Quantitative and qualitative assessment of acute myocardial injury by CMR at multiple time points after acute myocardial infarction

Introduction. Acute respiratory distress syndrome (ARDS) and cardiovascular events, acute myocardial injury being the most frequent of the latter, are among the leading causes of death in COVID-19 patients. The lack of consensus on acute myocardial injury pathogenesis mechanisms, the patients management, treatment an rehabilitation logistics, the anticoagulant treatment in identified SARS-CoV-2 or suspected COVID-19 patients setting indicates the need to assess, analyze and summarize the available data on the issue.Materials and methods. Scientific publications search was carried out in PubMed, Google Scholar databases for the period from December 2019 to September 2021.Results and Discussion. Cardiospecific troponin I increase beyond reference limits is reported to occur in at least every tenth patient with identified SARS-CoV-2, the elevated troponin detection rate increasing among persons with moderate to severe course of the infection. The mechanisms of acute myocardial injury in patients with COVID-19 are poorly understood. By September 2021, there are several pathogenesis theories. A high frequency viral myocarditis direct cardiomyocytes damage is explained by the high SARS-CoV-2 affinity to ACE2 expressed in the myocardium. The cytokine storm related myocardial damage is reported a multiple organ failure consequence. Coagulopathy may also trigger myocardial microvessels damage. Up to every third death of SARS-CoV-2 infected persons is related to the acute myocardial injury. At the same time, due to the high incidence of the acute myocardial injury, it is rather difficult to assess the true incidence of acute myocardial infarction in patients with COVID-19. In the pandemic setting, the waiting time for medical care increases, the population, trying to reduce social contacts, is less likely to seek medical help. In this regard, in order to provide effective medical care to patients with acute myocardial infarction, it is necessary to develop algorithms for providing care adapted to the current epidemiological situation.Conclusion. The treatment of patients with probable development of acute myocardial damage against the background of new coronavirus infection should be performed in accordance with the current clinical guidelines. Anticoagulant therapy should be administered in a prophylactic dose under control of hemostasis parameters and a wide range of biochemical parameters.

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Myocardial Perfusion Studies - Direct Imaging of Acute Myocardial Injury with 99mTc-Pyrophosphate

Nuklearmedizin ◽

10.1055/s-0037-1620685 ◽

1978 ◽

Vol 17 (04) ◽

pp. 157-160

Author(s):

J. W. Keyes

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Myocardial Perfusion ◽

Myocardial Injury ◽

Myocardial Tissue ◽

Direct Imaging ◽

Perfusion Studies ◽

Acute Myocardial Injury ◽

Myocardial Perfusion Studies

Imaging of acute myocardial injury is possible with a large number of agents. All of these agents share similar patterns of uptake in acutely injured myocardial tissue. The technique appears to be a reliable way of ruling in or out the diagnosis of acute myocardial infarction.

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Copeptin Testing in Acute Myocardial Infarction: Ready for Routine Use?

Disease Markers ◽

10.1155/2015/614145 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9 ◽

Cited By ~ 8

Author(s):

Sebastian Johannes Reinstadler ◽

Gert Klug ◽

Hans-Josef Feistritzer ◽

Bernhard Metzler ◽

Johannes Mair

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Risk Stratification ◽

Myocardial Injury ◽

Early Stage ◽

Additional Information ◽

Acute Myocardial Injury ◽

Coronary Syndromes ◽

Suspected Acute Myocardial Infarction ◽

Cardiac Troponins

Suspected acute myocardial infarction is one of the leading causes of admission to emergency departments. In the last decade, biomarkers revolutionized the management of patients with suspected acute coronary syndromes. Besides their pivotal assistance in timely diagnosis, biomarkers provide additional information for risk stratification. Cardiac troponins I and T are the most sensitive and specific markers of acute myocardial injury. Nonetheless, in order to overcome the remaining limitations of these markers, novel candidate biomarkers sensitive to early stage of disease are being extensively investigated. Among them, copeptin, a stable peptide derived from the precursor of vasopressin, emerged as a promising biomarker for the evaluation of suspected acute myocardial infarction. In this review, we summarize the currently available evidence for the usefulness of copeptin in the diagnosis and risk stratification of patients with suspected acute myocardial infarction in comparison with routine biomarkers.

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A Simplified Proposal to Redefine Acute Myocardial Infarction Versus Acute Myocardial Injury

Circulation ◽

10.1161/circulationaha.119.044996 ◽

2020 ◽

Vol 141 (18) ◽

pp. 1431-1433 ◽

Cited By ~ 2

Author(s):

Peter Nagele

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Myocardial Injury ◽

Acute Myocardial Injury

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Characterization of myocardial edema in rats with acute reperfused myocardial infarction at multiple time points by 7 T MR

Journal of Cardiovascular Magnetic Resonance ◽

10.1186/1532-429x-18-s1-p65 ◽

2016 ◽

Vol 18 (S1) ◽

Author(s):

Wei Chen ◽

Ziqian Xu ◽

Yushu Chen ◽

Ruzhi Zhang ◽

Jie Zheng ◽

...

Keyword(s):

Myocardial Infarction ◽

Myocardial Edema ◽

Multiple Time ◽

Reperfused Myocardial Infarction ◽

Time Points ◽

Multiple Time Points

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Type IV myocardial infarction associated with acute stent thrombosis in the early period after revascularization in a patient with new coronavirus infection COVID-19

Clinical Medicine (Russian Journal) ◽

10.30629/0023-2149-2021-99-5-6-369-374 ◽

2021 ◽

Vol 99 (5-6) ◽

pp. 369-374

Author(s):

V. N. Ardashev ◽

A. V. Nagovitsyn ◽

N. V. Zakaryan ◽

O. P. Donetskaya ◽

G. E. Kubenskiy ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Myocardial Injury ◽

Clinical Observation ◽

Early Period ◽

Thromboembolic Disease ◽

Type Iv ◽

Acute Myocardial Injury ◽

Coronavirus Infection ◽

Acute Stent Thrombosis

New facts suggest that COVID-19 coronavirus infection is partly mediated by hypercoagulability reactions characterized by micro- and macrovascular thrombotic angiopathy, which leads to acute myocardial injury, myocarditis, arrhythmias and numerous cases of pulmonary thromboembolic disease . The article presents a clinical observation of acute myocardial infarction development as a result of early thrombosis of an implanted coronary stent in a patient diagnosed with a new coronavirus infection COVID-19.

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Troponin least significant change (z-score) is associated with poor clinical outcomes in patients presenting to the emergency department

Annals of Clinical Biochemistry International Journal of Laboratory Medicine ◽

10.1177/0004563221992812 ◽

2021 ◽

pp. 000456322199281

Author(s):

Joel D Smith ◽

Kai'En Leong ◽

Timothy Fazio ◽

Cherie Chiang

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Emergency Department ◽

Length Of Stay ◽

Clinical Outcomes ◽

Myocardial Injury ◽

Significant Rise ◽

Z Score ◽

Troponin Elevation ◽

Acute Myocardial Injury

Background A rise and/or fall in high sensitivity cardiac troponin (hs-Tn) is critical in defining acute myocardial injury and therefore the diagnosis of acute myocardial infarction. A significant rise in hs-Tn is not well defined in current guidelines. Calculation of a z-score for two consecutive hs-Tn measurements is a method-independent measure of dynamic troponin elevation. However, the association of hs-Tn z-score with outcomes for unselected emergency department admissions is unknown. Moreover, the association of non-dynamic troponin elevations, as defined by a normal z-score, with clinical outcomes remains to be assessed. Methods We retrospectively calculated z-scores for patients presenting to emergency department over 18 months who had serial troponin measurements with at least one result >99th percentile using the Abbott hs-TnI assay. We assessed the association of z-score with discharge diagnosis, cardiac interventions, inpatient mortality, length of stay and readmission rates. Results There were 2062 presentations for 1830 patients where a z-score was calculated. Z-score was elevated in 1080 presentations. Dynamic troponin elevation (z-score ≥ 2) was associated with acute myocardial infarction (OR = 9.1, P < 0.01), admission to an inpatient unit (95 vs. 88%, P < 0.01), increased inpatient length of stay (97 vs. 65 days, P < 0.01), inpatient coronary intervention (21 vs. 6%, P < 0.01) and mortality (4.4 vs. 2.4%, P < 0.05) compared with myocardial injury with a static troponin elevation. Conclusions Z-score is an assay-independent tool to alert clinicians of significant, dynamic troponin elevation and acute myocardial injury. It is associated with poorer clinical outcomes.

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Use of TanDEM-X and SRTM-C Data for Detection of Deforestation Caused by Bark Beetle in Central European Mountains

Remote Sensing ◽

10.3390/rs13153042 ◽

2021 ◽

Vol 13 (15) ◽

pp. 3042

Author(s):

Kateřina Gdulová ◽

Jana Marešová ◽

Vojtěch Barták ◽

Marta Szostak ◽

Jaroslav Červenka ◽

...

Keyword(s):

Bark Beetle ◽

Synergistic Effects ◽

Canopy Height ◽

Surface Model ◽

Multiple Time ◽

Central European ◽

Time Points ◽

Bohemian Forest ◽

Multiple Time Points ◽

Surrounding Areas

The availability of global digital elevation models (DEMs) from multiple time points allows their combination for analysing vegetation changes. The combination of models (e.g., SRTM and TanDEM-X) can contain errors, which can, due to their synergistic effects, yield incorrect results. We used a high-resolution LiDAR-derived digital surface model (DSM) to evaluate the accuracy of canopy height estimates of the aforementioned global DEMs. In addition, we subtracted SRTM and TanDEM-X data at 90 and 30 m resolutions, respectively, to detect deforestation caused by bark beetle disturbance and evaluated the associations of their difference with terrain characteristics. The study areas covered three Central European mountain ranges and their surrounding areas: Bohemian Forest, Erzgebirge, and Giant Mountains. We found that vertical bias of SRTM and TanDEM-X, relative to the canopy height, is similar with negative values of up to −2.5 m and LE90s below 7.8 m in non-forest areas. In forests, the vertical bias of SRTM and TanDEM-X ranged from −0.5 to 4.1 m and LE90s from 7.2 to 11.0 m, respectively. The height differences between SRTM and TanDEM-X show moderate dependence on the slope and its orientation. LE90s for TDX-SRTM differences tended to be smaller for east-facing than for west-facing slopes, and varied, with aspect, by up to 1.5 m in non-forest areas and 3 m in forests, respectively. Finally, subtracting SRTM and NASA DEMs from TanDEM-X and Copernicus DEMs, respectively, successfully identified large areas of deforestation caused by hurricane Kyril in 2007 and a subsequent bark beetle disturbance in the Bohemian Forest. However, local errors in TanDEM-X, associated mainly with forest-covered west-facing slopes, resulted in erroneous identification of deforestation. Therefore, caution is needed when combining SRTM and TanDEM-X data in multitemporal studies in a mountain environment. Still, we can conclude that SRTM and TanDEM-X data represent suitable near global sources for the identification of deforestation in the period between the time points of their acquisition.

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Meta-analysis of effect sizes reported at multiple time points: A multivariate approach

Clinical Trials ◽

10.1177/1740774512453218 ◽

2012 ◽

Vol 9 (5) ◽

pp. 610-620 ◽

Cited By ~ 28

Author(s):

Thomas A Trikalinos ◽

Ingram Olkin

Keyword(s):

Random Effects ◽

Treatment Effects ◽

Multivariate Analyses ◽

Meta Analysis ◽

Effect Sizes ◽

Multiple Time ◽

Time Points ◽

Fixed And Random Effects ◽

Multiple Time Points ◽

Meta Analyses

Background Many comparative studies report results at multiple time points. Such data are correlated because they pertain to the same patients, but are typically meta-analyzed as separate quantitative syntheses at each time point, ignoring the correlations between time points. Purpose To develop a meta-analytic approach that estimates treatment effects at successive time points and takes account of the stochastic dependencies of those effects. Methods We present both fixed and random effects methods for multivariate meta-analysis of effect sizes reported at multiple time points. We provide formulas for calculating the covariance (and correlations) of the effect sizes at successive time points for four common metrics (log odds ratio, log risk ratio, risk difference, and arcsine difference) based on data reported in the primary studies. We work through an example of a meta-analysis of 17 randomized trials of radiotherapy and chemotherapy versus radiotherapy alone for the postoperative treatment of patients with malignant gliomas, where in each trial survival is assessed at 6, 12, 18, and 24 months post randomization. We also provide software code for the main analyses described in the article. Results We discuss the estimation of fixed and random effects models and explore five options for the structure of the covariance matrix of the random effects. In the example, we compare separate (univariate) meta-analyses at each of the four time points with joint analyses across all four time points using the proposed methods. Although results of univariate and multivariate analyses are generally similar in the example, there are small differences in the magnitude of the effect sizes and the corresponding standard errors. We also discuss conditional multivariate analyses where one compares treatment effects at later time points given observed data at earlier time points. Limitations Simulation and empirical studies are needed to clarify the gains of multivariate analyses compared with separate meta-analyses under a variety of conditions. Conclusions Data reported at multiple time points are multivariate in nature and are efficiently analyzed using multivariate methods. The latter are an attractive alternative or complement to performing separate meta-analyses.

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