Predicting Periprocedural Myocardial Infarction in Chronic Coronary Syndrome Using CT-derived Fat Attenuation Index...

Area of Science:

• Cardiology
• Radiology
• Biomarkers

Background:

• Chronic coronary syndrome (CCS) patients undergoing percutaneous coronary intervention (PCI) are at risk for periprocedural myocardial infarction (PMI) and major adverse cardiovascular events (MACEs).
• Identifying predictive biomarkers for these adverse outcomes is crucial for risk stratification and management.

Purpose of the Study:

• To evaluate the predictive value of pre-PCI pericoronary fat attenuation index (FAI) and triglyceride-glucose body mass index (TyG-BMI) for PMI and MACEs in CCS patients.

Main Methods:

• Prospective observational study of 476 CCS patients undergoing elective PCI.
• FAI measured via coronary CT angiography (CCTA); TyG-BMI calculated from laboratory tests.
• PMI defined by troponin levels post-PCI; MACEs included cardiovascular death, MI, restenosis, and revascularization.

Main Results:

• PMI occurred in 23.9% of participants.
• Higher TyG-BMI and less negative FAI scores were associated with PMI (P < .001).
• A combined model of FAI, TyG-BMI, and clinical variables showed improved prediction (AUC 0.72) compared to clinical variables alone (AUC 0.67).
• High TyG-BMI and FAI > -70.1 HU predicted the highest MACE rate (P < .001).

Conclusions:

• Preoperative FAI and TyG-BMI are independent predictors of PMI and MACEs in CCS patients undergoing PCI.
• These imaging and metabolic markers can enhance risk assessment in this population.