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Open accessJournal ArticleDOI: 10.1038/S41598-021-84643-6

Prognostic value of cardiac biomarkers in COVID-19 infection.

02 Mar 2021-Scientific Reports (Springer Science and Business Media LLC)-Vol. 11, Iss: 1, pp 4930-4930
Abstract: Multiple Biomarkers have recently been shown to be elevated in COVID-19, a respiratory infection with multi-organ dysfunction; however, information regarding the prognostic value of cardiac biomarkers as it relates to disease severity and cardiac injury are inconsistent. The goal of this meta-analysis was to summarize the evidence regarding the prognostic relevance of cardiac biomarkers from data available in published reports. PubMed, Embase and Web of Science were searched from inception through April 2020 for studies comparing median values of cardiac biomarkers in critically ill versus non-critically ill COVID-19 patients, or patients who died versus those who survived. The weighted mean differences (WMD) and 95% confidence interval (CI) between the groups were calculated for each study and combined using a random effects meta-analysis model. The odds ratio (OR) for mortality based on cardiac injury was combined from studies reporting it. Troponin levels were significantly higher in COVID-19 patients who died or were critically ill versus those who were alive or not critically ill (WMD 0.57, 95% CI 0.43–0.70, p < 0.001). Additionally, BNP levels were also significantly higher in patients who died or were critically ill (WMD 0.45, 95% CI − 0.21–0.69, p < 0.001). Cardiac injury was independently associated with significantly increased odds of mortality (OR 6.641, 95% CI 1.26–35.1, p = 0.03). A significant difference in levels of D-dimer was seen in those who died or were critically ill. CK levels were only significantly higher in those who died versus those who were alive (WMD 0.79, 95% CI 0.25–1.33, p = 0.004). Cardiac biomarkers add prognostic value to the determination of the severity of COVID-19 and can predict mortality.

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Topics: Respiratory infection (52%), Odds ratio (50%)
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Open accessJournal ArticleDOI: 10.1111/ECI.13629
Abstract: Background During COVID-19 outbreak, Italy was the first country in Europe to be heavily affected with an intensive care unit mortality of 26%. In order to reduce this percentage, physicians should establish clear and objective criteria to stratify COVID-19 patients at high risk of in-hospital death. Thus, the aim has been to test a large spectrum of variables ranging from clinical evaluation to laboratory biomarkers to identify which parameter would best predict all-cause in-hospital mortality in COVID-19 patients. Design observational study. Results Multivariate Cox regression analysis showed that each 5 years of increase in age corresponded to a hazard ratio (HR) of 1.28 (95% CI 1.00-1.65, P = .050); each increment of 803 ng/L of N-terminal pro-B-type natriuretic peptide (NT-proBNP) corresponded to a HR of 1.24 (95% CI 1.11-1.39, P < .001); each increment of 58 ng/L of interleukin (IL)-6 corresponded to a HR of 1.23 (95% CI 1.09-1.40, P < .001), and each increment of 250 U/L of lactate dehydrogenase (LDH) corresponded to a HR of 1.23 (95% CI 1.10-1.37, P < .001). According to the calculated cut-points for age (≥70 years), NT-proBNP (≥803 ng/L), IL-6 (≥58 ng/L) and LDH (≥371 U/L) when 2 out of these 4 were overcome, the HR was 2.96 (95% CI 1.97-4.45, P < .001). Conclusion In COVID-19 patients, besides age, the evaluation of three biochemical parameters, available in few hours after hospital admission can predict in-hospital mortality regardless of other comorbidities.

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4 Citations


Open accessJournal ArticleDOI: 10.3390/JCM10122535
Jean Bonnemain1, Zied Ltaief1, Lucas Liaudet1Institutions (1)
Abstract: Infection with the novel severe acute respiratory coronavirus-2 (SARS-CoV2) results in COVID-19, a disease primarily affecting the respiratory system to provoke a spectrum of clinical manifestations, the most severe being acute respiratory distress syndrome (ARDS). A significant proportion of COVID-19 patients also develop various cardiac complications, among which dysfunction of the right ventricle (RV) appears particularly common, especially in severe forms of the disease, and which is associated with a dismal prognosis. Echocardiographic studies indeed reveal right ventricular dysfunction in up to 40% of patients, a proportion even greater when the RV is explored with strain imaging echocardiography. The pathophysiological mechanisms of RV dysfunction in COVID-19 include processes increasing the pulmonary vascular hydraulic load and others reducing RV contractility, which precipitate the acute uncoupling of the RV with the pulmonary circulation. Understanding these mechanisms provides the fundamental basis for the adequate therapeutic management of RV dysfunction, which incorporates protective mechanical ventilation, the prevention and treatment of pulmonary vasoconstriction and thrombotic complications, as well as the appropriate management of RV preload and contractility. This comprehensive review provides a detailed update of the evidence of RV dysfunction in COVID-19, its pathophysiological mechanisms, and its therapy.

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Topics: ARDS (53%)

2 Citations


Open accessJournal ArticleDOI: 10.15829/1560-4071-2021-4456
Abstract: The coronavirus disease 2019 (COVID-19) affects not only the respiratory system, but also the cardiovascular system in 20-28% of cases, causing endothelial dysfunction, vasculitis, hyper- and hypocoagulation, myocarditis, endothelial dysfunction and other adverse effects. The presence of cardiovascular risk factors and diseases has been shown to worsen the disease severity and increase mortality from COVID-19. Recent studies have also found that elevations in some serum cardiovascular biomarkers can stratify the disease severity, in particular rates of hospitalizations to an internal medicine or intensive care unit, intubation, and mortality. They can be divided into markers of damage (TnT/I, creatine phosphokinase (CPK) and CPK-MB, myoglobin, NT-proBNP), coagulation (prothrombin time, fibrinogen and D-dimer), as well as prospective biomarkers for which the available evidence base is limited but there is a pathophysiological rationale (homocysteine and sST2). This review presents studies on the use of above serum biomarkers to stratify the risk of death in patients with COVID-19.

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Topics: Endothelial dysfunction (52%)

1 Citations


Journal ArticleDOI: 10.1093/EHJQCCO/QCAB053
Annapoorna Kini1, Davide Cao1, Matteo Nardin1, Matteo Nardin2  +13 moreInstitutions (3)
Abstract: AIMS: To evaluate the acute and chronic patterns of myocardial injury among patients with coronavirus disease-2019 (COVID-19), and their mid-term outcomes. METHODS AND RESULTS: Patients with laboratory-confirmed COVID-19 who had a hospital encounter within the Mount Sinai Health System (New York City) between 27 February 2020 and 15 October 2020 were evaluated for inclusion. Troponin levels assessed between 72 h before and 48 h after the COVID-19 diagnosis were used to stratify the study population by the presence of acute and chronic myocardial injury, as defined by the Fourth Universal Definition of Myocardial Infarction. Among 4695 patients, those with chronic myocardial injury (n = 319, 6.8%) had more comorbidities, including chronic kidney disease and heart failure, while acute myocardial injury (n = 1168, 24.9%) was more associated with increased levels of inflammatory markers. Both types of myocardial injury were strongly associated with impaired survival at 6 months [chronic: hazard ratio (HR) 4.17, 95% confidence interval (CI) 3.44-5.06; acute: HR 4.72, 95% CI 4.14-5.36], even after excluding events occurring in the first 30 days (chronic: HR 3.97, 95% CI 2.15-7.33; acute: HR 4.13, 95% CI 2.75-6.21). The mortality risk was not significantly different in patients with acute as compared with chronic myocardial injury (HR 1.13, 95% CI 0.94-1.36), except for a worse prognostic impact of acute myocardial injury in patients <65 years of age (P-interaction = 0.043) and in those without coronary artery disease (P-interaction = 0.041). CONCLUSION: Chronic and acute myocardial injury represent two distinctive patterns of cardiac involvement among COVID-19 patients. While both types of myocardial injury are associated with impaired survival at 6 months, mortality rates peak in the early phase of the infection but remain elevated even beyond 30 days during the convalescent phase.

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Topics: Myocardial infarction (56%), Coronary artery disease (54%), Kidney disease (52%) ... show more

1 Citations


Open accessPosted ContentDOI: 10.1101/2021.11.15.21266315
Claudia Fredolini1, Tea Dodig-Crnković1, Annika Bendes1, Leo Dahl1  +7 moreInstitutions (3)
16 Nov 2021-medRxiv
Abstract: Self-sampled blood provided valuable information about the COVID-19 seroprevalence in the general population. To enable an even deeper understanding of pathophysiological processes following SARS-CoV-2 infections, 276 circulating proteins were quantified by proximity extension assays in dried blood spots (DBS). Samples from undiagnosed individuals collected during the first wave of the pandemic were selected based on their serological immune response and matched on self-reported symptoms. We stratified these as seropositive (IgM+IgG+; N = 41) or seronegative (IgM-IgG-; N = 37), and to represent the acute (IgM+IgG-; N = 26) and convalescent phases (IgM-IgG+; N = 40). This revealed proteins from a variety of clinical processes including inflammation and immune response (MBL2, MMP3, IL2RA, FCGR2A, CCL5), haemostasis (GP1BA, VWF), stress response (ANG), virus entry (SDC4) or nerve regeneration (CHL1). The presented approach complements clinical surveys and enables a deep molecular and population-wide analysis of COVID-19 from blood specimens collected outside a hospital setting.

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Topics: Population (53%)

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45 results found


Open accessJournal ArticleDOI: 10.1136/BMJ.327.7414.557
04 Sep 2003-BMJ
Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice? Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis. Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4 Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted? A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …

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Topics: Study heterogeneity (62%), Systematic review (54%), Meta-analysis (53%) ... show more

37,135 Citations


Open accessJournal ArticleDOI: 10.1016/S0140-6736(20)30183-5
Chaolin Huang1, Yeming Wang2, Xingwang Li3, Lili Ren4  +25 moreInstitutions (8)
24 Jan 2020-The Lancet
Abstract: A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not.

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26,390 Citations


Journal ArticleDOI: 10.1002/SIM.1186
Abstract: The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity.

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Topics: Study heterogeneity (75%), Random effects model (54%), Funnel plot (51%) ... show more

21,054 Citations


Open accessJournal ArticleDOI: 10.1056/NEJMOA2002032
Wei-jie Guan1, Zhengyi Ni1, Yu Hu1, Wenhua Liang1  +33 moreInstitutions (1)
Abstract: Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of...

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16,855 Citations


Open accessJournal ArticleDOI: 10.1016/S0140-6736(20)30566-3
Fei Zhou1, Ting Yu, Ronghui Du, Guohui Fan2  +16 moreInstitutions (5)
28 Mar 2020-The Lancet
Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

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Topics: Cohort study (56%), Retrospective cohort study (56%), Odds ratio (53%) ... show more

15,279 Citations


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