Presepsin as a Predictive Biomarker of Severity in COVID-19: A Systematic Review

Presepsin levels and COVID-19 severity: a systematic review and meta-analysis

Plasmatic presepsin (PSP) is a novel biomarker reported to be useful for sepsis diagnosis and prognosis. During the pandemic, only few studies highlighted a possible correlation between PSP and COVID-19 severity, but results remain inconsistent. The present study aims to establish the correlation between PSP and COVID-19 severity. English-language papers assessing a correlation between COVID-19 and PSP from MEDLINE, PubMed, Google Scholar, Cochrane Library, MeSH, LitCovid NLM, EMBASE, CINAHL Plus and the World Health Organization (WHO) website, published from January 2020 were considered with no publication date limitations. Two independent reviewers performed data abstraction and quality assessment, and one reviewer resolved inconsistencies. The protocol was registered on PROSPERO (CRD42022325971).Fifteen articles met our eligibility criteria. The aggregate study population included 1373 COVID-19 patients who had undergone a PSP assessment. The random-effect meta-analysis was performed in 7 out of 15 selected studies, considering only those reporting the mean PSP levels in low- and high-severity cases (n = 707).The results showed that the pooled mean difference of PSP levels between high- and low-severity COVID-19 patients was 441.70 pg/ml (95%CI: 150.40-732.99 pg/ml).Our data show that presepsin is a promising biomarker that can express COVID-19 severity.

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.

Presepsin Predicts Severity and Secondary Bacterial Infection in COVID-19 by Bioinformatics Analysis

Introduction

Novel coronavirus pneumonia (COVID-19) is an acute respiratory disease caused by the novel coronavirus SARS-CoV-2. Severe and critical illness, especially secondary bacterial infection (SBI) cases, accounts for the vast majority of COVID-19-related deaths. However, the relevant biological indicators of COVID-19 and SBI are still unclear, which significantly limits the timely diagnosis and treatment.

Methods

The differentially expressed genes (DEGs) between severe COVID-19 patients with SBI and without SBI were screened through the analysis of GSE168017 and GSE168018 datasets. By performing Gene Ontology (GO) enrichment analysis for significant DEGs, significant biological processes, cellular components, and molecular functions were selected. To understand the high-level functions and utilities of the biological system, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed. By analyzing protein-protein interaction (PPI) and key subnetworks, the core DEGs were found.

Results

85 DEGs were upregulated, and 436 DEGs were downregulated. The CD14 expression was significantly increased in the SBI group of severe COVID-19 patients (P < 0.01). The area under the curve (AUC) of CD14 in the SBI group in severe COVID-19 patients was 0.9429. The presepsin expression was significantly higher in moderate to severe COVID-19 patients (P < 0.05). Presepsin has a diagnostic value for moderate to severe COVID-19 with the AUC of 0.9732. The presepsin expression of COVID-19 patients in the nonsurvivors was significantly higher than that in the survivors (P < 0.05).

Conclusion

Presepsin predicts severity and SBI in COVID-19 and may be associated with prognosis in COVID-19.

Role of Biomarkers and Its Trend to predict the Outcome of COVID-19 Patients: A Retrospective Study

Background

Biomarkers have been extensively studied and used in the diagnosis and management of various diseases. The trend of biomarkers helps in prognosticating and managing critically ill patients. In resource-limited settings, the availability and feasibility of using these biomarkers are challenging.

Our study aimed to see the trend of biomarkers and their effect on intensive care unit (ICU) mortality in coronavirus disease-2019 (COVID-19) patients.

Materials and methods

A retrospective observational study was done from 1 April 2020 to 30 September 2020. The primary objective was to evaluate the trend of biomarkers in patients with COVID-19 pneumonia and their effect on ICU mortality. The secondary objectives were the duration of mechanical ventilation and length of ICU stay.

Results

A total of 380 patients were included. The mean age was 54.9 (SD = 11.1) and 67% were males. The mean age, acute physiology and chronic health evaluation II (APACHE II) score was 29.54 (5.8). Among the biomarkers, total count (TC), ferritin, and procalcitonin (PCT) were higher in non-survivors than in survivors in bivariate analysis. The final multivariable logistic regression model showed age, APACHE II score, length of ICU stay, neutrophil:lymphocyte (NL) ratio, and ferritin as covariates. Among these variables, ferritin was the only biomarker [odds ratio (OR): 1.80, 95% confidence interval (CI) 1.17–2.77] with the APACHE II score (OR: 1.15, 95% CI 1.01–1.30) found to be significant.

Conclusion

Ferritin was the only significant biomarker with higher values in non-survivors than in survivors. The trend of biomarkers was not found to be useful in predicting outcome of the patients.

How to cite this article

Havaldar AA, Lobo V, Sushmitha EAC, Kumar VM, Raj JM, Thomas T. Role of Biomarkers and Its Trend to Predict the Outcome of COVID-19 Patients: A Retrospective Study. Indian J Crit Care Med 2022;26(9):1031–1035.

CHARACTERIZATION OF PATIENTS IN THE POST-ACUTE PHASE OF COVID-19 WHO PRESENTED THEMSELVES TO AN EMERGENCY DEPARTMENT

BACKGROUND

Patients that recovered from COVID-19 may remain with symptoms which can persist for an uncertain period of time.

AIM

The purpose of this study was to investigate the reasons why patients who passed the acute phase of COVID-19 presented themselves to the Emergency Department.

PATIENTS AND METHODS

We selected 87 patients admitted to the Emergency Department of the Bucharest University Emergency Hospital between 01.01.2021-31.05.2021. Patients had pulmonary fibrosis (11.49%), pleural effusion (16.09%) or a history of hypertension (73.56%), type 2 diabetes (42.53%), stroke (24.14%), malignant diseases (10.34%).

RESULTS

Association between neutrophil levels and acute stroke and between fibrinogen levels and alveolar condensation were identified. The percentage of deaths was significantly higher in the subgroup of subjects that had maxim 11 days of hospitalization (p=0.004); we observed a trend of association between the age of more than 51 years old and admission in the Emergency Unit at less than a month after the SARS Cov2 infection, the positive result at the RT-PCR test or a lung damage of over 30% (p<0.05).

CONCLUSION

A significant percentage of patients that were admitted to the Emergency Unit post COVID-19 had chronic pathologies and their characteristics were associated with neutrophilia, high fibrinogen levels or length of hospitalization.