral shedding) and for viral culturing. Weekly nasopharyngeal/throat swabs and stool samples, plus a blood sample on days 0 and 21 were also taken from HH members to determine whether and when they became infected. All participants were invited to continue follow-up at 3-, 6-, 12- and 18-months post-infection to assess long-term sequelae and immunological status.

Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application

Healthcare digitalization requires effective applications of human sensors, when various parameters of the human body are instantly monitored in everyday life due to the Internet of Things (IoT). In particular, machine learning (ML) sensors for the prompt diagnosis of COVID-19 are an important option for IoT application in healthcare and ambient assisted living (AAL). Determining a COVID-19 infected status with various diagnostic tests and imaging results is costly and time-consuming. This study provides a fast, reliable and cost-effective alternative tool for the diagnosis of COVID-19 based on the routine blood values (RBVs) measured at admission. The dataset of the study consists of a total of 5296 patients with the same number of negative and positive COVID-19 test results and 51 routine blood values. In this study, 13 popular classifier machine learning models and the LogNNet neural network model were exanimated. The most successful classifier model in terms of time and accuracy in the detection of the disease was the histogram-based gradient boosting (HGB) (accuracy: 100%, time: 6.39 sec). The HGB classifier identified the 11 most important features (LDL, cholesterol, HDL-C, MCHC, triglyceride, amylase, UA, LDH, CK-MB, ALP and MCH) to detect the disease with 100% accuracy. In addition, the importance of single, double and triple combinations of these features in the diagnosis of the disease was discussed. We propose to use these 11 features and their binary combinations as important biomarkers for ML sensors in the diagnosis of the disease, supporting edge computing on Arduino and cloud IoT service.

Changes in lactate dehydrogenase on admission throughout the COVID-19 pandemic and possible impacts on prognostic capability

Introduction: The enzyme lactate dehydrogenase (LDH) is a good marker of general hyperinflammation correlated with mortality for COVID-19, and is therefore used in prognosis tools. In a current COVID-19 clinical randomized trial (CRT), the blood level of LDH was selected as an inclusion criterion. However, LDH decreased during the pandemic; hence, the impact of this decrease on the prognostic value of LDH for mortality was evaluated. Methods: Data on LDH levels in 843 patients were obtained and analyzed. Relative risk, standard error and receiver operating characteristic curves were calculated for two cutoff values. Results: Relative risk lost validity and the area under the curve narrowed by trimester during the pandemic. Conclusion: The progressive decrease in LDH impacted the capacity to predict mortality in COVID-19. More studies are needed to validate this finding and its implications.