A total of 5231 subjects undergoing health check-up were included and assessed in this study. 55.9% (2922) of enrolled subjects were male and the mean age was 47.9 ± 10.7 years. Of the enrolled subjects, 56.7% had BMI values classified as overweight or obesity and 3108 subjects (59.4%) were detected HBsAb positive. Among subjects undergoing colonoscopy examination, haemorrhoid was found in 3000 subjects (57.4%) and 29 subjects (0.6%) were found with cancers. Regarding TCM syndrome differentiation, subjects diagnosed with SADH, IDSIBSB, YaDSK and YiDLK were 4490 (85.8%), 4576 (87.5%), 5207 (99.5%) and 4232 (80.9%) respectively. There were only 30 (0.6%) diagnosed with DQB. The clinical characteristics of the enrolled subjects are summarized in Table 1.
Table 1
Demographic characteristics of participants
Item | M ± SD | n | (%) | | Item | n | (%) |
Sex | | | | | Anti-HCV Ab | | |
Male | | 2922 | 55.9 | | Negative | 5161 | 98.7 |
Female | | 2309 | 44.1 | | Positive | 70 | 1.3 |
Age | 47.9 ± 10.7 | | | | OB | | |
BMI | | | | | Negative | 5177 | 99.0 |
< 18 | | 122 | 2.3 | | Positive | 54 | 1.0 |
18 ~ 24 | | 2799 | 53.5 | | AFP | | |
> 24 | | 2310 | 44.2 | | < 20 ng/ml | 4847 | 92.7 |
CA199 | | | | | > 21 ng/ml | 384 | 7.3 |
< 37 U/ml | | 5008 | 95.7 | | CEA | | |
> 38 U/ml | | 223 | 4.3 | | < 5 ng/ml | 4868 | 93.1 |
TG | | | | | > 6 ng/ml | 363 | 6.9 |
< 150 mg/dl | | 4000 | 76.5 | | HBsAg | | |
> 151 mg/dl | | 1231 | 23.5 | | Negative | 2755 | 52.7 |
choles | | | | | Positive | 2476 | 47.3 |
< 200 mg/dl | | 2734 | 52.3 | | IOP | | |
> 201 mg/dl | | 2497 | 47.7 | | 10 ~ 21 mmHg | 4790 | 91.6 |
AST | | | | | > 22 mmHg | 441 | 8.4 |
8 ~ 31U/L | | 4880 | 93.3 | | Colonoscopy | | |
< 7,>32U/L | | 351 | 6.7 | | Negative | 179 | 3.4 |
ALT | | | | | Hemorrhoid | 3000 | 57.4 |
0 ~ 41U/L | | 4634 | 88.6 | | Polyp | 308 | 5.9 |
> 42U/L | | 597 | 11.4 | | Polyp&Hemorrhoid | 1367 | 26.1 |
rGT | | | | | Tumor&Ca | 29 | 0.6 |
< 60U/L | | 3683 | 70.4 | | colitis | 95 | 1.8 |
> 61U/L | | 1548 | 29.6 | | Diverticulosis | 253 | 4.8 |
HBsAb | | | | | | | |
Negative | | 2123 | 40.6 | | | | |
Positive | | 3108 | 59.4 | | | | |
SADH | | 4490 | 85.8 | | | | |
IDSIBSB | | 4576 | 87.5 | | | | |
YaDSK | | 5207 | 99.5 | | | | |
YiDLK | | 4232 | 80.9 | | | | |
DQB | | 30 | 0.6 | | | | |
We next determined the correlation of 5 TCM syndromes with clinical indexes. The results showed that SADH had significant correlations with BMI, the symptoms in following systems including respiratory system, cardiovascular system, abdomen system, neurologic system, skeletomuscular system and colonoscopy (Table 2). We found that IDSIBSB was significantly correlated with tumour markers including CEA, CA199 and AFP. In addition, statistical correlations were found between IDSIBSB and symptoms in many systems (Table 3). YaDSK was found only to have significant correlations with colonoscopy and symptoms in cardiovascular system, abdomen system and skin (Table 4). YiDLK was correlated with the levels of diagnostic markers that were associated with liver including AST, ALT, rGT, AFP, HBsAb and HBsAg. It also had high correlations with the symptoms in following systems including head and neck/lymphatic, respiratory, cardiovascular, abdomen, neurologic, skin and skeletomuscular systems (Table 5). Statistical correlations of DQB with symptoms in several systems was observed, including head and neck/lymphatic, respiratory, cardiovascular, abdomen, neurologic, skin and skeletomuscular systems (Table 6).
Table 2
Correlation of various medical indicators to syndrome of accumulated dampness-heat (SADH) (Pearson Chi-Square Test)
Variable | Pearson Chi-Squared Test | df | p | Variable | Pearson Chi-Squared Test | df | p |
Correlation Coefficient | Correlation Coefficient |
sex | 7.696 | 1 | 0.006* | choles | 7.184 | 1 | 0.007* |
7.695 | 1 | 0.006* | 7.183 | 1 | 0.007* |
age | 8.546 | 4 | 0.074 | AST | 0.954 | 1 | 0.329 |
3.233 | 1 | 0.072 | 0.954 | 1 | 0.329 |
BMI | 14.732 | 2 | 0.001* | ALT | 0.127 | 1 | 0.721 |
10.539 | 1 | 0.001* | 0.127 | 1 | 0.721 |
Head and neck /Conjunctive/ Lymphatic | 205.110 | 1 | 0.000* | rGT | 4.628 | 1 | 0.031 |
205.071 | 1 | 0.000* | 4.627 | 1 | 0.031 |
Respiratory System | 205.110 | 1 | 0.000* | AFP | 2.931 | 1 | 0.087 |
205.071 | 1 | 0.000* | 2.931 | 1 | 0.087 |
Cardiovascular System | 8.316 | 1 | 0.004* | CEA | 0.014 | 1 | 0.907 |
8.314 | 1 | 0.004* | 0.014 | 1 | 0.907 |
Digestive System | 8.316 | 1 | 0.004* | HBsAb | 0.031 | 1 | 0.861 |
8.314 | 1 | 0.004* | 0.031 | 1 | 0.861 |
Neurologic System | 50.304 | 1 | 0.000* | hepatitis C antibody | 1.769 | 1 | 0.184 |
50.294 | 1 | 0.000* | 1.769 | 1 | 0.184 |
Skin | 160.842 | 1 | 0.000* | OB | 0.882 | 1 | 0.348 |
160.811 | 1 | 0.000* | 0.882 | 1 | 0.348 |
Skeletomuscular System | 59.966 | 1 | 0.000* | I.P | 0.307 | 1 | 0.579 |
59.955 | 1 | 0.000* | 0.307 | 1 | 0.579 |
CA199 | 0.053 | 1 | 0.818 | HBsAg | 0.985 | 1 | 0.321 |
0.053 | 1 | 0.818 | 0.985 | 1 | 0.321 |
TG | 2.114 | 1 | 0.146 | Colonoscopy | 2081.810 | 6 | 0.000* |
2.114 | 1 | 0.146 | 178.413 | 1 | 0.000* |
*p < 0.05 | | | | | | | |
Table 3
Correlation of various medical indicators to intermittent dysentery with syndrome of internal blockade of static blood (IDSIBSB) (Pearson Chi-Squared Test)
Variable | Pearson Chi-Squared Test | df | p | Variable | Pearson Chi-Squared Test | df | p |
Correlation Coefficient | Correlation Coefficient |
Sex | 5.090 | 1 | 0.024* | choles | 8.195 | 1 | 0.004* |
5.089 | 1 | 0.024* | 8.194 | 1 | 0.004* |
age | 4.916 | 4 | 0.296 | AST | 0.225 | 1 | 0.635 |
1.834 | 1 | 0.176 | 0.225 | 1 | 0.636 |
BMI | 15.391 | 2 | 0.000* | ALT | 0.073 | 1 | 0.786 |
9.505 | 1 | 0.002* | 0.073 | 1 | 0.786 |
Head and neck /Conjunctive/ Lymphatic | 178.334 | 1 | 0.000* | rGT | 2.555 | 1 | 0.110 |
178.300 | 1 | 0.000* | 2.554 | 1 | 0.110 |
Respiratory System | 178.334 | 1 | 0.000* | AFP | 15.538 | 1 | 0.000* |
178.300 | 1 | 0.000* | 15.535 | 1 | 0.000* |
Cardiovascular System | 8.364 | 1 | 0.004* | CEA | 22.393 | 1 | 0.000* |
8.363 | 1 | 0.004* | 22.389 | 1 | 0.000* |
Digestive System | 8.364 | 1 | 0.004* | HBsAb | 0.079 | 1 | 0.779 |
8.363 | 1 | 0.004* | 0.079 | 1 | 0.779 |
Neurologic System | 43.737 | 1 | 0.000* | hepatitis C antibody | 0.181 | 1 | 0.671 |
43.728 | 1 | 0.000* | 0.181 | 1 | 0.671 |
Skin | 139.845 | 1 | 0.000* | OB | 3.132 | 1 | 0.077 |
139.818 | 1 | 0.000* | 3.132 | 1 | 0.077 |
Skeletomuscular System | 55.833 | 1 | 0.000* | I.P | 0.000 | 1 | 0.990 |
55.823 | 1 | 0.000* | 0.000 | 1 | 0.990 |
CA199 | 13.372 | 1 | 0.000* | HBsAg | 0.857 | 1 | 0.355 |
13.370 | 1 | 0.000* | 0.857 | 1 | 0.355 |
TG | 2.580 | 1 | 0.108 | Colonoscopy | 1812.090 | 6 | 0.000* |
2.580 | 1 | 0.108 | 151.779 | 1 | 0.000* |
Table 4
Correlation of various medical indicators to yang deficiency of spleen and kidney (YaDSK) (Pearson Chi-Squared Test)
Variable | Pearson Chi-Squared Test | df | p | Variable | Pearson Chi-Squared Test | df | p |
Correlation Coefficient | Correlation Coefficient |
sex | 2.532 | 1 | 0.112 | choles | 1.827 | 1 | 0.176 |
2.531 | 1 | 0.112 | 1.827 | 1 | 0.176 |
age | 2.544 | 4 | 0.637 | AST | 0.144 | 1 | 0.704 |
1.981 | 1 | 0.159 | 0.144 | 1 | 0.704 |
BMI | 1.738 | 2 | 0.419 | ALT | 0.258 | 1 | 0.612 |
1.207 | 1 | 0.272 | 0.258 | 1 | 0.612 |
Head and neck/Conjunctive/ Lymphatic | 1.188 | 1 | 0.276 | rGT | 0.841 | 1 | 0.359 |
1.188 | 1 | 0.276 | 0.841 | 1 | 0.359 |
Respiratory System | 1.188 | 1 | 0.276 | AFP | 0.159 | 1 | 0.691 |
1.188 | 1 | 0.276 | 0.158 | 1 | 0.691 |
Cardiovascular System | 9.577 | 1 | 0.002* | CEA | 0.149 | 1 | 0.699 |
9.575 | 1 | 0.002* | 0.149 | 1 | 0.699 |
Digestive System | 9.577 | 1 | 0.002* | HBsAb | 1.367 | 1 | 0.242 |
9.575 | 1 | 0.002* | 1.366 | 1 | 0.242 |
Neurologic System | 0.291 | 1 | 0.589 | hepatitis C antibody | 0.027 | 1 | 0.869 |
0.291 | 1 | 0.589 | 0.027 | 1 | 0.869 |
Skin | 4.296 | 1 | 0.038* | OB | 0.021 | 1 | 0.885 |
4.296 | 1 | 0.038* | 0.021 | 1 | 0.885 |
Skeletomuscular System | 0.233 | 1 | 0.630 | I.P | 0.184 | 1 | 0.668 |
0.233 | 1 | 0.630 | 0.184 | 1 | 0.668 |
CA199 | 0.089 | 1 | 0.765 | HBsAg | 1.798 | 1 | 0.180 |
0.089 | 1 | 0.765 | 1.798 | 1 | 0.180 |
TG | 0.616 | 1 | 0.433 | Colonoscopy | 56.469 | 6 | 0.000* |
0.616 | 1 | 0.433 | 3.683 | 1 | 0.055* |
*p < 0.05 | | | | | | | |
Table 5
Correlation of various medical indicators to yin deficiency of liver and kidney (YiDLK) (Pearson Chi-Squared Test)
Variable | Pearson Chi-Squared Test | df | p | Variable | Pearson Chi-Squared Test | df | p |
Correlation Coefficient | Correlation Coefficient |
sex | 3.869 | 1 | 0.049* | choles | 0.028 | 1 | 0.867 |
3.869 | 1 | 0.049* | 0.028 | 1 | 0.867 |
age | 5.005 | 4 | 0.287 | AST | 5.547 | 1 | 0.019* |
0.149 | 1 | 0.700 | 5.546 | 1 | 0.019* |
BMI | 10.276 | 2 | 0.006* | ALT | 9.935 | 1 | 0.002* |
10.069 | 1 | 0.002* | 9.934 | 1 | 0.002* |
Head and neck/Conjunctive/ Lymphatic | 45.798 | 1 | 0.000* | rGT | 32.414 | 1 | 0.000* |
45.789 | 1 | 0.000* | 32.408 | 1 | 0.000* |
Respiratory System | 45.798 | 1 | 0.000* | AFP | 6.110 | 1 | 0.013* |
45.789 | 1 | 0.000* | 6.109 | 1 | 0.013* |
Cardiovascular System | 369.137 | 1 | 0.000* | CEA | 2.216 | 1 | 0.137 |
369.067 | 1 | 0.000* | 2.216 | 1 | 0.137 |
Digestive System | 369.137 | 1 | 0.000* | HBsAb | 52.679 | 1 | 0.000* |
369.067 | 1 | 0.000* | 52.669 | 1 | 0.000* |
Neurologic System | 11.232 | 1 | 0.001* | hepatitis C antibody | 1.046 | 1 | 0.306 |
11.230 | 1 | 0.001* | 1.046 | 1 | 0.306 |
Skin | 165.609 | 1 | 0.000* | OB | 0.804 | 1 | 0.370 |
165.578 | 1 | 0.000* | 0.804 | 1 | 0.370 |
Skeletomuscular System | 8.969 | 1 | 0.003* | I.P | 0.342 | 1 | 0.558 |
8.968 | 1 | 0.003* | 0.342 | 1 | 0.558 |
CA199 | 0.189 | 1 | 0.664 | HBsAg | 69.310 | 1 | 0.000* |
0.189 | 1 | 0.664 | 69.297 | 1 | 0.000* |
TG | 4.613 | 1 | 0.032* | Colonoscopy | 8.434 | 6 | 0.208 |
4.612 | 1 | 0.032* | 4.270 | 1 | 0.039* |
*p < 0.05 | | | | | | | |
Table 6
Correlation of various medical indicators to deficiency of both QI and blood (DQB) (Pearson Chi-Squared Test)
Variable | Pearson Chi-Squared Test | df | p | Variable | Pearson Chi-Squared Test | df | p |
Correlation Coefficient | Correlation Coefficient |
sex | 0.691 | 1 | 0.406 | choles | 1.819 | 1 | 0.177 |
0.691 | 1 | 0.406 | 1.818 | 1 | 0.178 |
age | 4.664 | 4 | 0.324 | AST | 0.279 | 1 | 0.597 |
0.340 | 1 | 0.560 | 0.279 | 1 | 0.597 |
BMI | 2.893 | 2 | 0.235 | ALT | 4.937 | 1 | 0.026* |
1.954 | 1 | 0.162 | 4.936 | 1 | 0.026* |
Head and neck/Conjunctive/ Lymphatic | 645.524 | 1 | 0.000* | rGT | 0.072 | 1 | 0.789 |
645.400 | 1 | 0.000* | 0.072 | 1 | 0.789 |
Respiratory System | 645.524 | 1 | 0.000* | AFP | 2.873 | 1 | 0.090 |
645.400 | 1 | 0.000* | 2.873 | 1 | 0.090 |
Cardiovascular System | 5203.044 | 1 | 0.000* | CEA | 0.866 | 1 | 0.352 |
5202.049 | 1 | 0.000* | 0.866 | 1 | 0.352 |
Digestive System | 5203.044 | 1 | 0.000* | ANTISB | 1.559 | 1 | 0.212 |
5202.049 | 1 | 0.000* | 1.558 | 1 | 0.212 |
Neurologic System | 158.316 | 1 | 0.000* | hepatitis C antibody | 0.111 | 1 | 0.739 |
158.286 | 1 | 0.000* | 0.111 | 1 | 0.739 |
Skin | 33.037 | 1 | 0.000* | OB | 1.422 | 1 | 0.233 |
33.030 | 1 | 0.000* | 1.422 | 1 | 0.233 |
Skeletomuscular System | 2876.011 | 1 | 0.000* | I.P | 1.695 | 1 | 0.193 |
2875.461 | 1 | 0.000* | 1.695 | 1 | 0.193 |
CA199 | 0.004 | 1 | 0.947 | HBsAg | 0.000 | 1 | 1.000 |
0.004 | 1 | 0.947 | 0.000 | 1 | 1.000 |
TG | 0.632 | 1 | 0.427 | Colonoscopy | 10.840 | 6 | 0.093 |
0.632 | 1 | 0.427 | 0.015 | 1 | 0.904 |
*p < 0.05 | | | | | | | |
We also evaluated the predictive potential of clinical indexes for 5 TCM syndromes with focus on colorectal malignancies using artificial neural networks approach. The strength of correlation of syndrome and variables was shown as the width of lines. The results showed that the predictive ANN model showed a good fitting with an accuracy of 100%. The three most predictive factors for SADH were colonoscopy, skin and neural system with importance of 0.24, 0.09 and 0.08 respectively. The interrelationships between predictor factor (input layer), hidden factors (hidden layer), and SADH are shown in Fig. 1. For IDSIBSB, the predictive model exhibited an accuracy of 99.7% and the most predictive factors was colonoscopy with importance of 0.24 (Fig. 2). We found that the accuracy of predictive model for YaDSK was 100% and three factors with high importance were colonoscopy (0.24), digestive system (0.13) and CEA (0.05) (Fig. 3). For YiDLK, the prediction accuracy of ANN model was 100%. The factor with highest importance was cardiovascular system (0.16) followed by digestive system (0.08) and age (0.07) (Fig. 4). The data showed that 3 factors with highest importance in the ANN predictive model for DQB were cardiovascular system (0.26), digestive system (0.2) and skeletomuscular system (0.07).