Post-ST-Segment Elevation Myocardial Infarction Follow-Up Care During the COVID-19 Pandemic and the Possible Benefit of Telemedicine: An Observational Study

Long-term Prognosis of Acute Myocardial Infarction Associated with Metabolic Health and Obesity Status

BACKGROUND

Emerging evidence supports the favourable cardiovascular health in non-obese subjects with healthy metabolism. However, little is known regarding the prognosis across the range of metabolic phenotypes once cardiovascular disease is established. We examined the prognosis of patients with acute myocardial infarction (AMI) stratified according to metabolic health and obesity status.

METHODS

This is a retrospective study on consecutive patients with AMI admitted to a tertiary hospital between 2014-2021. Patients were allocated into 4 groups based on metabolic and obesity profile: metabolically healthy obese (MHO), metabolically healthy non-obese (MHNO), metabolically unhealthy obese (MUO) and metabolically unhealthy non-obese (MUNO). Metabolic health was defined in accordance to the BioSHARE-EU Healthy Obese Project. The primary outcome was all-cause mortality. Cox regression analysis examined the independent association between mortality and metabolic phenotypes, adjusting for age, sex, AMI type, chronic kidney disease, smoking status and left ventricular ejection fraction.

RESULTS

Of 9958 patients, the majority (68.5%) were MUNO, followed by MUO (25.1%), MHNO (5.6%), and MHO (0.8%). MHO had the lowest mortality (7.4%), followed by MHNO (9.7%), MUO (19.2%) and MUNO (22.6%) (p<0.001). Compared to MHNO, MUO (HR 1.737, 95%CI 1.282-2.355, p<0.001) and MUNO (HR 1.482, 95%CI 1.108-1.981, p=0.008) had significantly higher mortality risk, but not MHO (HR 1.390, 95%CI 0.594-3.251, p=0.447), after adjusting for confounders. Kaplan-Meier curves showed favourable survival in the metabolically healthy and obesity groups, with the highest overall survival in the MHO followed by MHNO, MUO and MUNO (p<0.001).

CONCLUSION

Metabolically healthy and obese AMI patients have favourable prognosis compared to metabolically unhealthy and non-obese patients. It is equally important to prioritize intensive metabolic risk factor management to weight reduction in the early phase after AMI.

Incremental Prognostic Value of Pericoronary Adipose Tissue Thickness Measured Using Cardiac Magnetic Resonance Imaging After Revascularization in Patients With ST-Elevation Myocardial Infarction

Background and Aim

Pericoronary adipose tissue (PCAT) reflects pericoronary inflammation and is associated with coronary artery disease. We aimed to identify the association between local PCTA thickness using cardiac magnetic resonance (CMR) and prognosis of patients with ST-elevation myocardial infarction (STEMI), and to investigate the incremental prognostic value of PCAT thickness in STEMI after reperfusion.

Methods

A total of 245 patients with STEMI (mean age, 55.61 ± 10.52 years) who underwent CMR imaging within 1 week of percutaneous coronary intervention therapy and 35 matched controls (mean age, 53.89 ± 9.45 years) were enrolled. PCAT thickness indexed to body surface area at five locations, ventricular volume and function, infarct-related parameters, and global strain indices were evaluated using CMR. Associations between PCAT thickness index and 1-year major adverse cardiovascular events (MACE) after STEMI were calculated. The prognostic value of the standard model based on features of clinical and CMR and updated model including PACT thickness index were further assessed.

Results

Patients with MACE had a more significant increase in PCAT thickness index at superior interventricular groove (SIVGi) than patients without MACE. The SIVGi was significantly associated with left ventricular ejection fraction (LVEF), infarct size, and global deformation. SIVGi &gt; 4.98 mm/m2 was an independent predictor of MACE (hazard ratio, 3.2; 95% CI: 1.6–6.38; p &lt; 0.001). The updated model significantly improved the power of prediction and had better discrimination ability than that of the standard model for predicting 1-year MACE (areas under the ROC curve [AUC] = 0.8 [95% CI: 0.74–0.87] vs. AUC = 0.76 [95% CI: 0.68–0.83], p &lt; 0.05; category-free net reclassification index [cfNRI] = 0.38 [95% CI: 0.1–0.53, p = 0.01]; integrated discrimination improvement [IDI] = 0.09 [95% CI: 0.01–0.18, p = 0.02]).

Conclusions

This study demonstrated SIVGi as an independent predictor conferred incremental value over standard model based on clinical and CMR factors in 1-year MACE predictions for STEMI.