Li-Jiao Chen, Ming-Kai Wang, Xue-Qin Qin, Li-Fen Wang

Rules of prescriptions for diabetes in dictionary of traditional Chinese medicine prescriptions based on data mining

Li-Jiao Chen1, Ming-Kai Wang1, Xue-Qin Qin1, Li-Fen Wang1*

1First Affiliated Hospital of Yunnan University of Traditional Chinese Medicine/Yunnan Provincial Hospital of Traditional Chinese Medicine, Kunming 650021, China.

This study aimed to provide reference and guidance for the clinical use of traditional Chinese medicine based on the analysis of the prescriptions for the treatment of diabetes and the rules of drug use in.Prescriptions and drugs for the treatment of diabetes were found out from, and their natures, tastes, meridians and functions were found respectively. The data were statistically analyzed by SPSS 22.0, Weka 3.8, and Cytoscape 3.6.1 software.Five hundred and twenty prescriptions for diabetes were selected, involving 373 traditional Chinese medicines. The medium and high frequency drugs in the prescription are Maidong (), Gancao (), Tianhuafen (), Renshen (), Huanglian (), Fuling (), Dihuang (), Zhimu (), et al. Most of them are heat clearing drugs, tonic drugs, supplemented by drugs such as diuresis, dampness, astringency, et al., and are with cold and warm properties, sweet and bitter taste, and belong to lung meridian, heart meridian and stomach meridian. According to the association rule analysis of high-frequency drugs, the compatibility rules of drugs were obtained, such as Danggui () plus Dihuang (), Kushen () plus Tianhuafen (), Danggui () plus Gancao (), Roucongrong () plus Wuweizi (), Digupi () plus Maidong (), et al. Six new prescriptions were excavated by entropy level clustering, and the treatment methods were mainly nourishing Yin (it is the category of ancient philosophy, with the back to the sun as the Yin, opposite to the Yang; it is a generalization of the opposite attributes of some things or phenomena related to each other in nature), benefiting Qi (it is the most basic element that constitutes human body and maintains life activities in traditional Chinese medicine) and promoting body fluid, as well as benefiting water and dampness, clearing heat and reducing fire.The prescriptions for the treatment of diabetes included inare mainly for nourishing Yin and promoting body fluid, and also for invigorating lung and Qi, clearing heat and purging fire, which can provide reference for modern clinicians in the treatment of diabetes based on syndrome differentiation.

Traditional Chinese medicine, Data mining, Diabetes

Traditional Chinese medicine has a long history of treating diabetes and its complications.contains many prescriptions of famous Chinese medicine doctors from Qin and Han Dynasties to the beginning of new China for the treatment of this disease. This study summarized the rules of prescriptions for diabetes inbased on data mining technique.The prescriptions for the treatment of diabetes included inare mainly for nourishing Yin (it is the category of ancient philosophy, with the back to the sun as the Yin, opposite to the Yang; it is a generalization of the opposite attributes of some things or phenomena related to each other in nature) and promoting body fluid, invigorating lung and Qi (it is the most basic element that constitutes human body and maintains life activities in traditional Chinese medicine), clearing heat and purging fire, which can provide reference for modern clinicians in the treatment of diabetes based on syndrome differentiation.

Background

Diabetes is a common disease with typical symptoms of drinking more, eating more, urinating more and losing weight. The above symptoms are similar to thirst based on the symptomatology [1]. With the development of social economy, people’s diet structure and lifestyle have been changed, and the prevalence of diabetes remains high. According to International Diabetes Federation global diabetes overview 9th edition 2019 [2], the number of people suffering from diabetes in China was about 116.4 million, ranking first in the world. Diabetes has become a global public health problem. According to modern medicine, there is a close relationship between the onset of diabetes mellitus and the deficiency of insulin secretion and the decline of insulin bioavailability. Persistent hyperglycemia for a long time leads to the injury of multiple organs and systems in the patient’s whole body, which seriously affects the patient’s life, health and quality of life [3], and also brings huge economic burden. Many doctors think that Yin (it is the category of ancient philosophy, with the back to the sun as the Yin, opposite to the Yang; it is a generalization of the opposite attributes of some things or phenomena related to each other in nature) fluid depletion and hot fumigation are the pathogenesis of the disease [4]. Traditional Chinese medicine (TCM) has a long history of treating this disease and its complications. The[5] contains the prescriptions of famous Chinese medicine doctors from Qin and Han Dynasties to the beginning of new China for the treatment of thirst. This study aimed to summarize the rules of prescriptions for diabetes inbased on data mining.

Methods

Data source

Based on, a database was established to summarize 520 prescriptions for diabetes, including 373 TCMs.

Data standardization

The name of drugs were standardized according to the unified specifications of[6] and[7]. For example, “Weirui” is labelled as “”. In order to ensure the reliability of the data, the ancient and modern drugs with different names were standardized according to the. The drugs not included in the above books, such as “Daqingyan ()”, “Yunmu ()”, were not analyzed in this study. Flavor and meridian tropism were standardized according to the standard of.

Statistical analysis

The data of TCM compound drugs, including drug action, sexual taste and meridian tropism, were sorted out according to the requirements and specifications. Each TCM is assigned according to “no = 0, have = 1”, entered into excel 2010 software. SPSS 20.0 software was used to conduct descriptive statistics of drug frequency. The percentage of prescription use is equal to frequency of occurrence divided by total number of Chinese herbal decoction. The percentage of drug use is equal to frequency of occurrence divided by total frequency. Weka 3.8 software was used to analyze the potential association rules of drugs. The network figure was made using the association rules by Cytoscape 3.6.1 software. The unsupervised entropy hierarchical clustering algorithm was applied to carry out hierarchical clustering analysis, and then to obtain new combination of drugs.

Results

Frequency of drug use

According to the above methods, 520 prescriptions for diabetes were found in. There were 373 drugs of TCM used for 3,679 times. The frequency was 3,679/5,815/10,536 based on drug properties, taste, meridian tropism respectively.

Distribution of drugs with high frequency of use

The statistical results show that the 26 drugs with the frequency ≥ 30 are respectively Maidong (), Gancao (), Tianhuafen (), Renshen (), et al. The total frequency of these drugs is 2,040, accounting for 55.44% of the total frequency of drugs (3,679 times, Table 1).

Efficacy distribution of drugs with high frequency of use

The statistical results showed that the drugs with frequency ≥ 30 were heat clearing drugs, tonic drugs, diuretic drugs, surface resolving drugs and so on. The statistical results are shown in Table 2.

Properties distribution of drugs with high frequency of use

The statistical results showed that the distribution of drug properties was cold, warm, flat, cool, and hot. A total of 1,882 times were used for three kinds of drugs, accounting for 51.15% of the total frequency (3,679 times, Table 3).

Taste distribution of drugs with high frequency of use

The statistical results show that 7 drugs with frequency ≥ 30 were sweet, bitter, pungent, et al (Table 4).

Distribution of meridian tropism of drugs with high frequency of use

The statistical results show that 10 used channels are lung, heart, stomach, spleen, et al. (Table 5).

Association rules on drugs with high frequency of use

The purpose of association rule mining is to find out strong rules. The parameters to be determined are support, confidence, and promotion. After the association rule analysis of the above methods, the results of drug pair compatibility are obtained, and shown in Table 6 and Figure 1.

Table 1 Distribution of drugs with high frequency of use

Table 1 Distribution of drugs with high frequency of use (continued)

Table 1 Distribution of drugs with high frequency of use (continued)

Table 2 Efficacy distribution of drugs with high frequency of use

Table 2 Efficacy distribution of drugs with high frequency of use (continued)

TCM, traditional Chinese medicine.

Table 3 Properties distribution of drugs with high frequency of use

TCM, traditional Chinese medicine.

Distribution of meridian tropism of drugs with high frequency of use

The statistical results show that 10 used channels are lung, heart, stomach, spleen, et al (Table 5).

Association rules on drugs with high frequency of use

The purpose of association rule mining is to find out strong rules. The parameters to be determined are support, confidence, and promotion. After the association rule analysis of the above methods, the results of drug pair compatibility are obtained, and shown in Table 6 and Figure 1.

New prescription based on hierarchical clustering

Another goal of the study was to find a new and effective formula. After association rule analysis, according to the number of prescriptions and different parameters, the unsupervised entropy hierarchical clustering algorithm is applied to carry out entropy hierarchical clustering analysis, and a total of 6 new formulas are obtained (Table 7).

Discussion

After a deep analysis of the prescriptions for the treatment of thirst in, this paper summarized the characteristic factors such as the role of TCM, flavor and meridian tropism, and found a close relationship between the characteristics of TCM and the treatment of thirst, so as to provide a reference for clinicians in syndrome differentiation.

The related records of thirst (Xiaoke) were first found in the ancient book(, unknown author, written in the Warring States period) [8],(, unknown author, written in the Warring States period) [9], and aslo named as Feixiao, Gexiao and Xiaozhong due to their different etiology, pathogenesis and symptoms. Xiaoke was first recorded in the ancient book(, written by Zhang Zhongjing in 205 C.E.), and has been used so far [10]. The treatment of Xiaoke varies from generation to generation. In the ancient book(, written by Zhang Zhongjing in 205 C.E.), Zhang Zhongjing (150 C.E.–219 C.E.) first used the classic ancient prescription of Chinese medicine Baihu and Renshen decoction for the treatment of diabetes [11], which is still commonly used by modern doctors. Zhu Danxi (1281 C.E.–1358 C.E.) pointed out in the ancient book(, written by Zhu Zhenheng in 1481 C.E.) that patients suffered from thirst because Sanjiao was affected by evil [12]. According towritten by Ye Tianshi(1667 C.E.–1746 C.E.) [13], he mostly used Yin nourishing drugs to treat this disease [13]. Zhang Xichun (1860 C.E.–1933 C.E.) had rich experience in the treatment of diabetes, and usually used the classic ancient prescription of Chinese medicine Yuye decoction and the experienced prescription Zidu decoction for the treatment of diabetes [14]. It can be seen from the results of this study that the treatment of this disease is mainly based on the drugs of nourishing Yin, promoting body fluid and clearing away heat, which is similar with the views of various physicians and the law of clinical practice.

Distribution analysis of drugs with high frequency of use

The top three drugs were Maidong (, 193 times), Gancao (, 183 times) and Tianhuafen (, 167 times). Maidong () is the dry root tuber of Maidong ((L. f) Ker-Gaw), which is sweet and bitter in taste and cold in nature. It has the effect of nourishing Yin, benefiting lung, benefiting stomach, and promoting body fluid. According to Tao Hongjing’s, it can cure the body, the heart and the stomach, et al [15]. Modern pharmacological studies have shown that the effective component of Maidong () polysaccharide can significantly reduce the insulin sensitivity and reduce the insulin resistance of surrounding tissues [16]. The total saponin of Maidong () is the extract of Maidong ((L. f) Ker-GawL.), which can weaken the damage of alloxan to β cell of islet of langerhans, inhibit the hyperglycemic effect of adrenaline, and may be related to the inhibition of glycogen decomposition [17]. Gancao () has the function of harmonizing hundreds of drugs. It can be used together with cold and heat tonic and purgative drugs. It can not only reduce the toxicity and increase the efficiency, but also harmonize the taste of drugs [18]. The function of harmonizing various drugs is reflected in ancient and modern prescriptions. In addition, Gancao () has the functions of clearing away heat and detoxification, supplementing Qi, and nourishing lung. According to the famous medical records, Gancao () can warm the spleen and stomach, relieve the fullness of the ruff, stop coughing, and relieve the thirst. Modern research also shows that Gancao () and flavonoids have the functions of antioxidation and hypoglycemic, as well as inhibiting the oxidative stress and aldose reductase activity of high concentration glucose [19].

Tianhuafen () has the effect of promoting body fluid to quench thirst, clearing away heat and reducing fire. Volume 21 of the ancient book(, written by Sun Simiao in 652 C.E.) says that it can cure “thirst, strangulation, blood urination, and edema” [20]. Modern research shows that the clotting element extracted from Tianhuafen () has insulin-like effect [21]. The above three herbs have various effects such as nourishing Yin, promoting body fluid, benefiting Qi and clearing away heat.

Analysis of efficacy distribution of drugs with high frequency of use

The top three drugs of efficacy frequency were heat clearing drugs (730 times), deficiency tonic drugs (704 times) and diuretic drugs (186 times). Although doctors in different periods have different understandings of this disease, most of them think that the pathogenesis of thirst elimination is mainly Yin deficiency and heat excess, or deficiency of both Qi and Yin, blood stasis and Qi stagnation [22]. The treatment of this disease should be based on clearing heat and nourishing Yin, and tonic drugs should be used when there are deficiency syndromes, so the frequency of clearing heat drugs is the highest, followed by tonic drugs. In the early stage of the occurrence of diabetes, it is mainly responsible for the lung, and in the later stage, it is often related to the spleen and kidney. Therefore, it is necessary to take the medicine of promoting the dampness of the spleen.

Table 4 Taste distribution of drugs with high frequency of use

TCM, traditional Chinese medicine.

Table 5 Distribution of meridian tropism of drugs with high frequency of use

Table 5 Distribution of meridian tropism of drugs with high frequency of use (continued)

TCM, traditional Chinese medicine.

Table 6 Association rules on drugs with high frequency of use

Table 6 Association rules on drugs with high frequency of use (continued)

Table 7 New prescriptions based on entropy hierarchical clustering

Figure 1 Network figure of association rules on drugs with high frequency of use

Analysis of properties of drugs with high frequency of use

Top three properties of drugs were cold (970 times), warm (458 times) and flat (454 times). Ancient medical literature on the understanding of thirst, showed that the disease was divided into deficiency and excess, responsible for the lung, spleen, kidney, et al. The treatments mainly include nourishing Yin, clearing heat, promoting body fluid, replenishing lung, replenishing Qi, seeping wet, et al. The drugs with the above therapeutic effects mostly belong to cold, followed by warm, flat. Drugs with properties of cold, warm, or flat are frequently used.

Analysis of taste of drugs with high frequency of use

The top three taste frequencies were sweet (1,537 times), bitter (980 times) and pungent (282 times). The sweet medicine can nourish Qi, strengthen the spleen and stomach, and strengthen the blood and body fluid biochemical foundation. The bitter medicine can relieve fire, strengthen Yin, clear heat, and dry dampness. Yin fluid can be stored and damp heat can be removed. The pungent medicine can promote Qi and blood circulation, and the blood and body fluid can be homologous to help the body fluid run normally. Sweet, bitter, and pungent drugs are used together.

Analysis of meridian tropism of drugs with high frequency of use

The top 4 meridian tropism were lung meridian (1,427 times), heart meridian (1,024 times), stomach meridian (996 times) and spleen meridian (954 times). According to Luo’s meeting about medical treatment mirror, Shangxiao characterized thirsty, and thoracic injury [23]. According to the book, the occurrence of diabetes was related to the weakness of temper [24].

Analysis of association rules on drugs with high frequency of use

When the above research methods are used to analyze the drug association rules, we can get the drug compatibility rules, such as Danggui () plus Dihuang (), Kushen () plus Ait Tianhuafen (), Danggui () plus Gancao (), Roucongrong () plus Wuweizi (), et al. Among them, Danggui () plus Dihuang () is the most important pair of drugs.

New combination based on hierarchical clustering

Through data mining of 520 prescriptions, 6 new prescriptions for diabetes were obtained. According to the analysis of the composition of the new prescription, the main treatment is nourishing Yin, clearing heat and promoting fluid, and benefiting qi and permeability.

Conclusion

The prescriptions for the treatment of diabetes included in “” are mainly for nourishing Yin and promoting body fluid, and also for invigorating lung and Qi, clearing heat and purging fire, which can provide reference for modern clinicians in the treatment of diabetes based on syndrome differentiation.

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10.12032/MDM2020063002

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TCM, traditional Chinese medicine.

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The authors declare that they have no conflict of interest.

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Li-Jiao Chen, Ming-Kai Wang, Xue-Qin Qin, et al. Rules of prescriptions for diabetes in dictionary of traditional Chinese medicine prescriptions based on data mining. Medical Data Mining 2020, 3 (2): 59–72.

:Yu-Ping Shi.

:06 March 2020,

28 May 2020,

:23 June 2020

Li-Fen Wang. First Affiliated Hospital of Yunnan University of Traditional Chinese Medicine/Yunnan Provincial Hospital of Traditional Chinese Medicine, No.120 Guanghua Road, Wuhua District, Kunming 650021, China. Email: wlf15808711551@163.com.