Baseline characteristics of patients
A total of 1534 admitted hospital patients were included with a median follow-up time of 23.1 months (interquartile range, 17.4–29.5 years) and a mean age of 62.7 ± 8.2 years old. Patients who experienced events had the following characteristics: older; higher levels of TGs, TC, LDL-C, eGFR, GA, Creatinine, FPG and TyG index; more likely to use multiple SVGs rather than LIMA + SVGs; and more likely to have lipid-regulating agents than those who had no events (Table 1). Left ventricular ejection fraction, IABP support and medication at discharge were similar between these two groups.
Table 1
Baseline clinical and laboratory characteristics of the study patients stratified by the primary endpoint
| Total population(n = 1534) | Without event(n = 1370) | With event(n = 164) | P value |
Age, years | 62.7 ± 8.2 | 62.4 ± 8.1 | 64.8 ± 8.4 | < 0.001 |
Sex, male, n (%) | 1092 (71.2) | 981 (71.6) | 111 (67.7) | 0.339 |
BMI, kg/m2 | 25.91 ± 3.13 | 25.88 ± 3.10 | 26.13 ± 3.38 | 0.347 |
SBP, mmHg | 130.63 ± 16.63 | 130.66 ± 16.79) | 130.38 ± 15.34 | 0.836 |
DBP, mmHg | 74.44 ± 10.64 | 74.47 ± 10.69) | 74.15 ± 10.23) | 0.715 |
Current smoking, n (%) | 430 (28.0) | 392 (28.6) | 38 (23.2) | 0.169 |
Current drinking, n (%) | 314 (20.5) | 290 (21.2) | 24 (14.6) | 0.063 |
Medical History, n (%) | | | | |
Hypertension | 1114 (72.6) | 996 (72.7) | 118 (72.0) | 0.912 |
Dyslipidemia | 483 (31.5) | 415 (30.3) | 68 (41.5) | 0.005 |
Prior MI | 221 (14.4) | 196 (14.3) | 25 (15.2) | 0.837 |
Prior PCI | 360 (23.5) | 314 (22.9) | 46 (28.0) | 0.172 |
Prior stroke | 160 (10.4) | 145 (10.6) | 15 (9.1) | 0.664 |
PVD | 587 (38.3) | 505 (36.9) | 82 (50.0) | 0.001 |
Laboratory results | | | | |
TGs, mg/dL | 128.56 [94.87, 174.44] | 127.67 [93.09, 170.23] | 139.64 [104.40, 224.31] | < 0.001 |
TC, mg/dL | 146.54 (36.91) | 145.52 ± 35.88 | 155.00 ± 43.78 | 0.002 |
LDL-C, mg/dL | 86.72 ± 31.10 | 86.14 ± 30.43 | 91.53 ± 35.95 | 0.036 |
HDL-C, mg/dL | 37.40 ± 8.44 | 37.40 ± 8.31 | 37.41 ± 9.49 | 0.987 |
Hs-CRP, mg/L | 3.12 ± 4.21 | 3.09 ± 4.20 | 3.32 ± 4.30 | 0.511 |
Creatinine, µmol/L | 75.53 ± 46.57 | 74.54 ± 41.15 | 83.82 ± 78.11 | 0.016 |
eGFR, mL/(min*1.73cm2) | 91.16 ± 16.49 | 91.67 ± 16.15 | 86.89 ± 18.61 | < 0.001 |
Urid acid, µmol/L | 331.19 ± 92.22 | 329.92 ± 89.78 | 341.74 ± 110.32 | 0.121 |
FPG, mg/dL | 135.36 [111.46, 174.56] | 133.83 [110.74, 170.73] | 155.34 [120.82, 208.62] | < 0.001 |
GA, % | 18.88 ± 6.22 | 18.74 ± 6.16 | 20.05 ± 6.58 | 0.011 |
TyG index | 9.13 ± 0.63 | 9.09 ± 0.61 | 9.40 ± 0.66 | < 0.001 |
LVEF, % | 59.52 ± 7.69 | 59.61 ± 7.62 | 58.77 ± 8.22 | 0.185 |
Initial diagnosis, n (%) | | | | |
UA | 1451 (94.6) | 1302 (95.0) | 149 (90.9) | 0.040 |
NSTEMI | 83 (5.4) | 68 (5.0) | 15 (9.1) | 0.040 |
Number of bridges | | | | |
Only one bridge, n (%) | 135 (8.8) | 117 (8.5) | 18 (11.0) | 0.371 |
Two bridges, n (%) | 500 (32.6) | 454 (33.1) | 46 (28.0) | 0.220 |
Multiple bridges, n (%) | 899 (58.6) | 799 (58.3) | 100 (61.0) | 0.570 |
Bridge type, n (%) | | | | |
Single LIMA | 126 (8.2) | 112 (8.2) | 14 (8.5) | 0.993 |
Single SVG | 8 (0.5) | 4 (0.3) | 4 (2.4) | 0.002 |
LIMA + SVGs | 951 (62.0) | 875 (63.9) | 76 (46.3) | < 0.001 |
Multiple SVGs | 446 (29.1) | 376 (27.4) | 70 (42.7) | < 0.001 |
Medication at discharge, n (%) | | | | |
ACEI or ARB | 30 (2.0) | 24 (1.8) | 6 (3.7) | 0.171 |
DAPT | 1267 (82.6) | 1131 (82.6) | 136 (82.9) | 0.992 |
Aspirin | 1463 (95.4) | 1305 (95.3) | 158 (96.3) | 0.668 |
P2Y12R inhibitor | 1288 (84.0) | 1148 (83.8) | 140 (85.4) | 0.685 |
β-blocker | 1120 (73.0) | 1004 (73.3) | 116 (70.7) | 0.547 |
Lipid regulating agents | 1400 (91.3) | 1261 (92.0) | 139 (84.8) | 0.003 |
Oral hypoglycemic agents | 629 (41.0) | 566 (41.3) | 63 (38.4) | 0.529 |
Metformin | 422 (27.5) | 380 (27.7) | 42 (25.6) | 0.628 |
Alpha‑glucosidase inhibitor | 422 (27.5) | 372 (27.2) | 50 (30.5) | 0.417 |
Sulfonylurea | 18 (1.2) | 17 (1.2) | 1 (0.6) | 0.745 |
DPP-4 | 17 (1.1) | 15 (1.1) | 2 (1.2) | 1.000 |
Insulin | 49 (3.2) | 43 (3.1) | 6 (3.7) | 0.902 |
Instrument assistance | | | | |
IABP use, n (%) | 27 (1.8) | 23 (1.7) | 4 (2.4) | 0.700 |
Italic values indicate statistically significant associations |
BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, MI myocardial infarction, PCI percutaneous coronary intervention, PVD peripheral vascular disease, TGs triglycerides, TC total cholesterol, LDL-C low-density lipoprotein cholesterol, HDL-C high-density lipoprotein cholesterol, hs-CRP high-sensitivity C-reactive protein, eGFR estimated glomerular filtration rate, FPG fasting plasma glucose, GA glycated albumin, TyG triglyceride glucose, LVEF left ventricular ejection fraction, UA unstable angina, NSTEMI non-ST-segment elevation myocardial infarction, LIMA left internal mammary artery, SVG saphenous vein grafts, ACEI angiotensin converting enzyme inhibitor, ARB angiotensin receptor blocker, DAPT dual antiplatelet therapy, DPP-4 Dipeptidyl peptidase-4, IABP intra-aortic balloon pump |
ROC curve analysis showed that the AUC of the TyG index for predicting the primary endpoint was 0.631 (95% CI 0.584–0.677, P < 0.001). The optimal cutoff point of the TyG index was 9.42 with a sensitivity of 49.4% and a specificity of 71.2%. Patients with a higher TyG index were younger, had significantly higher BMI levels and had a higher proportion of dyslipidemia. Laboratory indexes, including TG, TC, LDL-C, hs-CRP, uric acid, FPG and GA, were significantly higher in patients with a higher TyG index, while HDL-C levels were relatively lower in these patients. However, Creatinine and eGFR, which were different between patients with and without events, were not significant between lower and higher TyG groups. In the higher TyG index group, more patients were diagnosed with NSTEMI (Table 2). Left ventricular ejection fraction, IABP support and medication at discharge were also similar between these two groups.
Table 2
Baseline clinical characteristics of the study patients according to the cut-off value of TyG index
| Total population (n = 1534) | Lower TyG index (≤ 9.42; n = 745) | Higher TyG index (> 9.42; n = 359) | P value |
Age, years | 62.68 ± 8.19 | 63.30 ± 7.77 | 61.31 ± 8.91 | < 0.001 |
Sex, male, n (%) | 442 (28.8) | 760 (71.9) | 332 (69.6) | 0.390 |
BMI, kg/m2 | 25.91 ± 3.13 | 25.59 ± 3.01 | 26.61 ± 3.28 | < 0.001 |
SBP, mmHg | 130.63 ± 16.63 | 130.97 ± 16.96 | 129.89 ± 15.87 | 0.238 |
DBP, mmHg | 74.44 ± 10.64 | 74.11 ± 10.89 | 75.16 ± 10.02 | 0.074 |
Current smoking, n (%) | 430 (28.0) | 287 (27.2) | 143 (30.0) | 0.280 |
Current drinking, n (%) | 314 (20.5) | 214 (20.2) | 100 (21.0) | 0.799 |
Medical History, n (%) | | | | |
Hypertension | 1114 (72.6) | 769 (72.8) | 345 (72.3) | 0.911 |
Dyslipidemia | 483 (31.5) | 315 (29.8) | 168 (35.2) | 0.040 |
Prior MI | 221 (14.4) | 148 (14.0) | 73 (15.3) | 0.553 |
Prior PCI | 360 (23.5) | 234 (22.1) | 126 (26.4) | 0.078 |
Prior stroke | 160 (10.4) | 114 (10.8) | 46 (9.6) | 0.557 |
PVD | 587 (38.3) | 397 (37.6) | 190 (39.8) | 0.429 |
Laboratory results | | | | |
TG, mg/dL | 128.56 [94.87, 174.44] | 108.17 [84.23, 134.76] | 207.46 [157.81, 266.87] | < 0.001 |
TC, mg/dL | 146.54 (36.91) | 140.68 (34.73) | 159.53 (38.28) | < 0.001 |
LDL-C, mg/dL | 86.72 (31.10) | 83.91 (29.87) | 92.94 (32.85) | < 0.001 |
HDL-C, mg/dL | 37.40 (8.44) | 38.56 (8.73) | 34.83 (7.12) | < 0.001 |
Hs-CRP, mg/L | 3.12 (4.21) | 2.95 (4.07) | 3.50 (4.49) | 0.018 |
Creatinine, µmol/L | 75.53 (46.57) | 74.07 (41.68) | 78.77 (55.82) | 0.067 |
eGFR, mL/(min*1.73cm2) | 91.16 (16.49) | 91.68 (15.73) | 90.00 (18.02) | 0.064 |
Uric acid, µmol/L | 331.19 (92.22) | 324.60 (88.09) | 345.79 (99.33) | < 0.001 |
FPG, mg/dL | 135.36 [111.46, 174.56] | 123.84 [105.12, 146.16] | 181.26 [147.60, 228.06] | < 0.001 |
GA, % | 18.88 (6.22) | 18.45 (5.96) | 19.85 (6.65) | < 0.001 |
TyG index | 9.13 ± 0.63 | 8.80 ± 0.42 | 9.85 ± 0.33 | < 0.001 |
LVEF, % | 59.52 ± 7.69 | 59.63 ± 7.57 | 59.27 ± 7.95 | 0.400 |
Initial diagnosis, n (%) | | | | |
UA | 1451 (94.6) | 1010 (95.6) | 441 (92.5) | 0.018 |
NSTEMI | 83 (5.4) | 47 (4.4) | 36 (7.5) | 0.018 |
Number of bridges | | | | |
Single bridge, n (%) | 135 (8.8) | 95 (9.0) | 40 (8.4) | 0.773 |
Two bridges, n (%) | 500 (32.6) | 333 (31.5) | 167 (35.0) | 0.195 |
Multiple bridges, n (%) | 899 (58.6) | 629 (59.5) | 270 (56.6) | 0.311 |
Type of bridge, n (%) | | | | |
Single LIMA | 126 (8.2) | 89 (8.4) | 37 (7.8) | 0.736 |
Single SVG | 8 (0.5) | 6 (0.6) | 2 (0.4) | 1.000 |
LIMA + SVGs | 951 (62.0) | 654 (61.9) | 297 (62.3) | 0.929 |
Multiple SVGs | 446 (29.1) | 307 (29.0) | 139 (29.1) | 1.000 |
Medication at discharge, n (%) | | | | |
ACEI or ARB | 30 (2.0) | 19 (1.8) | 11 (2.3) | 0.641 |
DAPT | 1267 (82.6) | 858 (81.2) | 409 (85.7) | 0.035 |
Aspirin | 1463 (95.4) | 1002 (94.8) | 461 (96.6) | 0.143 |
P2Y12R inhibitor | 1288 (84.0) | 877 (83.0) | 411 (86.2) | 0.133 |
β-blocker | 1120 (73.0) | 768 (72.7) | 352 (73.8) | 0.688 |
Statin | 1400 (91.3) | 970 (91.8) | 430 (90.1) | 0.345 |
Oral hypoglycemic agents | 629 (41.0) | 430 (40.7) | 199 (41.7) | 0.744 |
Metformin | 422 (27.5) | 287 (27.2) | 135 (28.3) | 0.686 |
Alpha‑glucosidase inhibitor | 422 (27.5) | 288 (27.2) | 134 (28.1) | 0.778 |
Sulfonylurea | 18 (1.2) | 12 (1.1) | 6 (1.3) | 1.000 |
DPP-4 | 17 (1.1) | 13 (1.2) | 4 (0.8) | 0.679 |
Insulin | 49 (3.2) | 30 (2.8) | 19 (4.0) | 0.306 |
Instrument assistance | | | | |
IABP use, n (%) | 27 (1.8) | 17 (1.6) | 10 (2.1) | 0.643 |
Italic values indicate statistically significant associations |
BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, MI myocardial infarction, PCI percutaneous coronary intervention, PVD peripheral vascular disease, TGs triglycerides, TC total cholesterol, LDL-C low-density lipoprotein cholesterol, HDL-C high-density lipoprotein cholesterol, hs-CRP high-sensitivity C-reactive protein, eGFR estimated glomerular filtration rate, FPG fasting plasma glucose, GA glycated albumin, TyG triglyceride glucose, LVEF left ventricular ejection fraction, UA unstable angina, NSTEMI non-ST-segment elevation myocardial infarction, LIMA left internal mammary artery, SVG saphenous vein grafts, ACEI angiotensin converting enzyme inhibitor, ARB angiotensin receptor blocker, DAPT dual antiplatelet therapy, DPP-4 Dipeptidyl peptidase-4, IABP intra-aortic balloon pump |
Cardiovascular risk factors related to TyG index
Spearman’s rank or Pearson correlation analysis was performed to determine the correlation between the TyG index and traditional or commonly used risk factors for cardiovascular disease.
The TyG index was positively correlated with sex (female), BMI, DBP, TGs, TC, LDL-C, hs-CRP, creatinine, uric acid, FPG, GA, diagnosis (NSTEMI) and dyslipidemia but negatively correlated with age, HDL-C and eGFR (Table 3).
Table 3
Correlations between the TyG and traditional cardiovascular risk factors
| Correlation coefficient | P value |
Age | -0.126 | < 0.001 |
Sex, female | 0.054 | 0.036 |
BMI | 0.197 | < 0.001 |
SBP | 0.008 | 0.752 |
DBP | 0.079 | 0.002 |
TGs | 0.797 | < 0.001 |
TC | 0.291 | < 0.001 |
LDL-C | 0.178 | < 0.001 |
HDL-C | -0.254 | < 0.001 |
Hs-CRP | 0.069 | 0.007 |
Creatinine | 0.060 | 0.020 |
eGFR | -0.056 | 0.027 |
Uric acid | 0.105 | < 0.001 |
FPG | 0.638 | < 0.001 |
GA | 0.124 | < 0.001 |
LVEF | -0.025 | 0.331 |
Current smoking | 0.042 | 0.104 |
Current alcohol | -0.011 | 0.677 |
Dyslipidemia | 0.068 | 0.008 |
prior MI | 0.029 | 0.258 |
prior PCI | 0.047 | 0.066 |
prior stroke | -0.037 | 0.145 |
Prior PVD | 0.016 | 0.529 |
NSTEMI | 0.067 | 0.009 |
IABP | 0.044 | 0.088 |
multiple bridges | -0.024 | 0.348 |
hypertension | -0.017 | 0.506 |
Italic values indicate statistically significant associations |
BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, PCI percutaneous coronary intervention, PVD peripheral vascular disease, TGs triglycerides, TC total cholesterol, LDL-C low-density lipoprotein cholesterol, HDL-C high-density lipoprotein cholesterol, hs-CRP high-sensitivity C-reactive protein, eGFR estimated glomerular filtration rate, FPG fasting plasma glucose, GA glycated albumin, TyG triglyceride glucose, LVEF left ventricular ejection fraction, UA unstable angina, NSTEMI non-ST-segment elevation myocardial infarction, IABP intra-aortic balloon pump |
Primary and secondary outcomes are all significantly different between the lower and higher TyG index groups
During the follow-up period, 164 (10.7%) MACCEs, including 25 (1.6%) all-cause deaths, 32 (0.2%) nonfatal MIs, 30 (0.2%) nonfatal strokes and 79 (5.1) symptomatic graft stenoses or occlusions, were documented and included in the present analyses. The incidence of the primary endpoint increased significantly in patients with a higher TyG index compared to those with a lower TyG index (all Chi-square P < 0.05) (Table 4). Kaplan–Meier curves for the incidence of the primary endpoint and each component according to the optimal cutoff point of the TyG index are shown in Fig. 2. Primary endpoint, all-cause death, nonfatal MI, nonfatal stroke and symptomatic graft stenosis and occlusion all showed a significant difference between the lower and higher TyG index groups (Fig. 2; primary endpoint log-rank P < 0.001; all secondary endpoints log-rank P < 0.05).
Table 4
Incidence of endpoint events according to the optimal cutoff point of TyG index
| Total population (n = 1534) | Lower TyG index (≤ 9.42; n = 745) | Higher TyG index (> 9.42; n = 359) | P value |
Primary endpoint, n (%) | 164 (10.7) | 83 (7.9) | 81 (17.0) | < 0.001 |
All-cause death, n (%) | 25 (1.6) | 10 (0.9) | 15 (3.1) | 0.003 |
Non-fatal MI, n (%) | 32 (0.2) | 15 (1.4) | 17 (3.6) | 0.011 |
Non-fatal stroke, n (%) | 30 (0.2) | 15 (1.4) | 15 (3.1) | 0.039 |
Symptomatic graft stenosis or occlusion, n (%) | 79 (5.1) | 44 (4.2) | 35 (7.3) | 0.013 |
The groups were stratified by the optimal cutoff point of TyG index determined by ROC curve analysis |
Italic values indicate statistically significant associations |
TyG triglyceride glucose, MI myocardial infarction |
Cox proportional hazard analyses of the prognostic implication of the TyG index
In the multivariate Cox proportional hazard analysis, four models (Models 1–4 as described above) comprised of variables that had statistical significance (P < 0.2) and/or clinical importance were constructed to evaluate the predictive potential of the TyG index for the primary endpoint. After adjusting for confounding variables, a higher TyG index remained an independent risk predictor of the primary endpoint despite regarding the TyG index as a nominal or continuous variable (all P < 0.001 in Models 1–4) (Table 5). Detailed information on Model 4 is shown in Additional file 1: Table S1.
Table 5
Predictive value of TyG index for primary endpoint in different Cox proportional hazards models
| TyG index as a continuous variablea | | TyG index as a nominal variableb |
HR | 95%CI | P value | HR | 95%CI | P value |
Crude model | 2.218 | 1.734–2.839 | < 0.001 | | 2.381 | 1.752–3.234 | < 0.001 |
Model 1 | 2.265 | 1.757–2.918 | < 0.001 | | 2.413 | 1.765–3.299 | < 0.001 |
Model 2 | 2.142 | 1.642–2.794 | < 0.001 | | 2.212 | 1.597–3.063 | < 0.001 |
Model 3 | 2.109 | 1.616–2.752 | < 0.001 | | 2.191 | 1.579–3.039 | < 0.001 |
Model 4 | 2.105 | 1.609–2.755 | < 0.001 | | 2.193 | 1.577–3.049 | < 0.001 |
Model 1: adjusted for age, sex(female), BMI, DBP, current smoking status, current drinking status, dyslipidemia, prior MI, prior PCI, prior stroke and PVD; |
Model 2: adjusted for variables included in Model 1 and diagnosis (NSTEMI), TC, HDL-C, hs-CRP, creatinine, eGFR, Uric Acid, GA, LVEF; |
Model 3: adjusted for variables included in Model 2 and multiple bridges, LIMA use, IABP use; |
Model 4: adjusted for variables included in Model 3 and DAPT at discharge, statin at discharge, oral hypoglycemic agents (metformin, alpha-glucosidase inhibitor, sulfonylurea, DPP-4) at discharge and insulin at discharge |
TyG triglyceride glucose, HR hazard ratio, CI confidence interval |
The HR was examined regarding lower TyG index as reference (stratified by the optimal cutoff point of TyG index determined by ROC curve analysis) |
a The HR was examined by per 1-unit increase of TyG index |
b The HR was examined regarding lower TyG index as reference (stratified by the optimal cutoff point of TyG index determined by ROC curve analysis) |
We used Model 4 to evaluate the predictive value of the TyG index for MACCEs and each component. The results showed that a 1-unit increase in the TyG index was independently associated with a higher risk of MACCEs [HR 2.218 (1.733–2.839), P < 0.001] and each component. A higher TyG index of more than 9.42 was independently associated with a higher risk of MACCEs [HR 2.092 (1.573–2.784), P < 0.001] and each component (Table 6).
Table 6
Predictive value of TyG index for primary endpoint and each component in univariate and multivariate analysis
| Univariate analysis | | Multivariate analysisc |
HR | 95%CI | P value | | HR | 95%CI | P value |
TyG index as a continuous variablea | | | | | | | |
Primary Endpoint | 2.218 | 1.734–2.839 | < 0.001 | | 2.092 | 1.573–2.784 | < 0.001 |
All-cause Death | 2.913 | 1.552–5.467 | < 0.001 | | 3.372 | 1.552–7.325 | 0.002 |
Non-fatal MI | 2.635 | 1.509–4.604 | < 0.001 | | 2.427 | 1.268–4.644 | 0.007 |
Non-fatal Stroke | 1.964 | 1.112–3.469 | 0.020 | | 2.022 | 1.042–3.925 | 0.038 |
Symptomatic graft stenosis or occlusion | 1.867 | 1.314–2.654 | < 0.001 | | 1.672 | 1.100-2.542 | 0.016 |
TyG index as a nominal variableb | | | | | | | |
Primary Endpoint | 2.381 | 1.752–3.234 | < 0.001 | | 2.115 | 1.501–2.980 | < 0.001 |
All-cause Death | 3.441 | 1.545–7.660 | 0.003 | | 3.187 | 1.281–7.929 | 0.013 |
Non-fatal MI | 2.716 | 1.356–5.441 | 0.005 | | 2.308 | 1.035–5.148 | 0.041 |
Non-fatal Stroke | 2.345 | 1.146-4.800 | 0.020 | | 2.374 | 1.068–5.274 | 0.034 |
Symptomatic graft stenosis or occlusion | 1.887 | 1.210–2.942 | 0.005 | | 1.567 | 0.950–2.585 | 0.079 |
Italic values indicate statistically significant associations |
TyG triglyceride glucose, MI myocardial infarction, HR hazard ratio, CI confidence interval |
a The HR was examined by per 1-unit increase of TyG index |
b The HR was examined regarding lower TyG index as reference (stratified by the optimal cutoff point of TyG index determined by ROC curve analysis) |
c The multivariate analysis was performed by using Model 4 [adjusted for age, sex (female), BMI, current smoking status, current drinking status, dyslipidemia, prior MI, prior PCI, prior stroke, PVD, diagnosis (NSTEMI), TC, HDL-C, hs-CRP, creatinine, eGFR, uric acid, GA, LVEF, multiple grafts, LIMA use and IABP use, DAPT at discharge, statin at discharge, oral hypoglycemic agents (metformin, alpha-glucosidase inhibitor, sulfonylurea or dipeptidyl peptidase 4 inhibitor) at discharge and insulin at discharge. |
Further evaluation of the risk stratification value of the TyG index for the primary endpoint was performed in various subgroups of the study population. The efficacy of TyG in increasing MACCE was consistent across all groups of age, sex, BMI, hypertension, LDL-C, oral hypoglycemic agents, LIMA, number of grafts and IABP groups (Fig. 3). Interestingly, the predictive value of the TyG index was prominent in patients who were supported by IABP perioperatively [HR (95% CI) without IABP 1.731 (1.103–2.718) vs. with IABP 51.960 (6.338-425.959), P < 0.001] (Fig. 3).