Angiotensin Converting Enzyme Inhibitors and Angiotensin Receptor Blockers and the Risk of SARS-CoV-2 Infection or Hospitalization With COVID-19 Disease: A Systematic Review and Meta-Analysis.

BACKGROUND: SARS-CoV-2 infects its target cells via angiotensin converting enzyme 2 receptor, a membrane-bound protein found on the surface of many human cells. Treatment with angiotensin converting enzyme inhibitors (ACEI) or angiotensin receptors blockers (ARB) has been shown to increase angiotensin converting enzyme 2 expression by up to 5-fold. AREAS OF UNCERTAINTY: These findings coupled with observations of the high prevalence and mortality among SARS-CoV-2-infected patients with underlying cardiovascular disease have led to a speculation that ACEIs/ARBs may predispose to higher risk of being infected with SARS-CoV-2. Therefore, we systematically reviewed the literature and performed a meta-analysis of the association between prior use of ACEIs and ARBs and the risk of SARS-CoV-2 infection or hospitalization due to COVID-19 disease. DATA SOURCES: We searched Ovid MEDLINE(R) and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Ovid Embase, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Web of Science, Scopus, and Medrxiv.org preprint server until June 18, 2020. THERAPEUTIC ADVANCES: Ten studies (6 cohorts and 4 case control) that enrolled a total of 23,892 patients and 853,369 controls were eligible for inclusion in our meta-analysis. One study was excluded from the analysis because of high risk of bias. Prior use of ACEIs was not associated with an increased risk of acquiring SARS-CoV-2 or hospitalization due to COVID-19 disease, odds ratio 0.98, 95% confidence interval (0.91-1.05), I2 = 15%. Similarly, prior use of ARBs was not associated with an increased risk of acquiring SARS-CoV-2, odds ratio 1.04, 95% confidence interval (0.98-1.10), I2 = 0%. CONCLUSION: Cumulative evidence suggests that prior use of ACEIs or ARBs is not associated with a higher risk of COVID-19 or hospitalization due to COVID-19 disease. Our results provide a reassurance to the public not to discontinue prescribed ACEIs/ARBs because of fear of COVID-19.

Thrombosis-related circulating miR-16-5p is associated with disease severity in patients hospitalised for COVID-19.

SARS-CoV-2 tropism for the ACE2 receptor, along with the multifaceted inflammatory reaction, is likely to drive the generalized hypercoagulable and thrombotic state seen in patients with COVID-19. Using the original bioinformatic workflow and network medicine approaches we reanalysed four coronavirus-related expression datasets and performed co-expression analysis focused on thrombosis and ACE2 related genes. We identified microRNAs (miRNAs) which play role in ACE2-related thrombosis in coronavirus infection and further, we validated the expressions of precisely selected miRNAs-related to thrombosis (miR-16-5p, miR-27a-3p, let-7b-5p and miR-155-5p) in 79 hospitalized COVID-19 patients and 32 healthy volunteers by qRT-PCR. Consequently, we aimed to unravel whether bioinformatic prioritization could guide selection of miRNAs with a potential of diagnostic and prognostic biomarkers associated with disease severity in patients hospitalized for COVID-19. In bioinformatic analysis, we identified EGFR, HSP90AA1, APP, TP53, PTEN, UBC, FN1, ELAVL1 and CALM1 as regulatory genes which could play a pivotal role in COVID-19 related thrombosis. We also found miR-16-5p, miR-27a-3p, let-7b-5p and miR-155-5p as regulators in the coagulation and thrombosis process. In silico predictions were further confirmed in patients hospitalized for COVID-19. The expression levels of miR-16-5p and let-7b in COVID-19 patients were lower at baseline, 7-days and 21-day after admission compared to the healthy controls (p < 0.0001 for all time points for both miRNAs). The expression levels of miR-27a-3p and miR-155-5p in COVID-19 patients were higher at day 21 compared to the healthy controls (p = 0.007 and p < 0.001, respectively). A low baseline miR-16-5p expression presents predictive utility in assessment of the hospital length of stay or death in follow-up as a composite endpoint (AUC:0.810, 95% CI, 0.71-0.91, p < 0.0001) and low baseline expression of miR-16-5p and diabetes mellitus are independent predictors of increased length of stay or death according to a multivariate analysis (OR: 9.417; 95% CI, 2.647-33.506; p = 0.0005 and OR: 6.257; 95% CI, 1.049-37.316; p = 0.044, respectively). This study enabled us to better characterize changes in gene expression and signalling pathways related to hypercoagulable and thrombotic conditions in COVID-19. In this study we identified and validated miRNAs which could serve as novel, thrombosis-related predictive biomarkers of the COVID-19 complications, and can be used for early stratification of patients and prediction of severity of infection development in an individual.Abbreviations: ACE2, angiotensin-converting enzyme 2AF, atrial fibrillationAPP, Amyloid Beta Precursor ProteinaPTT, activated partial thromboplastin timeAUC, Area under the curveAß, amyloid betaBMI, body mass indexCAD, coronary artery diseaseCALM1, Calmodulin 1 geneCaM, calmodulinCCND1, Cyclin D1CI, confidence intervalCOPD, chronic obstructive pulmonary diseaseCOVID-19, Coronavirus disease 2019CRP, C-reactive proteinCV, CardiovascularCVDs, cardiovascular diseasesDE, differentially expressedDM, diabetes mellitusEGFR, Epithelial growth factor receptorELAVL1, ELAV Like RNA Binding Protein 1FLNA, Filamin AFN1, Fibronectin 1GEO, Gene Expression OmnibushiPSC-CMs, Human induced pluripotent stem cell-derived cardiomyocytesHSP90AA1, Heat Shock Protein 90 Alpha Family Class A Member 1Hsp90α, heat shock protein 90αICU, intensive care unitIL, interleukinIQR, interquartile rangelncRNAs, long non-coding RNAsMI, myocardial infarctionMiRNA, MiR, microRNAmRNA, messenger RNAncRNA, non-coding RNANERI, network-medicine based integrative approachNF-kB, nuclear factor kappa-light-chain-enhancer of activated B cellsNPV, negative predictive valueNXF, nuclear export factorPBMCs, Peripheral blood mononuclear cellsPCT, procalcitoninPPI, Protein-protein interactionsPPV, positive predictive valuePTEN, phosphatase and tensin homologqPCR, quantitative polymerase chain reactionROC, receiver operating characteristicSARS-CoV-2, severe acute respiratory syndrome coronavirus 2SD, standard deviationTLR4, Toll-like receptor 4TM, thrombomodulinTP53, Tumour protein P53UBC, Ubiquitin CWBC, white blood cells.

Convalescent Plasma Treatment in Patients with Covid-19: A Systematic Review and Meta-Analysis.

Convalescent plasma is a suggested treatment for Coronavirus disease 2019 (Covid-19), but its efficacy is uncertain. We aimed to evaluate whether the use of convalescent plasma is associated with improved clinical outcomes in patients with Covid-19.In this systematic review and meta-analysis, we searched randomized controlled trials investigating the use of convalescent plasma in patients with Covid-19 in Medline, Embase, Web of Science, Cochrane Library, and medRxiv from inception to October 17th, 2021. Two reviewers independently extracted the data. The primary efficacy outcome was all-cause mortality. The Cochrane Risk of Bias Tool and GRADE (Grading of Recommendations Assessment, Development and Evaluation) method were used. This study was registered with PROSPERO, CRD42021284861. Of the 8874 studies identified in the initial search, sixteen trials comprising 16 317 patients with Covid-19 were included. In the overall population, the all-cause mortality was 23.8% (2025 of 8524) with convalescent plasma and 24.4% (1903 of 7769) with standard of care (risk ratio (RR) 0.97, 95% CI 0.90-1.04) (high-certainty evidence). All-cause mortality did not differ in the subgroups of noncritically ill (21.7% [1288 of 5929] vs. 22.4% [1320 of 5882]) and critically ill (36.9% [518 of 1404] vs. 36.4% [455 of 1247]) patients with Covid-19. The use of convalescent plasma in patients who tested negative for anti-SARS-CoV-2 antibodies at baseline was not associated with significantly improved survival (RR 0.94, 95% CI 0.87-1.02). In the overall study population, initiation of mechanical ventilation (RR 0.97, 95% CI 0.88-1.07), time to clinical improvement (HR 1.09, 95% CI 0.91-1.30), and time to discharge (HR 0.95, 95% CI 0.89-1.02) were similar between the two groups. In patients with Covid-19, treatment with convalescent plasma, as compared with control, was not associated with lower all-cause mortality or improved disease progression, irrespective of disease severity and baseline antibody status. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier PROSPERO (CRD42021284861).

Simplified Acute Physiology Score 3 Performance in Austrian COVID-19 Patients Admitted to Intensive Care Units with and without Diabetes.

This study evaluated and compared the performance of simplified acute physiology score 3 (SAPS 3) for predicting in-hospital mortality in COVID-19 patients admitted to intensive care units (ICUs) with and without diabetes in Austria. The Austrian national public health institute (GÖG) data of COVID-19 patients admitted to ICUs (n = 5850) were analyzed. Three versions of SAPS 3 were used: standard equation, Central European equation, and Austrian equation customized for COVID-19 patients. The observed in-hospital mortality was 38.9%, 42.9%, and 37.3% in all, diabetes, and non-diabetes patients, respectively. The overall C-statistics was 0.69 with an insignificant (p = 0.193) difference between diabetes (0.70) and non-diabetes (0.68) patients. The Brier score was > 0.20 for all SAPS 3 equations in all cohorts. Calibration was unsatisfactory for both standard and Central European equations in all cohorts, whereas it was satisfactory for the Austrian equation in diabetes patients only. The SAPS 3 score demonstrated low discrimination and accuracy in Austrian COVID-19 patients, with an insignificant difference between diabetes and non-diabetes. All equations were miscalibrated particularly in non-diabetes patients, while the Austrian equation showed satisfactory calibration in diabetes patients only. Both uncalibrated and calibrated versions of SAPS 3 should be used with caution in COVID-19 patients.

COVID-19 In-Hospital Mortality in People with Diabetes Is Driven by Comorbidities and Age-Propensity Score-Matched Analysis of Austrian National Public Health Institute Data.

BACKGROUND: It is a matter of debate whether diabetes alone or its associated comorbidities are responsible for severe COVID-19 outcomes. This study assessed the impact of diabetes on intensive care unit (ICU) admission and in-hospital mortality in hospitalized COVID-19 patients. METHODS: A retrospective analysis was performed on a countrywide cohort of 40,632 COVID-19 patients hospitalized between March 2020 and March 2021. Data were provided by the Austrian data platform. The association of diabetes with outcomes was assessed using unmatched and propensity-score matched (PSM) logistic regression. RESULTS: 12.2% of patients had diabetes, 14.5% were admitted to the ICU, and 16.2% died in the hospital. Unmatched logistic regression analysis showed a significant association of diabetes (odds ratio [OR]: 1.24, 95% confidence interval [CI]: 1.15-1.34, p < 0.001) with in-hospital mortality, whereas PSM analysis showed no significant association of diabetes with in-hospital mortality (OR: 1.08, 95%CI: 0.97-1.19, p = 0.146). Diabetes was associated with higher odds of ICU admissions in both unmatched (OR: 1.36, 95%CI: 1.25-1.47, p < 0.001) and PSM analysis (OR: 1.15, 95%CI: 1.04-1.28, p = 0.009). CONCLUSIONS: People with diabetes were more likely to be admitted to ICU compared to those without diabetes. However, advanced age and comorbidities rather than diabetes itself were associated with increased in-hospital mortality in COVID-19 patients.

Anticoagulant Treatment Regimens in Patients With Covid-19: A Meta-Analysis.

Coronavirus disease 2019 (COVID-19) is associated with a hypercoagulable state. It has been hypothesized that higher-dose anticoagulation, including therapeutic-dose and intermediate-dose anticoagulation, is superior to prophylactic-dose anticoagulation in the treatment of COVID-19. This meta-analysis evaluated the efficacy and safety of higher-dose anticoagulation compared with prophylactic-dose anticoagulation in patients with COVID-19. Ten randomized controlled open-label trials with a total of 5,753 patients were included. The risk of death and net adverse clinical events (including death, thromboembolic events, and major bleeding) were similar between higher-dose and prophylactic-dose anticoagulation (risk ratio (RR) 0.96, 95% CI, 0.79-1.16, P = 0.66 and RR 0.87, 95% CI, 0.73-1.03, P = 0.11, respectively). Higher-dose anticoagulation, compared with prophylactic-dose anticoagulation, decreased the risk of thromboembolic events (RR 0.63, 95% CI, 0.47-0.84, P = 0.002) but increased the risk of major bleeding (RR 1.76, 95% CI, 1.19-2.62, P = 0.005). The risk of death showed no statistically significant difference between higher-dose anticoagulation and prophylactic-dose anticoagulation in noncritically ill patients (RR 0.87, 95% CI, 0.50-1.52, P = 0.62) and in critically ill patients with COVID-19 (RR 1.04, 95% CI, 0.93-1.17, P = 0.5). The risk of death was similar between therapeutic-dose vs. prophylactic-dose anticoagulation (RR 0.92, 95% CI 0.69-1.21, P = 0.54) and between intermediate-dose vs. prophylactic-dose anticoagulation (RR 1.01, 95% CI 0.63-1.61, P = 0.98). In patients with markedly increased d-dimer levels, higher-dose anticoagulation was also not associated with a decreased risk of death as compared with prophylactic-dose anticoagulation (RR 0.86, 95% CI, 0.64-1.16, P = 0.34). Without any clear evidence of survival benefit, these findings do not support the routine use of therapeutic-dose or intermediate-dose anticoagulation in critically or noncritically ill patients with COVID-19.

ACE2 Interaction Networks in COVID-19: A Physiological Framework for Prediction of Outcome in Patients with Cardiovascular Risk Factors.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease 2019; COVID-19) is associated with adverse outcomes in patients with cardiovascular disease (CVD). The aim of the study was to characterize the interaction between SARS-CoV-2 and Angiotensin-Converting Enzyme 2 (ACE2) functional networks with a focus on CVD. METHODS: Using the network medicine approach and publicly available datasets, we investigated ACE2 tissue expression and described ACE2 interaction networks that could be affected by SARS-CoV-2 infection in the heart, lungs and nervous system. We compared them with changes in ACE-2 networks following SARS-CoV-2 infection by analyzing public data of human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). This analysis was performed using the Network by Relative Importance (NERI) algorithm, which integrates protein-protein interaction with co-expression networks. We also performed miRNA-target predictions to identify which miRNAs regulate ACE2-related networks and could play a role in the COVID19 outcome. Finally, we performed enrichment analysis for identifying the main COVID-19 risk groups. RESULTS: We found similar ACE2 expression confidence levels in respiratory and cardiovascular systems, supporting that heart tissue is a potential target of SARS-CoV-2. Analysis of ACE2 interaction networks in infected hiPSC-CMs identified multiple hub genes with corrupted signaling which can be responsible for cardiovascular symptoms. The most affected genes were EGFR (Epidermal Growth Factor Receptor), FN1 (Fibronectin 1), TP53, HSP90AA1, and APP (Amyloid Beta Precursor Protein), while the most affected interactions were associated with MAST2 and CALM1 (Calmodulin 1). Enrichment analysis revealed multiple diseases associated with the interaction networks of ACE2, especially cancerous diseases, obesity, hypertensive disease, Alzheimer's disease, non-insulin-dependent diabetes mellitus, and congestive heart failure. Among affected ACE2-network components connected with the SARS-Cov-2 interactome, we identified AGT (Angiotensinogen), CAT (Catalase), DPP4 (Dipeptidyl Peptidase 4), CCL2 (C-C Motif Chemokine Ligand 2), TFRC (Transferrin Receptor) and CAV1 (Caveolin-1), associated with cardiovascular risk factors. We described for the first time miRNAs which were common regulators of ACE2 networks and virus-related proteins in all analyzed datasets. The top miRNAs regulating ACE2 networks were miR-27a-3p, miR-26b-5p, miR-10b-5p, miR-302c-5p, hsa-miR-587, hsa-miR-1305, hsa-miR-200b-3p, hsa-miR-124-3p, and hsa-miR-16-5p. CONCLUSION: Our study provides a complete mechanistic framework for investigating the ACE2 network which was validated by expression data. This framework predicted risk groups, including the established ones, thus providing reliable novel information regarding the complexity of signaling pathways affected by SARS-CoV-2. It also identified miRNAs that could be used in personalized diagnosis in COVID-19.

Atrial fibrillation: a risk factor for unfavourable outcome in COVID-19? A case report.

BACKGROUND: Fulminant cardiac involvement in COVID-19 patients has been reported; the underlying suspected mechanisms include myocarditis, arrhythmia, and cardiac tamponade. In parallel, atrial fibrillation is common in the elderly population which is at particularly high risk for COVID-19 morbidity and mortality. CASE SUMMARY: A 72-year-old male SARS-CoV2-positive patient was admitted to the intensive care unit due to delirium and acute respiratory failure. Atrial fibrillation known from history was exacerbated, and made complex rate and rhythm control necessary. Progressive heart failure with haemodynamic deterioration and acute kidney injury with the need for continuous renal replacement therapy were further aggravated by pericardial tamponade. DISCUSSION: Treatment of acute heart failure in COVID-19 patients with a cytokine storm complicated by tachycardic atrial fibrillation should include adequate rate or rhythm control, and potentially immunomodulation.