B-Type Natriuretic Peptide as Biomarker of COVID-19 Disease Severity-A Meta-Analysis

Association of Abnormal Cardiac Biomarkers and Cardiovascular Complications, with Mortality in Patients with SARS-CoV-2 Infection in Latin America

BACKGROUND

The COVID-19 pandemic has highlighted a correlation between cardiac complications and elevated cardiac biomarkers, which are linked to poorer clinical outcomes.

OBJECTIVE

This study aims to determine the clinical impact of cardiac biomarkers in COVID-19 patients in Latin America.

SUBJECTS AND METHODS

The CARDIO COVID 19-20 Registry is a multicenter observational study across 44 hospitals in Latin America and the Caribbean. It included hospitalized COVID-19 patients (n = 476) who underwent troponin, natriuretic peptide, and D-dimer tests. Patients were grouped based on the number of positive biomarkers.

RESULTS

Among the 476 patients tested, 139 had one positive biomarker (Group C), 190 had two (Group B), 118 had three (Group A), and 29 had none (Group D). A directly proportional relationship was observed between the number of positive biomarkers and the incidence of decompensated heart failure. Similarly, there was a proportional relationship between the number of positive biomarkers and increased mortality. In Group B, patients with elevated troponin and natriuretic peptide and those with elevated troponin and D-dimer had 1.4 and 1.5 times higher mortality, respectively, than those with elevated natriuretic peptide and D-dimer.

CONCLUSIONS

In Latin American COVID-19 patients, a higher number of positive cardiac biomarkers is associated with increased cardiovascular complications and mortality. These findings suggest that cardiac biomarkers should be utilized to guide acute-phase treatment strategies.

Association between echocardiographic features, troponin levels, and survival time in hospitalized COVID-19 patients with cardiovascular events

Introduction

This study aims to explore the predictive roles of echocardiographic parameters and biomarkers in determining outcomes among hospitalized COVID-19 patients experiencing cardiovascular events.

Methods

A retrospective cohort study was conducted involving 49 COVID-19 patients who encountered cardiovascular events during hospitalization and underwent echocardiography. Our findings revealed notable associations between echocardiographic parameters and survival time.

Results

A decrease in left ventricular ejection fraction (LVEF) of 10% was linked to a 20% reduction in survival time (TR: 0.80, 95% CI: 0.67 - 0.96, p = .017). Similarly, an increase in left ventricular (LV) volume by 10 mL was associated with a 9% decrease in survival time (TR: 0.91, 95% CI: 0.84 - 0.98, p = .011). Moreover, an increase in left atrial (LA) volume by 10 mL corresponded to an 8% decrease in survival time (TR: 0.92, 95% CI: 0.86 - 0.99, p = .026). Additionally, each 1 cm increase in right ventricular (RV) diameter was linked to a 22% reduction in survival time (TR: 0.78, 95% CI: 0.61 - 0.99, p = .043). Furthermore, a 10 mL increase in right atrial (RA) volume was associated with a 12% decrease in survival time (TR: 0.88, 95% CI: 0.78 - 0.98, p = .017). Notably, a tenfold rise in troponin levels was linked to a 33% decrease in survival time (TR: 0.67, 95% CI: 0.48 - 0.93, p = .014).

Conclusions

Our study emphasizes the significant associations between various echocardiographic parameters and troponin levels with reduced survival time among COVID-19 patients experiencing cardiovascular events. These findings highlight the potential utility of echocardiography and troponin assessment in predicting outcomes and guiding management strategies in this patient population.

NT-proBNP ratio is a potential predictor for COVID-19 outcomes in adult Chinese patients: a retrospective study

Despite the progressive decline in the virulence of the novel coronavirus, there has been no corresponding reduction in its associated hospital mortality. Our aim was to redefine an accurate predictor of mortality risk in COVID-19 patients, enabling effective management and resource allocation. We conducted a retrospective analysis of 2917 adult Chinese patients diagnosed with COVID-19 who were admitted to our hospital during two waves of epidemics, involving the Beta and Omicron variants. Upon admission, NT-proBNP levels were measured, and we collected demographic, clinical, and laboratory data. We introduced a new concept called the NT-proBNP ratio, which measures the NT-proBNP level relative to age-specific maximum normal values. The primary outcome was all-cause in-hospital mortality. Our analysis revealed a higher in-hospital mortality rate in 2022, as shown by the Kaplan-Meier Survival Curve. To assess the predictive value of the NT-proBNP ratio, we employed the time-dependent receiver operating characteristic (ROC) curve. Notably, the NT-proBNP ratio emerged as the strongest predictor of mortality in adult Chinese hospitalized COVID-19 patients (area under the curve, AUC = 0.826; adjusted hazard ratio [HR], 3.959; 95% confidence interval [CI] 3.001-5.221; P < 0.001). This finding consistently held true for both the 2020 and 2022 subgroups. The NT-proBNP ratio demonstrates potential predictive capability compared to several established risk factors, including NT-proBNP, hsCRP, and neutrophil-to-lymphocyte ratio, when it comes to forecasting in-hospital mortality among adult Chinese patients with COVID-19.Trial registration Clinical Trial Registration: www.clinicaltrials.gov NCT05615792.

Evaluation of various blood biomarkers associated with the outcomes of patients with COVID‑19 treated in intensive care units

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the resulting coronavirus disease 2019 (COVID-19) represented a global public health crisis and the most significant pandemic in modern times. Transmission characteristics, and the lack of effective antiviral treatment protocol and protective vaccines, pushed healthcare systems, particularly intensive care units (ICUs), to their limits and led to extreme quarantine measures to control the pandemic. It was evident from an early stage that patient stratification approaches needed to be developed to better predict disease progression. In the present study, the predictive value of clinical and blood biomarkers for the outcomes of patients with COVID-19 hospitalized in the ICU were investigated, taking age and sex into consideration. The present study analyzed blood samples from 3,050 patients with COVID-19 hospitalized in the ICU. The analysis revealed that the levels of procalcitonin, N-terminal pro-B-type natriuretic peptide, D-dimer, ferritin, liver enzymes, C-reactive protein and lactate dehydrogenase were increased and were associated with disease progression, resulting in a prolonged hospitalization period and severe COVID-19 related complications. Additionally, significant age and sex disparities among these biomarkers were documented and discussed in specific cases. On the whole, the results of the present study suggest a potential association of the demographic characteristics and blood biomarkers with prolonged hospitalization in the ICU and the mortality of patients with COVID-19.

Baseline NT-proBNP levels as a predictor of short-and long-term prognosis in COVID-19 patients: a prospective observational study

BACKGROUND

Up to 20% of COVID-19 patients can suffer COVID-19-related myocardial injury. Elevated cardiac biomarkers, such as hs-cTnT and NT-proBNP, have been related to worse short-term prognosis. However, data on NT-proBNP and long-term prognosis are scarce. We have evaluated the potential association of baseline age-adjusted NT-proBNP levels and outcomes at one-year follow-up in COVID-19 patients.

METHODS

This was a single-center prospective study of 499 COVID-19 patients in whom NT-proBNP was assessed at hospital admission. NT-proBNP levels were age-adjusted and patients were classified as high or low NT-proBNP. Clinical and demographic characteristics, comorbidities, laboratory results, and in-hospital complications and mortality were compared between the two groups. Survivors of the acute phase of COVID-19 were followed up for one year from admission to detect readmissions and mortality.

RESULTS

The 68 patients with high NT-proBNP levels at hospital admission were older, with more cardiovascular risk factors, cardiovascular disease, comorbidities, myocardial injury, and higher levels of inflammatory markers than patients with low NT-proBNP levels. They also had more in-hospital complications and a higher acute-phase mortality rate (60.3% vs. 10.2%, p < 0.001). High NT-proBNP levels were an independent marker of death during hospitalization (HR 1.95; CI 1.07-3.52). At one-year follow-up, high NT-proBNP levels were independently associated with mortality (HR 2.69; CI 1.47-4.89). Among survivors of the acute phase of COVID-19, there were no differences in hospital readmissions between those with high vs. low NT-proBNP levels, but survivors with high baseline NT-proBNP levels showed a higher 1-year mortality rate (7.4% vs. 1.3%, p = 0.018).

CONCLUSIONS

High age-adjusted NT-proBNP levels at the time of hospital admission for COVID-19 are associated with poor short and long-term prognosis. High NT-proBNP seems also to be related to worse prognosis in survivors of the acute phase of COVID-19. A closer follow-up on these patients may be crucial.

Pathophysiological effects of SARS-CoV-2 infection on the cardiovascular system and its clinical manifestations-a mini review

Coronavirus disease 2019 (COVID-19) is a viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 may have a mild presentation, with few symptoms, or progress to a severe condition, characterized by generalized inflammation, systemic microvascular involvement, coagulopathy, and pulmonary and cardiovascular complications. Men present with more severe symptoms than women, especially men who are older and who present with comorbidities such as hypertension, diabetes mellitus, and a history of atherosclerotic diseases. Owing to its association with endothelial dysfunction, inflammation, thrombosis, and microvascular obstruction, SARS-CoV-2 infection can cause lesions in several organs, including the myocardium and the coronary arterial bed, which can result in clinical manifestations involving the cardiovascular system. In this mini review, we summarize the effects of SARS-CoV-2 infection on the cardiovascular system in both children and adults and characterize the various clinical manifestations associated with this disease.

Natural Course of COVID-19 and Independent Predictors of Mortality

BACKGROUND

During the SARS-CoV-2 pandemic, several biomarkers were shown to be helpful in determining the prognosis of COVID-19 patients. The aim of our study was to evaluate the prognostic value of N-terminal pro-Brain Natriuretic Peptide (NT-pro-BNP) in a cohort of patients with COVID-19.

METHODS

One-hundred and seven patients admitted to the Covid Hospital of Messina University between June 2022 and January 2023 were enrolled in our study. The demographic, clinical, biochemical, instrumental, and therapeutic parameters were recorded. The primary outcome was in-hospital mortality. A comparison between patients who recovered and were discharged and those who died during the hospitalization was performed. The independent parameters associated with in-hospital death were assessed by multivariable analysis and a stepwise regression logistic model.

RESULTS

A total of 27 events with an in-hospital mortality rate of 25.2% occurred during our study. Those who died during hospitalization were older, with lower GCS and PaO2/FiO2 ratio, elevated D-dimer values, INR, creatinine values and shorter PT (prothrombin time). They had an increased frequency of diagnosis of heart failure (p < 0.0001) and higher NT-pro-BNP values. A multivariate logistic regression analysis showed that higher NT-pro-BNP values and lower PT and PaO2/FiO2 at admission were independent predictors of mortality during hospitalization.

CONCLUSIONS

This study shows that NT-pro-BNP levels, PT, and PaO2/FiO2 ratio are independently associated with in-hospital mortality in subjects with COVID-19 pneumonia. Further longitudinal studies are warranted to confirm the results of this study.

Rapid Assessment of COVID-19 Mortality Risk with GASS Classifiers

Risk prediction models are fundamental to effectively triage incoming COVID-19 patients. However, current triaging methods often have poor predictive performance, are based on variables that are expensive to measure, and often lead to hard-to-interpret decisions. We introduce two new classification methods that can predict COVID-19 mortality risk from the automatic analysis of routine clinical variables with high accuracy and interpretability. SVM22-GASS and Clinical-GASS classifiers leverage machine learning methods and clinical expertise, respectively. Both were developed using a derivation cohort of 499 patients from the first wave of the pandemic and were validated with an independent validation cohort of 250 patients from the second pandemic phase. The Clinical-GASS classifier is a threshold-based classifier that leverages the General Assessment of SARS-CoV-2 Severity (GASS) score, a COVID-19-specific clinical score that recently showed its effectiveness in predicting the COVID-19 mortality risk. The SVM22-GASS model is a binary classifier that non-linearly processes clinical data using a Support Vector Machine (SVM). In this study, we show that SMV22-GASS was able to predict the mortality risk of the validation cohort with an AUC of 0.87 and an accuracy of 0.88, better than most scores previously developed. Similarly, the Clinical-GASS classifier predicted the mortality risk of the validation cohort with an AUC of 0.77 and an accuracy of 0.78, on par with other established and emerging machine-learning-based methods. Our results demonstrate the feasibility of accurate COVID-19 mortality risk prediction using only routine clinical variables, readily collected in the early stages of hospital admission.

Rapid Assessment of COVID-19 Mortality Risk with GASS Classifiers

Risk prediction models are fundamental to effectively triage incoming COVID-19 patients. However, current triaging methods often have poor predictive performance, are based on variables that are expensive to measure, and often lead to hard-to-interpret decisions. We introduce two new classification methods that can predict COVID-19 mortality risk from the automatic analysis of routine clinical variables with high accuracy and interpretability. SVM22-GASS and Clinical-GASS classifiers leverage machine learning methods and clinical expertise, respectively. Both were developed using a derivation cohort of 499 patients from the first wave of the pandemic and were validated with an independent validation cohort of 250 patients from the second pandemic phase. The Clinical-GASS classifier is a threshold-based classifier that leverages the General Assessment of SARS-CoV-2 Severity (GASS) score, a COVID-19-specific clinical score that recently showed its effectiveness in predicting the COVID-19 mortality risk. The SVM22-GASS model is a binary classifier that non-linearly processes clinical data using a Support Vector Machine (SVM). In this study, we show that SMV22-GASS was able to predict the mortality risk of the validation cohort with an AUC of 0.87 and an accuracy of 0.88, better than most scores previously developed. Similarly, the Clinical-GASS classifier predicted the mortality risk of the validation cohort with an AUC of 0.77 and an accuracy of 0.78, on par with other established and emerging machine-learning-based methods. Our results demonstrate the feasibility of accurate COVID-19 mortality risk prediction using only routine clinical variables, readily collected in the early stages of hospital admission.

Deep Survival Analysis With Clinical Variables for COVID-19

OBJECTIVE

Millions of people have been affected by coronavirus disease 2019 (COVID-19), which has caused millions of deaths around the world. Artificial intelligence (AI) plays an increasing role in all areas of patient care, including prognostics. This paper proposes a novel predictive model based on one dimensional convolutional neural networks (1D CNN) to use clinical variables in predicting the survival outcome of COVID-19 patients.

METHODS AND PROCEDURES

We have considered two scenarios for survival analysis, 1) uni-variate analysis using the Log-rank test and Kaplan-Meier estimator and 2) combining all clinical variables ([Formula: see text]=44) for predicting the short-term from long-term survival. We considered the random forest (RF) model as a baseline model, comparing to our proposed 1D CNN in predicting survival groups.

RESULTS

Our experiments using the univariate analysis show that nine clinical variables are significantly associated with the survival outcome with corrected p < 0.05. Our approach of 1D CNN shows a significant improvement in performance metrics compared to the RF and the state-of-the-art techniques (i.e., 1D CNN) in predicting the survival group of patients with COVID-19.

CONCLUSION

Our model has been tested using clinical variables, where the performance is found promising. The 1D CNN model could be a useful tool for detecting the risk of mortality and developing treatment plans in a timely manner.

CLINICAL IMPACT

The findings indicate that using both Heparin and Exnox for treatment is typically the most useful factor in predicting a patient's chances of survival from COVID-19. Moreover, our predictive model shows that the combination of AI and clinical data can be applied to point-of-care services through fast-learning healthcare systems.

Cardiovascular markers and COVID-19

COVID-19 is an emerging viral disease with incompletely elucidated pathogenesis, a heterogeneous clinical profile, and significant interindividual variability. The major cardiovascular complications of COVID-19 include acute cardiac injury, acute myocardial infarction (AMI), myocarditis, arrhythmia, heart failure, and venous thromboembolism (VTE)/pulmonary embolism (PE). Elevated BNP /NT-proBNP, troponin and d-dimer levels has been found in a significant proportion of patients since the first data analysis, suggesting that myocardial damage is a likely pathogenic mechanism contributing to severe disease and mortality. The level of these markers is now associated with a risk of adverse outcome, namely mortality. The aim of our study is to highlight the importance of these biomarkers for the prediction of cardiovascular complications and their potential role in the evolution of COVID-19.

The use of cardiac troponins and B-type natriuretic peptide in COVID-19

Coronavirus disease 2019 (COVID-19) is still challenging health care systems worldwide. Over time, it has become clear that respiratory disease is not the only important entity as critically ill patients are also more prone to develop complications, such as acute cardiac injury. Despite extensive research, the mainstay of treatment still relies on supportive care and targeted therapy of these complications. The development of a prognostic model which helps clinicians to diverge patients to an appropriate level of care is thus crucial. As a result, several prognostic markers have been studied in the past few months. Among them are the cardiac biomarkers, especially cardiac troponins T/I and brain natriuretic peptide, which seem to have important prognostic values as several reports have confirmed their strong association with adverse clinical outcomes and death. The use of these biomarkers as part of a prognostic tool could potentially result in more precise risk stratification of COVID-19 patients and divergence to an adequate level of care. However, several caveats persist causing international guidelines to still recommend in favour of a more conservative approach to cardiac biomarker testing for prognostic purposes.

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

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

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

Cardiac biomarkers and mortality in COVID-19 infection: A review

Lots of meta-analysis emphasize that a great number of hospitalized patients with moderate and severe forms of COVID-19 developed acute myocardial damage, defined as an increase of cardiac biomarkers, such N-terminal pro-B-type natriuretic peptide (NT-pro-BNP), creatine kinase-myocardial band (CK-MB) and of all type of troponins. The highest mortality rate is related with progressively increasing biomarkers levels and with a history of cardiovascular disease. In fact, the biomarkers dosage should be considered as a prognostic marker in all patients with COVID-19 disease at admission, during hospitalization and in the case of clinical deterioration. The purpose of this review is to evaluate cardiovascular prognostic factors in COVID-19 disease throughout the analysis of cardiac biomarkers to early identify the most serious patients and to optimize their outcomes.

Laboratory Biomarkers for Diagnosis and Prognosis in COVID-19

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) causes a wide spectrum of clinical manifestations, with progression to multiorgan failure in the most severe cases. Several biomarkers can be altered in coronavirus disease 2019 (COVID-19), and they can be associated with diagnosis, prognosis, and outcomes. The most used biomarkers in COVID-19 include several proinflammatory cytokines, neuron-specific enolase (NSE), lactate dehydrogenase (LDH), aspartate transaminase (AST), neutrophil count, neutrophils-to-lymphocytes ratio, troponins, creatine kinase (MB), myoglobin, D-dimer, brain natriuretic peptide (BNP), and its N-terminal pro-hormone (NT-proBNP). Some of these biomarkers can be readily used to predict disease severity, hospitalization, intensive care unit (ICU) admission, and mortality, while others, such as metabolomic and proteomic analysis, have not yet translated to clinical practice. This narrative review aims to identify laboratory biomarkers that have shown significant diagnostic and prognostic value for risk stratification in COVID-19 and discuss the possible clinical application of novel analytic strategies, like metabolomics and proteomics. Future research should focus on identifying a limited but essential number of laboratory biomarkers to easily predict prognosis and outcome in severe COVID-19.

Biomarkers Associated with Cardiovascular Disease in COVID-19

Coronavirus disease-19 (COVID-19) emerged late December 2019 in the city of Wuhan, China and has since spread rapidly all over the world causing a global pandemic. While the respiratory system is the primary target of disease manifestation, COVID-19 has been shown to also affect several other organs, making it a rather complex, multi-system disease. As such, cardiovascular involvement has been a topic of discussion since the beginning of the COVID-19 pandemic, primarily due to early reports of excessive myocardial injury in these patients. Treating physicians are faced with multiple challenges in the management and early triage of patients with COVID-19, as disease severity is highly variable ranging from an asymptomatic infection to critical cases rapidly deteriorating to intensive care treatment or even fatality. Laboratory biomarkers provide important prognostic information which can guide decision making in the emergency department, especially in patients with atypical presentations. Several cardiac biomarkers, most notably high-sensitive cardiac troponin (hs-cTn) and N-terminal pro-B-type natriuretic peptide (NT-proBNP), have emerged as valuable predictors of prognosis in patients with COVID-19. The purpose of this review was to offer a concise summary on prognostic cardiac biomarkers in COVID-19 and discuss whether routine measurements of these biomarkers are warranted upon hospital admission.

Heart Failure Probability and Early Outcomes of Critically Ill Patients With COVID-19: A Prospective, Multicenter Study

Background: The relationship between cardiac functions and the fatal outcome of coronavirus disease 2019 (COVID-19) is still largely underestimated. We aim to explore the role of heart failure (HF) and NT-proBNP in the prognosis of critically ill patients with COVID-19 and construct an easy-to-use predictive model using machine learning.

Methods: In this multicenter and prospective study, a total of 1,050 patients with clinical suspicion of COVID-19 were consecutively screened. Finally, 402 laboratory-confirmed critically ill patients with COVID-19 were enrolled. A “triple cut-point” strategy of NT-proBNP was applied to assess the probability of HF. The primary outcome was 30-day all-cause in-hospital death. Prognostic risk factors were analyzed using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression, further formulating a nomogram to predict mortality.

Results: Within a 30-day follow-up, 27.4% of the 402 patients died. The mortality rate of patients with HF likely was significantly higher than that of the patient with gray zone and HF unlikely (40.8% vs. 25 and 16.5%, respectively, P < 0.001). HF likely [Odds ratio (OR) 1.97, 95% CI 1.13–3.42], age (OR 1.04, 95% CI 1.02–1.06), lymphocyte (OR 0.36, 95% CI 0.19–0.68), albumin (OR 0.92, 95% CI 0.87–0.96), and total bilirubin (OR 1.02, 95% CI 1–1.04) were independently associated with the prognosis of critically ill patients with COVID-19. Moreover, a nomogram was developed by bootstrap validation, and C-index was 0.8 (95% CI 0.74–0.86).

Conclusions: This study established a novel nomogram to predict the 30-day all-cause mortality of critically ill patients with COVID-19, highlighting the predominant role of the “triple cut-point” strategy of NT-proBNP, which could assist in risk stratification and improve clinical sequelae.

The Prognostic Value of Cardiac Biomarkers and Echocardiography in Critical COVID-19

Background: Early risk stratification is crucial in critically ill COVID-19 patients. Myocardial injury is associated with worse outcome. This study aimed to evaluate cardiac biomarkers and echocardiographic findings in critically ill COVID-19 patients and to assess their association with 30-day mortality in comparison to other biomarkers, risk factors and clinical severity scores.

Methods: Prospective, single-center, cohort study in patients with PCR-confirmed, critical COVID-19. Laboratory assessment included high sensitive troponin T (hs-cTnT) and N-terminal pro-brain natriuretic peptide (NT-proBNP) on admission to ICU: a hs-cTnT ≥ 14 pg/mL and a NT-proBNP ≥ 450 pg/mL were considered as elevated. Transthoracic echocardiographic evaluation was performed within the first 48 h of ICU admission. The primary outcome was 30-day all-cause mortality. Predictive markers for mortality were assessed by ROC analysis and cut-off values by the Youden Index.

Results: A total of 100 patients were included. The median age was 63.5 years, the population was predominantly male (66%). At the time of ICU admission, 47% of patients had elevated hs-cTnT and 39% had elevated NT-proBNP. Left ventricular ejection fraction was below 50% in 19.1%. Elevated cardiac biomarkers (hs-cTnT P-value < 0.001, NT-proBNP P-value = 0.001) and impaired left ventricular function (P-value = 0.011) were significantly associated with mortality, while other biomarkers (D-dimer, ferritin, C-reactive protein) and clinical scores (SOFA) did not differ significantly between survivors and non-survivors. An optimal cut-off value to predict increased risk for 30-day all-cause mortality was 16.5 pg/mL for hs-cTnT (OR 8.5, 95% CI: 2.9, 25.0) and 415.5 pg/ml for NT-proBNP (OR 5.1, 95% CI: 1.8, 14.7).

Conclusion: Myocardial injury in COVID-19 is common. Early detection of elevated hs-cTnT and NT-proBNP are predictive for 30-day mortality in patients with critical COVID-19. These markers outperform other routinely used biomarkers, as well as clinical indices of disease severity in ICU. The additive value of routine transthoracic echocardiography is disputable and should only be considered if it is likely to impact therapeutic management.

Vasoactive Peptides: Role in COVID-19 Pathogenesis and Potential Use as Biomarkers and Therapeutic Targets

BACKGROUND

The ongoing outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as the latest threat to global health, causes overwhelming effects for the public healthcare systems worldwide. Of note, in addition to the respiratory complications, some patients with coronavirus disease 2019 (COVID-19) also develop serious cardiovascular injuries. Vasoactive peptides play an important role in a wide range of physiological and pathological conditions.

AIM

With the urgent need for exploring the specific therapeutic targets and biomarkers for the emerging COVID-19, the general aim of this review is to discuss the potentials of the vasoactive peptides including Angiotensin II (Ang II), vasoactive intestinal peptide (VIP), endothelin-1 (ET-1), calcitonin gene-related peptide (CGRP), natriuretic peptides, substance P (SP) and bradykinin (BK) as therapeutic targets and/or prognostic indicators for the COVID-19 pandemic.

CONCLUSION

Based on various observations some authors conclude that the assessment of vasoactive peptides shall be considered a routine part of COVID-19 patient monitoring, and they can serve as potential therapeutic targets for the disease management.

Risk factors, predictions, and progression of acute kidney injury in hospitalized COVID-19 patients: An observational retrospective cohort study

Objectives

Studies have shown that acute kidney injury (AKI) occurrence post SARS-CoV-2 infection is complex and has a poor prognosis. Therefore, more studies are needed to understand the rate and the predications of AKI involvement among hospitalized COVID-19 patients and AKI’s impact on prognosis while under different types of medications.

Patients and methods

This study is a retrospective observational cohort study conducted at Bahrain Defence Force (BDF) Royal Medical Services. Medical records of COVID-19 patients admitted to BDF hospital, treated, and followed up from April 2020 to October 2020 were retrieved. Data were analyzed using univariate and multivariate logistic regression with covariate adjustment, and the odds ratio (OR) and 95% confidence (95% CI) interval were reported.

Results

Among 353 patients admitted with COVID-19, 47.6% developed AKI. Overall, 51.8% of patients with AKI died compared to 2.2% of patients who did not develop AKI (p< 0.001 with OR 48.6 and 95% CI 17.2–136.9). Besides, deaths in patients classified with AKI staging were positively correlated and multivariate regression analysis revealed that moderate to severe hypoalbuminemia (<32 g/L) was independently correlated to death in AKI patients with an OR of 10.99 (CI 95% 4.1–29.3, p<0.001). In addition, 78.2% of the dead patients were on mechanical ventilation. Besides age as a predictor of AKI development, diabetes and hypertension were the major risk factors of AKI development (OR 2.04, p<0.01, and 0.05 for diabetes and hypertension, respectively). Also, two or more comorbidities substantially increased the risk of AKI development in COVID-19 patients. Furthermore, high levels upon hospital admission of D-Dimer, Troponin I, and ProBNP and low serum albumin were associated with AKI development. Lastly, patients taking ACEI/ARBs had less chance to develop AKI stage II/III with OR of 0.19–0.27 (p<0.05–0.01).

Conclusions

The incidence of AKI in hospitalized COVID-19 patients and the mortality rate among AKI patients were high and correlated with AKI staging. Furthermore, laboratory testing for serum albumin, hypercoagulability and cardiac injury markers maybe indicative for AKI development. Therefore, clinicians should be mandated to perform such tests on admission and follow-up in hospitalized patients.

Admission NT-proBNP and outcomes in patients without history of heart failure hospitalized with COVID-19

Aims

We examined the value of N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) in patients admitted for coronavirus disease 2019 (COVID‐19) without prior history of heart failure (HF) or cardiomyopathy.

Methods and results

Retrospective cohort of consecutive adults (N = 679; median age 59 years; 38.7% women; 87.5% White; 7.1% Black; 5.4% Asian; 34.3% Hispanic) admitted with documented COVID‐19 in an academic centre in Long Island, NY. Admission NT‐proBNP was categorized using the European Society of Cardiology Heart Failure Association age‐specific criteria for acute presentations. We examined (i) mortality and the composite of death or mechanical ventilation and (ii) out‐of‐hospital, intensive care unit (ICU)‐free, and ventilator‐free days at 28 days. Estimates were adjusted for confounders using a lasso selection process. Using age‐specific criteria, 417 patients (61.4%) had low, 141 (20.8%) borderline, and 121 (17.8%) high NT‐proBNP. Mortality was 5.8%, 20.6%, and 36.4% for patients with low, borderline, and high NT‐proBNP, respectively. In lasso‐adjusted models, high NT‐proBNP was associated with higher mortality [hazard ratio (HR) 2.15; 95% confidence interval (CI) 1.06–4.39; P = 0.034] and composite endpoint rates (HR 1.66; 95%CI 1.04–2.66; P = 0.035). Patients with high NT‐proBNP had 32%, 33%, and 33% fewer out‐of‐hospital, ICU‐free, and ventilator‐free days compared with low NT‐proBNP counterparts. Results were consistent across age, sex, and race, and regardless of coronary artery disease or hypertension, except for stronger mortality signal with high NT‐proBNP in women.

Conclusions

In patients with COVID‐19 and no HF history, high admission NT‐proBNP is associated with higher mortality and healthcare resources utilization. Preventive strategies may be required for these patients.

A Contemporary View of Natriuretic Peptides in the SARS-CoV-2 Era

The heart releases natriuretic peptides (NPs) which represent an important hormonal axis with cardiorenal protective effects. In view of their properties, NPs have pathophysiologic, diagnostic and prognostic implications in several cardiovascular diseases (CVDs). Severe pulmonary inflammation, as induced by the SARS-COV2, may increase pulmonary pressure with potential influence on NPs release, whereby normal cardiovascular integrity becomes impaired. Moreover, pre-existing CVDs are strong negative prognostic factors since they exacerbate the effects of the viral infection and lead to worse outcomes. In this context, it may be expected that NPs exert a key protective role toward the virus infection whereas an impairment of NPs release contributes to the virus deleterious effects. In this review article we explore the potential involvement of NPs in the COVID-19 disease. To this aim, we will first focus on the interactions between NPs and the Ang II/ATIR arm of the renin-angiotensin-aldosterone system (RAAS) as well as with the protective ACE2/Ang (1-7) arm of the RAAS. Subsequently, we will review evidence that strongly supports the role of increased NT-proBNP level as a marker of cardiac damage and of worse prognosis in the COVID-19 affected patients. Finally, we will discuss the potential therapeutic benefits of these protective hormones toward the viral infection through their endothelial protective function, anti-inflammatory and anti-thrombotic effects. In conclusion, the potential implications of NPs in the SARS-CoV-2 infection, as discussed in our article, represent an important issue that deserves to be fully investigated.

Prognostic significance of N-Terminal Pro-BNP in patients with COVID-19 pneumonia without previous history of heart failure

Introduction: The objective of the present research was to evaluate the possible association between the N-terminal pro-brain type natriuretic peptide (NT-proBNP) levels and in-hospital mortality in coronavirus disease 2019 (COVID-19) pneumonia patients who did not have pre-existing heart failure (HF). Methods: A total of 137 consecutive patients without pre-existing HF and hospitalized due to COVID-19 pneumonia were enrolled into the current research. The main outcome of the research was the in-hospital death. The independent parameters linked with the in-hospital death were determined by multivariable analysis. Results: A total of 26 deaths with an in-hospital mortality rate of 18.9% was noted. Those who died were older with an increased frequency of co-morbidities such as hypertension, chronic kidney disease, coronary artery disease, stroke and dementia. They had also increased white blood cell (WBC) counts and had elevated glucose, creatinine, troponin I, and NT-pro-BNP levels but had decreased levels of hemoglobin. By multivariable analysis; age, NT-pro-BNP, WBC, troponin I, and creatinine levels were independently linked with the in-hospital mortality. After ROC evaluation, the ideal value of the NT-pro-BNP to predict the in-hospital mortality was found as 260 ng/L reflecting a sensitivity of 82% and a specificity of 93% (AUC:0.86; 95%CI:0.76-0.97). Conclusion: The current research clearly shows that the NT-proBNP levels are independently linked with the in-hospital mortality rates in subjects with COVID-19 pneumonia and without HF. Thus, we believe that this biomarker can be used as a valuable prognostic parameter in such cases.

Meta-analysis of cardiac markers for predictive factors on severity and mortality of COVID-19

OBJECTIVES

Previous observational studies have suggested that increased cardiac markers are commonly found in COVID-19. This study aimed to determine the relationship between several cardiac markers and the severity/mortality of COVID-19 patients.

METHODS

Several cardiac markers were analysed in this meta-analysis. RevMan 5.4 was used to provide pooled estimates for standardised mean difference (SMD) with 95% confidence intervals.

RESULTS

Twenty-nine clinical studies were included in this meta-analysis. Significantly higher CK-MB (0.64, 95% CI = 0.19-1.09), PCT (0.47, 95% CI = 0.26-0.68), NT-proBNP (1.90, 95% CI = 1.63-2.17), BNP (1.86, 95% CI = 1.63-2.09), and d-dimer (1.30, 95% CI = 0.91-1.69) were found in severe compared with non-severe COVID-19. Significantly higher CK-MB (3.84, 95% CI = 0.62-7.05), PCT (1.49, 95% CI = 0.86-2.13), NT-proBNP (4.66, 95% CI = 2.42-6.91), BNP (1.96, 95% CI = 0.78-3.14), troponin (1.64 (95% CI = 0.83-2.45), and d-dimer (2.72, 95% CI = 2.14-3.29) were found in those who died from compared with survivors of COVID-19.

CONCLUSIONS

High CK-MB, PCT, NT-proBNP, BNP, and d-dimer could be predictive markers for severity of COVID-19, while high CK-MB, PCT, NT-proBNP, BNP, troponin, and d-dimer could be predictive markers for survival of COVID-19 patients.

Characterization of NT-proBNP in a large cohort of COVID-19 patients

Aims

Extensive research regarding the association of troponin and prognosis in coronavirus disease 2019 (COVID‐19) has been performed. However, data regarding natriuretic peptides are scarce. N‐terminal pro B‐type natriuretic peptide (NT‐proBNP) reflects haemodynamic stress and has proven useful for risk stratification in heart failure (HF) and other conditions such as pulmonary embolism and pneumonia. We aimed to adequately characterize NT‐proBNP concentrations using a large cohort of patients with COVID‐19, and to investigate its association with prognosis.

Methods and results

Consecutive patients with confirmed severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection and available NT‐proBNP determinations, from March 1st to April 20th, 2020 who completed at least 1‐month follow‐up or died, were studied. Of 3080 screened patients, a total of 396 (mean age 71.8 ± 14.6 years, 61.1% male) fulfilled all the selection criteria and were finally included, with a median follow‐up of 53 (18–62) days. Of those, 192 (48.5%) presented NT‐proBNP levels above the recommended cut‐off for the identification of HF. However, only 47 fulfilled the clinical criteria for the diagnosis of HF. Patients with higher NT‐proBNP during admission experienced more frequent bleeding, arrhythmias and HF decompensations. NT‐proBNP was associated with mortality both in the whole study population and after excluding patients with HF. A multivariable Cox model confirmed that NT‐proBNP was independently associated with mortality after adjusting for all relevant confounders (hazard ratio 1.28, 95% confidence interval 1.13–1.44, per logarithmic unit).

Conclusion

NT‐proBNP is frequently elevated in COVID‐19. It is strongly and independently associated with mortality after adjusting for relevant confounders, including chronic HF and acute HF. Therefore, its use may improve early prognostic stratification in this condition.