
Journal of Shanghai Jiao Tong University (Medical Science) ›› 2025, Vol. 45 ›› Issue (3): 292-300.doi: 10.3969/j.issn.1674-8115.2025.03.005
• Clinical research • Previous Articles Next Articles
YANG Chendie1(
), HU Changqing2(
), YUAN He3, TAY Guan Poh3, AMUTI Abulikemu3, ZHANG Ruiyan1, WANG Xiaoqun1,3(
)
Received:2024-08-26
Accepted:2024-11-04
Online:2025-03-28
Published:2025-03-18
Contact:
WANG Xiaoqun
E-mail:yangcd1029@163.com;690068686@qq.com;wangxq@shsmu.edu.cn
Supported by:CLC Number:
YANG Chendie, HU Changqing, YUAN He, TAY Guan Poh, AMUTI Abulikemu, ZHANG Ruiyan, WANG Xiaoqun. Association between insulin resistance and left ventricular remodeling after STEMI in patients without a history of diabetes mellitus[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2025, 45(3): 292-300.
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URL: https://xuebao.shsmu.edu.cn/EN/10.3969/j.issn.1674-8115.2025.03.005
| Item | Mean HOMA-IR level | P value | |||
|---|---|---|---|---|---|
Low (≤1.58) (n=55) | Low-medium (>1.58 and ≤2.41) (n=56) | Medium-high (>2.41 and ≤3.98) (n=54) | High (>3.98) (n=54) | ||
Demographic characteristics and clinical assessment | |||||
| Gender (male)/n (%) | 48 (87.3) | 46 (82.1) | 47 (87.0) | 46 (85.2) | 0.862 |
| Age/year | 63.40±12.28 | 66.04±10.56 | 60.39±10.45 | 60.70±13.47 | 0.042 |
| Hypertension/% | 27 (49.1) | 25 (44.6) | 28 (51.9) | 39 (72.2) | 0.020 |
| Current smoker/% | 27 (49.1) | 22 (39.3) | 27 (50.0) | 30 (55.6) | 0.386 |
| BMI/(kg·m-2) | 23.24±3.48 | 23.67±3.27 | 25.80±2.74 | 27.27±6.61 | <0.001 |
| Systolic blood pressure/mmHg | 121.89±22.83 | 121.36±16.63 | 121.72±20.59 | 127.48±17.38 | 0.305 |
| Diastolic blood pressure/mmHg | 73.78±13.63 | 76.68±12.50 | 74.61±14.66 | 77.39±13.11 | 0.460 |
| Laboratory measurement | |||||
| HbA1c/% | 5.61±0.32 | 5.66±0.38 | 5.87±0.84 | 6.19±1.22 | 0.001 |
| Fasting glucose/(mmol·L-1) | 5.60 (4.96‒7.53) | 6.68 (5.34‒8.48) | 5.84 (4.78‒7.50) | 6.54 (5.62‒9.00) | 0.073 |
| 2 h Postprandial blood glucose/(mmol·L-1) | 8.61 (7.46‒12.40) | 8.72 (7.37‒10.40) | 8.30 (7.01‒10.59) | 8.61 (7.46‒12.40) | 0.587 |
| Fasting insulin/(μIU·mL-1) | 6.69(5.02‒9.12) | 9.27 (7.22‒12.45) | 14.29 (11.31‒17.47) | 16.67 (12.83‒21.80) | <0.001 |
| Alanine transaminase/(IU·L-1) | 34.80±26.54 | 42.71±39.29 | 37.28±22.18 | 46.44±31.00 | 0.188 |
| Triglyceride/(mmol·L-1) | 1.08 (0.77‒1.60) | 1.43 (1.00‒1.80) | 1.82 (1.31‒2.41) | 1.90 (1.35‒2.45) | <0.001 |
| Total cholesterol/(mmol·L-1) | 4.68±1.39 | 4.60±1.29 | 4.77±1.05 | 4.86±1.05 | 0.700 |
| LDL-C/(mmol·L-1) | 3.04±1.36 | 2.91±1.01 | 3.01±1.00 | 3.01±0.85 | 0.928 |
| HDL-C/(mmol·L-1) | 1.14±0.28 | 1.09±0.24 | 1.03±0.20 | 1.02±0.20 | 0.030 |
| Serum creatine/(μmol·L-1) | 79.42±17.26 | 82.36±16.11 | 84.83±22.32 | 84.24±25.95 | 0.521 |
| Blood urea nitrogen/(mmol·L-1) | 5.81±1.58 | 5.74±1.52 | 5.52±1.63 | 5.61±1.60 | 0.775 |
| eGFR/[mL·min-1·(1.732 m)-2] | 97.50±21.38 | 91.00±12.33 | 98.45±25.65 | 97.94±22.95 | 0.208 |
| NT-proBNP/(pg·mL-1) | 355.50 (148.40‒1 525.00) | 493.25 (192.78‒1 364.50) | 602.15 (135.18‒1 861.00) | 253.20 (110.62‒1 069.00) | 0.285 |
| Peak cTnI level/(ng·mL-1) | 41.20 (5.47‒87.67) | 54.70 (15.42‒104.85) | 44.64 (9.69‒110.19) | 31.40 (25.61‒95.52) | 0.389 |
| Medication use | |||||
| Aspirin/n (%) | 50 (90.9) | 56 (100.0) | 54 (100.0) | 51 (94.4) | 0.025 |
| P2Y12 inhibitor/n (%) | 55 (100.0) | 52 (92.9) | 54 (100.0) | 50 (92.6) | 0.041 |
| β blocker/n (%) | 53 (96.4) | 40 (71.4) | 47 (87.0) | 50 (92.6) | 0.001 |
| ACEI/ARB/n (%) | 36 (65.5) | 39 (69.6) | 39 (72.2) | 47 (87.0) | 0.061 |
| ARNI/n (%) | 15 (27.3) | 12 (21.4) | 16 (29.6) | 17 (31.5) | 0.661 |
| SGLT2 inhibitor/n (%) | 2 (3.6) | 2 (3.6) | 2 (3.7) | 7 (13.0) | 0.096 |
| MRA/n (%) | 4 (7.3) | 6 (10.7) | 7 (13.0) | 6 (11.1) | 0.806 |
| Diuretics/n (%) | 1 (1.8) | 6 (10.7) | 7 (13.0) | 4 (7.4) | 0.164 |
Tab 1 Baseline characteristics of patients with different HOMA-IR levels
| Item | Mean HOMA-IR level | P value | |||
|---|---|---|---|---|---|
Low (≤1.58) (n=55) | Low-medium (>1.58 and ≤2.41) (n=56) | Medium-high (>2.41 and ≤3.98) (n=54) | High (>3.98) (n=54) | ||
Demographic characteristics and clinical assessment | |||||
| Gender (male)/n (%) | 48 (87.3) | 46 (82.1) | 47 (87.0) | 46 (85.2) | 0.862 |
| Age/year | 63.40±12.28 | 66.04±10.56 | 60.39±10.45 | 60.70±13.47 | 0.042 |
| Hypertension/% | 27 (49.1) | 25 (44.6) | 28 (51.9) | 39 (72.2) | 0.020 |
| Current smoker/% | 27 (49.1) | 22 (39.3) | 27 (50.0) | 30 (55.6) | 0.386 |
| BMI/(kg·m-2) | 23.24±3.48 | 23.67±3.27 | 25.80±2.74 | 27.27±6.61 | <0.001 |
| Systolic blood pressure/mmHg | 121.89±22.83 | 121.36±16.63 | 121.72±20.59 | 127.48±17.38 | 0.305 |
| Diastolic blood pressure/mmHg | 73.78±13.63 | 76.68±12.50 | 74.61±14.66 | 77.39±13.11 | 0.460 |
| Laboratory measurement | |||||
| HbA1c/% | 5.61±0.32 | 5.66±0.38 | 5.87±0.84 | 6.19±1.22 | 0.001 |
| Fasting glucose/(mmol·L-1) | 5.60 (4.96‒7.53) | 6.68 (5.34‒8.48) | 5.84 (4.78‒7.50) | 6.54 (5.62‒9.00) | 0.073 |
| 2 h Postprandial blood glucose/(mmol·L-1) | 8.61 (7.46‒12.40) | 8.72 (7.37‒10.40) | 8.30 (7.01‒10.59) | 8.61 (7.46‒12.40) | 0.587 |
| Fasting insulin/(μIU·mL-1) | 6.69(5.02‒9.12) | 9.27 (7.22‒12.45) | 14.29 (11.31‒17.47) | 16.67 (12.83‒21.80) | <0.001 |
| Alanine transaminase/(IU·L-1) | 34.80±26.54 | 42.71±39.29 | 37.28±22.18 | 46.44±31.00 | 0.188 |
| Triglyceride/(mmol·L-1) | 1.08 (0.77‒1.60) | 1.43 (1.00‒1.80) | 1.82 (1.31‒2.41) | 1.90 (1.35‒2.45) | <0.001 |
| Total cholesterol/(mmol·L-1) | 4.68±1.39 | 4.60±1.29 | 4.77±1.05 | 4.86±1.05 | 0.700 |
| LDL-C/(mmol·L-1) | 3.04±1.36 | 2.91±1.01 | 3.01±1.00 | 3.01±0.85 | 0.928 |
| HDL-C/(mmol·L-1) | 1.14±0.28 | 1.09±0.24 | 1.03±0.20 | 1.02±0.20 | 0.030 |
| Serum creatine/(μmol·L-1) | 79.42±17.26 | 82.36±16.11 | 84.83±22.32 | 84.24±25.95 | 0.521 |
| Blood urea nitrogen/(mmol·L-1) | 5.81±1.58 | 5.74±1.52 | 5.52±1.63 | 5.61±1.60 | 0.775 |
| eGFR/[mL·min-1·(1.732 m)-2] | 97.50±21.38 | 91.00±12.33 | 98.45±25.65 | 97.94±22.95 | 0.208 |
| NT-proBNP/(pg·mL-1) | 355.50 (148.40‒1 525.00) | 493.25 (192.78‒1 364.50) | 602.15 (135.18‒1 861.00) | 253.20 (110.62‒1 069.00) | 0.285 |
| Peak cTnI level/(ng·mL-1) | 41.20 (5.47‒87.67) | 54.70 (15.42‒104.85) | 44.64 (9.69‒110.19) | 31.40 (25.61‒95.52) | 0.389 |
| Medication use | |||||
| Aspirin/n (%) | 50 (90.9) | 56 (100.0) | 54 (100.0) | 51 (94.4) | 0.025 |
| P2Y12 inhibitor/n (%) | 55 (100.0) | 52 (92.9) | 54 (100.0) | 50 (92.6) | 0.041 |
| β blocker/n (%) | 53 (96.4) | 40 (71.4) | 47 (87.0) | 50 (92.6) | 0.001 |
| ACEI/ARB/n (%) | 36 (65.5) | 39 (69.6) | 39 (72.2) | 47 (87.0) | 0.061 |
| ARNI/n (%) | 15 (27.3) | 12 (21.4) | 16 (29.6) | 17 (31.5) | 0.661 |
| SGLT2 inhibitor/n (%) | 2 (3.6) | 2 (3.6) | 2 (3.7) | 7 (13.0) | 0.096 |
| MRA/n (%) | 4 (7.3) | 6 (10.7) | 7 (13.0) | 6 (11.1) | 0.806 |
| Diuretics/n (%) | 1 (1.8) | 6 (10.7) | 7 (13.0) | 4 (7.4) | 0.164 |
| Item | Mean HOMA-IR level | P value | |||
|---|---|---|---|---|---|
| Low(≤1.58) | Low-medium (>1.58 and ≤2.41) | Medium-high (>2.41 and ≤3.98) | High (>3.98) | ||
| LVEDV index/(mL·m-2) | |||||
| Baseline | 71.41±20.42 | 68.22±15.72 | 73.52±18.68 | 63.09±11.13 | 0.009 |
| Follow-up | 68.69±21.54 | 69.11±16.91 | 71.99±14.54 | 66.85±12.42 | 0.455 |
| Δ | -2.73±12.30 | 0.88±9.58 | -1.52±12.01 | 3.77±9.93 | 0.013 |
| LVESV index/(mL·m-2) | |||||
| Baseline | 30.01±15.62 | 27.96±12.03 | 31.20±14.04 | 24.48±6.23 | 0.032 |
| Follow-up | 28.45±16.11 | 28.33±12.47 | 28.74±10.16 | 25.67±8.75 | 0.528 |
| Δ | -1.56±6.22 | 0.37±5.87 | -2.46±9.57 | 1.19±8.10 | 0.047 |
| LVEDD/mm | |||||
| Baseline | 50.56±6.50 | 49.84±6.06 | 52.46±5.45 | 49.87±4.01 | 0.051 |
| Follow-up | 49.76±6.99 | 50.00±5.93 | 52.07±4.41 | 50.91±4.13 | 0.118 |
| Δ | -0.80±3.46 | 0.16±3.03 | -0.39±3.49 | 1.04±3.31 | 0.027 |
| LVESD/mm | |||||
| Baseline | 34.44±7.14 | 33.88±6.55 | 35.91±6.33 | 33.39±4.15 | 0.168 |
| Follow-up | 33.64±7.40 | 33.91±6.31 | 35.00±4.67 | 33.72±4.64 | 0.599 |
| Δ | -0.80±2.59 | 0.04±2.91 | -0.91±3.67 | 0.33±4.11 | 0.147 |
| IVST/mm | |||||
| Baseline | 9.36±1.01 | 9.32±1.16 | 9.93±1.53 | 9.46±1.30 | 0.050 |
| Follow-up | 9.33±1.02 | 9.11±1.14 | 9.54±1.22 | 9.46±1.19 | 0.216 |
| Δ | -0.04±0.90 | -0.21±0.99 | -0.39±1.17 | 0±1.17 | 0.204 |
| LVPWT/mm | |||||
| Baseline | 8.93±0.63 | 8.66±0.84 | 9.33±0.95 | 9.00±1.18 | 0.002 |
| Follow-up | 8.87±0.75 | 8.79±0.85 | 9.13±0.97 | 8.91±0.96 | 0.216 |
| Δ | -0.05±0.65 | 0.12±0.72 | -0.20±0.88 | -0.09±1.15 | 0.255 |
| LVMI/(g·mm-2) | |||||
| Baseline | 96.11±24.27 | 90.16±18.38 | 103.38±28.52 | 86.74±18.06 | 0.001 |
| Follow-up | 92.94±24.73 | 90.57±21.50 | 97.43±22.24 | 89.89±20.66 | 0.288 |
| Δ | -3.17±15.22 | 0.42±12.82 | -5.95±14.79 | 3.15±15.28 | 0.008 |
| LVEF/% | |||||
| Baseline | 57.85±8.97 | 58.20±8.85 | 56.69±9.80 | 59.31±8.09 | 0.500 |
| Follow-up | 58.44±9.98 | 57.91±9.55 | 58.33±8.33 | 60.24±7.33 | 0.531 |
| Δ | 0.58±4.89 | -0.29±4.77 | 1.65±3.89 | 0.93±7.08 | 0.285 |
Tab 2 Changes in echocardiography parameters during follow-up grouped by HOMA-IR quartiles
| Item | Mean HOMA-IR level | P value | |||
|---|---|---|---|---|---|
| Low(≤1.58) | Low-medium (>1.58 and ≤2.41) | Medium-high (>2.41 and ≤3.98) | High (>3.98) | ||
| LVEDV index/(mL·m-2) | |||||
| Baseline | 71.41±20.42 | 68.22±15.72 | 73.52±18.68 | 63.09±11.13 | 0.009 |
| Follow-up | 68.69±21.54 | 69.11±16.91 | 71.99±14.54 | 66.85±12.42 | 0.455 |
| Δ | -2.73±12.30 | 0.88±9.58 | -1.52±12.01 | 3.77±9.93 | 0.013 |
| LVESV index/(mL·m-2) | |||||
| Baseline | 30.01±15.62 | 27.96±12.03 | 31.20±14.04 | 24.48±6.23 | 0.032 |
| Follow-up | 28.45±16.11 | 28.33±12.47 | 28.74±10.16 | 25.67±8.75 | 0.528 |
| Δ | -1.56±6.22 | 0.37±5.87 | -2.46±9.57 | 1.19±8.10 | 0.047 |
| LVEDD/mm | |||||
| Baseline | 50.56±6.50 | 49.84±6.06 | 52.46±5.45 | 49.87±4.01 | 0.051 |
| Follow-up | 49.76±6.99 | 50.00±5.93 | 52.07±4.41 | 50.91±4.13 | 0.118 |
| Δ | -0.80±3.46 | 0.16±3.03 | -0.39±3.49 | 1.04±3.31 | 0.027 |
| LVESD/mm | |||||
| Baseline | 34.44±7.14 | 33.88±6.55 | 35.91±6.33 | 33.39±4.15 | 0.168 |
| Follow-up | 33.64±7.40 | 33.91±6.31 | 35.00±4.67 | 33.72±4.64 | 0.599 |
| Δ | -0.80±2.59 | 0.04±2.91 | -0.91±3.67 | 0.33±4.11 | 0.147 |
| IVST/mm | |||||
| Baseline | 9.36±1.01 | 9.32±1.16 | 9.93±1.53 | 9.46±1.30 | 0.050 |
| Follow-up | 9.33±1.02 | 9.11±1.14 | 9.54±1.22 | 9.46±1.19 | 0.216 |
| Δ | -0.04±0.90 | -0.21±0.99 | -0.39±1.17 | 0±1.17 | 0.204 |
| LVPWT/mm | |||||
| Baseline | 8.93±0.63 | 8.66±0.84 | 9.33±0.95 | 9.00±1.18 | 0.002 |
| Follow-up | 8.87±0.75 | 8.79±0.85 | 9.13±0.97 | 8.91±0.96 | 0.216 |
| Δ | -0.05±0.65 | 0.12±0.72 | -0.20±0.88 | -0.09±1.15 | 0.255 |
| LVMI/(g·mm-2) | |||||
| Baseline | 96.11±24.27 | 90.16±18.38 | 103.38±28.52 | 86.74±18.06 | 0.001 |
| Follow-up | 92.94±24.73 | 90.57±21.50 | 97.43±22.24 | 89.89±20.66 | 0.288 |
| Δ | -3.17±15.22 | 0.42±12.82 | -5.95±14.79 | 3.15±15.28 | 0.008 |
| LVEF/% | |||||
| Baseline | 57.85±8.97 | 58.20±8.85 | 56.69±9.80 | 59.31±8.09 | 0.500 |
| Follow-up | 58.44±9.98 | 57.91±9.55 | 58.33±8.33 | 60.24±7.33 | 0.531 |
| Δ | 0.58±4.89 | -0.29±4.77 | 1.65±3.89 | 0.93±7.08 | 0.285 |
| Mean HOMA-IR level | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
|---|---|---|---|---|---|
| Low (≤1.58) | Reference | Reference | Reference | Reference | Reference |
| Low-medium (>1.58 and ≤2.41) | |||||
| Coefficient (95%CI) | 3.608 (-0.515‒7.730) | 3.506 (-0.645‒7.657) | 4.036 (-0.206‒8.279) | 5.541 (1.169‒9.914) | 3.036 (-1.373‒7.445) |
| Standardized β | 0.141 | 0.137 | 0.157 | 0.216 | 0.118 |
| P value | 0.086 | 0.097 | 0.062 | 0.013 | 0.176 |
| Medium-high (>2.41 and ≤3.98) | |||||
| Coefficient (95%CI) | 1.201 (-2.959‒5.361) | 1.199 (-2.990‒5.388) | 1.918 (-2.434‒6.270) | 2.386 (-1.915‒6.688) | 2.674 (-1.492‒6.839) |
| Standardized β | 0.046 | 0.046 | 0.074 | 0.092 | 0.103 |
| P value | 0.570 | 0.573 | 0.386 | 0.275 | 0.207 |
| High (>3.98) | |||||
| Coefficient (95%CI) | 6.492 (2.332‒10.652) | 6.453 (2.266‒10.641) | 7.348 (2.786‒11.910) | 8.028 (3.530‒12.526) | 7.727 (3.317‒12.136) |
| Standardized β | 0.250 | 0.248 | 0.283 | 0.309 | 0.298 |
| P value | 0.002 | 0.003 | 0.002 | <0.001 | <0.001 |
Tab 3 Multivariate linear regression analysis for ∆LVEDV index and HOMA-IR levels after STEMI
| Mean HOMA-IR level | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
|---|---|---|---|---|---|
| Low (≤1.58) | Reference | Reference | Reference | Reference | Reference |
| Low-medium (>1.58 and ≤2.41) | |||||
| Coefficient (95%CI) | 3.608 (-0.515‒7.730) | 3.506 (-0.645‒7.657) | 4.036 (-0.206‒8.279) | 5.541 (1.169‒9.914) | 3.036 (-1.373‒7.445) |
| Standardized β | 0.141 | 0.137 | 0.157 | 0.216 | 0.118 |
| P value | 0.086 | 0.097 | 0.062 | 0.013 | 0.176 |
| Medium-high (>2.41 and ≤3.98) | |||||
| Coefficient (95%CI) | 1.201 (-2.959‒5.361) | 1.199 (-2.990‒5.388) | 1.918 (-2.434‒6.270) | 2.386 (-1.915‒6.688) | 2.674 (-1.492‒6.839) |
| Standardized β | 0.046 | 0.046 | 0.074 | 0.092 | 0.103 |
| P value | 0.570 | 0.573 | 0.386 | 0.275 | 0.207 |
| High (>3.98) | |||||
| Coefficient (95%CI) | 6.492 (2.332‒10.652) | 6.453 (2.266‒10.641) | 7.348 (2.786‒11.910) | 8.028 (3.530‒12.526) | 7.727 (3.317‒12.136) |
| Standardized β | 0.250 | 0.248 | 0.283 | 0.309 | 0.298 |
| P value | 0.002 | 0.003 | 0.002 | <0.001 | <0.001 |
| 1 | JENČA D, MELENOVSKÝ V, STEHLIK J, et al. Heart failure after myocardial infarction: incidence and predictors[J]. ESC Heart Fail, 2021, 8(1): 222-237. |
| 2 | FRANTZ S, HUNDERTMARK M J, SCHULZ-MENGER J, et al. Left ventricular remodelling post-myocardial infarction: pathophysiology, imaging, and novel therapies[J]. Eur Heart J, 2022, 43(27): 2549-2561. |
| 3 | YAP J, IREI J, LOZANO-GERONA J, et al. Macrophages in cardiac remodelling after myocardial infarction[J]. Nat Rev Cardiol, 2023, 20(6): 373-385. |
| 4 | QUIJADA P, PARK S, ZHAO P, et al. Cardiac pericytes mediate the remodeling response to myocardial infarction[J]. J Clin Invest, 2023, 133(10): e162188. |
| 5 | BULLUCK H, CARBERRY J, CARRICK D, et al. Redefining adverse and reverse left ventricular remodeling by cardiovascular magnetic resonance following ST-segment-elevation myocardial infarction and their implications on long-term prognosis[J]. Circ Cardiovasc Imaging, 2020, 13(7): e009937. |
| 6 | BOSTAN M M, STĂTESCU C, ANGHEL L, et al. Post-myocardial infarction ventricular remodeling biomarkers-the key link between pathophysiology and clinic[J]. Biomolecules, 2020, 10(11): 1587. |
| 7 | YANG C D, SHEN Y, DING F H, et al. Visit-to-visit fasting plasma glucose variability is associated with left ventricular adverse remodeling in diabetic patients with STEMI[J]. Cardiovasc Diabetol, 2020, 19(1): 131. |
| 8 | LEE S H, PARK S Y, CHOI C S. Insulin resistance: from mechanisms to therapeutic strategies[J]. Diabetes Metab J, 2022, 46(1): 15-37. |
| 9 | DI PINO A, DEFRONZO R A. Insulin resistance and atherosclerosis: implications for insulin-sensitizing agents[J]. Endocr Rev, 2019, 40(6): 1447-1467. |
| 10 | ROKICKA D, HUDZIK B, WRÓBEL M, et al. The prognostic impact of insulin resistance surrogates in patients with acute myocardial infarction with and without type 2 diabetes[J]. Cardiovasc Diabetol, 2024, 23(1): 147. |
| 11 | JIANG H D, LIU Y T, GUO H Y, et al. The association between the triglyceride-glucose index and in-stent restenosis in patients undergoing percutaneous coronary intervention: a systematic review and meta-analysis[J]. BMC Cardiovasc Disord, 2024, 24(1): 234. |
| 12 | SUNDSTRÖM J, LIND L, NYSTRÖM N, et al. Left ventricular concentric remodeling rather than left ventricular hypertrophy is related to the insulin resistance syndrome in elderly men[J]. Circulation, 2000, 101(22): 2595-2600. |
| 13 | PARIZO J, MAHAFFEY K W. Diabetes and heart failure post-acute myocardial infarction: important associations and need for evidence-based interventions[J]. Eur J Prev Cardiol, 2020, 27(17): 1887-1889. |
| 14 | INGELSSON E, SUNDSTRÖM J, ARNLÖV J, et al. Insulin resistance and risk of congestive heart failure[J]. JAMA, 2005, 294(3): 334-341. |
| 15 | SHAH R V, ABBASI S A, HEYDARI B, et al. Insulin resistance, subclinical left ventricular remodeling, and the obesity paradox: MESA (Multi-Ethnic Study of Atherosclerosis)[J]. J Am Coll Cardiol, 2013, 61(16): 1698-1706. |
| 16 | QIAO T T, LUO T, PEI H L, et al. Association between abdominal obesity indices and risk of cardiovascular events in Chinese populations with type 2 diabetes: a prospective cohort study[J]. Cardiovasc Diabetol, 2022, 21(1): 225. |
| 17 | LIU Y K, LING S S, LUI L M W, et al. Prevalence of type 2 diabetes mellitus, impaired fasting glucose, general obesity, and abdominal obesity in patients with bipolar disorder: a systematic review and meta-analysis[J]. J Affect Disord, 2022, 300: 449-461. |
| 18 | WAN H, WANG Y Y, XIANG Q, et al. Associations between abdominal obesity indices and diabetic complications: Chinese visceral adiposity index and neck circumference[J]. Cardiovasc Diabetol, 2020, 19(1): 118. |
| 19 | MOHAMMADI H, OHM J, DISCACCIATI A, et al. Abdominal obesity and the risk of recurrent atherosclerotic cardiovascular disease after myocardial infarction[J]. Eur J Prev Cardiol, 2020, 27(18): 1944-1952. |
| 20 | POWELL-WILEY T M, POIRIER P, BURKE L E, et al. Obesity and cardiovascular disease: a scientific statement from the American heart association[J]. Circulation, 2021, 143(21): e984-e1010. |
| 21 | DALE ABEL E. Insulin signaling in the heart[J]. Am J Physiol Endocrinol Metab, 2021, 321(1): E130-E145. |
| 22 | TRIFUNOVIC D, STANKOVIC S, SOBIC-SARANOVIC D, et al. Acute insulin resistance in ST-segment elevation myocardial infarction in non-diabetic patients is associated with incomplete myocardial reperfusion and impaired coronary microcirculatory function[J]. Cardiovasc Diabetol, 2014, 13: 73. |
| 23 | THAKKER G D, FRANGOGIANNIS N G, BUJAK M, et al. Effects of diet-induced obesity on inflammation and remodeling after myocardial infarction[J]. Am J Physiol Heart Circ Physiol, 2006, 291(5): H2504-H2514. |
| 24 | MENG Z J, ZHANG Z, ZHAO J L, et al. Nitrative modification of caveolin-3: a novel mechanism of cardiac insulin resistance and a potential therapeutic target against ischemic heart failure in prediabetic animals[J]. Circulation, 2023, 147(15): 1162-1179. |
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