Prognostic implications of quantified coronary atherosclerosis and myocardial perfusion in diabetes
Authors' conclusion
Coronary atherosclerotic plaque burden appears as an important predictor of long-term cardiovascular outcomes both in diabetic and non-diabetic patients. In patients with diabetes, normal myocardial perfusion does not necessarily imply low event risk, partly attributable to higher coronary plaque burden. Quantitative imaging methods for detailed CAD phenotyping shed light on the complex relationship between diabetes and clinical outcomes.
Study context
- Population
- Symptomatic patients with suspected coronary artery disease (CAD) undergoing coronary computed tomography angiography (CTA) and [15O]H2O positron emission tomography (PET) perfusion imaging; 251 (19%) with diabetes251 with diabetes
- Participants
- 1,311 patients
- Exposure
- Diabetic vs non-diabetic patients with suspected CAD; quantified plaque burden (percent atheroma volume (PAV)) and PET myocardial perfusion
- Outcome
- Composite of:
- All-cause death
- Myocardial infarction (MI)
- Unstable angina pectoris
- Follow-up
- 7 years
Methodological detailsPlaque burden quantified by artificial intelligence-based analysis as PAV
- Plaque burden quantified by artificial intelligence-based analysis as PAV
Main finding
As reported in the abstract
P < 0.001
- Patients with an adverse event during follow-up
- 134 (10%)
Observational data: associations, not effects.
Further findings
| Outcome | Diabetes | P value |
|---|---|---|
| PAV among patients with normal perfusionDiabetes vs Non-diabetic · two-fold PAV with diabetes | median 8.2 % | P < 0.001 |
- PAV among patients with normal perfusion: Non-diabetic median 4.1 %
Predictors of adverse outcome, non-diabetic patients (multivariable Cox)
- PAV, HR per 1% increase
- HR 1.03 (95% CI 1.01-1.05), p < 0.001
- Regional stress myocardial blood flow (sMBF), HR per 0.1 ml/g/min decrease
- HR 1.04 (95% CI 1.01-1.07), p = 0.016
- Multivariable Cox regression
Predictors of adverse outcome, diabetic patients (multivariable Cox)
- PAV, HR
- HR 1.04 (95% CI 1.01-1.07), p = 0.014
- sMBF was not predictive
- Multivariable Cox regression
Original publication
Composed by AI from the published abstract and checked against it. How Briefs are made →