| Literature DB >> 24371451 |
Shuzhen Guo1, Jianxin Chen1, Wenjing Chuo1, Lei Liu2, Xuanchao Feng1, Hongjian Lian1, Lei Zheng1, Yong Wang1, Hua Xie1, Liangtao Luo1, Chenglong Zheng1, Bangze Fu1, Wei Wang1.
Abstract
Objective. To explore new diagnostic patterns for syndromes to overcome the insufficiency of obtainable macrocharacteristics and specific biomarkers. Methods. Chinese miniswines were subjected to Ameroid constrictor, placed around the proximal left anterior descending branch. On the 4th week, macrocharacteristics, coronary angiography, echocardiography, and hemorheology indices were detected for diagnosis. IL-1, IL-6, IL-8, IL-10, TNF- α , and hsCRP in serum were detected, and Decision Tree was built. Results. According to current official-issued standard, model animals matched the diagnosis of blood stasis syndrome with myocardial ischemia based on findings, including >90% occlusion, attenuated left ventricular segmental motion, dark red or purple tongues, and higher blood viscosity. Significant decrease of IL-10 and increase of TNF- α were found in model animals. However, in the Decision Tree, besides IL-10 and TNF- α , IL-8 helped to increase the accuracy of classification to 86%. Conclusions. The Decision Tree building with TNF- α , IL-10, and IL-8 is helpful for the diagnosis of blood stasis syndrome in myocardial ischemia animals. What is more is that our data set up a new path to the differentiation of syndrome by feature patterns consisting of multiple biomarkers not only for animals but also for patients. We believe that it will contribute to the standardization and international application of syndromes.Entities:
Year: 2013 PMID: 24371451 PMCID: PMC3859256 DOI: 10.1155/2013/130702
Source DB: PubMed Journal: Evid Based Complement Alternat Med ISSN: 1741-427X Impact factor: 2.629
Figure 1Coronary angiography.
Changes of heart function evaluated by echocardiography (Mean ± SEM).
| Control ( | Model ( |
| |
|---|---|---|---|
| LVEDd (cm) | 3.208 ± 0.124** | 3.895 ± 0.076 | 0.000 |
| LVEDs (cm) | 2.041 ± 0.043** | 2.657 ± 0.072 | 0.000 |
| ESV (mL) | 8.559 ± 0.940** | 16.115 ± 1.217 | 0.003 |
| EDV (mL) | 22.542 ± 2.117** | 36.371 ± 1.628 | 0.000 |
| IVSDs (cm) | 1.185 ± 0.199** | 0.833 ± 0.032 | 0.004 |
| IVSDd (cm) | 0.692 ± 0.029* | 0.592 ± 0.020 | 0.024 |
| LVAWTs (cm) | |||
| Mitral valve level | 1.029 ± 0.055 | 1.004 ± 0.027 | 0.665 |
| Papillary muscles level | 1.153 ± 0.032** | 0.849 ± 0.044 | 0.001 |
| Apex level | 1.145 ± 0.045** | 0.623 ± 0.044 | 0.000 |
| LVAWTd (cm) | |||
| Mitral valve level | 0.728 ± 0.025 | 0.739 ± 0.017 | 0.754 |
| Papillary muscles level | 0.794 ± 0.034* | 0.648 ± 0.027 | 0.012 |
| Apex level | 0.808 ± 0.040** | 0.546 ± 0.032 | 0.000 |
| Wall thickening (%) | |||
| Mitral valve level | 41.748 ± 6.016 | 36.317 ± 2.498 | 0.350 |
| Papillary muscles level | 47.325 ± 7.038 | 30.136 ± 3.268 | 0.023 |
| Apex level | 42.564 ± 3.194** | 12.072 ± 1.887 | 0.000 |
| FS (%) | 35.818 ± 1.752 | 30.835 ± 2.780 | 0.372 |
| EF (%) | 61.770 ± 2.067 | 56.299 ± 2.020 | 0.189 |
Model versus Control group, *P < 0.05; **P < 0.01.
LVEDd: left ventricular end-diastolic dimension; LVEDs: left ventricular end-systolic dimension; ESV: end-systolic volume; EDV: end-diastolic volume; IVSDs: interventricular end-systolic septal depth; IVSDd: interventricular end-diastolic septal depth; LVAWTs: left ventricular end systolic anterior wall thickness; LVAWTd: left ventricular end diastolic anterior wall thickness; FS: fractional shortening; EF: ejection fraction.
Hemorheology indices (Mean ± SEM).
| Control ( | Model ( |
| |
|---|---|---|---|
| Whole blood viscosity 1/150 (mPa.s) | 5.224 ± 0.149 | 5.275 ± 0.091 | 0.795 |
| Whole blood viscosity 1/38 (mPa.s) | 8.758 ± 0.234 | 9.563 ± 0.163* | 0.025 |
| Whole blood viscosity 1/10 (mPa.s) | 3.727 ± 0.112 | 3.608 ± 0.068 | 0.395 |
| Whole blood viscosity 1/5 (mPa.s) | 12.590 ± 0.362 | 13.987 ± 0.253* | 0.012 |
| Reduced viscosity 1/150 (mPa.s) | 10.091 ± 0.300 | 10.438 ± 0.191 | 0.350 |
| Reduced viscosity 1/38 (mPa.s) | 18.861 ± 0.600 | 20.593 ± 0.385* | 0.026 |
| Reduced viscosity 1/10 (mPa.s) | 6.189 ± 0.189 | 6.272 ± 0.128 | 0.725 |
| Reduced viscosity 1/5 (mPa.s) | 28.835 ± 0.921 | 31.328 ± 0.621* | 0.047 |
| Plasma viscosity (mPa.s) | 1.843 ± 0.054 | 1.899 ± 0.042 | 0.465 |
| Hematocrit (%) | 43.545 ± 0.928 | 42.727 ± 0.717 | 0.550 |
| Erythrocyte aggregation index | 2.651 ± 0.069 | 2.534 ± 0.042 | 0.163 |
| Aggregation index of integral area | 498.500 ± 15.307 | 498.500 ± 8.502 | 1.000 |
| Erythrocyte deformability index | 0.367 ± 0.007 | 0.382 ± 0.006 | 0.208 |
| Deformation index of integral area | 191.800 ± 5.736 | 190.848 ± 3.289 | 0.889 |
Model versus Control group, *P < 0.05; **P < 0.01.
Changes of inflammation related cytokines (Mean ± SEM).
| Control ( | Model ( |
| |
|---|---|---|---|
| IL-1 (ng/mL) | 0.279 ± 0.021 | 0.308 ± 0.036 | 0.466 |
| IL-6 (pg/mL) | 288.037 ± 15.161 | 307.662 ± 27.806 | 0.542 |
| IL-8 (pg/mL) | 97.436 ± 6.673 | 86.832 ± 10.958 | 0.387 |
| IL-10 (pg/mL) | 1.467 ± 0.129 | 0.962 ± 0.142* | 0.018 |
| TNF- | 1.266 ± 0.117 | 1.769 ± 0.147* | 0.012 |
| hsCRP (ng/mL) | 10.591 ± 0.839 | 12.936 ± 1.324 | 0.126 |
Model versus Control group, *P < 0.05; **P < 0.01.
Figure 2Importance of inflammation related cytokines in the Decision Tree of blood stasis syndrome. Growing method: CRT. Dependent variable: blood stasis in heart.
Figure 3Decision Tree of blood stasis syndrome building by inflammation related cytokines.
Prediction accuracy of the Decision Tree.
| Observed | Predicted | ||
|---|---|---|---|
| Control | Model | Percent correct | |
| Control | 26 | 2 | 92.9% |
| Model | 4 | 11 | 73.3% |
| Overall percentage | 69.8% | 30.2% | 86.0% |