ABSTRACT
Objective To investigate the relationship between cardiac Tei index and plasma amino terminal brain natriuretic peptide precursor (NT- proBNP), glycosylated hemoglobin (HbA1c) in type 2 diabetes mellitus and its value in predicting the occurrence of major adverse cardiovascular events (MACE). Methods The clinical data of 160 patients with type 2 diabetes mellitus from March 2015 to October 2017 were retrospectively analyzed. The patients were divided into MACE group (45 cases) and non-MACE group (115 cases). The clinical indexes were compared between 2 groups, and the relationship between cardiac Tei index and NT-proBNP, HbA1c was analyzed. Logistic regression analysis was used to analyze the risk factors of MACE in patients with type 2 diabetes mellitus. Results The systolic blood pressure and diastolic blood pressure in MACE group were significantly lower than those in non-MACE group: (109.10 ± 14.53) mmHg (1 mmHg = 0.133 kPa) vs. (120.76 ± 18.74) mmHg and (64.29 ± 9.82) mmHg vs. (73.58 ± 12.11) mmHg, the heart rate, Killip grade > Ⅱ rate, cardiac Tei index and NT- proBNP were significantly higher than those in non- MACE group: (77.56 ± 13.36) times/min vs. (71.68 ± 11.39) times/min, 28.89％ (13/45) vs. 2.61％ (3/115), 0.63 ± 0.12 vs. 0.52 ± 0.08 and (1193.20 ± 145.69) μg/L vs. (823.87 ± 89.22) μg/L, and there were statistical difference (P<0.01). Pearson regression analysis result showed that cardiac Tei index was positively correlated with NT- proBNP and HbA1c (r = 0.817 and 0.793, P < 0.05), and there was positive correlation between NT-proBNP and HbA1c (r = 0.649, P < 0.05). Logistic regression analysis result showed that cardiac Tei index, NT-proBNP and HbA1c were the independent risk factors of MACE in patients with type 2 diabetes mellitus (OR = 1.015, 1.041 and 1.027; 95％ CI 1.005 to 0.213, 1.012 to 7.036 and 1.002 to 4.222; P<0.01 or <0.05). Conclusions The cardiac Tei index has positive correlation with NT- proBNP and HbA1c in patients with type 2 diabetes mellitus, and both are risk factors for the occurrence of MACE. The combination of the 3 indexes can effectively predict the occurrence of MACE and assess the prognosis.