In:
Journal of Thoracic Imaging, Ovid Technologies (Wolters Kluwer Health), Vol. 38, No. 3 ( 2023-05), p. 179-185
Abstract:
To investigate the long-term prognostic value of coronary computed tomography angiography (cCTA)-derived plaque information on major adverse cardiac events (MACE) in patients with and without diabetes mellitus. Materials and Methods: In all, 64 patients with diabetes (63.3±10.1 y, 66% male) and suspected coronary artery disease who underwent cCTA were matched with 297 patients without diabetes according to age, sex, cardiovascular risk factors, and statin and antithrombotic therapy. MACE were recorded. cCTA-derived risk scores and plaque measures were assessed. The discriminatory power to identify MACE was evaluated using multivariable regression analysis and concordance indices. Results: After a median follow-up of 5.4 years, MACE occurred in 31 patients (8.6%). In patients with diabetes, cCTA risk scores and plaque measures were significantly higher compared with nondiabetic patients (all P 〈 0.05). The following plaque measures were predictors of MACE using multivariable Cox regression analysis (hazard ratio [HR]) in patients with diabetes: segment stenosis score (HR=1.20, P 〈 0.001), low-attenuation plaque (HR=3.47, P =0.05), and in nondiabetic patients: segment stenosis score (HR=1.92, P 〈 0.001), Agatston score (HR=1.0009, P =0.04), and low-attenuation plaque (HR=4.15, P =0.04). A multivariable model showed a significantly improved C-index of 0.96 (95% confidence interval: 0.94-0.0.97) for MACE prediction, when compared with single measures alone. Conclusion: Diabetes is associated with a significantly higher extent of coronary artery disease and plaque features, which have independent predictive values for MACE. cCTA-derived plaque information portends improved risk stratification of patients with diabetes beyond the assessment of obstructive stenosis on cCTA alone with subsequent impact on individualized treatment decision-making.
Type of Medium:
Online Resource
ISSN:
0883-5993
DOI:
10.1097/RTI.0000000000000626
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2023
detail.hit.zdb_id:
2048799-X
