Key result
Type 2 diabetes fails to independently predict major CV events after imaging adjustment.
Why the study?
Patients with prediabetes or diabetes are at increased risk of cardiovascular disease and adverse outcomes, but the impact of diabetes on the relationship between CAD and long-term outcome is unclear.
Does prediabetes or type 2 diabetes increase the risk of a composite of all-cause mortality, MI, and UAP in patients with suspected coronary artery disease?
Cohort (n=1,743)
No
Does prediabetes or type 2 diabetes increase the risk of a composite of all-cause mortality, MI, and UAP in patients with suspected coronary artery disease?
Hazard Ratio: 1.12 (95% CI 0.76–1.64)
Absolute Event Rate: 2.16% vs 1.23%
p-value: p=0.570
Coronary CTA followed by selective PET myocardial perfusion imaging predicts long-term outcomes similarly in non-diabetic and diabetic patients, with diabetes not being an independent predictor after adjusting for imaging findings.
CTA/PET findings may supersede diabetes status for prognostication in suspected CAD; hypothesis-generating for imaging-based risk models.
BACKGROUND: Patients with prediabetes or diabetes are at increased risk of developing cardiovascular disease and adverse outcomes. First-line coronary computed tomography angiography (CTA) followed by selective use of positron emission tomography (PET) myocardial perfusion imaging is a feasible strategy to diagnose and risk-stratify patients with suspected coronary artery disease (CAD). The aim of the present study was to study whether diabetes changes the relationship of CAD and long-term outcome. METHODS: O-water PET myocardial perfusion imaging. The relationship of the phenotype of CAD and long-term outcome in patients with no diabetes, prediabetes, or type 2 diabetes was investigated. A composite endpoint included all-cause mortality, myocardial infarction (MI), and unstable angina pectoris (UAP). RESULTS: A total of 1743 patients were included: 1214 (70%) non-diabetic, 259 (15%) prediabetic, and 270 (16%) type 2 diabetic patients. During 6.43 years of median follow-up, 164 adverse events occurred (106 deaths, 41 MIs, 17 UAPs). The prevalence of normal coronary arteries on CTA was highest in the non-diabetic patients (39%). The prevalence of hemodynamically significant CAD (abnormal perfusion) increased from 14% in non-diabetic patients to 20% in prediabetic and 27% in diabetic patients. The event rate was lowest in patients with normal coronary arteries and highest in patients with concomitant type 2 diabetes and hemodynamically significant CAD (annual event rate 0.2% vs. 4.7%). However, neither prediabetes nor diabetes were independent predictors of the composite adverse outcome after adjustment for the clinical risk factors and imaging findings. CONCLUSIONS: Coronary CTA followed by selective downstream use of PET myocardial perfusion imaging predicts long-term outcome similarly in non-diabetic and diabetic patients.
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Mäenpää et al. (2023) conducted a cohort in Suspected coronary artery disease (n=1,743). Type 2 diabetes vs. No diabetes was evaluated on Composite of all-cause mortality, myocardial infarction (MI), and unstable angina pectoris (UAP) (HR 1.12, 95% CI 0.76-1.64, p=0.570). Type 2 diabetes was not an independent predictor of all-cause mortality, myocardial infarction, or unstable angina (HR 1.12) after adjusting for clinical risk factors and CTA/PET imaging findings.
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