scholarly journals Myocardial injury and COVID-19: Serum hs-cTnI level in risk stratification and the prediction of 30-day fatality in COVID-19 patients with no prior cardiovascular disease

Theranostics ◽  
2020 ◽  
Vol 10 (21) ◽  
pp. 9663-9673
Author(s):  
Jiatian Cao ◽  
Yan Zheng ◽  
Zhe Luo ◽  
Zhendong Mei ◽  
Yumeng Yao ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Risk Stratification ◽  
Myocardial Injury ◽  
Ctni Level

scholarly journals Pattern of serum cardiac troponin-I in symptomatic acute myocardial infarction patients in national institute of cardiovascular disease in Bangladesh

2014 ◽  
Vol 42 (1) ◽  
pp. 3-6
Author(s):  
SS Shahina ◽  
JU Ahmed ◽  
S Ahmed ◽  
E Shahriar ◽  
MN Uddin ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Cardiovascular Disease ◽  
Acute Myocardial Infarction ◽  
Myocardial Injury ◽  
Troponin I ◽  
Clinical Symptoms ◽  
Cardiac Injury ◽  
Circadian Variation ◽  
Assay Method ◽  
Ctni Level

Troponin I (cTnI) isoform is cardiac muscle specific protein and shown to have several features as a preferred marker of myocardial injury. It rises early in acute myocardial infarction (AMI) and attains levels that are clearly separated from baseline values. It remains elevated for several days providing a long window for detection of cardiac injury. The objective of the study was to evaluate for the profile of cTnI level among symptomatic AMI patients. The study was conducted at National Institute of Cardiovascular Disease, Dhaka, Bangladesh from July 2007 to June 2008 and total 9552 patients with type 1 or type 2 MI were included. Blood Sample was taken within 3 days of symptoms and cTnI was measured by chemiluminescent immunometric assay method. cTnI was considered positive when the value was >1ng/ml and study population was divided as per age, sex and cTnI level. The mean (+ SD) age of all patients was 55(+ 12.8) years and majority was males (82.20%). Seasonal variation showed highest positive cases in winter. In case of circadian variation positive cTnI results were suggestive of morning peak of AMI. Positive results were obtained in 32.3% of Cases. cTnI is now considered as a better indicator of myocardial injury. Further study in depth is necessary to correlate with clinical symptoms and other diagnostic tests to make a complete profile of AMI according to the latest subtypes. DOI: http://dx.doi.org/10.3329/bmj.v42i1.18969 Bangladesh Med J. 2013 Jan; 42 (1): 3-6

scholarly journals Imaging Evaluation of Pulmonary and Non-Ischaemic Cardiovascular Manifestations of COVID-19

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1271
Author(s):  
Sebastiano Cicco ◽  
Antonio Vacca ◽  
Christel Cariddi ◽  
Rossella Carella ◽  
Gianluca Altamura ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Myocardial Injury ◽  
Nuclear Imaging ◽  
Emergency Setting ◽  
Imaging Evaluation ◽  
Coagulation Abnormalities ◽  
Cardiovascular Involvement ◽  
Highly Sensitive ◽  
Inflammatory Syndrome ◽  
Inflammatory Burden

Coronavirus Disease 2019 (COVID-19) has been a pandemic challenge for the last year. Cardiovascular disease is the most described comorbidity in COVID-19 patients, and it is related to the disease severity and progression. COVID-19 induces direct damage on cardiovascular system, leading to arrhythmias and myocarditis, and indirect damage due to endothelial dysfunction and systemic inflammation with a high inflammatory burden. Indirect damage leads to myocarditis, coagulation abnormalities and venous thromboembolism, Takotsubo cardiomyopathy, Kawasaki-like disease and multisystem inflammatory syndrome in children. Imaging can support the management, assessment and prognostic evaluation of these patients. Ultrasound is the most reliable and easy to use in emergency setting and in the ICU as a first approach. The focused approach is useful in management of these patients due its ability to obtain quick and focused results. This tool is useful to evaluate cardiovascular disease and its interplay with lungs. However, a detailed echocardiography evaluation is necessary in a complete assessment of cardiovascular involvement. Computerized tomography is highly sensitive, but it might not always be available. Cardiovascular magnetic resonance and nuclear imaging may be helpful to evaluate COVID-19-related myocardial injury, but further studies are needed. This review deals with different modalities of imaging evaluation in the management of cardiovascular non-ischaemic manifestations of COVID-19, comparing their use in emergency and in intensive care.

Biological variation of cardiac myosin-binding protein C in healthy individuals

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Bashir Alaour ◽  
Torbjørn Omland ◽  
Janniche Torsvik ◽  
Thomas E. Kaier ◽  
Marit S. Sylte ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Protein C ◽  
Myocardial Injury ◽  
Binding Protein ◽  
Biological Variation ◽  
Cardiac Myosin ◽  
Analytical Quality ◽  
Myosin Binding Protein ◽  
Myosin Binding Protein C ◽  
Myosin Binding

Abstract Objectives Cardiac myosin-binding protein C (cMyC) is a novel biomarker of myocardial injury, with a promising role in the triage and risk stratification of patients presenting with acute cardiac disease. In this study, we assess the weekly biological variation of cMyC, to examine its potential in monitoring chronic myocardial injury, and to suggest analytical quality specification for routine use of the test in clinical practice. Methods Thirty healthy volunteers were included. Non-fasting samples were obtained once a week for ten consecutive weeks. Samples were tested in duplicate on the Erenna® platform by EMD Millipore Corporation. Outlying measurements and subjects were identified and excluded systematically, and homogeneity of analytical and within-subject variances was achieved before calculating the biological variability (CVI and CVG), reference change values (RCV) and index of individuality (II). Results Mean age was 38 (range, 21–64) years, and 16 participants were women (53%). The biological variation, RCV and II with 95% confidence interval (CI) were: CVA (%) 19.5 (17.8–21.6), CVI (%) 17.8 (14.8–21.0), CVG (%) 66.9 (50.4–109.9), RCV (%) 106.7 (96.6–120.1)/−51.6 (−54.6 to −49.1) and II 0.42 (0.29–0.56). There was a trend for women to have lower CVG. The calculated RCVs were comparable between genders. Conclusions cMyC exhibits acceptable RCV and low II suggesting that it could be suitable for disease monitoring, risk stratification and prognostication if measured serially. Analytical quality specifications based on biological variation are similar to those for cardiac troponin and should be achievable at clinically relevant concentrations.

scholarly journals ST-Elevation Myocardial Infarction and COVID-19 Pneumonia: The Importance of Risk-Stratification of Myocardial Injury in COVID-19 Era

2021 ◽  
pp. 263246362199238
Author(s):  
Julio C. Sauza-Sosa ◽  
Oscar Millan-Iturbe ◽  
Jorge Mendoza-Ramirez ◽  
Carlos N. Velazquez-Gutierrez ◽  
Erika Lizeth De la Cruz Reyna ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Injury Risk ◽  
Myocardial Injury ◽  
Cardiovascular Complications ◽  
Adverse Outcomes ◽  
St Elevation ◽  
Diagnostic Coronary Angiography ◽  
Serial Measurements ◽  
Initial Classification

Background: Myocardial injury is a common manifestation in patients with coronavirus disease (COVID-19), and the correlation with adverse outcomes has been demonstrated; therefore, adequate monitoring of myocardial injury markers is very important. Case Summary: A patient with COVID-19 was hospitalized in our hospital with an initial classification of intermediate risk for myocardial injury, after serial measurements of myocardial injury markers, risk was readjusted to high, as shown later by electrocardiographic abnormalities. The patient underwent emergency diagnostic coronary angiography and successful angioplasty. The patient was discharged to home. Discussion: Myocardial injury risk-stratification is essential in patients with COVID-19, since it is essential in the recognition of patients who are susceptible to cardiovascular complications.

scholarly journals Cardiac MRI and Myocardial Injury in COVID-19: Diagnosis, Risk Stratification and Prognosis

Diagnostics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 130
Author(s):  
Saagar K. Sanghvi ◽  
Logan S. Schwarzman ◽  
Noreen T. Nazir
Keyword(s):  
Risk Stratification ◽  
Myocardial Injury ◽  
Cardiac Tissue ◽  
Contractile Function ◽  
Imaging Modality ◽  
Acute Myocarditis ◽  
Myocardial Inflammation ◽  
Critical Data ◽  
Non Invasive ◽  
Risk Of Exposure

Myocardial injury is a common complication of the COVID-19 illness and is associated with a worsened prognosis. Systemic hyperinflammation seen in the advanced stage of COVID-19 likely contributes to myocardial injury. Cardiac magnetic resonance imaging (CMR) is the preferred imaging modality for non-invasive evaluation in acute myocarditis, enabling risk stratification and prognostication. Modified scanning protocols in the pandemic setting reduce risk of exposure while providing critical data regarding cardiac tissue inflammation and fibrosis, chamber remodeling, and contractile function. The growing use of CMR in clinical practice to assess myocardial injury will improve understanding of the acute and chronic sequelae of myocardial inflammation from various pathological etiologies.

Abstract 16185: Biomarker-based Heart Failure Risk Stratification in Patients With Atherosclerotic Cardiovascular Disease: Observations From HPS-3/TIMI-55-REVEAL

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
David Berg ◽  
Stephen D Wiviott ◽  
Eugene Braunwald ◽  
David A Morrow ◽  
Keyword(s):  
Heart Failure ◽  
Cardiovascular Disease ◽  
Myocardial Injury ◽  
Cox Regression ◽  
Troponin T ◽  
Risk Indicators ◽  
Atherosclerotic Cardiovascular Disease ◽  
Circulating Biomarkers ◽  
Clinical Risk ◽  
Hemodynamic Stress

Background: Circulating biomarkers reflecting pathways implicated in heart failure (HF) may improve HF risk assessment in patients with stable atherosclerotic cardiovascular disease (ASCVD). Hypothesis: We aimed to evaluate the performance of circulating biomarkers of hemodynamic stress, myocardial injury, and inflammation for the prediction of hospitalization for HF (HHF) in a large well-characterized cohort with stable ASCVD followed for a median of 4.1 years. Methods: HPS3/TIMI 55-REVEAL was a randomized, double-blind, placebo-controlled trial of the CETP inhibitor anacetrapib in patients with stable ASCVD. We performed a nested prospective biomarker study, measuring high-sensitivity troponin T (hsTnT), N-terminal pro-B-type natriuretic peptide (NT-proBNP), and growth differentiation factor-15 (GDF-15) (all Roche Diagnostics) at randomization (n=29,673). Hazard ratios were adjusted for covariates of a priori clinical relevance to HHF risk: age, prior HF, hypertension, diabetes mellitus, eGFR <60, body-mass index, and polyvascular disease. Discrimination was assessed using Harrell’s c-index. Results: A significant graded risk of HHF was observed with increasing deciles of hsTnT, NT-proBNP, and GDF-15 (p-trend <0.001 for each) ( Figure ). These associations remained significant after multivariable adjustment for clinical risk factors (p<0.001 for each). When added to a multivariable Cox regression model of clinical risk indicators (c-index 0.74), these 3 biomarkers significantly improved the prognostic performance of the model (c-index 0.85; p<0.001). There was no treatment interaction with anacetrapib. Conclusions: In patients with stable ASCVD, biomarkers of myocardial injury, hemodynamic stress, and inflammation provide incremental information for prediction of HHF. Future studies should address whether these patients are more likely to benefit from emerging HF preventive therapies.

Abstract P019: A Single Model For Predicting Major Adverse Cardiovascular Events In Individuals With And Without History Of Atherosclerotic Cardiovascular Disease: The Atherosclerosis Risk In Communities (aric) Study

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Yejin Mok ◽  
Lena Mathews ◽  
Ron C Hoogeveen ◽  
Michael J Blaha ◽  
Christie M Ballantyne ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Cardiovascular Disease ◽  
High Risk ◽  
Risk Stratification ◽  
Cardiovascular Events ◽  
Major Adverse Cardiovascular Events ◽  
Atherosclerotic Cardiovascular Disease ◽  
Single Model ◽  
History Of ◽  
Very High

Background: In the 2018 AHA/ACC Cholesterol guideline, risk stratification is an essential element. The use of a Pooled Cohort Equation (PCE) is recommended for individuals without atherosclerotic cardiovascular disease (ASCVD), and the new dichotomous classification of very high-risk vs. high-risk has been introduced for patients with ASCVD. These distinct risk stratification systems mainly rely on traditional risk factors, raising the possibility that a single model can predict major adverse cardiovascular events (MACEs) in persons with and without ASCVD. Methods: We studied 11,335 ARIC participants with (n=885) and without (n=10,450) a history of ASCVD (myocardial infarction, ischemic stroke, and symptomatic peripheral artery disease) at baseline (1996-98). We modeled factors in the PCE and the new classification for ASCVD patients (Figure legend) in a single CVD prediction model. We examined their associations with MACEs (myocardial infarction, stroke, and heart failure) using Cox models and evaluated the discrimination and calibration for a single model including those factors. Results: During a median follow-up of 18.4 years, there were 3,658 MACEs (3,105 in participants without ASCVD). In general, the factors in the PCE and the risk classification system for ASCVD patients were associated similarly with MACEs regardless of baseline ASCVD status, although age and systolic blood pressure showed significant interactions. A single model with these predictors and the relevant interaction terms showed good calibration and discrimination for those with and without ASCVD (c-statistic=0.729 and 0.704, respectively) (Figure). Conclusion: A single CVD prediction model performed well in persons with and without ASCVD. This approach will provide a specific predicted risk to ASCVD patients (instead of dichotomy of very high vs. high risk) and eliminate a practice gap between primary vs. secondary prevention due to different risk prediction tools.

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