Objective We aimed to investigate the relationship between coronary artery disease (CAD) and systemic inflammation indices and lipid metabolism-related factors and subsequently, discuss the clinical application of these factors in CAD. Methods We enrolled 284 consecutive inpatients with suspected CAD and divided them into a CAD group and a non-CAD group according to coronary angiography results. Serum levels of angiopoietin-like protein 3 (ANGPTL3), angiopoietin-like protein 4 (ANGPTL4), fatty acid-binding protein 4 (FABP4), and tumor necrosis factor-α (TNF-α) levels were assessed using the ELISA and the systemic inflammation indices were calculated. Multivariate logistic regression was used to assess the risk factors of CAD. The receiver operating characteristic curve was used to determine the cutoff and diagnostic values. Results The neutrophil-to-high density lipoprotein cholesterol ratio (5.04 vs. 3.47), neutrophil-to-lymphocyte ratio (3.25 vs. 2.45), monocyte-to-high density lipoprotein cholesterol ratio (MHR) (0.46 vs. 0.36), monocyte-to-lymphocyte ratio (0.31 vs. 0.26), systemic immune-inflammation index (SII) (696.00 vs. 544.82), serum TNF-α (398.15 ng/l vs. 350.65 ng/l), FABP4 (1644.00 ng/l vs. 1553.00 ng/l), ANGPTL3 (57.60 ng/ml vs. 52.85 ng/ml), and ANGPTL4 (37.35 ng/ml vs. 35.20 ng/ml) values showed a significant difference between the CAD and non-CAD groups (P < 0.05). After adjusting for confounding factors, the following values were obtained: ANGPTL3 > 67.53 ng/ml [odds ratio (OR) = 8.108, 95% confidence interval (CI) (1.022–65.620)]; ANGPTL4 > 29.95 ng/ml [OR = 5.599, 95% CI (1.809–17.334)]; MHR > 0.47 [OR = 4.872, 95% CI (1.715–13.835)]; SII > 589.12 [OR = 5.131, 95% CI (1.995–13.200)]. These factors were found to be independently associated with CAD (P < 0.05). Diabetes combined with MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l had the highest diagnostic value for CAD [area under the curve: 0.921, 95% CI, (0.881–0.960), Sensitivity: 88.9%, Specificity: 82.2%, P < 0.001]. Conclusion MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l were identified as independent CAD risk factors and have valuable clinical implications in the diagnosis and treatment of CAD.

Objective To establish a predictive model for poor prognosis after incomplete revascularization (ICR) in patients with multivessel coronary artery disease (MVD). Methods Clinical data of 757 patients with MVD and ICR after percutaneous coronary intervention (PCI) in the Affiliated Hospital of Chengde Medical University from January 2020 to August 2021 were retrospectively collected. The least absolute shrinkage and selection operator regression method was used to screen variables, and multivariate logistic regression was used to establish a predictive model. An independent cohort was used to validate the model. The C-statistic was used to verify and evaluate the discriminative ability of the model; the calibration curve was drawn, and the decision curve analysis (DCA) was performed to evaluate the calibration degree, the clinical net benefit, and the practicability of the model. Results The predictive factors included female, age, unconjugated bilirubin, uric acid, low-density lipoprotein, hyperglycemia, total occlusion, and severe tortuosity lesion on coronary angiography. The C-statistic of the training and validation sets were 0.628 and 0.745, respectively. The statistical value of the Hosmer–Lemeshow test for the calibration curve of the training and validation sets were 5.27(P = 0.873) and 6.27 (P = 0.792), respectively. DCA showed that the model was clinically applicable when the predicted probability value of major adverse cardiovascular events(MACEs) ranged from 0.07 to 0.68. Conclusions We established a predictive model for poor prognosis after ICR in patients with MVD. The predictive and calibration ability and the clinical net benefit of the predictive model were good, indicating that it can be used as an effective tool for the early prediction of poor prognosis after ICR in patients with MVD.