COVID19 biomarkers: What did we learn from systematic reviews?

Role of Procalcitonin as a Prognostic Biomarker in Hospitalized COVID-19 Patients: A Comparative Analysis

Background

Procalcitonin (PCT) is recognized as an inflammatory biomarker, often elevated in COVID-19 pneumonia alongside other biomarkers. Understanding its association with severe outcomes and comparing its predictive ability with other biomarkers is crucial for clinical management.

Objectives

This retrospective multicenter observational study aimed to investigate the association between PCT levels and adverse outcomes in hospitalized COVID-19 patients. Additionally, it sought to compare the predictive performance of various biomarkers.

Design

The study analyzed data from the Society of Critical Care Medicine (SCCM) Viral Infection and Respiratory Illness Universal Study (VIRUS) registry, comprising COVID-19 patients hospitalized across multiple Mayo Clinic sites between March 2020 and June 2022.

Methods

A total of 7851 adult COVID-19 patients were included. Patients were categorized into 6 groups based on the worst WHO ordinal scale. Multivariate models were constructed using peak biomarker levels within 72 hours of admission, adjusted for confounders.

Results

Elevated PCT levels were independently associated with increased odds of adverse outcomes, including ICU admission (adjusted odds ratio [aOR] 1.32, 95%CI 1.27-1.38), IMV requirement (aOR 1.35, 95%CI: 1.28-1.42), and in-hospital mortality (aOR 1.30, 95%CI: 1.22-1.37). A 3.48-fold increase in IMV requirement and 3.55 times increase in in-hospital mortality were noted with peak PCT ⩾ 0.25 ng/ml. Similar associations were observed with other biomarkers like NLR (AUC 0.730), CRP, IL-6, LDH (AUC 0.800), and D-dimer (AUC 0.719). Models incorporating NLR, LDH, D-dimer, and PCT demonstrated the highest predictive accuracy, with a combined model exhibiting an area under the curve (AUC) of 0.826 (95%CI 0.803-0.849).

Conclusions

Higher PCT levels were significantly linked to worse outcomes in COVID-19 patients, emphasizing its potential as a prognostic marker. Biomarker-based predictive models, particularly those including PCT, showed promising utility for risk assessment and clinical decision-making. Further prospective studies are warranted to validate these findings on a larger scale.

Forecasting readmission in COVID-19 patients utilizing blood biomarkers and machine learning in the Hospital-at-Home program

Objectives

During the coronavirus disease 2019 (COVID-19) pandemic, the Hospital-at-Home (HaH) program played a key role in expanding healthcare capacity and managing COVID-19 pneumonia. This study aims to evaluate the factors contributing to readmission from HaH to conventional hospitalization and to apply classification algorithms that support discharge decisions from conventional hospitalization to HaH.

Methods

Blood biomarkers (IL-6, Hs-TnT, CRP, ferritin, and D-dimer) were collected from 871 patients transferred to HaH after conventional hospitalization for COVID-19 at the Hospital Universitari Germans Trias i Pujol. Of these, 840 patients completed their recovery without any complications, while 31 of them required readmission. Statistical tests were conducted to assess differences in blood biomarkers between the first day of conventional hospitalization and the first day of HaH, as well as between patients who successfully completed HaH and those who were readmitted. Various classification algorithms (bagged trees, KNN, LDA, logistic regression, Naïve Bayes, and the support vector machine [SVM]) were implemented to predict readmission, with performance evaluated using accuracy, sensitivity, specificity, F1 score, and the Matthews Correlation Coefficient (MCC).

Results

Significant differences were observed in IL-6, Hs-TnT, CRP (p < 0.001), and ferritin (p < 0.01) between the first day of conventional hospitalization and the first day of HaH for patients who were not readmitted. However, no significant differences were found in patients who were readmitted. At HaH, readmitted patients exhibited higher CRP and Hs-TnT values. Among the classification algorithms, the SVM showed the best performance, achieving 85% sensitivity, 87% specificity, 86% accuracy, 84% F1 score, and 71% MCC.

Conclusion

Hs-TnT was a key predictor of readmission for COVID-19 patients discharged to HaH. Classification algorithms can aid clinicians in making informed decisions regarding patient transfers from conventional hospitalization to HaH.

Elevated Serum Presepsin Identifies Herpes Simplex Virus-1 Reactivation in COVID-19 Patients

Presepsin, a cleaved peptide of soluble CD14, may become a promising biomarker for assessing disease severity and mortality in coronavirus disease 2019 (COVID-19). Patients with severe COVID-19 frequently develop bacterial and fungal superinfections, as well as herpes simplex virus-1 (HSV-1) reactivation, which may exacerbate disease progression. This study aimed to evaluate the impact of concomitant infections on serum presepsin levels. Serum presepsin levels were measured using an enzyme-linked immunosorbent assay (ELISA) in 63 patients with moderate COVID-19, 60 patients with severe disease, and 49 healthy controls. Correlations with procalcitonin and the presence of superinfections or HSV-1 reactivation were assessed. Consistent with previous studies, serum presepsin levels were the highest in patients with severe COVID-19 (p = 0.002 compared to patients with moderate disease). Within this group, non-survivors exhibited significantly elevated presepsin levels (p = 0.027). A positive correlation between presepsin and procalcitonin was observed in both moderate and severe COVID-19 cases. Patients with bacterial or fungal superinfections showed presepsin levels comparable to those without secondary infections. However, presepsin levels were markedly elevated in patients with HSV-1 reactivation (p = 0.002). After excluding patients with HSV-1 reactivation, presepsin levels no longer differed between moderate and severe COVID-19 cases, though they remained higher than in healthy controls (p < 0.001 for both comparisons). In conclusion, these findings suggest that elevated serum presepsin levels in severe COVID-19 are primarily driven by HSV-1 reactivation rather than bacterial or fungal superinfections.

Potential Correlation Between Hematological Parameters and Palpitation in Outpatients With COVID-19: A Retrospective Study

BACKGROUND

Research on heart injury caused by COVID-19 is limited to large observational and retrospective cohort studies using imaging or pathological data. Reported changes in the levels of myocardial markers in severe diseases have been limited, with few studies on mild infections. The effects of COVID-19 on cardiac function and changes in myocardial marker levels have not yet been reported.

METHODS

We analyzed data from outpatient blood samples collected at Beijing Anzhen Hospital during the 2022 COVID-19 outbreak and used the same periods in 2020 and 2021 as controls, focusing on changes in routine blood tests, coagulation, myocardial markers, and other blood indices in patients with palpitations.

RESULTS

The number of patients with palpitations increased by 4.87-fold during the COVID-19 mass outbreak in 2022. The indices of myocardial damage did not show any symptom-related increases but decreased within the normal range. The proportion of patients with palpitations whose D-dimer and fibrinogen/fibrin degradation product (FDP) values exceeded the reference ranges increased, as did the numbers of neutrophils, monocytes, and platelets. In this retrospective analysis, we found little change in the myocardial markers in patients with mild COVID-19.

CONCLUSIONS

In patients with mild COVID-19, attention should be diverted from detecting myocardial markers to changes in coagulation test results, focusing on the levels of coagulation indices to improve circulation and prevent thrombosis.

Red blood cell distribution width-to-monocyte ratio for predicting 90-day mortality of COVID-19 in patients with chronic kidney disease during the Omicron period: a prospective single-center study

We aimed to test whether red blood cell distribution width (RDW) to monocyte percentage ratio (RMR) was associated with the acute-phase prognosis of coronavirus disease 2019 (COVID-19) in chronic kidney disease (CKD) patients. Prospective enrollment and 90-day follow-up of CKD patients with COVID-19 were conducted from December 1, 2022 to January 31, 2023. Demographics, clinical data, and laboratory and radiographic findings were collected, and multiple logistic regression, subgroup analysis, and receiver operating characteristic (ROC) curve analysis were performed. A total of 218 patients were enrolled, with a mean age of 59 years and 69.7% being male. The 90-day mortality rate was 24.8%. The lnRMR level was 5.18 (4.91-5.43) and emerged as an independent risk factor (OR: 3.01, 95% CI: 1.72-5.85). The lnRMR-mortality association was consistent across sex, age, CKD stage, COVID-19 vaccination, and comorbidity subgroups. The area under the ROC curve of lnRMR was 0.737 (95% CI: 0.655-0.819). Our findings indicate that lnRMR is a simple and practical predictor for identifying high-risk CKD patients during the acute phase of COVID-19.

Study on the predictive value of laboratory inflammatory markers and blood count-derived inflammatory markers for disease severity and prognosis in COVID-19 patients: a study conducted at a university-affiliated infectious disease hospital

BACKGROUND

Since the outbreak of coronavirus disease 2019 (COVID-19), studies have found correlations between blood cell count-derived inflammatory markers (BCDIMs) and disease severity and prognosis in COVID-19 patients. However, there is currently a lack of systematic comparisons between procalcitonin (PCT), C-reactive protein (CRP), C-reactive protein-to-albumin ratio (CAR) and BCDIMs for assessing the severity and prognosis of COVID-19 patients.

METHODS

A total of 1040 COVID-19 patients were included in the study. Demographics, comorbidities and laboratory results were analysed. BCDIMs refer to the following ratios: neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-C-reactive protein ratio (LCR), systemic inflammation response index (SIRI) and systemic inflammation index (SII). Disease severity and 28-day mortality are clinical outcomes of this study. Area under the curve (AUC) of receiver operating characteristic (ROC) curve was calculated for these markers, and DeLong's test compared their statistical differences. Cox regression analysis assessed their predictive value for the 28-day mortality rate.

RESULTS

Among the 1040 patients, 35.3% were severe/critical, 49.6% were moderate and 15.1% were mild cases. Within 28 days, 15.1% died. The NLR had the highest predictive value for disease severity (AUC: 0.790, 95% CI: 0.762-0.818). NLR differed significantly from other markers, except LCR. LCR best predicted 28-day mortality (AUC: 0.798, 95% CI: 0.766-0.829). Some markers showed significant differences in AUC with LCR. Multivariable Cox regression identified BCDIMs, PCT, CRP and CAR as significant risk factors for 28-day mortality.

CONCLUSIONS

PCT, CRP, CAR and BCDIMs, easily obtained in clinical settings, are valuable predictors of disease severity and the 28-day mortality in COVID-19 patients. The NLR is particularly effective for disease severity, while the LCR is highly predictive of 28-day mortality. These markers provide guidance for stratified management of COVID-19 patients.

Prognostic performance of early immune and endothelial activation markers in mild-to-moderate COVID-19 outpatients: a nested case-control study

Introduction

Evidence on the association of biomarkers of host response to infection with COVID-19 clinical outcomes has focused mainly on hospitalized patients. We investigated the prognostic performance of 39 immune and endothelial activation markers measured early in the course of disease to predict the development of severe COVID-19 and hospitalization.

Methods

We conducted a nested case-control study from a randomized clinical trial evaluating the efficacy of COVID-19 convalescent plasma in outpatients aged 50 years or older presenting with mild-to-moderate COVID-19. We selected participants who were hospitalized within 28 days (cases) and who were not (controls) to compare their biomarker levels in plasma samples collected at enrolment.

Results

A total of 42 cases and 42 controls were included in this study. The levels of CRP, IL6, IP10, ferritin, IFNα, IL8, IL1RA, MCP1, and RANTES, determined within 7 days of symptoms onset, showed good individual prognostic performance for COVID-19 associated hospitalization by day 28. The biomarkers CRP, IL6, IP10, IL8, IL1RA, and suPAR showed good individual prognostic performance for severe COVID-19. CRP, IL6 and IP10 had the most robust association with both hospitalization and severe COVID-19, with CRP having the highest discriminatory capacity with hospitalization, and IL6 for severe COVID-19.

Discussion

Our study shows good prognostic performance of CRP and IL6 for 28-day hospitalization in patients with mild-to-moderate COVID-19, in the absence of clinical criteria for admission upon enrolment. These findings confirm the value of these biomarkers at early stages of COVID-19 disease in the outpatient setting to support management decisions.

Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality

BACKGROUND

There exists consistent empirical evidence in the literature pointing out ample heterogeneity in terms of the clinical evolution of patients with COVID-19. The identification of specific phenotypes underlying in the population might contribute towards a better understanding and characterization of the different courses of the disease. The aim of this study was to identify distinct clinical phenotypes among hospitalized patients with SARS-CoV-2 pneumonia using machine learning clustering, and to study their association with subsequent clinical outcomes as severity and mortality.

METHODS

Multicentric observational, prospective, longitudinal, cohort study conducted in four hospitals in Spain. We included adult patients admitted for in-hospital stay due to SARS-CoV-2 pneumonia. We collected a broad spectrum of variables to describe exhaustively each case: patient demographics, comorbidities, symptoms, physiological status, baseline examinations (blood analytics, arterial gas test), etc. For the development and internal validation of the clustering/phenotype models, the dataset was split into training and test sets (50% each). We proposed a sequence of machine learning stages: feature scaling, missing data imputation, reduction of data dimensionality via Kernel Principal Component Analysis (KPCA), and clustering with the k-means algorithm. The optimal cluster model parameters -including k, the number of phenotypes- were chosen automatically, by maximizing the average Silhouette score across the training set.

RESULTS

We enrolled 1548 patients, each of them characterized by 92 clinical attributes (d=109 features after variable encoding). Our clustering algorithm identified k=3 distinct phenotypes and 18 strongly informative variables: Phenotype A (788 cases [50.9% prevalence] - age ∼ 57, Charlson comorbidity ∼ 1, pneumonia CURB-65 score ∼ 0 to 1, respiratory rate at admission ∼ 18 min-1, FiO2 ∼ 21%, C-reactive protein CRP ∼ 49.5 mg/dL [median within cluster]); phenotype B (620 cases [40.0%] - age ∼ 75, Charlson ∼ 5, CURB-65 ∼ 1 to 2, respiration ∼ 20 min-1, FiO2 ∼ 21%, CRP ∼ 101.5 mg/dL); and phenotype C (140 cases [9.0%] - age ∼ 71, Charlson ∼ 4, CURB-65 ∼ 0 to 2, respiration ∼ 30 min-1, FiO2 ∼ 38%, CRP ∼ 152.3 mg/dL). Hypothesis testing provided solid statistical evidence supporting an interaction between phenotype and each clinical outcome: severity and mortality. By computing their corresponding odds ratios, a clear trend was found for higher frequencies of unfavourable evolution in phenotype C with respect to B, as well as more unfavourable in phenotype B than in A.

CONCLUSION

A compound unsupervised clustering technique (including a fully-automated optimization of its internal parameters) revealed the existence of three distinct groups of patients - phenotypes. In turn, these showed strong associations with the clinical severity in the progression of pneumonia, and with mortality.

Evaluating the diagnostic and prognostic ability of ischemia modified albumin in COVID-19

BACKGROUND

Patients with COVID-19 can rapidly deteriorate and develop acute hypoxic respiratory failure. Prominent features of the disease include severe inflammation, endotheliitis, and thrombosis.

OBJECTIVES

The aim of the study was to evaluate the diagnostic and prognostic effectiveness of ischemia modified albumin (ΙΜΑ) in a cohort of COVID-19 patients.

METHODS

This prospective observational study included adults with SARS-CoV-2 infection confirmed by reverse transcription polymerase chain reaction test, who were hospitalized specifically for COVID-19. The outcomes of interest were progression to severe acute respiratory failure during the index hospitalization defined as partial pressure of oxygen/fraction of inspired oxygen lower or equal to 150, admission to the intensive care unit (ICU) and in-hospital mortality. Admission IMA levels were determined using the commercially available "IMA Assay Kit" method (Abbexa LTD, Cambridge, UK). Adults without SARS-CoV-2 infection were used as controls.

RESULTS

135 COVID-19 patients and 64 controls were included. Admission IMA levels were significantly higher in COVID-19 patients compared to controls [[24.38 (11.94) ng/ml vs. 14.69 (3.52) ng/ml, p < 0.01]. Receiver operating characteristic analysis of admission IMA showed an area under the curve (AUC) of 94% (p < 0.0001) for COVID-19 diagnosis (cut-off value: 17.5 ng/ml; sensitivity: 90.37%; specificity: 87.5%). Admission IMA was also associated with mortality (AUC: 68%, p = 0.01). However, it was not associated with severe acute respiratory failure (AUC: 47%, p = 0.53) or ICU admission (AUC: 58%, p = 0.41).

CONCLUSION

Admission IMA was significantly increased in COVID-19 patients and was associated with in-hospital mortality.

Clinical and prognostic implications of hyaluronic acid in patients with COVID-19 reinfection and first infection

Objective

Previous research has shown that human identical sequences of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) promote coronavirus disease 2019 (COVID-19) progression by upregulating hyaluronic acid (HA). However, the association of HA with mortality and long COVID in SARS-CoV-2 reinfection and first infection is unclear.

Methods

Patients with COVID-19 at Beijing Ditan Hospital from September 2023 to November 2023 were consecutively enrolled. SARS-CoV-2 reinfections were matched 1:2 with first infections using a nearest neighbor propensity score matching algorithm. We compared the hospital outcomes between patients with COVID-19 reinfection and first infection. The association between HA levels and mortality and long COVID in the matched cohort was analyzed.

Results

The reinfection rate among COVID-19 hospitalized patients was 25.4% (62 cases). After propensity score matching, we found that reinfection was associated with a better clinical course and prognosis, including lower levels of C-reactive protein and erythrocyte sedimentation rate, fewer cases of bilateral lung infiltration and respiratory failure, and shorter viral clearance time and duration of symptoms (p < 0.05). HA levels were significantly higher in patients with primary infection [128.0 (90.5, 185.0) vs. 94.5 (62.0, 167.3), p = 0.008], those with prolonged viral clearance time [90.5 (61.5, 130.8) vs. 130.0 (95.0, 188.0), p < 0.001], and deceased patients [105.5 (76.8, 164.5) vs. 188.0 (118.0, 208.0), p = 0.002]. Further analysis showed that HA was an independent predictor of death (AUC: 0.789), and the risk of death increased by 4.435 times (OR = 5.435, 95% CI = 1.205-24.510, p = 0.028) in patients with high HA levels. We found that patients with HA levels above 116 ng/mL had an increased risk of death. However, the incidence of long COVID was similar in the different HA level groups (p > 0.05).

Conclusion

Serum HA may serve as a novel biomarker for predicting COVID-19 mortality in patients with SARS-CoV-2 reinfection and first infection. However, HA levels may not be associated with long COVID.

Algorithms for predicting COVID outcome using ready-to-use laboratorial and clinical data

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging crisis affecting the public health system. The clinical features of COVID-19 can range from an asymptomatic state to acute respiratory syndrome and multiple organ dysfunction. Although some hematological and biochemical parameters are altered during moderate and severe COVID-19, there is still a lack of tools to combine these parameters to predict the clinical outcome of a patient with COVID-19. Thus, this study aimed at employing hematological and biochemical parameters of patients diagnosed with COVID-19 in order to build machine learning algorithms for predicting COVID mortality or survival. Patients included in the study had a diagnosis of SARS-CoV-2 infection confirmed by RT-PCR and biochemical and hematological measurements were performed in three different time points upon hospital admission. Among the parameters evaluated, the ones that stand out the most are the important features of the T1 time point (urea, lymphocytes, glucose, basophils and age), which could be possible biomarkers for the severity of COVID-19 patients. This study shows that urea is the parameter that best classifies patient severity and rises over time, making it a crucial analyte to be used in machine learning algorithms to predict patient outcome. In this study optimal and medically interpretable machine learning algorithms for outcome prediction are presented for each time point. It was found that urea is the most paramount variable for outcome prediction over all three time points. However, the order of importance of other variables changes for each time point, demonstrating the importance of a dynamic approach for an effective patient's outcome prediction. All in all, the use of machine learning algorithms can be a defining tool for laboratory monitoring and clinical outcome prediction, which may bring benefits to public health in future pandemics with newly emerging and reemerging SARS-CoV-2 variants of concern.

Advances in research on biomarkers associated with acute myocardial infarction: A review

Acute myocardial infarction (AMI), the most severe cardiovascular event in clinical settings, imposes a significant burden with its annual increase in morbidity and mortality rates. However, it is noteworthy that mortality due to AMI in developed countries has experienced a decline, largely attributable to the advancements in medical interventions such as percutaneous coronary intervention. This trend highlights the importance of accurate diagnosis and effective treatment to preserve the myocardium at risk and improve patient outcomes. Conventional biomarkers such as myoglobin, creatine kinase isoenzymes, and troponin have been instrumental in the diagnosis of AMI. However, recent years have witnessed the emergence of new biomarkers demonstrating the potential to further enhance the accuracy of AMI diagnosis. This literature review focuses on the recent advancements in biomarker research in the context of AMI diagnosis.

How we manage a high D-dimer

D-dimer, a soluble fibrin degradation product that originates from plasmin-induced degradation of cross-linked fibrin, is an important biomarker of coagulation activation and secondary fibrinolysis that is routinely used to rule out venous thromboembolism (VTE), and to evaluate the risk of VTE recurrence, as well as the optimal duration of anticoagulant therapy. Besides VTE, D-dimer may be high due to physiologic conditions, including aging, pregnancy, and strenuous physical activity. In addition, several disorders have been associated with increased D-dimer levels, ranging from disseminated intravascular coagulation to infectious diseases and cancers. Thus, it is far from unusual for hematologists to have to deal with ambulatory individuals with increased D-dimer without signs or symptoms of thrombus formation. This narrative review is dedicated to the management of these cases by the hematologist.

Systematic review and evidence gap mapping of biomarkers associated with neurological manifestations in patients with COVID-19

OBJECTIVE

This study aimed to synthesize the existing evidence on biomarkers related to coronavirus disease 2019 (COVID-19) patients who presented neurological events.

METHODS

A systematic review of observational studies (any design) following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and the Cochrane Collaboration recommendations was performed (PROSPERO: CRD42021266995). Searches were conducted in PubMed and Scopus (updated April 2023). The methodological quality of nonrandomized studies was assessed using the Newcastle‒Ottawa Scale (NOS). An evidence gap map was built considering the reported biomarkers and NOS results.

RESULTS

Nine specific markers of glial activation and neuronal injury were mapped from 35 studies published between 2020 and 2023. A total of 2,237 adult patients were evaluated in the included studies, especially during the acute phase of COVID-19. Neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) biomarkers were the most frequently assessed (n = 27 studies, 77%, and n = 14 studies, 40%, respectively). Although these biomarkers were found to be correlated with disease severity and worse outcomes in the acute phase in several studies (p < 0.05), they were not necessarily associated with neurological events. Overall, 12 studies (34%) were judged as having low methodological quality, 9 (26%) had moderate quality, and 9 (26%) had high quality.

CONCLUSIONS

Different neurological biomarkers in neurosymptomatic COVID-19 patients were identified in observational studies. Although the evidence is still scarce and conflicting for some biomarkers, well-designed longitudinal studies should further explore the pathophysiological role of NfL, GFAP, and tau protein and their potential use for COVID-19 diagnosis and management.

[Factors of the hemostasis system as biomarkers of severe course of acute viral infections]

The authors give literature review of hemostasis and immune system factors intraction as main biomarkers of a severe cause of viral infectious diseases. Pro-inflamatory cytokines as the main markers of inflammation, can serve both as biomarkers of the clinical severity of the infectious process and reflect the state of the hemostatic and fibrinolytic systems, since components of these systems are present in various structures of the central nervous system and affect the development of neurons and synaptic plasticity. An inverse correlation has been proven between the concentration of D-dimer and the oxygenation index, and the development of DIC is not associated with the presence of respiratory failure in patients with influenza type A, while the ferritin concentration directly reflects the severity of the disease. One of the markers of endothelial damage may be soluble thrombomodulin, which, however, is rarely used in routine clinical practice. Cytoflavin is a highly effective pathogenetic drug that affects various parts of the hemostasis system, has anti-ischemic, antioxidant, antihypoxic, immunocorrective effect, which is indicated for any generalized infectious disease since its debut.

Kinetics of IL-6, C-reactive Protein and Fibrinogen Levels in COVID-19 Outpatients Who Evolved to Hypoxemia

Introduction

Despite the efficacy of the COVID-19, the search for improvements in the management of severe/critical cases continues to be important. The aim is to demonstrate the kinetics of 4 serological markers in patients with COVID-19 who evolved in hypoxemia.

Methods

From June to December 2020, the Health Secretariat of Rondônia State, Brazil, established a home medical care service team (HMCS) that provided clinical follow-up for health professionals and military personnel with COVID-19. The clinical and laboratory monitoring was individualized at home by a nursing and medical team. In addition to laboratory parameters, C-reactive protein (CRP), interleukin-6 (IL-6), fibrinogen, and D-dimer levels were periodically taken to monitor the evolution of treatment.

Results

Of 218 patients telemonitored, 48 patients needed special care by the HMCS team due to shortness of breath. Chest tomography showed multiple ground-glass shadows and lung parenchymal condensations that was compatible with secondary bacterial infection associated with leukocytosis, for which antibiotics were prescribed. The symptoms were accompanied by increases of CRP and IL-6 levels followed by fibrinogen after a few days, for which an anticoagulant therapy was included. Thirty-three patients evolved to improvements in clinical signs and laboratory results. Between the sixth and eighth day of illness, 15 patients presented signs of hypoxemia with low O2 saturation accompanied with an increase in the respiratory rate, with some of them requiring oxygen therapy. As they did not present signs of clinical severity, but their laboratory markers showed an abrupt IL-6 peak that was higher than the increase in CRP and a new alteration in fibrinogen levels, they received a supplemental dose of anticoagulant and a high dose of corticosteroids, which resulted in clinical improvement.

Conclusion

Our study demonstrates that monitoring of IL-6 and CRP may identify precocious hypoxemia in COVID-19 patients and prevented the progressive deterioration of the lung injury.

Plasma Insulin-like Growth Factor-Binding Protein-2 of Critically Ill Patients Is Related to Disease Severity and Survival

Insulin-like growth factor-binding protein (IGFBP)-2 regulates the bioactivity of the anabolic hormone's insulin-like growth factors, which are decreased in sepsis and contribute to the catabolic status of severely ill patients. The circulating levels of IGFBP-2 in critical illness have been rarely studied; therefore, we evaluated IGFBP-2 plasma levels in patients with systemic inflammatory response syndrome (SIRS) or sepsis as well as healthy controls. Our analysis of 157 SIRS/sepsis patients revealed higher plasma IGFBP-2 levels compared to 22 healthy controls. Plasma IGFBP-2 levels correlated positively with procalcitonin but not with C-reactive protein, interleukin-6, or the leukocyte count. Septic shock patients exhibited higher IGFBP-2 levels than those with SIRS. Bacterial or SARS-CoV-2 infection did not influence plasma IGFBP-2 levels. There was no difference in the IGFBP-2 levels between ventilated and non-ventilated SIRS/sepsis patients, and vasopressor therapy did not alter these levels. Dialysis patients had elevated plasma IGFBP-2 levels. Survivors had lower plasma IGFBP-2 levels than non-survivors. In conclusion, our study indicates that plasma IGFBP-2 levels are associated with disease severity, renal failure, and mortality in SIRS/sepsis patients.

Searching for New Biomarkers to Assess COVID-19 Patients: A Pilot Study

During the initial diagnosis of urgent medical conditions, which include acute infectious diseases, it is important to assess the severity of the patient's clinical state as quickly as possible. Unlike individual biochemical or physiological indicators, derived indices make it possible to better characterize a complex syndrome as a set of symptoms, and therefore quickly take a set of adequate measures. Recently, we reported on novel diagnostic indices containing butyrylcholinesterase (BChE) activity, which is decreased in COVID-19 patients. Also, in these patients, the secretion of von Willebrand factor (vWF) increases, which leads to thrombosis in the microvascular bed. The objective of this study was the determination of the concentration and activity of vWF in patients with COVID-19, and the search for new diagnostic indices. One of the main objectives was to compare the prognostic values of some individual and newly derived indices. Patients with COVID-19 were retrospectively divided into two groups: survivors (n = 77) and deceased (n = 24). According to clinical symptoms and computed tomography (CT) results, the course of disease was predominantly moderate in severity. The first blood sample (first point) was taken upon admission to the hospital, the second sample (second point)-within 4-6 days after admission. Along with the standard spectrum of biochemical indicators, BChE activity (BChEa or BChEb for acetylthiocholin or butyrylthiocholin, respectively), malondialdehyde (MDA), and vWF analysis (its antigen level, AGFW, and its activity, ActWF) were determined and new diagnostic indices were derived. The pooled sensitivity, specificity, and area under the receiver operating curve (AUC), as well as Likelihood ratio (LR) and Odds ratio (OR) were calculated. The level of vWF antigen in the deceased group was 1.5-fold higher than the level in the group of survivors. Indices that include vWF antigen levels are superior to indices using vWF activity. It was found that the index [Urea] × [AGWF] × 1000/(BChEb × [ALB]) had the best discriminatory power to predict COVID-19 mortality (AUC = 0.91 [0.83, 1.00], p < 0.0001; OR = 72.0 [7.5, 689], p = 0.0002). In addition, [Urea] × 1000/(BChEb × [ALB]) was a good predictor of mortality (AUC = 0.95 [0.89, 1.00], p < 0.0001; OR = 31.5 [3.4, 293], p = 0.0024). The index [Urea] × [AGWF] × 1000/(BChEb × [ALB]) was the best predictor of mortality associated with COVID-19 infection, followed by [Urea] × 1000/(BChEb × [ALB]). After validation in a subsequent cohort, these two indices could be recommended for diagnostic laboratories.

Mitochondrial mass of circulating NK cells as a novel biomarker in severe SARS-CoV-2 infection

BACKGROUND

Severe SARS-CoV-2 infection results in lymphopenia and impaired function of T, B, and NK (TBNK-dominant) lymphocytes. Mitochondria are essential targets of SARS-CoV-2 and the efficacy of lymphocyte mitochondrial function for immunosurveillance in COVID-19 patients has not been evaluated.

METHODS

Multi-parametric flow cytometry was used to characterize mitochondrial function, including mitochondrial mass (MM) and low mitochondrial membrane potential (MMPlow), in TBNK-dominant lymphocytes from severe (n = 93) and moderate (n = 77) hospitalized COVID-19 patients. We compared the role of novel lymphocyte mitochondrial indicators and routine infection biomarkers as early predictors of severity and death in COVID-19 patients. We then developed a mortality decision tree prediction model based on immunosurveillance indicators through machine learning.

RESULTS

At admission, the MM of circulating NK cells (NK-MM) was the best discriminator of severe/moderate disease (AUC = 0.8067) compared with the routine infection biomarkers. The NK cell count and NK-MM displayed superior diagnostic effects to distinguish patients with non-fatal or fatal outcomes. Interestingly, NK-MM was significantly polarized in non-survivors, with some patients showing a decrease and others showing an abnormal increase. Kaplan-Meier analysis showed that NK-MM had the optimal predictive efficacy (hazard ratio = 11.66). The decision tree model has the highest proportion of importance for NK-MM, which is superior to the single diagnostic effect of the above indicators (AUC = 0.8900).

CONCLUSION

NK-MM was not only associated with disease severity, its abnormal increases or decreases also predicted mortality risk. The resulting decision tree prediction model is the first to focus on immune monitoring indicators to provide decision-making clues for COVID-19 clinical management.

Blood Biomarkers as Prognostic Indicators for Neurological Injury in COVID-19 Patients: A Systematic Review and Meta-Analysis

Coronavirus disease 2019 (COVID-19) has been linked to various neurological complications. This meta-analysis assessed the relationship between glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) levels in the blood and neurological injury in COVID-19 patients. A comprehensive search of various databases was conducted until 18 August 2023, to find studies reporting GFAP and NfL blood levels in COVID-19 patients with neurological complications. GFAP and NfL levels were estimated between COVID-19 patients and healthy controls, and meta-analyses were performed using RevMan 5.4 software for analysis. In the 21 collected studies, it was found that COVID-19 patients had significantly higher levels of pooled GFAP (SMD = 0.52; 95% CI: 0.31, 0.73; p ≤ 0.001) and NfL (SMD = 0.60; 95% CI: 0.37, 0.82; p ≤ 0.001) when compared to the healthy controls. The pooled GFAP (SMD = 0.86; 95% CI: 0.26, 1.45; p ≤ 0.01) and NfL (SMD = 0.87; 95% CI: 0.48, 1.26; p ≤ 0.001) were significantly higher in non-survivors. These findings indicate a significant association between COVID-19 severity and elevated levels of GFAP and NfL, suggesting that GFAP and NfL could serve as potential diagnostic and prognostic markers for the early detection and monitoring of COVID-19-related neurological injuries.

Persistence is key: unresolved immune dysfunction is lethal in both COVID-19 and non-COVID-19 sepsis

Introduction

Severe COVID-19 and non-COVID-19 pulmonary sepsis share pathophysiological, immunological, and clinical features, suggesting that severe COVID-19 is a form of viral sepsis. Our objective was to identify shared gene expression trajectories strongly associated with eventual mortality between severe COVID-19 patients and contemporaneous non-COVID-19 sepsis patients in the intensive care unit (ICU) for potential therapeutic implications.

Methods

Whole blood was drawn from 20 COVID-19 patients and 22 non-COVID-19 adult sepsis patients at two timepoints: ICU admission and approximately a week later. RNA-Seq was performed on whole blood to identify differentially expressed genes and significantly enriched pathways. Using systems biology methods, drug candidates targeting key genes in the pathophysiology of COVID-19 and sepsis were identified.

Results

When compared to survivors, non-survivors (irrespective of COVID-19 status) had 3.6-fold more "persistent" genes (genes that stayed up/downregulated at both timepoints) (4,289 vs. 1,186 genes); these included persistently downregulated genes in T-cell signaling and persistently upregulated genes in select innate immune and metabolic pathways, indicating unresolved immune dysfunction in non-survivors, while resolution of these processes occurred in survivors. These findings of persistence were further confirmed using two publicly available datasets of COVID-19 and sepsis patients. Systems biology methods identified multiple immunomodulatory drug candidates that could target this persistent immune dysfunction, which could be repurposed for possible therapeutic use in both COVID-19 and sepsis.

Discussion

Transcriptional evidence of persistent immune dysfunction was associated with 28-day mortality in both COVID-19 and non-COVID-19 septic patients. These findings highlight the opportunity for mitigating common mechanisms of immune dysfunction with immunomodulatory therapies for both diseases.

Soluble TREM-1 plasma concentration predicts poor outcome in COVID-19 patients

BACKGROUND

The immuno-receptor Triggering Expressed on Myeloid cells-1 (TREM-1) is activated during bacterial infectious diseases, where it amplifies the inflammatory response. Small studies suggest that TREM-1 could be involved in viral infections, including COVID-19. We here aim to decipher whether plasma concentration of the soluble form of TREM-1 (sTREM-1) could predict the outcome of hospitalized COVID-19 patients.

METHODS

We conducted a multicentre prospective observational study in 3 university hospitals in France. Consecutive hospitalized patients with confirmed infection with SARS-CoV-2 were enrolled. Plasma concentration of sTREM-1 was measured on admission and then at days 4, 6, 8, 14, 21, and 28 in patients admitted into an ICU (ICU cohort: ICUC) or 3 times a week for patients hospitalized in a medical ward (Conventional Cohort: ConvC). Clinical and biological data were prospectively recorded and patients were followed-up for 90 days. For medical ward patients, the outcome was deemed complicated in case of requirement of increased oxygen supply > 5 L/min, transfer to an ICU, or death. For Intensive Care Unit (ICU) patients, complicated outcome was defined by death in the ICU.

RESULTS

Plasma concentration of sTREM-1 at inclusion was higher in ICU patients (n = 269) than in medical ward patients (n = 562) (224 pg/mL (IQR 144-320) vs 147 pg/mL (76-249), p < 0.0001), and higher in patients with a complicated outcome in both cohorts: 178 (94-300) vs 135 pg/mL (70-220), p < 0.0001 in the ward patients, and 342 (288-532) vs 206 pg/mL (134-291), p < 0.0001 in the ICU patients. Elevated sTREM-1 baseline concentration was an independent predictor of complicated outcomes (Hazard Ratio (HR) = 1.5 (1.1-2.1), p = 0.02 in ward patients; HR = 3.8 (1.8-8.0), p = 0.0003 in ICU patients). An sTREM-1 plasma concentration of 224 pg/mL had a sensitivity of 42%, and a specificity of 76% in the ConvC for complicated outcome. In the ICUC, a 287 pg/mL cutoff had a sensitivity of 78%, and a specificity of 74% for death. The sTREM-1 concentrations increased over time in the ConvC patients with a complicated outcome (p = 0.017), but not in the ICUC patients.

CONCLUSIONS

In COVID-19 patients, plasma concentration of sTREM-1 is an independent predictor of the outcome, although its positive and negative likelihood ratio are not good enough to guide clinical decision as a standalone marker.

Albumin Is a Component of the Esterase Status of Human Blood Plasma

The esterase status of blood plasma can claim to be one of the universal markers of various diseases; therefore, it deserves attention when searching for markers of the severity of COVID-19 and other infectious and non-infectious pathologies. When analyzing the esterase status of blood plasma, the esterase activity of serum albumin, which is the major protein in the blood of mammals, should not be ignored. The purpose of this study is to expand understanding of the esterase status of blood plasma and to evaluate the relationship of the esterase status, which includes information on the amount and enzymatic activity of human serum albumin (HSA), with other biochemical parameters of human blood, using the example of surviving and deceased patients with confirmed COVID-19. In experiments in vitro and in silico, the activity of human plasma and pure HSA towards various substrates was studied, and the effect of various inhibitors on this activity was tested. Then, a comparative analysis of the esterase status and a number of basic biochemical parameters of the blood plasma of healthy subjects and patients with confirmed COVID-19 was performed. Statistically significant differences have been found in esterase status and biochemical indices (including albumin levels) between healthy subjects and patients with COVID-19, as well as between surviving and deceased patients. Additional evidence has been obtained for the importance of albumin as a diagnostic marker. Of particular interest is a new index, [Urea] × [MDA] × 1000/(BChEb × [ALB]), which in the group of deceased patients was 10 times higher than in the group of survivors and 26 times higher than the value in the group of apparently healthy elderly subjects.

Extracellular Vesicle-Based SARS-CoV-2 Vaccine

Messenger ribonucleic acid (RNA) vaccines are mainly used as SARS-CoV-2 vaccines. Despite several issues concerning storage, stability, effective period, and side effects, viral vector vaccines are widely used for the prevention and treatment of various diseases. Recently, viral vector-encapsulated extracellular vesicles (EVs) have been suggested as useful tools, owing to their safety and ability to escape from neutral antibodies. Herein, we summarize the possible cellular mechanisms underlying EV-based SARS-CoV-2 vaccines.

The Role of the Plasminogen/Plasmin System in Inflammation of the Oral Cavity

The oral cavity is a unique environment that consists of teeth surrounded by periodontal tissues, oral mucosae with minor salivary glands, and terminal parts of major salivary glands that open into the oral cavity. The cavity is constantly exposed to viral and microbial pathogens. Recent studies indicate that components of the plasminogen (Plg)/plasmin (Pm) system are expressed in tissues of the oral cavity, such as the salivary gland, and contribute to microbial infection and inflammation, such as periodontitis. The Plg/Pm system fulfills two major functions: (a) the destruction of fibrin deposits in the bloodstream or damaged tissues, a process called fibrinolysis, and (b) non-fibrinolytic actions that include the proteolytic modulation of proteins. One can observe both functions during inflammation. The virus that causes the coronavirus disease 2019 (COVID-19) exploits the fibrinolytic and non-fibrinolytic functions of the Plg/Pm system in the oral cavity. During COVID-19, well-established coagulopathy with the development of microthrombi requires constant activation of the fibrinolytic function. Furthermore, viral entry is modulated by receptors such as TMPRSS2, which is necessary in the oral cavity, leading to a derailed immune response that peaks in cytokine storm syndrome. This paper outlines the significance of the Plg/Pm system for infectious and inflammatory diseases that start in the oral cavity.