Abstract
Background:
Prediabetes mellitus (PDM) and impaired glucose regulation precedes diabetes and serve as early warning signals. A 2018 Chinese epidemiological survey reported prediabetes at 25.5% prevalence and type 2 diabetes at 10.8%, respectively. Untreated carries one-third of the risk of diabetes progression. This study aimed to understand traditional Chinese medicine syndromes in PDM to guide clinical practice and diabetes prevention.
Methods:
We systematically searched the Chinese and English literature in PubMed, EMBASE, Sinomed, CNKI, VIP, Wanfang until March 31, 2023. We manually explored the Chinese prediabetes literature, trial registrations, and references, adhering to predefined criteria. The results were independently summarized by 2 researchers. Statistical analysis was performed using EXCEL, IBM SPSS 27.0, and IBM SPSS Modeler 18.0, with data mining techniques including association and cluster analysis.
Results:
Analysis of 23 clinical trials (8943 patients) identified phlegm dampness syndrome as predominant, with qi deficiency, dampness, and phlegm as the principal pathogenic elements. Spleen syndrome elements dominated, with a priori correlation analysis favoring spleen dampness. The prevalent PDM clinical symptoms include amnesia, mental fatigue, limb fatigue, dizziness, and lumbar discomfort.
Conclusion:
Prediabetes is strongly associated with spleen dampness, highlighting its role. Common traditional Chinese medicine syndrome elements include qi deficiency, phlegm, and dampness. Clinical diagnosis and treatment should prioritize syndrome differentiation and emphasize spleen-focused approaches. Although limited research exists on prediabetes syndromes, further exploration of PDM and spleen dampness is crucial.
Keywords: clinical symptoms, cluster analysis, prediabetes mellitus, TCM syndrome elements
1. Introduction
Prediabetes mellitus (PDM) is an intermediate hyperglycemic state between normal blood glucose and diabetes, including impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and their mixed state (IFG + IGT), which is a transitional stage before the onset of diabetes. Survey data in China showed that the prevalence rate of PDM has increased from 35.7% to 38.1%, with nearly 500 million people suffering from PDM, far exceeding the amount of diabetes. PDM is characterized by great harm and strong concealment.[1–3] PDM increases the risk of diabetes and its complications as well as cardiovascular disease, microvascular disease, tumors, dementia, and other diseases.[4] At the same time, patients with PDM have no overt typical symptoms of diabetes, and most of them are in the state of the asymptomatic or “latent syndrome,” which is often difficult to detect, and most of them are found on physical examination or examination for other diseases.[5] It is difficult to make breakthrough progress in the prevention and control of diabetes, which is one of the main reasons for the high incidence of diabetes in modern society. Early diagnosis of diabetes has become a major public health issue.
PDM is a reversible stage and its reversion can be achieved through early effective intervention.[6] Traditional Chinese medicine (TCM) has advantages and characteristics in the prevention and treatment of prediabetes.[7] Most TCM doctors believe that the period of PDM is consistent with the concept of “spleen dan.” The main reasons for this condition include innate endowments, overeating sweetness, emotional imbalance, and ease of movement.[8] However, environmental changes, dietary patterns, lifestyle choices, and cultural influences have diminished the significance of weakened appetite as the primary cause of weakness in these 5 organs. Poor dietary habits, including consuming a high-calorie diet, consistently staying up late, indulging in cold and raw foods, and experiencing mental fatigue and physical inactivity, have contributed to a complex pathogenesis characterized by a combination of deficiency and excess. Currently, the majority of studies concentrate on diabetes cases with a confirmed diagnosis, whereas the early stages of diabetes receive limited attention.[9] The criteria for syndrome differentiation have not been clearly defined or standardized, leading to poor repeatability in clinical research. By analyzing modern clinical literature and incorporating the theory of syndrome differentiation, we employed data mining techniques to identify the distribution patterns of syndrome types in prediabetes and combinations of syndrome elements. This study aimed to enhance the precision of clinical treatment through syndrome differentiation in prediabetes management and to offer novel insights and approaches for the clinical prevention of diabetes.
2. Materials and methods
2.1. Literature search
We searched PubMed, EMBASE, Sinomed, VIP Database, Wanfang Database from December 1, 2022, to March 31, 2023. In addition, we manually searched for Chinese cancer, traditional Chinese medicine constitution, Chinese medical trial registration centers, and unpublished survey or reference materials. Key phrases and clinical subject headings (“prediabetes” [MeSH] or “impaired glucose tolerance” or “impaired fasting glucose”) and (“syndrome type” [tiab] or “syndrome element” [tiab]) and (“clinical symptoms” [MeSH]) were used to establish the research methods. The retrieval policies of other libraries were adjusted to comply with their retrieval guidelines. The titles and abstracts of the publications were assessed by 2 reviewers, independently.
2.2. Inclusive criteria
The research was deemed to be eligible when the below criterion was achieved.
Research type. Retrospective case studies and case–control studies were included in this review.
Research objectives. Patients with PDM, impaired glucose regulation, and IGF were included in this study.
Research content. Clarify the presence of TCM syndrome types.
Select one of the studies published from different perspectives.
2.3. Exclusive criteria
Studies with the below characteristics were eliminated.
Research type. Literature review, conference papers, basic research, etc.
Disease diagnosis. This review was not included when it was combined with other symptoms.
2.4. Subjects observation
In this review, the syndrome types with slightly different names but similar meanings were standardized based on the reference to “Diagnosis of Traditional Chinese Medicine,” and the syndrome types were decomposed into syndrome elements, among which the Qi and Yin deficiency syndromes are decomposed into pathological syndrome elements of Qi deficiency and Yin deficiency. The syndrome of sputum moisture accumulation in the spleen is decomposed into the disease location syndrome element spleen, disease nature syndrome element moisture, and sputum.
2.5. Data extraction and quality assessment
All data in this review were organized using Excel, and IBM SPSS software (version 27.0) was used for frequency and clustering statistics of the syndrome elements. Two reviewers independently collected and evaluated the data, and any discrepancies between the assessments were resolved through discussion. IBM SPSS Modeler software (version 18.0) was used to perform association rule analysis and cluster analysis on the evidence elements using the Apriori algorithm.
3. Results
3.1. Literature search results
We searched PubMed, EMBASE, Sinomed, CNKI, VIP database, Wanfang database and identified a total of 422 studies. After removing duplicate studies, 255 were identified and reviewed. Following a thorough screening process, 232 studies were excluded owing to factors such as pathological studies, animal studies, or statistical analysis studies. Finally, 23 studies were included in the analysis (Fig. 1 and Table 1).
Figure 1.
Floe diagram of literature retrieval.
Table 1.
Project information extraction form.
| Study | Design | Sample | Distribution of syndrome types | Disease location | Pathogenicity |
|---|---|---|---|---|---|
| Xu 2013[10] | PDM | 71 | Phlegm-dampness syndrome 23; Yin deficiency syndrome 23; spleen deficiency syndrome 25 | Spleen 37; liver 34 | Sputum 19; moisture 22; Qi stagnation 10; Qi deficiency 11; Yin deficiency 9 |
| Tan 2017[11] | PDM | 822 | Phlegm-dampness syndrome 156; blood stasis syndrome 150; Yin deficiency syndrome 169; Qi deficiency syndrome 173; spleen deficiency syndrome 174 | Spleen 382; liver 240; lungs 102; Kidney 92 |
Sputum 162; moisture 188; Qi stagnation 151; Qi deficiency 164; Yin deficiency 157 |
| Meng 2015[12] | IGR | 159 | Phlegm-dampness syndrome 22; Blood stasis syndrome 40; Yin deficiency syndrome 12; Qi deficiency syndrome 34; spleen deficiency syndrome 51 | Spleen 88; liver 71 | Sputum 34; moisture 43; blood stasis 32; Qi deficiency 24; Yin deficiency 26 |
| Dou 2010[13] | PDM | 164 | Phlegm-dampness syndrome 21; Blood stasis syndrome 18; Yin deficiency syndrome 30; Qi deficiency syndrome 26; spleen deficiency syndrome 69; | Spleen 76; liver 88 | |
| Cao 2012[14] | PDM | 437 | Phlegm-dampness syndrome 45; Blood stasis syndrome 22; Yin deficiency syndrome 125; Qi deficiency syndrome 92; spleen deficiency syndrome 153 | Spleen 126; liver 104; lungs 89; Kidney 118 |
Sputum 71; moisture 84; Qi stagnation 67; blood stasis 78; blood deficiency 55; Qi deficiency 41; Yin deficiency 41 |
| Wang 2017[15] | PDM | 1868 | Phlegm-dampness syndrome 273; Blood stasis syndrome 311; Yin deficiency syndrome 540; Qi deficiency syndrome 472; spleen deficiency syndrome 272 | Spleen 574; liver 481; lungs 403; Kidney 410 |
Sputum 341; moisture 451; Qi stagnation 211; blood stasis 183; Blood deficiency 212; Qi deficiency 245; Yin deficiency 225 |
| Huang 2018[16] | PDM | 486 | Phlegm-dampness syndrome 123; Blood stasis syndrome 34; Yin deficiency syndrome 206; Qi deficiency syndrome 36; spleen deficiency syndrome 87 | Spleen 121; liver 150; lungs 103; Kidney 112 |
Sputum 76; moisture 54; Qi stagnation 77; blood stasis 82; Blood deficiency 66; Qi deficiency 66; Yin deficiency 65 |
| Qiu 2014[17] | IGR | 530 | Phlegm-dampness syndrome 130; Blood stasis syndrome 80; Yin deficiency syndrome 110; Qi deficiency syndrome 90; spleen deficiency syndrome 120 | Spleen 173; liver 181; kidney 176 | Sputum 94; moisture 121; blood stasis 89; Qi deficiency 98; Yin deficiency 128 |
| Cai 2015[18] | PDM | 444 | Phlegm-dampness syndrome 100; blood stasis syndrome 94; Yin deficiency syndrome 68; Qi deficiency syndrome 74; spleen deficiency syndrome 108 | Spleen 177; liver 142; kidney 125 | Sputum 151; moisture 121; Qi deficiency 78; Yin deficiency 94 |
| Bao 2023[19] | PDM | 1323 | Phlegm-dampness syndrome 169; blood stasis syndrome 207; Yin deficiency syndrome 436; Qi deficiency syndrome 370; spleen deficiency syndrome 141 | Spleen 440; liver 486; kidney 397 | Sputum 358; moisture 213; blood stasis 287; Qi deficiency 250; Yin deficiency 215 |
| Tao 2007[20] | IGR | 411 | Phlegm-dampness syndrome 91; blood stasis syndrome 77; Yin deficiency syndrome 58; Qi deficiency syndrome 93; spleen deficiency syndrome 92 | Spleen 146; liver 132; kidney 133 | Sputum 65; moisture 91; blood stasis 73; Qi deficiency 79; Yin deficiency 103 |
| Wang 2021[21] | IGR | 505 | Phlegm-dampness syndrome 139; blood stasis syndrome 67; Yin deficiency syndrome 98; Qi deficiency syndrome 98; spleen deficiency syndrome 103 | Liver 162; lungs 189; kidney 154 | Sputum 101; moisture 142; blood stasis 76; Qi deficiency 89; Yin deficiency 97 |
| Wang 2011[22] | IGR | 178 | Phlegm-dampness syndrome 24; blood stasis syndrome 24; Yin deficiency syndrome 37; Qi deficiency syndrome 55; spleen deficiency syndrome38 | Spleen 60; liver 31; lungs 30; Kidney 57 |
Sputum 23; Moisture 43; Qi stagnation 34; blood stasis 55; Qi deficiency 14; Yin deficiency 9 |
| Chen 2019[23] | IGR | 190 | Phlegm-dampness syndrome 36; blood stasis syndrome 23; Yin deficiency syndrome 20; Qi deficiency syndrome 40; spleen deficiency syndrome 71 | Spleen 52; liver 58; lungs 23; Kidney 32 |
Sputum 32; moisture 57; Qi stagnation 11; blood stasis 19; Blood deficiency 8; Qi deficiency 37; Yin deficiency 26 |
| Ai 2009[24] | IGR | 102 | Phlegm-dampness syndrome 25; blood stasis syndrome 4; Yin deficiency syndrome 22; Qi deficiency syndrome 18; spleen deficiency syndrome 33 | Spleen 36; liver 31; kidney 35 |
Sputum 12; moisture 35; blood stasis 11; Qi deficiency 23; Yin deficiency 21 |
| Song 2007[25] | IGR | 127 | Phlegm-dampness syndrome 33; blood stasis syndrome 10; Yin deficiency syndrome 22; Qi deficiency syndrome 34; spleen deficiency syndrome 28 | Spleen 46; liver 31; lungs 24; Kidney 26 |
Sputum 34; moisture 12; blood stasis 21; Qi deficiency 24; Yin deficiency 36 |
| Liu 2014[17] | IGR | 155 | Phlegm-dampness syndrome 31; blood stasis syndrome 15; Yin deficiency syndrome 20; Qi deficiency syndrome 35; spleen deficiency syndrome 54 | Spleen 31; liver 51; lungs 21; Kidney 52 |
Sputum 52; moisture 31; Qi stagnation 34; Qi deficiency 21; Yin deficiency 17 |
| Mu 2014[26] | IGR | 111 | Phlegm-dampness syndrome 22; blood stasis syndrome 18; Yin deficiency syndrome 17; Qi deficiency syndrome 39; spleen deficiency syndrome 15 | Spleen 42; liver 31; kidney 38 |
Sputum 19; moisture 12; Qi stagnation 21; Qi deficiency 25; Yin deficiency 34 |
| Wu 2021[27] | IGR | 150 | Phlegm-dampness syndrome 38; blood stasis syndrome 9; Yin deficiency syndrome 34; Qi deficiency syndrome 15; spleen deficiency syndrome 54 | Spleen 54; liver 58; kidney 38 |
Sputum 45; moisture 23; Qi stagnation 39; Qi deficiency 24; Yin deficiency 19 |
| Zhang 2010[28] | PDM | 140 | Phlegm-dampness syndrome 39; blood stasis syndrome 18; Yin deficiency syndrome 21; Qi deficiency syndrome 22; spleen deficiency syndrome 40 | Spleen 43; liver 34; lungs 23; kidney 40 | Sputum 28; moisture 49; Qi stagnation 21; Qi deficiency 8; Yin deficiency 34 |
| Ren 2018[29] | PDM | 360 | Phlegm-dampness syndrome 60; blood stasis syndrome 39; Yin deficiency syndrome 88; Qi deficiency syndrome 95; spleen deficiency syndrome 78; | Spleen 121; liver 89; lungs 72; Kidney 78 |
Sputum 86; moisture 103; blood stasis 34; Qi deficiency 65; Yin deficiency 72 |
| Wang 2014[30] | PDM | 110 | Phlegm-dampness syndrome 30; blood stasis syndrome 16; Yin deficiency syndrome 11; Qi deficiency syndrome 12; spleen deficiency syndrome 41 | Spleen 34; liver 40; lungs 13; Kidney 23 |
Sputum 11; moisture 34; Qi deficiency 42; Yin deficiency 23 |
| Luo 2017[31] | PDM | 104 | Phlegm-dampness syndrome 19; blood stasis syndrome 13; Yin deficiency syndrome 10; Qi deficiency syndrome 21; spleen deficiency syndrome 41 | Spleen 32; liver 38; lungs 10; Kidney 24 |
Sputum 9; moisture 20; Qi stagnation 17; blood stasis 14; Blood deficiency 15; Qi deficiency 18; Yin deficiency 11 |
IGR = impaired glucose regulation; PDM = pre-diabetes.
3.2. Distribution of TCM syndrome types
In this study, we obtained 18 TCM syndrome types. After sorting them, we standardized them into 5 syndrome types. We conducted frequency and frequency statistics on the syndrome types of TCM included in this study. The specific distribution of TCM syndrome types is shown in Table 2.
Table 2.
Distribution of syndrome type in prediabetes.
| Types | Frequency | Frequency rate (%) |
|---|---|---|
| Phlegm-dampness syndrome | 273 | 24.12 |
| Blood stasis syndrome | 311 | 34.75 |
| Yin deficiency syndrome | 540 | 44.75 |
| Qi deficiency syndrome | 472 | 41.53 |
| Spleen deficiency syndrome | 272 | 21.24 |
3.3. Distribution of TCM syndrome elements
We extracted TCM syndrome elements from the 23 studies included in this study, and we extracted 11 syndrome elements of TCM, including 4 location syndrome elements and 7 nature syndrome elements. We conducted frequency and frequency statistical analyses on the extracted 11 syndrome elements of TCM, and the specific distribution statistics of TCM syndrome elements are shown in Table 3.
Table 3.
Distribution of syndrome elements in prediabetes.
| Disease location | Frequency | Frequency rate (%) | Pathogenicity | Frequency | Frequency rate (%) |
|---|---|---|---|---|---|
| Spleen | 574 | 37.56 | Sputum | 358 | 22.87 |
| Liver | 486 | 32.23 | Moisture | 451 | 27.45 |
| Lungs | 303 | 16.15 | Qi stagnation | 211 | 13.01 |
| Kidneys | 410 | 27.74 | Blood stasis | 287 | 19.23 |
| Blood deficiency | 212 | 14.31 | |||
| Qi deficiency | 250 | 15.26 | |||
| Yin deficiency | 225 | 14.94 |
3.4. Distribution of clinical symptoms in PDM
We extracted the clinical symptoms mentioned in the 23 studies included in this review, and a total of 40 clinical symptoms were extracted. After summarizing and organizing, we condensed the 12 common clinical symptoms. The frequencies and counts of the 12 classified clinical symptoms were statistically analyzed, and the specific distribution of the clinical symptoms is shown in Table 4.
Table 4.
Distribution of clinical symptoms in prediabetes.
| The clinical symptoms | Frequency | Frequency rate (%) | Clinical symptoms | Frequency | Frequency rate (%) |
|---|---|---|---|---|---|
| Fatigue of spirit | 31 | 73.75 | Blurred vision | 11 | 42.75 |
| Forgetful | 5 | 53.25 | Lumbago | 23 | 45.00 |
| Dazzle | 11 | 54.00 | Dry | 5 | 19.25 |
| Joint pain | 14 | 27.50 | Tinnitus | 4 | 10.00 |
| Soreness of waist | 17 | 43.25 | Insomnia | 10 | 35.5 |
| Sizzy | 8 | 35.25 | Fondness for a cold drink | 3 | 16.00 |
3.5. Association rule analysis
We used the Apriori algorithm in IBM SPSS 27 to perform a correlation analysis on TCM syndrome elements and clinical symptoms, with a minimum support of 5% and a minimum confidence of 80%. The support level indicates the frequency of combining TCM evidence elements with clinical symptoms and the confidence level indicates the reliability and predictive strength of the association rules for combining TCM evidence elements with clinical symptoms. We sorted the syndrome elements and clinical symptoms of TCM patients based on their confidence levels. The specific degree of correlation of TCM syndrome element combinations is shown in Table 5, and the specific degree of correlation of clinical symptom combinations is shown in Table 6.
Table 5.
Association rules of syndrome elements in prediabetes.
| Preceding paragraph | Consequent | Consequent (%) | Confidence level (%) |
|---|---|---|---|
| Spleen | Moisture | 82.61 | 100 |
| Spleen | Moisture and sputum | 52.17 | 100 |
| Moisture | Qi deficiency and sputum | 47.82 | 100 |
| Moisture | Spleen and Qi deficiency | 30.43 | 100 |
| Moisture | Spleen | 60.87 | 100 |
| Sputum | Moisture and spleen | 78.26 | 100 |
| Qi deficiency | Yin deficiency | 13.04 | 91.30 |
| Sputum | Spleen and Qi deficiency | 17.39 | 81.65 |
Table 6.
Association rules of clinical symptoms in prediabetes.
| Preceding paragraph | Consequent | Consequent (%) | Confidence level (%) |
|---|---|---|---|
| Dazzle | Forgetful and insomnia | 17.39 | 100 |
| Tinnitus | Forgetful and insomnia | 17.39 | 100 |
| Tinnitus | Blurred vision and insomnia | 21.73 | 100 |
| Tinnitus | Dry and dizzy and the fondness for a cold drink | 17.39 | 100 |
| Blurred vision | Dazzle and forgetful and lumbago and tinnitus | 13.04 | 100 |
| Sputum | Moisture and spleen | 78.26 | 100 |
| Blurred vision | Dazzle and forgetful | 30.43 | 85.71 |
| Joint pain | Insomnia and tinnitus | 34.78 | 87.50 |
| Joint pain | Fondness of a cold drink | 56.52 | 84.61 |
| Lumbago | Forgetful and dizzy | 26.08 | 83.33 |
3.6. Association analysis
We used IBM SPSS Modeler 18.0, to carry out association analysis on TCM syndrome elements and clinical symptoms in PDM and build a network diagram of the association analysis. The depth of the line represents the degree of association between the 2 variables. The deeper the line color, the closer the association. The lighter the color, the sparser is the association. A specific network diagram of the correlation between TCM syndrome elements is shown in Figure 2, and a specific network diagram of the correlation between clinical symptoms is shown in Figure 3.
Figure 2.
Correlation network diagram between syndrome elements.
Figure 3.
Clinical symptom correlation network diagram.
3.7. Cluster analysis
We conducted a cluster analysis on the 11 syndrome elements of the TCM extracted in this study. The results of cluster analysis showed that the 11 syndrome elements of TCM could be divided into 3 categories: qi deficiency, yin deficiency, and blood stasis. The second type was spleen, dampness, and phlegm. The third category included qi stagnation, blood deficiency, and the liver. Specific classifications are shown in Figure 4.
Figure 4.
Evidence element clustering analysis chart.
4. Discussion
According to TCM, yin deficiency, dryness, and heat are the basic causes and pathogenesis of diabetes. Different from diabetes, PDM belongs to the category of “spleen dane” and “food stagnation” in TCM.[32] The etiology of spleen dane is mostly caused by “this fat and beauty,” and “fat makes people feel hot inside, and sweet makes people feel satisfied,” indicating its pathogenesis.[4,33,34] The formation mechanism of “Spleen Dane” is the stagnation of spleen qi and accumulation of heat. Some scholars have studied the differentiation of TCM syndrome from IGT.[35] According to the TCM syndrome differentiation standard, 56.28%, Qi and Yin deficiency syndrome accounted for 32.73%, and Yang deficiency and blood stasis syndrome account for 10 99%. It can be seen that among patients with low glucose tolerance, phlegm dampness, and spleen stagnation type account for a large proportion. Fang Chaohui[36] et al classified the early stage of diabetes as the syndrome of dampness and heat accumulation in the spleen, the syndrome of liver stagnation and qi stagnation, the syndrome of spleen deficiency and damp excess, and the syndrome of deficiency of both qi and yin.[2] Scholars have proposed that the early stage of obesity can be differentiated into spleen stomach stagnation syndrome, damp heat accumulation syndrome, spleen deficiency, and phlegm dampness syndrome, while the early stage of nonobese diabetes can be differentiated into liver qi stagnation syndrome and qi yin deficiency syndrome, which should be clinically treated according to different syndrome types.[37,38] Modern medical scholars’ understanding of PDM is mostly from the spleen, but there is still a phenomenon of disunity in the syndrome types of PDM.
A syndrome is a summary of the occurrence and development of diseases and is the prerequisite and foundation for the diagnosis and treatment of diseases in TCM. The key element of TCM syndrome names is dampness, which can fundamentally reveal the laws, essence, and characteristics of TCM syndrome differentiation.[39–41] Disease location syndrome elements and disease nature syndrome elements are important components of TCM syndrome elements, of which disease nature syndrome elements include wind, cold, summer, dampness, dryness, fire, heat, and so on. This study mainly collated 23 studies, scientifically and normatively collated the syndrome types of PDM, extracted syndrome elements, and clinical symptoms of TCM, and analyzed them using frequency statistics, association rules, association analysis, cluster analysis, and other statistical methods to explore the distribution of syndrome elements and clinical symptoms of TCM related to PDM.
Our results showed that the syndrome types of PDM are mostly spleen deficiency and phlegm dampness syndrome. We obtained 11 syndrome elements of TCM, including 4 disease location syndrome elements, namely the spleen, liver, kidney, and lung, with the spleen accounting for the highest proportion. It can be seen that the disease location of PDM is mainly in the spleen. The liver, kidneys, and other viscera are involved. There are 7 pathogenic syndrome elements: qi deficiency, dampness, phlegm, yin deficiency, qi stagnation, heat, and blood stasis. We found that 7 pathogenic syndrome elements include both “deficiency” and “excess.” The excess syndrome elements are mainly phlegm and dampness, whereas the deficiency syndrome elements are mainly qi and yin deficiencies. We found that the combination of syndrome elements in TCM in PDM is more complex, suggesting the characteristics of deficiency and excess. PDM syndrome elements are still mostly solid syndrome elements, indicating that the disease is still in the early stages of diabetes development and does not damage the healthy qi of the human body. From the association analysis network diagram and association rules, we found a close relationship between the 4 syndrome elements of the spleen, dampness, phlegm, and qi deficiency, among which the support and confidence of spleen dampness were the highest. The results of the cluster analysis showed that high-frequency syndrome elements can be classified into 3 categories: disease location syndrome element spleen and disease nature syndrome element dampness and phlegm are one category. The occurrence of early diabetes is closely related to people’s living habits, dietary characteristics, emotional conditions, etc.[34,39] Much thinking injures the spleen, sedentary behavior, and lack of exercise leads to poor qi and blood circulation, muscle relaxation, and weakness, which can easily lead to stagnation of qi in the spleen and stomach, and weakness of the spleen. A study of common body types in early diabetes mellitus found that phlegm dampness, qi deficiency, and dampness-heat were the most common. There was also a correlation between the body type and the type of Chinese medicine evidence, indicating that the “spleen” is the main disease site in early diabetes and that the pathology is dominated by dampness, phlegm, heat, and qi deficiency. As the patient’s condition progresses, the patient may develop symptoms of yin deficiency or yin-yang deficiency due to spleen deficiency that cannot be cleared, phlegm-dampness that cannot be dispersed, liver depression that burns the yin fluids for a long period of time, aging, body weakness, and kidney yin deficiency. Spleen yin deficiency is the main pathological basis of blood glucose metabolism disorders. The development of the disease gradually affects the spleen yang, and the imbalance between yin and yang affects the spleen’s transportation and essence dissipation functions.[40]
In our research, we also found that patients with PDM had more symptoms, such as fatigue, weakness of the waist and knee, dizziness, and blurred vision. Cluster analysis revealed a strong correlation between symptoms such as blurred vision, dizziness, and soreness in the waist and knees. This can be attributed to the progressive nature of the disease, which tends to exacerbate the burning of yin fluid, accelerate aging, and result in a physical decline. Ultimately, this process leads to deficiencies in kidney yin and kidney yang. Consequently, symptoms such as dizziness and soreness of the waist and knees manifest as a consequence of this underlying condition. PDM is a key stage in preventing the development of diabetes, and good compliance with treatment at this stage can effectively slow the progression of PDM to diabetes, thereby reducing the incidence of diabetic complications.[41] We found that the clinical symptoms of patients with PDM were relatively mild, showing the characteristics of deficiency and excess of syndrome types, which led to certain difficulties in early clinical diagnosis, easy misdiagnosis, missed diagnosis, and other situations, and easy to cause patients to ignore the disease. Therefore, this study provides TCM diagnostic and therapeutic ideas for the clinical treatment of PDM by exploring the evidence types, elements, and clinical symptoms of PDM. However, the number of patients included in this study is limited, and the available evidence cannot be fully applied to clinical practice. The study suggests that further research should expand the sample size to enhance the applicability of TCM findings to clinical practice. Larger-scale studies could strengthen the evidence base for TCM interventions in PDM.
5. Conclusion
PDM is most closely related to spleen dampness and PDM is in the spleen. Qi deficiency, phlegm, and dampness are the most common syndromes in TCM. Therefore, it is recommended to treat PDM based on syndrome type and treatment starting from the spleen.
Author contributions
Conceptualization: Qin Lan, Hui Jian.
Data curation: Caiyun Yang, Xingzhen Lin, Juan Wu.
Formal analysis: Qin Lan, Hui Jian.
Investigation: Qin Lan, Hui Jian.
Methodology: Qin Lan, Jianhe Fang, Xinyu Yu, Lei Yan, Hui Jian.
Project administration: Qin Lan, Hui Jian.
Software: Qin Lan, Caiyun Yang, Xingzhen Lin, Juan Wu, Hui Jian.
Validation: Qin Lan, Jianhe Fang, Xinyu Yu, Lei Yan, Hui Jian.
Visualization: Qin Lan, Hui Jian.
Writing – original draft: Qin Lan, Hui Jian.
Writing – review & editing: Qin Lan, Jianhe Fang, Xinyu Yu, Lei Yan, Hui Jian.
Abbreviations:
- IGT
- impaired glucose tolerance
- PDM
- prediabetes mellitus
- TCM
- traditional Chinese medicine
This study was funded by the Jiangxi Province traditional Chinese medicine Middle and Young Backbone Talent Training Program Project (Gan Traditional Chinese Medicine Science and Education Zi [2020] No. 2).
The authors have no conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.
How to cite this article: Lan Q, Fang J, Yu X, Yang C, Lin X, Wu J, Yan L, Jian H. Analysis of traditional Chinese medicine syndrome elements and clinical symptoms in prediabetes: A systematic review. Medicine 2024;103:27(e36789).
The review was not registered.
Contributor Information
Qin Lan, Email: lanq0716@163.com.
Jianhe Fang, Email: 956116344@qq.com.
Xinyu Yu, Email: dores_1210@163.com.
Caiyun Yang, Email: Zcl_0809@163.com.
Xingzhen Lin, Email: dzh_0925@163.com.
Juan Wu, Email: nhy_1003@163.com.
Lei Yan, Email: yxy_15979099569@163.com.
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