Prognostic Value of Cardiovascular Biomarkers in COVID-19: A Review

Thromboinflammation in COVID-19: Unraveling the interplay of coagulation and inflammation

The coronavirus disease 2019 (COVID-19) pandemic has not only challenged global health systems but also spurred intense scientific inquiry into its pathophysiology. Among the multifaceted aspects of the disease, coagulation abnormalities have emerged as a significant contributor to morbidity and mortality. From endothelial dysfunction to dysregulated immune responses, various factors contribute to the hypercoagulable state seen in severe COVID-19 cases. The dysregulation of coagulation in COVID-19 extends beyond traditional thromboembolic events, encompassing a spectrum of abnormalities ranging from microvascular thrombosis to disseminated intravascular coagulation (DIC). Endothelial injury induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection triggers a cascade of events involving platelet activation, coagulation factor consumption, and fibrinolysis impairment. Moreover, the virus direct effects on immune cells and the cytokine storm further exacerbate the prothrombotic milieu. Unraveling this intricate web of interactions between viral pathogenesis and host responses is essential for elucidating novel therapeutic targets and refining existing management strategies for COVID-19-associated coagulopathy. In the quest to unravel the complex interplay between coagulation and COVID-19, numerous clinical and laboratory studies have yielded invaluable insights into potential biomarkers, prognostic indicators, and therapeutic avenues. Anticoagulation therapy has emerged as a cornerstone in the management of severe COVID-19, although optimal dosing regimens and patient selection criteria remain subjects of ongoing investigation. Additionally, innovative approaches such as targeting specific components of the coagulation cascade or modulating endothelial function hold promise for future therapeutic development.

Desmoglein-2 and COVID-19 complications: insights into its role as a biomarker, pathogenesis and clinical implications

Desmoglein-2 (DSG2) has emerged as a potential biomarker for coronavirus disease 2019 (COVID-19) complications, particularly cardiac and cardiovascular involvement. The expression of DSG2 in lung tissues has been detected at elevated levels, and circulating DSG2 levels correlate with COVID-19 severity. DSG2 may contribute to myocardial injury, cardiac dysfunction and vascular endothelial dysfunction in COVID-19. Monitoring DSG2 levels could aid in risk stratification, early detection and prognostication of COVID-19 complications. However, further research is required to validate DSG2 as a biomarker. Such research will aim to elucidate its precise role in pathogenesis, establishing standardized assays for its measurement and possibly identifying therapeutic targets.

A critical review on brain and heart axis response in COVID-19 patients: Molecular mechanisms, mediators, biomarkers, and therapeutics

Since the outbreak of highly virulent coronaviruses, significant interest was assessed to the brain and heart axis (BHA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-affected patients. The majority of clinical reports accounted for unusual symptoms associated with SARS-CoV-2 infections which are of the neurological type, such as headache, nausea, dysgeusia, anosmia, and cerebral infarction. The SARS-CoV-2 enters the cells through the angiotensin-converting enzyme (ACE-2) receptor. Patients with prior cardiovascular disease (CVD) have a higher risk of COVID-19 infection and it has related to various cardiovascular (CV) complications. Infected patients with pre-existing CVDs are also particularly exposed to critical health outcomes. Overall, COVID-19 affected patients admitted to intensive care units (ICU) and exposed to stressful environmental constraints, featured with a cluster of neurological and CV complications. In this review, we summarized the main contributions in the literature on how SARS-CoV-2 could interfere with the BHA and its role in affecting multiorgan disorders. Specifically, the central nervous system involvement, mainly in relation to CV alterations in COVID-19-affected patients, is considered. This review also emphasizes the biomarkers and therapy options for COVID-19 patients presenting with CV problems.

COVID-19 and coronary artery disease; A systematic review and meta-analysis

Background and aim

Patients with underlying cardiovascular disorders such as coronary artery disease (CAD) are more prone to severe forms and multiple complications of COVID-19. The present systematic review and meta-analysis aimed to investigate the impact of CAD on patients with COVID-19.

Methods

Main electronic databases, including Medline (via PubMed), EMBASE, and Web of Science, were carefully searched and reviewed for original research articles published between 2019 and 2021. One hundred nine studies that address CAD in patients with COVID-19 were selected and analyzed.

Results

Following search and screening processes, 109 relevant publications were selected for analysis. The meta-analysis of prevalence studies indicated that the frequency of CAD among patients with COVID-19 was reported in 10 countries with an overall frequency of 12.4% [(95% CI) 11.1-13.8] among 20079 COVID-19 patients. According to case reports/case series studies, 50.9% of COVID-19 patients suffered from CAD. Fever was the most common symptom in these patients (47%); 36.5% also had hypertension.

Conclusion

The results obtained during the present study show that the simultaneous presence of COVID-19 and CAD, especially in men and elderly patients, can increase the risks and complications of both diseases. Therefore, careful examination of the condition of this group of patients for timely diagnosis and treatment is strongly recommended.

CVD22: Explainable artificial intelligence determination of the relationship of troponin to D-Dimer, mortality, and CK-MB in COVID-19 patients

BACKGROUND AND PURPOSE

COVID-19, which emerged in Wuhan (China), is one of the deadliest and fastest-spreading pandemics as of the end of 2019. According to the World Health Organization (WHO), there are more than 100 million infectious cases worldwide. Therefore, research models are crucial for managing the pandemic scenario. However, because the behavior of this epidemic is so complex and difficult to understand, an effective model must not only produce accurate predictive results but must also have a clear explanation that enables human experts to act proactively. For this reason, an innovative study has been planned to diagnose Troponin levels in the COVID-19 process with explainable white box algorithms to reach a clear explanation.

METHODS

Using the pandemic data provided by Erzurum Training and Research Hospital (decision number: 2022/13-145), an interpretable explanation of Troponin data was provided in the COVID-19 process with SHApley Additive exPlanations (SHAP) algorithms. Five machine learning (ML) algorithms were developed. Model performances were determined based on training, test accuracies, precision, F1-score, recall, and AUC (Area Under the Curve) values. Feature importance was estimated according to Shapley values by applying the SHApley Additive exPlanations (SHAP) method to the model with high accuracy. The model created with Streamlit v.3.9 was integrated into the interface with the name CVD22.

RESULTS

Among the five-machine learning (ML) models created with pandemic data, the best model was selected with the values of 1.0, 0.83, 0.86, 0.83, 0.80, and 0.91 in train and test accuracy, precision, F1-score, recall, and AUC values, respectively. As a result of feature selection and SHApley Additive exPlanations (SHAP) algorithms applied to the XGBoost model, it was determined that DDimer mean, mortality, CKMB (creatine kinase myocardial band), and Glucose were the features with the highest importance over the model estimation.

CONCLUSIONS

Recent advances in new explainable artificial intelligence (XAI) models have successfully made it possible to predict the future using large historical datasets. Therefore, throughout the ongoing pandemic, CVD22 (https://cvd22covid.streamlitapp.com/) can be used as a guide to help authorities or medical professionals make the best decisions quickly.

Biomarkers: Promising and valuable tools towards diagnosis, prognosis and treatment of Covid-19 and other diseases

The use of biomarkers as early warning systems in the evaluation of disease risk has increased markedly in the last decade. Biomarkers are indicators of typical biological processes, pathogenic processes, or pharmacological reactions to therapy. The application and identification of biomarkers in the medical and clinical fields have an enormous impact on society. In this review, we discuss the history, various definitions, classifications, characteristics, and discovery of biomarkers. Furthermore, the potential application of biomarkers in the diagnosis, prognosis, and treatment of various diseases over the last decade are reviewed. The present review aims to inspire readers to explore new avenues in biomarker research and development.

A review of cardiac troponin I detection by surface enhanced Raman spectroscopy: Under the spotlight of point-of-care testing

Cardiac troponin I (cTnI) is a biomarker widely related to acute myocardial infarction (AMI), one of the leading causes of death around the world. Point-of-care testing (POCT) of cTnI not only demands a short turnaround time for its detection but the highest accuracy levels to set expeditious and adequate clinical decisions. The analytical technique Surface-enhanced Raman spectroscopy (SERS) possesses several properties that tailor to the POCT format, such as its flexibility to couple with rapid assay platforms like microfluidics and paper-based immunoassays. Here, we analyze the strategies used for the detection of cTnI by SERS considering POCT requirements. From the detection ranges reported in the reviewed literature, we suggest the diseases other than AMI that could be diagnosed with this technique. For this, a section with information about cardiac and non-cardiac diseases with cTnI release, including their release kinetics or cut-off values are presented. Likewise, POCT features, the use of SERS as a POCT technique, and the biochemistry of cTnI are discussed. The information provided in this review allowed the identification of strengths and lacks of the available SERS-based point-of-care tests for cTnI and the disclosing of requirements for future assays design.

Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19

Background

The COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information.

Methods

Gene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD.

Results

The best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-β) signalling.

Conclusions

Gene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.

Prognostic Role of sST2 in Acute Heart Failure and COVID-19 Infection-A Narrative Review on Pathophysiology and Clinical Prospective

The importance of cardiovascular biomarkers in clinical practice increased dramatically in the last years, and the interest extends from the diagnosis purpose to prognostic applications and response to specific treatment. Acute heart failure, ischemic heart failure, and COVID-19 infection represent different clinical settings that are challenging in terms of the proper prognostic establishment. The aim of the present review is to establish the useful role of sST2, the soluble form of the interleukin-1 receptor superfamily (ST2), physiologically involved in the signaling of interleukin-33 (IL-33)-ST2 axis, in the clinical setting of acute heart failure (HF), ischemic heart disease, and SARS-CoV-2 acute infection. Molecular mechanisms associated with the IL33/ST2 signaling pathways are discussed in view of the clinical usefulness of biomarkers to early diagnosis, evaluation therapy to response, and prediction of adverse outcomes in cardiovascular diseases.

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.

Real-Time Prediction of Mortality, Cardiac Arrest, and Thromboembolic Complications in Hospitalized Patients With COVID-19

Background

COVID-19 infection carries significant morbidity and mortality. Current risk prediction for complications in COVID-19 is limited, and existing approaches fail to account for the dynamic course of the disease.

Objectives

The purpose of this study was to develop and validate the COVID-HEART predictor, a novel continuously updating risk-prediction technology to forecast adverse events in hospitalized patients with COVID-19.

Methods

Retrospective registry data from patients with severe acute respiratory syndrome coronavirus 2 infection admitted to 5 hospitals were used to train COVID-HEART to predict all-cause mortality/cardiac arrest (AM/CA) and imaging-confirmed thromboembolic events (TEs) (n = 2,550 and n = 1,854, respectively). To assess COVID-HEART's performance in the face of rapidly changing clinical treatment guidelines, an additional 1,100 and 796 patients, admitted after the completion of development data collection, were used for testing. Leave-hospital-out validation was performed.

Results

Over 20 iterations of temporally divided testing, the mean area under the receiver operating characteristic curve were 0.917 (95% confidence interval [CI]: 0.916-0.919) and 0.757 (95% CI: 0.751-0.763) for prediction of AM/CA and TE, respectively. The interquartile ranges of median early warning times were 14 to 21 hours for AM/CA and 12 to 60 hours for TE. The mean area under the receiver operating characteristic curve for the left-out hospitals were 0.956 (95% CI: 0.936-0.976) and 0.781 (95% CI: 0.642-0.919) for prediction of AM/CA and TE, respectively.

Conclusions

The continuously updating, fully interpretable COVID-HEART predictor accurately predicts AM/CA and TE within multiple time windows in hospitalized COVID-19 patients. In its current implementation, the predictor can facilitate practical, meaningful changes in patient triage and resource allocation by providing real-time risk scores for these outcomes. The potential utility of the predictor extends to COVID-19 patients after hospitalization and beyond COVID-19.

Optimal cut points of N-terminal of the prohormone brain natriuretic peptide (NT-proBNP) in patients with COVID-19

Background

COVID19 patients may suffer from multiple cardiovascular complications. Recently, N-terminal of the prohormone brain natriuretic peptide (NT-proBNP) was a potentially independent risk factor for COVID-19 in-hospital death. The present study aimed to find new optimal cut points for NT-proBNP across censored survival failure time outcomes in hospitalized COVID-19 patients.

Results

This cohort study was conducted on 272 patients with COVID-19 whose initial records were recorded from March 2020 to July 2020. Demographic characteristics, clinical examinations, and laboratory measurements were collected at the beginning of the admission registered in the patient record system located in the hospital. We used the maximally selected rank statistics to determine the optimal cut points for NT-proBNP (the most significant split based on the standardized log-rank test). Survival time was defined as the days from hospital admission to discharge day. In this cohort study, two optimal cut points for NT-proBNP were 331 (pg/mL) and 11,126 (pg/mL) based on a survival model. The adjusted HR of NT-proBNP for in-hospital death was 3.41 (95% CI: 1.22–9.51, P = 0.02) for medium against low category, and 3.84 (95% CI: 1.30–11.57, P = 0.01) for high in comparison with low group.

Conclusions

We reported a dramatically increased concentration of NT-proBNP among COVID-19 patients without heart failure in both severe and non-severe cases. Moreover, our study showed that a high level of NT-proBNP was highly associated with the prolonged survival time of patients with COVID-19. NT-proBNP is a strong prognostic indicator of in-hospital death in the second week of admission.

Cardiac biomarkers alterations in patients with SARS-CoV-2 infection

Reliable biomarkers are necessary for the risk stratification of patients infected with SARS-CoV-2. This novel coronavirus is now established to affect several organs in addition to the lungs, most prominently the heart. This is achieved through direct damage to the myocardium and indirect immune-associated effects during the cytokine storm. We performed a literature review aiming to identify the prognostic value of alterations of cardiac biomarkers in SARS-CoV-2 infection. Cardiac biomarkers are significantly elevated in patients with severe COVID-19 and are independent predictors of mortality. High-sensitivity troponin I and T are correlated with multiple inflammatory indexes and poor outcomes. Although cut-off values have been established for most of cardiac biomarkers, lower limits for troponins may have better prognostic values and longitudinal monitoring of cardiac biomarkers can help the clinician assess the patient's course. Additional measurements of NT-proBNP, can detect the subgroup of patients with poor prognosis.

Prognostic Accuracy of Cardiovascular Disease Biomarkers in Patients with COVID-19: A Diagnostic Test Accuracy Meta-Analysis

Background: Several reports have determined that cardiovascular diseases (CVDs) are common complications in patients with coronavirus disease 2019 (COVID-19) and lead them to poor outcomes. CVD biomarkers have, thus, great potential to be used as prognostic biomarkers. We aimed to determine the accuracy of CVD biomarkers for the prognosis of the COVID-19 patient’s outcome via a diagnostic test accuracy (DTA) meta-analysis.

Methods: Until September 30, 2020, we searched Web of Sciences, Scopus, and MEDLINE/PubMed databases to obtain related papers. The summary points and lines were calculated using bivariate/HSROC model. As outcomes, we considered critical conditions and mortality.

Results: A total of 17 659 patients from 33 studies were included. Five biomarkers, namely increased levels of lactate dehydrogenase (LDH), cardiac troponin I (cTnI), creatine kinase (CK), D-dimer, and thrombocytopenia, met the inclusion criteria. Our results indicated that LDH and cTnI had good accuracy for the prognosis of critical condition (AUC_HSROC=0.83 and 0.80, respectively), while LDH, cTnI, and D-dimer had acceptable accuracy (AUC_HSROC=0.74, 0.71, and 0.72, respectively) for the prognosis of mortality. LDH and D-dimer had high sensitivity, whereas cTnI had high specificity. The other biomarkers did not have acceptable accuracy. Significant publication bias was found for D-dimer (P=0.053).

Conclusion: Among CVD biomarkers, LDH and cTnI had good accuracy for the prognosis of critical outcomes and acceptable accuracy for the prognosis of mortality, without publication bias. Given their different sensitivities and specificities, we recommend the use of these 2 biomarkers concomitantly.

Plant bioactive compounds affecting biomarkers and final outcome of COVID-19

Herbal medicinal products are known for their widespread use toward various viral infections and ease of disease symptoms. Therefore, the sudden appearance of the Severe Acute Respiratory Syndrome-related Coronavirus 2 (SARS-CoV-2) and COVID-19 disease was no exception. Bioactive compounds from natural plant origin could act on several disease levels: through essential immunological pathways, affecting COVID-19 biomarkers, or by halting or modulating SARS-CoV-2. In this paper, we review the recently published data regarding the use of plant bioactive compounds in the prevention/treatment of COVID-19. The mode of actions responsible for these effects is discussed, including the inhibition of attachment, penetration and release of the virus, actions affecting RNA, protein synthesis and viral proteases, as well as other mechanisms. The reviewed information suggests that plant bioactive compounds can be used alone or in combinations, but upcoming, extensive and global studies on several factors involved are needed to recognize indicative characteristics and various patterns of bioactive compounds use, related with an array of biomarkers connected to different elements of inflammatory and immune-related processes of COVID-19 disease.

Analyzing Correlation of Clinical Severity of COVID-19 with Other Biochemical Parameters: A Retrospective Study from Pakistan

The third wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing damage all over the world, especially in Pakistan and India. Although vaccines are available and preventive measures are being taken, but SARS-CoV-2 is unstoppable. Currently, there are around 841,636 positive cases in Pakistan and 18,429 deaths, whereas, in India, both are high. From April 8th to 12th, 2021, nasopharyngeal swabs of 190 patients were submitted to PRL (PACP) lab for the SARS-CoV-2 testing, and blood samples were collected at the Mayo Hospital lab for ferritin, D-dimers, lactate dehydrogenase (LDH), and C-reactive protein (CRP) testing. This study observed that coronavirus disease 2019 (COVID-19) was more likely in individuals aged 51-60 than 61-70. In addition, our study found that COVID-19 patients exhibited a statistically significant increase in levels of ferritin, D-dimers, LDH, and CRP. In addition, this study found that COVID-19 patients had significantly higher levels of ferritin, D-dimers, LDH, and CRP. Our study revealed that SARS-CoV-2 relapsed. Furthermore, we concluded that these biochemical parameters are useful indicators for severity of COVID-19.

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.

COVID-19 and RAAS inhibitors: is there a final conclusion?

Coronavirus disease 2019 (COVID-19), the first pandemic caused by a human infecting coronavirus, has drawn global attention from the first time it appeared in Wuhan city of China in late December 2019. Detection of the responsible viral pathogen, named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by WHO, and its possible pathogenesis lead to the forming of many hypotheses about the factors that may affect the patients' outcome. One of the SARS-CoV-2 infection concerns was the potential role of angiotensin-converting enzyme (ACE) inhibitors and angiotensin-receptor blockers (ARBs) in COVID-19 patients' morbidity and mortality. Studies demonstrated that because SARS-CoV-2 uses human ACE2 cell receptors as an entry receptor to invade the cells, there might be an association between antihypertensive drugs such as RAAS inhibitors (specifically ACEIs and ARBs) and the COVID-19 disease. Data are scarce and conflicting regarding ACEI or ARB consumption and how it influences disease outcomes, and a single conclusion has not been reached yet. According to the literature review in our article, the most evidentially supported theory about the use of RAAS inhibitors in COVID-19 is that these medications, including ACEI/ARB, are not associated with the increased risk of infection, disease severity, and patient prognosis. However, further studies are needed to support the hypothesis.

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.

Laboratory parameters related to severe disease and death in SARS-CoV-2 pneumonia: Retrospective analysis

The clinical evolution of coronavirus disease 2019 (COVID-19) is highly variable and hospitalized patients can rapidly develop conditions requiring oxygen support, intensive care unit (ICU) or high dependency unit (HDU) care. Early identification of high-risk patients is mandatory. We retrospectively collected the medical history, symptoms, radiological, and laboratory findings of COVID-19 patients hospitalized between February and April 2020. Laboratory data were collected at the first, last, and middle times of hospitalization. We used arterial oxygen partial pressure and fractional inspired oxygen ratio (P/F) to evaluate respiratory status. Outcomes considered were death and ICU/HDU admission. We used the χ2 or Fisher's exact test to examine differences between categorical variables. Continuous variables were analyzed using the Wilcoxon matched pairs signed-ranks test and Mann-Whitney test sample test. Of 71 patients admitted, 92% had interstitial pneumonia, and 17% an unfavorable outcome. Negative predictors were age, cerebrovascular disease, obesity, and chronic obstructive pulmonary disease. Baseline P/F was strongly associated with all outcomes. Markers linked to immunological dysregulation like elevated neutrophil-to-lymphocyte ratio exhibited prognostic significance over time. A validated prognostic score comprehensive of all these conditions for early staging and management of COVID-19 patients is urgently needed. Further studies are desirable to evaluate whether laboratory tests can target early treatment in high-risk patients.

A simple prognostic score based on troponin and presepsin for COVID-19 patients admitted to the emergency department: a single-center pilot study

BACKGROUND

The need to determine prognostic factors that can predict a particularly severe or, conversely, the benign course of COVID-19 is particularly perceived in the Emergency Department (ED), considering the scarcity of resources for a conspicuous mass of patients. The aim of our study was to identify some predictors for 30-day mortality among some clinical, laboratory, and ultrasound variables in a COVID-19 patients population.

METHODS

Prospective single-center pilot study conducted in an ED of a University Hospital. A consecutive sample of confirmed COVID-19 patients with acute respiratory failure was enrolled from March 8th to April 15th, 2020.

RESULTS

143 patients were enrolled. Deceased patients (n = 65) were older (81 vs. 61 years, p <0.001), and they had more frequently a history of heart disease, neurological disease, or chronic obstructive pulmonary disease (p-values = 0.026, 0.025, and 0.034, respectively) than survived patients. Troponin I and presepsin had a significant correlation with a worse outcome. Troponin achieved a sensitivity of 77% and a specificity of 82% for a cut-off value of 27.6 ng/L. The presepsin achieved a sensitivity of 54% and a specificity of 92% for a cut-off value of 871 pg/mL.

CONCLUSION

In a population of COVID-19 patients with acute respiratory failure in an ED, presepsin and troponin I are accurate predictors of 30-day mortality. Presepsin is highly specific and could permit the early identification of patients who could benefit from more intensive care as soon as they enter the ED. Further validation studies are needed to confirm this result.

Cardiac biomarkers and COVID-19: A systematic review and meta-analysis

OBJECTIVE

To systematically investigate the relationship between cardiac biomarkers and COVID-19 severity and mortality.

METHODS

We performed a literature search using PubMed, Web of Science, and Google Scholar. The standardized mean difference (SMD) and 95% confidence interval (CI) were applied to estimate the combined results of 67 studies. A meta-analysis of cardiac biomarkers was used to evaluate disease mortality and severity in COVID-19 patients.

RESULTS

A meta-analysis of 7812 patients revealed that patients with high levels of cardiac troponin I (SMD = 0.81 U/L, 95% CI = 0.14-1.48, P = 0.017), cardiac troponin T (SMD = 0.78 U/L, 95% CI = 0.07-1.49, P = 0.032), high-sensitive cardiac troponin I (SMD = 0.66 pg/mL, 95% CI = 0.51-0.81, P < 0.001), high-sensitive cardiac troponin T (SMD = 0.93 U/L, 95% CI = 0.21-1.65, P = 0.012), creatine kinase-MB (SMD = 0.54 U/L, 95% CI = 0.39-0.69, P < 0.001), and myoglobin (SMD = 0.80 U/L, 95% CI = 0.57-1.03, P < 0.001) were associated with prominent disease severity in COVID-19 infection. Moreover, 9532 patients with a higher serum level of cardiac troponin I (SMD = 0.51 U/L, 95% CI = 0.37-0.64, P < 0.001), high-sensitive cardiac troponin (SMD = 0.51 ng/L, 95% CI = 0.29-0.73, P < 0.001), high-sensitive cardiac troponin I (SMD = 0.51 pg/mL, 95% CI = 0.38-0.63, P < 0.001), high-sensitive cardiac troponin T (SMD = 0.85 U/L, 95% CI = 0.63-1.07, P < 0.001), creatine kinase-MB (SMD = 0.48 U/L, 95% CI = 0.32-0.65, P < 0.001), and myoglobin (SMD = 0.55 U/L, 95% CI = 0.45-0.65, P < 0.001) exhibited a prominent level of mortality from COVID-19 infection.

CONCLUSION

Cardiac biomarkers (cardiac troponin I, cardiac troponin T, high-sensitive cardiac troponin, high-sensitive cardiac troponin I, high-sensitive cardiac troponin T, creatine kinase-MB, and myoglobin) should be more frequently applied in identifying high-risk COVID-19 patients so that timely treatment can be implemented to reduce severity and mortality in COVID-19 patients.

Laboratory analysis of symptomatic and asymptomatic pregnant patients with SARS-CoV-2 infection

BACKGROUND

Inflammatory biomarkers have been used to portend disease severity in nonpregnant individuals with SARS-CoV-2 infection. However, currently, limited data are available, and with mixed results, to elucidate which inflammatory biomarkers may be most associated with clinical phenotype in pregnant patients.

OBJECTIVE

We aimed to compare laboratory findings among pregnant patients with SARS-CoV-2 infection by symptom status and disease severity.

STUDY DESIGN

We retrospectively evaluated pregnant patients with positive SARS-CoV-2 infection, confirmed through polymerase chain reaction testing, at an urban academic US hospital between March 2020 and October 2020, performed for reported symptoms or universal screening on admission. In our hospital, all patients with SARS-CoV-2 infection were recommended to have baseline laboratory testing, including leukocyte, neutrophil, and lymphocyte counts; aspartate aminotransferase and alanine aminotransferase; high-sensitivity C-reactive protein; procalcitonin; lactate dehydrogenase; D-dimer; and ferritin. We performed multivariable logistic regression to evaluate peak laboratory abnormalities significantly associated with symptomatic SARS-CoV-2 infection and disease severity with gestational age at diagnosis, maternal age, and obesity as covariates. The sensitivity and specificity of laboratory abnormalities were calculated to identify symptomatic vs asymptomatic infection and severe to critical disease vs mild to moderate disease.

RESULTS

We identified 175 pregnant patients with SARS-CoV-2 infection, of whom 100 (57%) were symptomatic; 17 (17%) of those who were symptomatic had a severe to critical disease. Laboratory data were available for 128 patients, of whom 67 (52%) were symptomatic. Compared with asymptomatic individuals, symptomatic individuals were more likely to exhibit elevated high-sensitivity C-reactive protein levels after adjusting for gestational age (adjusted odds ratio, 5.67; 95% confidence interval, 1.42–22.52; sensitivity, 81%; specificity, 43%). In symptomatic individuals, transaminitis (adjusted odds ratio, 5.67; 95% confidence interval, 1.27–25.43), elevated procalcitonin levels (adjusted odds ratio, 16.60; 95% confidence interval, 2.61–105.46), and elevated lactate dehydrogenase levels (adjusted odds ratio, 17.55; 95% confidence interval, 2.51–122.78) were independently associated with severe to critical disease rather than mild to moderate disease after adjusting for maternal age and obesity. For differentiating disease severity, sensitivity rates for transaminitis, procalcitonin elevation, and lactate dehydrogenase elevation were 47%, 87%, and 53%, respectively, whereas the specificity rates were 89%, 63%, and 90%, respectively.

CONCLUSION

Inflammatory biomarkers in pregnant patients with SARS-CoV-2 infection exhibited vast heterogeneity, poor discriminative ability, and thereby limited clinical utility. Larger registry studies should evaluate which inflammatory biomarkers may be most useful for risk stratification and prognostication of pregnant patients with SARS-CoV-2 infection, taking into account the physiology of pregnancy.

Cardiovascular Risk Assessment in COVID-19

COVID-19 bezeichnet eine der schlimmsten Krisen unserer Generation und stellt (nicht nur) für das Gesundheitssystem eine schwer bewältigbare Herausforderung dar. Mortalität und Morbidität sind im Vergleich zu anderen saisonalen Erkrankungen wie der Influenza deutlich erhöht. COVID-19 bedroht allerdings nicht die gesamte Bevölkerung in gleichem Maße. Hochrisikopatienten sind älter und leiden an kardiovaskulären Erkrankungen wie Bluthochdruck, Diabetes mellitus oder einer koronaren Herzerkrankung. Um das Risiko für einen schweren Erkrankungsverlaufs zu quantifizieren bedarf es einer multimodalen Herangehensweise. Verschiedene Risikostratifizierungssysteme stehen zu Verfügung um ungünstige Verläufe wie Intensivbehandlung oder Gesamtmortalität vorauszusagen. Biomarker wie Troponin-I, D-Dimere und NT pro-BNP kombiniert mit echokardiographischen Parametern wie links- und rechtsventrikulärer Pumpfunktion sowie pulmonalarteriellem Druck können hilfreich sein um Hochrisikopatienten zu identifizieren, die ein intensiviertes Monitoring und eine stringentere Behandlung benötigen. Da kardiovaskuläre Risikofaktoren und Komorbiditäten von großer Bedeutung zur Abschätzung des Verlaufs einer SARS-CoV-2 Infektion sind, könnten alle hospitalisierten COVID-19 Patienten von einer routinemäßigen kardiologischen Betreuung durch ein COVID-19-Heart-Team profitieren. Ein frühzeitiges Erkennen von (kardiovaskulären) Hochrisikopatienten könnte das Management erleichtern sowie die Prognose einer schweren SARS-CoV-2 Infektion verbessern.

Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection

To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a new diagnosis platform using a deep convolutional neural network (DCNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 pneumonia from non-COVID-19 pneumonia in patients based on chest X-ray classification and analysis. Such a tool can save time in interpreting chest X-rays and increase the accuracy and thereby enhance our medical capacity for the detection and diagnosis of COVID-19. The explainable method is also used in the DCNN to select instances of the X-ray dataset images to explain the behavior of training-learning models to achieve higher prediction accuracy. The average accuracy of our method is above 96%, which can replace manual reading and has the potential to be applied to large-scale rapid screening of COVID-9 for widely use cases.

Biomarkers for Prognosis and Treatment Response in COVID-19 Patients

During a severe infection such as coronavirus disease 2019 (COVID-19), the level of almost all analytes can change, presenting a correlation with disease severity and survival; however, a biomarker cannot be translated into clinical practice for treatment guidance until it is proven to have a significant impact. Several studies have documented the association between COVID-19 severity and circulating levels of C-reactive protein (CRP) and interleukin-6, and the accuracy of the CRP level in predicting treatment responses has been evaluated. Moreover, promising findings on prothrombin and D-dimer have been reported. However, the clinical usefulness of these biomarkers in COVID-19 is far from proven. The burst of data generation during this pandemic has led to the publication of numerous studies with several notable drawbacks, weakening the strength of their findings. We provide an overview of the key findings of studies on biomarkers for the prognosis and treatment response in COVID-19 patients. We also highlight the main drawbacks of these studies that have limited the clinical use of these biomarkers.

OMICS approaches in cardiovascular diseases: a mini review

Ranked in the topmost position among the deadliest diseases in the world, cardiovascular diseases (CVDs) are a global burden with alterations in heart and blood vessels. Early diagnostics and prognostics could be the best possible solution in CVD management. OMICS (genomics, proteomics, transcriptomics, and metabolomics) approaches could be able to tackle the challenges against CVDs. Genome-wide association studies along with next-generation sequencing with various computational biology tools could lead a new sight in early detection and possible therapeutics of CVDs. Human cardiac proteins are also characterized by mass spectrophotometry which could open the scope of proteomics approaches in CVD. Besides this, regulation of gene expression by transcriptomics approaches exhibits a new insight while metabolomics is the endpoint on the downstream of multi-omics approaches to confront CVDs from the early onset. Although a lot of challenges needed to overcome in CVD management, OMICS approaches are certainly a new prospect.

Prognostic Value of Bioactive Adrenomedullin in Critically Ill Patients with COVID-19 in Germany: An Observational Cohort Study

The coronavirus disease 2019 (COVID-19) pandemic has placed a significant burden on hospitals worldwide. Objective biomarkers for early risk stratification and clinical management are still lacking. The aim of this work was to determine whether bioactive adrenomedullin can assist in the risk stratification and clinical management of critically ill COVID-19 patients. Fifty-three patients with confirmed COVID-19 were included in this prospective observational cohort study between March and April 2020. Bioactive adrenomedullin (bio-ADM) plasma concentration was measured daily for seven days after admission. The prognostic value and clinical significance of bio-ADM plasma levels were evaluated for the severity of respiratory failure, the need for extracorporeal organ support and outcome (28-day mortality). Bio-ADM levels increased with the severity of acute respiratory distress syndrome (ARDS; p < 0.001) and were significantly elevated in invasively ventilated patients (p = 0.006) and patients in need of extracorporeal membrane oxygenation (p = 0.040) or renal replacement therapy (RRT; p < 0.001) compared to patients without these conditions. Non-survivors showed significantly higher bio-ADM levels than survivors (p = 0.010). Bio-ADM levels predicted 28-day mortality (C-index 0.72, 95% confidence interval 0.56–0.87, p < 0.001). Bio-ADM plasma levels correlate with disease severity, the need for extracorporeal organ assistance, and outcome, and highlight the promising value of bio-ADM in the early risk stratification and management of patients with COVID-19.

New-onset myocardial injury in pregnant patients with coronavirus disease 2019: a case series of 15 patients

Background

Severe acute respiratory syndrome coronavirus 2 is the new coronavirus responsible for the coronavirus disease 2019 pandemic, characterized by acute respiratory distress syndrome and atypical pneumonia. In nonpregnant women, studies have shown that severe acute respiratory syndrome coronavirus 2 causes cardiac injury, which can result in myocardial inflammation and damage. Despite many studies investigating the extent of cardiac compromise in patients with severe coronavirus disease 2019, little is known regarding its impact on pregnant women.

Objective

This study aimed to illustrate the clinical, laboratory, radiologic findings and outcomes of pregnant patients with coronavirus disease 2019 who developed myocardial injury with ventricular dysfunction.

Study Design

We retrospectively reviewed the paper records of 15 pregnant women with coronavirus disease 2019, who developed myocardial injury on a single tertiary care hospital in the Dominican Republic. Patients’ baseline characteristics, clinical picture, and laboratory and radiologic findings were presented, and maternal and fetal outcomes were analyzed.

Results

Of 154 pregnant patients diagnosed as having coronavirus disease 2019 at our hospital during the study period, 15 (9.7%), developed myocardial injury. These patients’ mean age and gestational age were 29.87±5.83 and 32.31±3.68, respectively. Furthermore, 66.7% of patients presented with shortness of breath and 16.3% with palpitations. All patients were admitted to the intensive care unit, and 86.6% needed intubation. Patients developed myocardial injury, confirmed with highly elevated troponin (34.6 [14.4–55.5 ng/mL]), and pro–B-type natriuretic peptide concentrations (209 [184–246 pg/mL]). In addition, all patients developed left ventricular dysfunction demonstrated by an echocardiogram with a mean left ventricular ejection fraction of 37.67±6.4. Unfortunately, 2 patients who presented with palpitations died a few days after admission.

Conclusion

Our study showed coronavirus disease 2019 induced myocardial injury and left ventricular dysfunction in pregnant women with a 13.3% mortality rate, which was attributed to malignant arrhythmias.

The Novel Perspectives Opened by ST2 in the Pandemic: A Review of Its Role in the Diagnosis and Prognosis of Patients with Heart Failure and COVID-19

The increasing incidence of coronavirus disease 19 (COVID-19) and its polymorphic clinical manifestations due to local and systemic inflammation represent a high burden for many public health systems. Multiple evidence revealed the interdependence between the presence of cardiovascular comorbidities and a severe course of COVID-19, with heart failure (HF) being incriminated as an independent predictor of mortality. Suppression of tumorigenicity-2 ST2 has emerged as one of the most promising biomarkers in assessing the evolution and prognosis of patients with HF. The uniqueness of ST2 is determined by its structural particularities. Its transmembrane isoform exerts cardioprotective effects, while the soluble isoform (sST2), which is detectable in serum, is associated with myocardial fibrosis and poor outcome in patients with HF. Some recent data also suggested the potential role of sST2 as a marker of inflammation, while other studies highlighted it as a valuable prognostic factor in patients with COVID-19. In this review, we summarized the pathways by which sST2 is related to myocardial injury and its connection to the severity of inflammation in patients with COVID-19. Also, we reviewed possible perspectives of using it as a dual cardio-inflammatory biomarker, for both early diagnosis, risk stratification and prognosis assessment of patients with concomitant HF and COVID-19.

Biomarkers and short-term prognosis in COVID-19

Purpose

The aim of our study was to analyse the short-term prognostic value of different biomarkers in patients with COVID-19.

Methods

We included patients admitted to emergency department with COVID-19 and available concentrations of cardiac troponin I (cTnI), D-dimer, C-reactive protein (CRP) and lactate dehydrogenase (LDH). Patients were classified for each biomarker into two groups (low vs. high concentrations) according to their best cut-off point, and 30-day all-cause death was evaluated.

Results

After multivariate adjustment, cTnI ≥21 ng/L, D-dimer ≥1112 ng/mL, CRP ≥10 mg/dL and LDH ≥334 U/L at admission were associated with an increased risk of 30-day all-cause death (hazard ratio (HR) 4.30; 95% CI 1.74–10.58; p = 0.002; HR 3.35; 95% CI 1.58–7.13; p = 0.002; HR 2.25; 95% CI 1.13–4.50; p = 0.021; HR 2.00; 95% CI 1.04–3.84; p = 0.039, respectively). The area under the curve for cTnI was 0.825 (95% CI 0.759–0.892) and, in comparison, was significantly better than CRP (0.685; 95% CI 0.600–0.770; p = 0.009) and LDH (0.643; 95% CI 0.534–0.753; p = 0.006) but non-significantly better than D-dimer (0.756; 95% CI 0.674–0.837; p = 0.115).

Conclusions

In patients with COVID-19, increased concentrations of cTnI, D-dimer, CRP and LDH are associated with short-term mortality. Of these, cTnI provides better mortality risk prediction. However, differences with D-dimer were non-significant.

SARS-CoV-2 Infection and Oral Health: Therapeutic Opportunities and Challenges

The novel corona virus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), and the disease it causes, COVID-19 (Coronavirus Disease-2019) have had multi-faceted effects on a number of lives on a global scale both directly and indirectly. A growing body of evidence suggest that COVID-19 patients experience several oral health problems such as dry mouth, mucosal blistering, mouth rash, lip necrosis, and loss of taste and smell. Periodontal disease (PD), a severe inflammatory gum disease, may worsen the symptoms associated with COVID-19. Routine dental and periodontal treatment may help decrease the symptoms of COVID-19. PD is more prevalent among patients experiencing metabolic diseases such as obesity, diabetes mellitus and cardiovascular risk. Studies have shown that these patients are highly susceptible for SARS-CoV-2 infection. Pro-inflammatory cytokines and oxidative stress known to contribute to the development of PD and other metabolic diseases are highly elevated among COVID-19 patients. Periodontal health may help to determine the severity of COVID-19 infection. Accumulating evidence shows that African-Americans (AAs) and vulnerable populations are disproportionately susceptible to PD, metabolic diseases and COVID-19 compared to other ethnicities in the United States. Dentistry and dental healthcare professionals are particularly susceptible to this virus due to the transferability via the oral cavity and the use of aerosol creating instruments that are ubiquitous in this field. In this review, we attempt to provide a comprehensive and updated source of information about SARS-CoV-2/COVID-19 and the various effects it has had on the dental profession and patients visits to dental clinics. Finally, this review is a valuable resource for the management of oral hygiene and reduction of the severity of infection.

Nomogram prediction of severe risk in patients with COVID-19 pneumonia

Coronavirus disease-2019 (COVID-19) elicits a range of different responses in patients and can manifest into mild to very severe cases in different individuals, depending on many factors. We aimed to establish a prediction model of severe risk in COVID-19 patients, to help clinicians achieve early prevention, intervention and aid them in choosing effective therapeutic strategy. We selected confirmed COVID-19 patients who were admitted to First Hospital of Changsha city between 29 January and 15 February 2020 and collected their clinical data. Multivariate logical regression was used to identify the factors associated with severe risk. These factors were incorporated into the nomogram to establish the model. The ROC curve, calibration plot and decision curve were used to assess the performance of the model. A total of 228 patients were enrolled and 33 (14.47%) patients developed severe pneumonia. Univariate and multivariate analysis showed that shortness of breath, fatigue, creatine kinase, lymphocytes and h CRP were independent factors for severe risk in COVID-19 patients. Incorporating age, chronic obstructive pulmonary disease (COPD) and these factors, the nomogram achieved good concordance indexes of 0.89 [95% confidence interval (CI) 0.832–0.949] and well-fitted calibration plot curves (Hosmer–Lemeshow test: P = 0.97). The model provided superior net benefit when clinical decision thresholds were between 15% and 85% predicted risk. Using the model, clinicians can intervene early, improve therapeutic effects and reduce the severity of COVID-19, thus ensuring more targeted and efficient use of medical resources.

Blood Biomarkers for Detection of Brain Injury in COVID-19 Patients

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus attacks multiple organs of coronavirus disease 2019 (COVID-19) patients, including the brain. There are worldwide descriptions of neurological deficits in COVID-19 patients. Central nervous system (CNS) symptoms can be present early in the course of the disease. As many as 55% of hospitalized COVID-19 patients have been reported to have neurological disturbances three months after infection by SARS-CoV-2. The mutability of the SARS-COV-2 virus and its potential to directly affect the CNS highlight the urgency of developing technology to diagnose, manage, and treat brain injury in COVID-19 patients. The pathobiology of CNS infection by SARS-CoV-2 and the associated neurological sequelae of this infection remain poorly understood. In this review, we outline the rationale for the use of blood biomarkers (BBs) for diagnosis of brain injury in COVID-19 patients, the research needed to incorporate their use into clinical practice, and the improvements in patient management and outcomes that can result. BBs of brain injury could potentially provide tools for detection of brain injury in COVID-19 patients. Elevations of BBs have been reported in cerebrospinal fluid (CSF) and blood of COVID-19 patients. BB proteins have been analyzed in CSF to detect CNS involvement in patients with infectious diseases, including human immunodeficiency virus and tuberculous meningitis. BBs are approved by the U.S. Food and Drug Administration for diagnosis of mild versus moderate traumatic brain injury and have identified brain injury after stroke, cardiac arrest, hypoxia, and epilepsy. BBs, integrated with other diagnostic tools, could enhance understanding of viral mechanisms of brain injury, predict severity of neurological deficits, guide triage of patients and assignment to appropriate medical pathways, and assess efficacy of therapeutic interventions in COVID-19 patients.

Will Remdesivir Reshape Cardiovascular Practice in COVID 19 Era?

Infection with the novel coronavirus, SARS-CoV2, produces the clinical syndrome COVID-19. COVID-19 is a systemic illness inducing hyperinflammation and cytokine storm affecting multiple organs including the myocardium which is reflected in elevated cardiac biomarkers such as troponin, lactate dehydrogenase, and creatinine kinase MB. Furthermore, COVID-19 has been implicated in increased predilection to thromboembolic phenomena. Hence, mortality in patients with associated cardiovascular disease has been higher compared with the cohort with no cardiovascular comorbidity. It is entirely unknown how remdesivir will change the facet of cardiovascular medicine and surgery. In the present constantly changing climate, this review of remdesivir and its association with cardiovascular disease is comprehensive as of June 17, 2020 and it highlights the science behind this drug and its potential implications to cardiovascular practice.

Prospective role of thyroid disorders in monitoring COVID-19 pandemic

COVID-19 pandemic has affected more than 200 countries and 1.3 million individuals have deceased within eleven months. Intense research on COVID-19 occurrence and prevalence enable us to understand that comorbidities play a crucial role in spread and severity of SARS-CoV-2 infection. Chronic kidney disease, diabetes, respiratory diseases and hypertension are among the various morbidities that are prevalent in symptomatic COVID-19 patients. However, the effect of altered thyroid-driven disorders cannot be ignored. Since thyroid hormone critically coordinate and regulate the major metabolism and biochemical pathways, this review is on the potential role of prevailing thyroid disorders in SARS-CoV-2 infection. Direct link of thyroid hormone with several disorders such as diabetes, vitamin D deficiency, obesity, kidney and liver disorders etc. suggests that the prevailing thyroid conditions may affect SARS-CoV-2 infection. Further, we discuss the oxidative stress-induced aging is associated with the degree of SARS-CoV-2 infection. Importantly, ACE2 protein which facilitates the host-cell entry of SARS-CoV-2 using the spike protein, are highly expressed in individuals with abnormal level of thyroid hormone. Altogether, we report that the malfunction of thyroid hormone synthesis may aggravate SARS-CoV-2 infection and thus monitoring the thyroid hormone may help in understanding the pathogenesis of COVID-19.

Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?-The IDENTIFY Trial

Therapeutic agents for the novel coronavirus disease 2019 (COVID-19) have been proposed, but evidence supporting their use is limited. A machine learning algorithm was developed in order to identify a subpopulation of COVID-19 patients for whom hydroxychloroquine was associated with improved survival; this population might be relevant for study in a clinical trial. A pragmatic trial was conducted at six United States hospitals. We enrolled COVID-19 patients that were admitted between 10 March and 4 June 2020. Treatment was not randomized. The study endpoint was mortality; discharge was a competing event. Hazard ratios were obtained on the entire population, and on the subpopulation indicated by the algorithm as suitable for treatment. A total of 290 patients were enrolled. In the subpopulation that was identified by the algorithm, hydroxychloroquine was associated with a statistically significant (p = 0.011) increase in survival (adjusted hazard ratio 0.29, 95% confidence interval (CI) 0.11–0.75). Adjusted survival among the algorithm indicated patients was 82.6% in the treated arm and 51.2% in the arm not treated. No association between treatment and mortality was observed in the general population. A 31% increase in survival at the end of the study was observed in a population of COVID-19 patients that were identified by a machine learning algorithm as having a better outcome with hydroxychloroquine treatment. Precision medicine approaches may be useful in identifying a subpopulation of COVID-19 patients more likely to be proven to benefit from hydroxychloroquine treatment in a clinical trial.

Possible Correlations between Atherosclerosis, Acute Coronary Syndromes and COVID-19

An outbreak of SARS-CoV-2 infection in December 2019 became a major global concern in 2020. Since then, several articles analyzing the course, complications and mechanisms of the infection have appeared. However, there are very few papers explaining the possible correlations between COVID-19, atherosclerosis and acute coronary syndromes. We performed an analysis of PubMed, Cochrane, Google Scholar, and MEDLINE databases. As of September 15, 2020, the results were as follows: for "COVID-19" and "cardiovascular system" we obtained 687 results; for "COVID-19" and "myocardial infarction" together with "COVID-19" and "acute coronary syndrome" we obtained 328 results; for "COVID-19" and "atherosclerosis" we obtained 57 results. Some of them did not fulfill the search criteria or concerned the field of neurology. Only articles written in English, German and Polish were analyzed for a total number of 432 papers. While the link between inflammatory response, COVID- 19 and atherosclerosis still remains unclear, there is evidence that suggests a more likely correlation between them. Practitioners' efforts should be focused on the prevention of excessive inflammatory response and possible complications, while there are limited specific therapeutic options against SARS-CoV-2. Furthermore, special attention should be paid to cardioprotection during the pandemic.

SARS-CoV-2 and the cardiovascular system

The coronavirus disease COVID-19 is a public health emergency caused by a novel coronavirus named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). SARS-CoV-2 infection uses the angiotensin-converting enzyme 2 (ACE2) receptor, and typically spreads through the respiratory tract. Invading viruses can elicit an exaggerated host immune response, frequently leading to a cytokine storm that may be fueling some COVID-19 death. This response contributes to multi-organ dysfunction. Accumulating data points to an increased cardiovascular disease morbidity, and mortality in COVID-19 patients. This brief review explores potential available evidence regarding the association between COVID-19, and cardiovascular complications.

Elevated cardiac biomarkers may be effective prognostic predictors for patients with COVID-19: A multicenter, observational study

PURPOSE

The coronavirus disease 19 (COVID-19) has become a global health event. Cardiac biomarkers like creatine kinase isoenzyme (CK-MB), myoglobin, and high-sensitivity troponin T were usually elevated in early stages. This study aimed to investigate whether the elevated cardiac biomarkers could become effective prognostic predictors for COVID-19 patients.

METHODS

The present study involved 357 COVID-19 patients. The potential predictors for two study outcomes (in-hospital death and recovery status) in 28 days were selected by LASSO regression analysis. Prognostic values of cardiac biomarkers selected were evaluated using the receiver operating characteristic curve (ROC) and the area under ROC (AUC).

RESULTS

After 28-day follow-up, overall 357 patients were divided into death group (n = 25) and survival group (n = 332), or non-recovery group (n = 43) and recovery group (n = 314). The LASSO regression analysis showed elevated CK-MB and myoglobin were independent risk predictors for in-hospital death, and CK-MB and myoglobin were also independent risk predictors for non-recovery. The AUC of CK-MB and myoglobin for in-hospital death were 0.862 (95%CL: 0.804-0.920, p < 0.001) and 0.838 respectively (95%CL: 0.729-0.947, p < 0.001). The AUC of CK-MB and myoglobin for non-recovery were 0.839 (95%CL: 0.786-0.892, p < 0.001) and 0.841 (95%CL: 0.765-0.918, p < 0.001) respectively. We also found AUC of combined use of CK-MB and myoglobin for in-hospital death and non-recovery were 0.883 (95CL: 0.813-0.952, p < 0.001), and 0.873 (95%CL: 0.817-0.930, p < 0.001) respectively.

CONCLUSIONS

In patients with COVID-19, elevated CK-MB and myoglobin on admission may be effective predictors for adverse outcomes, and combined use of CK-MB and myoglobin had a better performance for prediction.

Valor pronóstico de los marcadores bioquímicos en pacientes con COVID-19

El SARS-CoV-2 es un virus de la familia Coronaviridae, subfamilia coronavirus (CoV) y género β. Este se ha convertido en una amenaza inminente para toda la humanidad por ser el agente causal de la pandemia COVID-19, la cual llevó, por un lado, a la declaratoria de emergencia sanitaria a nivel mundial por parte de la Organización Mundial de la Salud (OMS) y, por otro, a instituir estrictas medidas de control para prevenir su contagio por parte de muchos gobiernos. En cuanto a la fisiopatología presentada en esta entidad, aunque las lesiones pulmonares han sido consideradas como las principales consecuencias de esta infección, a medida que avanza el conocimiento sobre el virus se han identificado también lesiones a nivel cardiaco, hepático y renal, que potencian la severidad de la infección y generan un mayor deterioro de los pacientes, su ingreso a las Unidades de Cuidados Intensivos y un mayor riesgo de mortalidad. Con base en esto, diversas investigaciones se han encaminado a determinar aquellos hallazgos clínicos y paraclínicos que puedan ser relevantes frente al pronóstico de los pacientes. Por lo anterior, la presente revisión aborda literatura disponible sobre los principales biomarcadores bioquímicos reportados por su asociación a daños cardiaco, hepático y renal, los cuales presentan mayor significancia para evaluar el curso, severidad, manejo y pronóstico de la infección, y cuya alteración conlleva finalmente a un mayor riesgo de mortalidad en pacientes hospitalizados que presentan COVID-19.

Effects of Antimalarial Drugs on Neuroinflammation-Potential Use for Treatment of COVID-19-Related Neurologic Complications

The SARS-CoV-2 virus that is the cause of coronavirus disease 2019 (COVID-19) affects not only peripheral organs such as the lungs and blood vessels, but also the central nervous system (CNS)—as seen by effects on smell, taste, seizures, stroke, neuropathological findings and possibly, loss of control of respiration resulting in silent hypoxemia. COVID-19 induces an inflammatory response and, in severe cases, a cytokine storm that can damage the CNS. Antimalarials have unique properties that distinguish them from other anti-inflammatory drugs. (A) They are very lipophilic, which enhances their ability to cross the blood-brain barrier (BBB). Hence, they have the potential to act not only in the periphery but also in the CNS, and could be a useful addition to our limited armamentarium against the SARS-CoV-2 virus. (B) They are non-selective inhibitors of phospholipase A₂ isoforms, including cytosolic phospholipase A₂ (cPLA₂). The latter is not only activated by cytokines but itself generates arachidonic acid, which is metabolized by cyclooxygenase (COX) to pro-inflammatory eicosanoids. Free radicals are produced in this process, which can lead to oxidative damage to the CNS. There are at least 4 ways that antimalarials could be useful in combating COVID-19. (1) They inhibit PLA_2. (2) They are basic molecules capable of affecting the pH of lysosomes and inhibiting the activity of lysosomal enzymes. (3) They may affect the expression and Fe²⁺/H⁺ symporter activity of iron transporters such as divalent metal transporter 1 (DMT1), hence reducing iron accumulation in tissues and iron-catalysed free radical formation. (4) They could affect viral replication. The latter may be related to their effect on inhibition of PLA₂ isoforms. Inhibition of cPLA₂ impairs an early step of coronavirus replication in cell culture. In addition, a secretory PLA₂ (sPLA₂) isoform, PLA2G2D, has been shown to be essential for the lethality of SARS-CoV in mice. It is important to take note of what ongoing clinical trials on chloroquine and hydroxychloroquine can eventually tell us about the use of antimalarials and other anti-inflammatory agents, not only for the treatment of COVID-19, but also for neurovascular disorders such as stroke and vascular dementia.

Increase in Video Consultations During the COVID-19 Pandemic: Healthcare Professionals' Perceptions about Their Implementation and Adequate Management

In response to the COVID-19 pandemic, health care modalities such as video consultations have been rapidly developed to provide safe health care and to minimize the risk of spread. The purpose of our study is to explore Spanish healthcare professionals’ perceptions about the implementation of video consultations. Based on the testimonies of 53 professionals, different categories emerged related to the four identified themes: benefits of video consultations (for professionals, patients, and the health system, and compared to phone calls), negative aspects (inherent to new technologies and the risk of a perceived distancing from the professional), difficulties associated with the implementation of video consultations (technological difficulties, lack of technical skills and refusal to use video consultation among professionals and patients), and the need for training (technological, nontechnical, and social-emotional skills, and adaptation of technical skills). Additionally, the interviewees indicated that this new modality of health care may be extended to a broader variety of patients and clinical settings. Therefore, since video consultations are becoming more widespread, it would be advisable for health policies and systems to support this modality of health care, promoting their implementation and guaranteeing their operability, equal access and quality.