Yu-ting Jiang, Zhen-ming Yan, Wei Gu, Hong-shan Guo, Xiu-ting Li, Si-qi Zheng, Xuan Liao, De-gang Xue

Department of Cardiology, General Hospital of Fushun Mining Bureau of Liaoning Health Industry, Fushun, Liaoning Province, People’s Republic of China

Correspondence: De-gang Xue, Email fskzxuedegang@163.com

Background: The advanced lung cancer inflammation index (ALI) is associated with the prognosis of cardiovascular diseases. However, the relationship between ALI and the occurrence of coronary slow flow phenomenon (CSFP) remains unclear.
Methods: We consecutively enrolled 1495 patients with angina and non-obstructive coronary arteries (ANOCA). In total, 93 patients were diagnosed with CSFP. A 1:2 age- and sex-matched patient with a normal coronary blood flow was selected as the control group. Demographic characteristics, laboratory parameters, and angiographic findings were compared between groups. Univariate and multivariate logistic regression analyses were performed to identify the independent predictors of CSFP in patients with ANOCA.
Results: A total of 93 individuals developed CSFP, accounting for 6.4% of the ANOCA patients. Compared with controls, patients with CSFP had a lower body mass index (BMI) and a higher incidence of nitrates before admission (P< 0.05). The neutrophil count, neutrophil-to-lymphocyte ratio (NLR), and fasting blood glucose (FBG) level were significantly higher in patients with CSFP, whereas decreased lymphocyte count, albumin level, and ALI were found in patients with CSFP. Multivariable logistic regression analyses revealed that ALI was an independent predictor of CSFP. The receiver operating characteristic (ROC) curve showed that when ALI was ≤ 389.5, the specificity and sensitivity were 0.624 and 0.652, respectively (AUC, 0.694; 95% CI, 0.633– 0.755, P< 0.001). Moreover, ALI demonstrated a better predictive value than indicators alone, including albumin level, BMI, and NLR.
Conclusion: A lower ALI demonstrated a reliable predictive value for the occurrence of CSFP in patients with ANOCA. As an easily calculated and acquired parameter, ALI can be used for risk stratification and optimal management of patients with ANOCA.

Keywords: advanced lung cancer inflammation index, coronary slow flow phenomenon, predictor, angina and nonobstructive coronary arteries