Background <p>Epicardial adipose tissue (EAT) independently predicts adverse cardiovascular events. Prediabetes with metabolic syndrome carries high cardiovascular risk, yet EAT in this critical subpopulation versus incident type-2 diabetes (T2D) remains unexplored.</p> Methods <p>Coronary CT-angiography records were retrospectively reviewed to compare adults with prediabetes (impaired fasting glucose 110–125&#xa0;mg/dL and HbA1c &lt; 6.5%) having ≥ 3 of 4 cardiometabolic risk indicators (overweight/obese, hypertension, statin use/hypertriglyceridemia, and statin use/low HDL-cholesterol; <i>n</i> = 44) with drug-naïve T2D (<i>n</i> = 44) and normoglycemic individuals (<i>n</i> = 50). Groups were matched for age, gender, body mass index (BMI), hypertension, statin use, smoking and coronary artery calcium score (CACS). EAT volume and attenuation were quantified using semi-automated software.</p> Results <p>The high-risk prediabetes cohort (median age 53.5 [IQR 47–61] years; males 59.1%; overweight/obese, 95.5%; CACS &gt; 0, 47.7%) exhibited EAT volume similar to T2D (median [IQR]: 93 [76.5-120.5] mL <i>versus</i> 88.4 [72.5–112] mL; p<sub>bonferroni</sub>=0.713), with both being significantly greater than normoglycemic individuals (72.8 [51–104] mL, p<sub>bonferroni</sub>&lt;0.05). EAT/height<sup>2</sup>, EAT/body surface area(BSA) and EAT/BMI demonstrated similar trends; whereas average EAT attenuation did not differ across the groups. EAT/BSA demonstrated highest discriminatory ability for prediabetes (AUC = 0.683) and T2D (AUC = 0.692) from normoglycemia (<i>p</i> &lt; 0.007). An EAT/BSA threshold of 48.0 mL/m<sup>2</sup> for high-risk prediabetes yielded 66% specificity and 70.5% sensitivity.</p> Conclusion <p>Substantial EAT accumulation is evident in individuals with prediabetes and additional cardiometabolic risk indicators such as overweight, hypertension, and dyslipidemia. These findings highlight a critical need to explore timely targeted interventions to mitigate cardiovascular risk in this vulnerable subgroup akin to those employed in T2D.</p>

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Comparable epicardial adipose tissue burden in prediabetes with high cardiometabolic risk and early type 2 diabetes: A need for timely targeted therapies

  • Mainak Banerjee,
  • Subhajit Das,
  • Debrupa Deb,
  • Debabrata Roy,
  • Pradeep Narayan,
  • Debasree Biswas,
  • Debika Chatterjee

摘要

Background

Epicardial adipose tissue (EAT) independently predicts adverse cardiovascular events. Prediabetes with metabolic syndrome carries high cardiovascular risk, yet EAT in this critical subpopulation versus incident type-2 diabetes (T2D) remains unexplored.

Methods

Coronary CT-angiography records were retrospectively reviewed to compare adults with prediabetes (impaired fasting glucose 110–125 mg/dL and HbA1c < 6.5%) having ≥ 3 of 4 cardiometabolic risk indicators (overweight/obese, hypertension, statin use/hypertriglyceridemia, and statin use/low HDL-cholesterol; n = 44) with drug-naïve T2D (n = 44) and normoglycemic individuals (n = 50). Groups were matched for age, gender, body mass index (BMI), hypertension, statin use, smoking and coronary artery calcium score (CACS). EAT volume and attenuation were quantified using semi-automated software.

Results

The high-risk prediabetes cohort (median age 53.5 [IQR 47–61] years; males 59.1%; overweight/obese, 95.5%; CACS > 0, 47.7%) exhibited EAT volume similar to T2D (median [IQR]: 93 [76.5-120.5] mL versus 88.4 [72.5–112] mL; pbonferroni=0.713), with both being significantly greater than normoglycemic individuals (72.8 [51–104] mL, pbonferroni<0.05). EAT/height2, EAT/body surface area(BSA) and EAT/BMI demonstrated similar trends; whereas average EAT attenuation did not differ across the groups. EAT/BSA demonstrated highest discriminatory ability for prediabetes (AUC = 0.683) and T2D (AUC = 0.692) from normoglycemia (p < 0.007). An EAT/BSA threshold of 48.0 mL/m2 for high-risk prediabetes yielded 66% specificity and 70.5% sensitivity.

Conclusion

Substantial EAT accumulation is evident in individuals with prediabetes and additional cardiometabolic risk indicators such as overweight, hypertension, and dyslipidemia. These findings highlight a critical need to explore timely targeted interventions to mitigate cardiovascular risk in this vulnerable subgroup akin to those employed in T2D.