Prevalence, Consequences, and Implications for Clinical Trials of Unrecognized Myocardial Infarction

Pride, Yuri B.; Piccirillo, Bryan; Gibson, C. Michael

doi:10.1016/j.amjcard.2012.11.042

Cited by 64 publications

(55 citation statements)

References 44 publications

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“…CMR can identify myocardial scar related to myocardial infarction as well as other nonischemic etiologies. Clinical trials now accept unrecognized myocardial scars detected by CMR as endpoints, 9 as they often lead to major adverse cardiac events. 1,5 …”

Section: Introductionmentioning

confidence: 99%

Prevalence and Correlates of Myocardial Scar in a US Cohort

Türkbey

Nacif

Guo

et al. 2015

JAMA

123

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Importance Myocardial scarring leads to cardiac dysfunction and poor prognosis. The prevalence of and factors associated with unrecognized myocardial infarction and scar have not been previously defined using current methods in a multi-ethnic US population. Objective To determine prevalence of and factors associated with myocardial scar in middle and older aged individuals in the United States (U.S). Design, Setting, and Participants Multi-Ethnic Study of Atherosclerosis (MESA) is a population based cohort in the U.S. MESA participants were 45-84 years old and free of clinical cardiovascular disease (CVD) at baseline in 2000-2002. In the 10th year examination of MESA (2010-2012), 1840 participants underwent cardiac magnetic resonance imaging (CMR) with gadolinium to detect myocardial scar. CVD risk factors and coronary artery calcium scores were measured at baseline and year 10. Logistic regression models were used to estimate adjusted odds ratios for myocardial scar. Exposures Cardiovascular risk factors, coronary artery calcium, left ventricle size and function, carotid intima media thickness Main Outcome Measure Myocardial scar detected by CMR. Results Of 1840 participants (mean age 68±9 yrs, 52% male), 146 had myocardial scars (7.9%). Most myocardial scars (114/146, 78%) were undetected by electrocardiogram or by clinical adjudication. In adjusted models, age, male gender, body mass index, hypertension, and current smoking at baseline were associated with myocardial scar at year 10 [OR (95% CI): 1.6 (1.4, 1.9) per 8.9 years, p<0.001; 5.8 (3.6, 9.2) men vs. women, p<0.001; 1.3 (1.1, 1.6) per 4.8 kg/m2, p=0.005, 1.6 (1.1, 2.3) for hypertension present, p=0.009; 2.0 (1.2, 3.3) current vs. never smokers, p=0.006, respectively]. Age, gender and ethnicity adjusted CAC score at baseline was also associated with myocardial scar at year 10 [CAC categories of 1-99, 100-399 and ≥ 400 vs. CAC =0: OR (95% CI): 2.4 (1.5, 3.9), 3.0 (1.7, 5.1), 3.3 (1.7, 6.1), respectively, p≤0.001]. CAC score significantly added to the association of myocardial scar with age, gender, ethnicity and traditional CVD risk factors (c-statistic: 0.81 vs. 0.79, with vs. without CAC, respectively, p=0.012). Conclusions and Relevance The prevalence of myocardial scars in a US community based multiethnic cohort was 7.9%, of which 78% were unrecognized by electrocardiography or clinical evaluation. Further studies are needed to understand the clinical consequences of these undetected scars and the utility of their identification.

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Section: Introductionmentioning

confidence: 99%

Prevalence and Correlates of Myocardial Scar in a US Cohort

Türkbey

Nacif

Guo

et al. 2015

JAMA

123

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“…11) At the same time, aging also increases the risk of heart failure, cardiogenic shock, atrial fibrillation, and cardiac perforation. 3) Growing evidences suggest miRNAs as potential diagnostic markers to distinguish patients with ACS from those without ACS. 12,13) However, there are few studies aiming to investigate elderly ACS patients, especially the early diagnosis of UA.…”

Section: Discussionmentioning

confidence: 99%

Plasmatic MicroRNA Signatures in Elderly People with Stable and Unstable Angina

Cui

Song

et al. 2018

Int. Heart J.

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SummaryWe aimed to investigate the distinctive miRNA profiles in the plasma of elderly patients with unstable angina (UA) and stable angina (SA), and to find more effective markers of UA in elderly people. We compared miRNA expression levels in plasma samples from 10 elderly patients with UA and 10 elderly patients with SA by using microarray-based miRNA chip, and then performed validation with Real-time PCR. Mir-1202, mir-1207-5p, and mir-1225-5p showed a statistically significant down-regulation (P < 0.05), while mir-3162-3p showed an up-regulation (P < 0.05) during validation. Among all single miRNAs, miR-3162-3p showed the highest discriminatory power in the diagnosis of elderly patients with UA (AUC: 0.79, 95% CI: 0.675-0.905). The discriminatory power of a panel of three miRNAs (mir-3162-3p/mir-1225-5p/mir-1207-5p) was highest with an AUC of 0.91 (95% CI: 0.84-0.98), followed by mir-3162-3p/mir-1225-5p (AUC: 0.833, 95% CI: 0.732-0.934) and mir-3162-3p/mir-1207-5p (AUC: 0.817, 95% CI: 0.712-0.922). In conclusion, multi-miRNA panel could provide higher diagnostic value for the diagnosis of elderly patients with UA.(Int Heart J 2018; 59: 43-50)

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“…We thus adjusted the baseline value of hs-CRP/WBC when estimating the effect of longitudinal changes in hs-CRP/WBC values on MI events. Further, the resting electrocardiogram has a low sensitivity to detect silent MI (36 ). To increase the sensitivity, we censored participants with abnormal Q-waves or ST-segment elevation in the sensitivity analysis.…”

Section: Discussionmentioning

confidence: 99%