AIM To analyze the serum indicators affecting the efficacy and prognosis of percutaneous coronary intervention (PCI) in patients with coronary heart disease (CHD) and construct a prediction model.
METHODS This study retrospectively analyzed 326 patients with newly diagnosed CHD who received PCI treatment in our hospital between October 2020 and May 2021. The systemic immune inflammatory index (SII) was calculated, which was defined as peripheral platelet count × neutrophil/lymphocyte count. The biomarkers of systemic inflammation C-reactive protein (CRP), tumor necrosis factor (TNF-α), interleukin-6 (IL-6) and IL-1β in plasma were evaluated by Enzyme-linked immunosorbent assay (ELISA) kit. The endpoint event of follow-up was the occurrence of major adverse cardiovascular events (MACE) within 3 years after PCI treatment. A nomogram prediction model of MACE events in CHD patients three years after PCI was constructed.
RESULTS 59 patients (18.1%) experienced MACE during the follow-up period. Compared with the patients without MACE, the age, diabetes ratio, TNF - α, IL-6, CRP, eGFR、and SII of patients with MACE were increased, eGFR was reduced (all P<0.05). Multivariate logistic regression model showed that age (OR=1.070, 95% CI: 1.005~1.140), diabetes (OR=3.326, 95% CI: 1.033~10.706), SII (OR=1.001, 95% CI: 1.000~1.002), CRP (OR=2.583, 95% CI: 1.827~3.651), TNF-α (OR=1.167, 95% CI: 1.096~1.243), IL-6 (OR=1.167, 95% CI: 1.096~1.243) and eGFR (OR=0.974, 95% CI: 0.950~0.999) were the major risk factors for coronary heart disease in three years. Independent influencing factors of MACE during follow-up. Use the above independent influencing factors to generate a column chart for predicting the occurrence of MACE. The AUC of MACE predicted by the column chart is 0.98 (95% CI: 0.95~1.00), with an accuracy of 0.96 (0.92~0.98), sensitivity of 0.96 (0.94~0.99), and specificity of 0.92 (0.83~1.00).
CONCLUSION This study has developed a nomogram model for predicting MACE in CHD patients after PCI. This model is easy to operate and has good discrimination and calibration.
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