Key result
Novel inflammatory and pericoronary fat nomogram accurately identifies coronary ischemia with ~0.91 AUC.
Why the study?
The value of integrating systemic inflammatory biomarkers and pericoronary fat attenuation index for identifying functional coronary ischemia in patients with MAFLD and CHD remains unclear.
Do systemic inflammatory biomarkers and pericoronary fat attenuation index independently predict functionally significant coronary ischemia in patients with MAFLD and CHD?
Cross-Sectional (n=261)
No
Do systemic inflammatory biomarkers and pericoronary fat attenuation index independently predict functionally significant coronary ischemia in patients with MAFLD and CHD?
Effect estimate: AUC 0.9146 (95% CI 0.8825-0.9466)
Combining pericoronary fat attenuation index with systemic inflammatory biomarkers provides a highly discriminatory, noninvasive approach to predict functional coronary ischemia in MAFLD patients with CHD.
May support noninvasive ischemia prediction in MAFLD-CHD; hypothesis-generating and leaves open prospective validation before practice change.
Patients with metabolic dysfunction-associated fatty liver disease (MAFLD) and coronary heart disease (CHD) exhibit systemic and coronary inflammation. However, the value of integrating systemic inflammatory biomarkers and the pericoronary fat attenuation index (FAI) for identifying functional coronary ischemia remains unclear. This study aimed to identify factors associated with functional coronary ischemia and to develop an exploratory risk stratification tool. A total of 261 consecutive patients with MAFLD and CHD were retrospectively enrolled between June 2019 and July 2025. Patients were divided according to computed tomography-derived fractional flow reserve (CT-FFR) values into CT-FFR > 0.80 and CT-FFR ≤ 0.80 groups. Least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression were performed to identify independent factors associated with the outcome and to construct a nomogram. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC), with nested internal validation that repeated the entire model-building process in each resample. LASSO regression retained 10 variables. In multivariable analysis, hypertension, alanine aminotransferase (ALT), low-density lipoprotein cholesterol (LDL-C), white blood cell count (WBC), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), FAI, and triglycerides (TG) were independent risk factors and high-density lipoprotein cholesterol (HDL-C) was protective ( P < 0.05). The nomogram showed good discrimination (apparent AUC = 0.9146, 95% CI: 0.8825–0.9466; nested optimism-corrected AUC 0.8874; nested 10-fold cross-validated AUC 0.8711) and no evidence of miscalibration in the development sample. Systemic inflammatory biomarkers combined with FAI are independently associated with CT-FFR-defined functional coronary ischemia in patients with MAFLD and CHD. The resulting nomogram is an exploratory risk stratification tool that requires external, prospective multicenter validation before any clinical application.
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Bai et al. (2026) conducted a cross-sectional in Metabolic dysfunction-associated fatty liver disease (MAFLD) and coronary heart disease (CHD) (n=261). Systemic inflammatory biomarkers combined with pericoronary fat attenuation index (FAI) vs. Patients with CT-FFR > 0.80 (no functional ischemia) was evaluated on Functionally significant coronary ischemia (defined as CT-FFR ≤ 0.80) (AUC 0.9146, 95% CI 0.8825-0.9466). A nomogram integrating systemic inflammatory biomarkers and pericoronary fat attenuation index effectively identified functionally significant coronary ischemia with an apparent AUC of 0.9146.
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