Objective:To investigate the distribution law of TCM syndrome types and the differences in influencing factors among different syndrome types in unstable angina pectoris (UA), so as to provide an objective basis for TCM syndrome differentiation and treatment of UA.Methods:A retrospective study chose 1 684 inpatients in the Department of Cardiovascular Medicine of the First Affiliated Hospital of Henan University of Chinese Medicine from August 2015 to April 2019. Epidata 3.0 software was used to input general information of patients [gender, age, length of hospital stay, BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP)], laboratory indicators[TC, TG, HDL-C, LDL-C, fibrinogen (FIB), thrombin time (TT), D-dimer (D-dimer), HbA1c], TCM syndrome types (qi and yin deficiency syndrome, phlegm turbidity and obstruction syndrome, qi deficiency and blood stasis syndrome, heart blood stasis syndrome, qi stagnation and blood stasis syndrome, heart and kidney yang deficiency syndrome) and other information. A database was established to analyze the distribution of TCM syndrome types and the relationship with the general information of patients, blood lipids, blood sugar and coagulation indexes. Logistic regression was used to analyze the influencing factors of different syndrome types.Results:The distribution of syndrome types in 1 684 UA patients was as follows: qi and yin deficiency syndrome (44.7%), phlegm turbidity and obstruction syndrome (35.3%), qi deficiency and blood stasis syndrome (7.4%), heart blood stasis syndrome (5.3%), qi stagnation and blood stasis syndrome (4.6%), heart and kidney yang deficiency syndrome (2.6%); more men than women ( P<0.05); there were significant differences in the distribution of gender, age, BMI, TC, and HDL-C among the 6 syndrome types ( P<0.05); the age of patients with phlegm turbidity and obstruction syndrome was younger than that of qi and yin deficiency syndrome and heart blood stasis syndrome ( P<0.05); the age of patients with qi stagnation and blood stasis syndrome was younger than that of qi and yin deficiency syndrome, heart blood stasis syndrome, and heart kidney yang deficiency syndrome ( P<0.05); BMI of patients with phlegm turbidity and obstruction syndrome was higher than that of qi and yin deficiency syndrome and qi stagnation and blood stasis syndrome ( P<0.05); the level of TC in patients with phlegm turbidity and obstruction syndrome was lower than that of qi and yin deficiency syndrome and qi deficiency and blood stasis syndrome ( P<0.05); the level of HDL in patients with qi and yin deficiency syndrome was lower than that in qi deficiency and blood stasis syndrome and qi stagnation and blood stasis syndrome. Binary Logistic regression analysis found that TC [ OR(95% CI)=0.761(0.592, 0.978)] and HDL-C [ OR(95% CI)=2.131(1.145, 3.966)] were independent influencing factors for predicting qi deficiency and blood stasis syndrome ( P<0.05); age[ OR(95% CI)=1.017 (1.008, 1.026)], length of hospital stay [ OR(95% CI)=1.019 (1.001, 1.038)], DBP [ OR(95% CI)=0.984(0.975, 0.993)] and HDL-C [ OR(95% CI)=0.984(0.975, 0.993)] were independent influencing factors for predicting qi and yin deficiency syndrome ( P<0.05); age [ OR(95% CI)=0.965 (0.946, 0.985)], and HDL-C [ OR(95% CI)=2.329(1.206, 4.500)] were independent influencing factors for predicting qi stagnation and blood stasis syndrome ( P<0.05); age [ OR(95% CI)=0.982 (0.973, 0.991)], length of hospital stay [ OR(95% CI)= 0.978 (0.958, 0.997)], BMI [ OR(95% CI)=1.048 (1.015, 1.082)], DBP [ OR(95% CI)=1.014 (1.004, 1.024)] and HDL-C [ OR(95% CI)=0.505 (0.351, 0.726)] were independent influencing factors for predicting phlegm turbidity and obstruction syndrome ( P<0.05); age [ OR(95% CI)=1.031(1.003, 1.060)] and DBP [ OR(95% CI)=1.028(1.001, 1.056)] were independent influencing factors for predicting heart kidney yang deficiency syndrome ( P<0.05). Conclusion:The distribution of TCM syndrome types in UA shows a certain regularity, among which qi and yin deficiency syndrome and phlegm turbidity and obstruction syndrome are more common. Gender, age, BMI, TC, HDL-C are different among TCM syndrome types, which can provide some reference for UA TCM syndrome differentiation and treatment.