Silent MIs associated with high risk of developing HF
Silent Myocardial Infarction and Long-Term Risk of Heart Failure The ARIC StudyLiterature - Qureshi WT, Zhang Z-M, Chang PP, et al. - J Am Coll Cardiol 2018;71:1–8
- During a median follow-up of 13.0 years (IQR: 12.2-13.9 years), the incidence rates of HF were higher in CMI and SMI patients compared with individuals without MI (30.4, 16.2, and 7.8 per 1,000 person-years, respectively [P<0.001]). The cumulative incidence of HF stratified by MI status was 31.4% for CMI, 17.7% for SMI, and 9.5% for no MI.
- In multivariable-adjusted Cox proportional hazard models, compared with no MI, both CMI and SMI were significantly associated with HF (fully adjHR for CMI: 2.85; 95% CI: 2.31-3.51; P<0.001; fully adjHR for SMI: 1.35; 95% CI: 1.02-1.78; P=0.035), independently of demographics and clinical risk factors.
- In subgroup analyses stratified by demographics and HF risk factors, the pattern of associations between MI status and HF was consistent among subgroups with the exception of age. The risk of HF associated with SMI was higher in younger patients compared with those at or older than the median age of 53 years (HR: 1.66; 95% CI: 1.00 to 2.75 vs. HR: 1.19; 95% CI: 0.85 to 1.66, respectively).
In a large, community-based study, both CMI and SMI were significantly associated with HF, compared with the absence of MI. These results suggest that it might be worth paying particular attention to patients with SMI in the context of HF prevention.
In their editorial article , Gibson et al. comment that the analysis of Qureshi et al. contributes with new evidence to the early identification of an elevated HF risk in patients with SMI. As SMI accounts for 5 to 30% of the total number of all nonfatal MI , the addition of this outcome to a composite endpoint may increase the number of events in a clinical trial. This would result in increased statistical power, reduce the required sample size and thereby reduce the duration and cost of RCTs. In addition, early identification of patients with increased risk of HF is crucial because early initiation of treatment may improve the prognosis of patients and thereby reduce healthcare costs. Furthermore, the authors discuss the limitations of the study: the exclusion of a large number of patients with missing ECGs, the retrospective nature of the HF diagnosis, the use of ECGs only for the diagnosis of SMI, and the lack of imaging evidence of the SMIs. They conclude: ‘Nonetheless, in an era when complex microRNA samples and biomarkers are being developed to identify patients with an increased risk of heart failure, Qureshi et al. remind us that, sometimes, preventive cardiology could be as simple as a Q-wave.’