Incremental predictive value of liver fat fraction based on spectral detector CT for major adverse cardiovascular events in T2DM patients with suspected coronary artery disease.

Background: The purpose of this study was to explore the incremental predictive value of liver fat fraction (LFF) in forecasting major adverse cardiovascular events (MACE) among patients with type 2 diabetes mellitus (T2DM).

Methods: We prospectively enrolled 265 patients with T2DM who presented to our hospital with symptoms of chest distress and pain suggestive of coronary artery disease (CAD) between August 2021 and August 2022. All participants underwent both coronary computed tomography angiography (CCTA) and upper abdominal dual-layer spectral detector computed tomography (SDCT) examinations within a 7-day interval. Detailed clinical data, CCTA imaging features, and LFF determined by SDCT multi-material decomposition algorithm were meticulously recorded. MACE was defined as the occurrence of cardiac death, acute coronary syndrome (ACS), late-phase coronary revascularization procedures, and hospital admissions due to heart failure.

Results: Among 265 patients (41% male), 51 cases of MACE were documented during a median follow-up of 30 months. The LFF in T2DM patients who experienced MACE was notably higher compared to those without MACE (p < 0.001). The LFF was divided into tertiles using the cutoffs of 4.10 and 8.30. Kaplan-Meier analysis indicated that patients with higher LFF were more likely to develop MACE, regardless of different subgroups in framingham risk score (FRS) or coronary artery calcium score (CACS). The multivariate Cox regression results indicated that, compared with patients in the lowest tertile, those in the second tertile (hazard ratio [HR] = 3.161, 95% confidence interval [CI] 1.163-8.593, P = 0.024) and third tertile (HR = 4.372, 95% CI 1.591-12.014, P = 0.004) had a significantly higher risk of MACE in patients with T2DM. Even after adjusting for early revascularization, both LFF tertile and CACS remained independently associated with MACE. Moreover, compared with the traditional FRS model, the model that included LFF, CACS, and FRS showed stable clinical net benefit and demonstrated better predictive performance, with a C-index of 0.725, a net reclassification improvement (NRI) of 0.397 (95% CI 0.187-0.528, P < 0.01), and an integrated discrimination improvement (IDI) of 0.100 (95% CI 0.043-0.190, P < 0.01).

Conclusions: The elevated LFF emerged as an independent prognostic factor for MACE in patients with T2DM. Incorporating LFF with FRS and CACS provided incremental predictive power for MACE in patients with T2DM.

Research insights: WHAT IS CURRENTLY KNOWN ABOUT THIS TOPIC?: T2DM is associated with increased MACE rates, underscoring the need for improved risk prediction. CACS is a well-established tool for MACE risk assessment but may not capture all risk factors. Hepatic steatosis is a common comorbidity in metabolic syndrome and T2DM. WHAT IS THE KEY RESEARCH QUESTION?: Does the incorporation of LFF derived from SDCT into existing risk prediction models enhance the accuracy of MACE forecasting in patients with T2DM? WHAT IS NEW?: SDCT-LFF measurement introduces a more accurate method for assessing hepatic steatosis. LFF as an independent predictor of MACE in T2DM patients is a novel finding. The study presents LFF as an additional tool for risk stratification, complementing FRS and CACS. HOW MIGHT THIS STUDY INFLUENCE CLINICAL PRACTICE?: Study findings may guide personalized prevention for T2DM patients at higher MACE risk.