Parameter study on characteristic pulse diagram of polycystic ovary syndrome based on logistic regression analysis

Abstract

This study aimed to explore the parameters of the independent predictive characteristic pulse diagram of polycystic ovary syndrome (PCOS) by analysing the pulse characteristics between healthy women and the PCOS group. A total of 278 women were recruited for this study. Pulse wave parameters were collected by the pulse spectrum analyser. The single-factor analysis of the pulse diagram parameters was used to identify significant indicators, and the logistic regression analysis was carried out on the above indicators with statistical differences to obtain independent predictors. According to the single-factor and multi-factor analyses, h₁, h₅, h₃/h₁, t, t₁ and t₅ were independent predictors of PCOS diagnosis. The results showed that PCOS patients had a faster heart rate, decreased left ventricular systolic function and decreased aortic compliance compared to healthy individuals. These findings suggested that the characteristic pulse parameters screened out are valuable for the diagnosis of PCOS.

IMPACT STATEMENT

• What is already known on this subject? Polycystic ovary syndrome (PCOS) is a common gynecological reproductive endocrine and metabolic disease, which is significant for screening and early intervention in the disease. However, due to the lack of pulse’s diagnostic evidence of PCOS, there is still an unknown area in the research on the correlation between PCOS and pulse diagram parameters.

• What do the results of this study add? This study fills the gap between the research on PCOS and pulse wave. The study also shows that the pulse characteristic parameters h₁, h₅, h₃/h₁, t, t₁, and t₅ are independent predictors of PCOS, suggesting that the patients have a higher heart rate, lower ventricular systolic function, and aortic compliance than healthy individuals.

• What are the implications of these findings for clinical practice and/or further research? Prominent risk factors for pulse parameters associated with the occurrence of PCOS facilitate early screening and diagnosis of the disease. The objectification of pulse diagnosis helps to establish a health management model, which can be used for the accurate assessment and treatment of PCOS by traditional Chinese medicine (TCM). It provides a clinical reference for the study of pulse diagnosis objectification.

Keywords:

• Polycystic ovary syndrome
• pulse characteristics
• traditional Chinese medicine
• logistic regression analysis
• diagnosis
• cardiovascular risk

1. Introduction

Pulse diagnosis is the most distinctive type and the essence of traditional Chinese medicine (TCM) diagnosis of the four diagnostic methods and has been summarised through prolonged medical practice. The objectified theory of pulse diagnosis combines the theory of modern medicine with traditional pulse theory (Sang 2014). With the progress on the concept and the content of pulse diagnosis, several studies have focussed on pulse diagnosis since the 1950s (Matos et al. 2021). Most of these used advanced precision instruments, detection tools, and indicators to investigate TCM pulse syndrome.

In recent years, modernisation of pulse diagnosis has made significant progress. With pulse diagram analysis technology as the core, time-domain analysis method has been recognised by many scholars (Li et al. 1989, Chen et al. 2018). The shape of pulse wave, related to many factors such as cardiac output, arterial blood pressure and vascular resistance, reflects the functional state of cardiovascular system and the physiological and pathological state of the whole body through neurohumoral regulation. The pulse map is the trajectory of the vascular pulse, which integrates the cardiac ejection activity and varied information carried by the pulse wave along the vascular tree. The time domain analysis method is used to analyse the correlation between the height of the pulse wave amplitude and the time direction of the pulse, including parameters such as the pulse wave, the height of the gorge (h), and the corresponding time value (t) (Fei 2003). The pulse diagram and its parameters are illustrated in Figure 1 and specific parameters are defined in Supplementary Table 1.

Figure 1. Pulse diagram and its parameters.

In addition, many studies (Wan et al. 2000, Su et al. 2000, Wang et al. 2000, Wang et al. 2003, Hua and Feng 2013) have shown that differences in pulse parameters have a specific application in a health evaluation, efficacy evaluation and disease prevention, thereby offering a new direction for the objectification of pulse diagnosis in TCM (O'Brien et al. 2013). Objective pulse diagnosis uses signal technology for time-domain analysis (O'Rourke 2009), which is non-invasive, convenient, fast, repeatable and cheap and has a marked significance in disease diagnosis and treatment.

As a common gynaecological reproductive endocrine and metabolic disease (Cui et al. 2018), the prevalence rate of polycystic ovary syndrome (PCOS) is about 15% (Fauser et al. 2012), and has been increasing with high work pressure in modern life. Due to the involvement of multiple pathways and lacking common clues, PCOS shows multi-factorial characteristics and symptom heterogeneity. The patients are often accompanied by endocrine, reproductive, and metabolic diseases, such as menstrual disorders, obesity, insulin resistance (IR), ovarian changes, hirsutism and acne (Gilbert et al. 2021). These conditions cause infertility in about 70% of PCOS females (Evanthia and Andrea 2012). In addition, the incidence of complications, such as endometrial disease, hyperlipidaemia, diabetes and cardiovascular disease (CVD) is also rising. Although its pathogenesis and treatment are not accurate (Łebkowska et al. 2021), a recent study (Stener-Victorin and Deng 2021) suggested that the core aetiology and main endocrine characteristics of PCOS are hyperandrogenemia and IR.

Presently, the study on the correlation between PCOS and pulse parameters has gained increasing attention. Feng et al. (2022) demonstrated that PCOS patients with different body mass index (BMI) levels have different pulse parameters. However, there are no studies comparing the differences in pulse parameters between PCOS patients and normal population. Herein, we aimed to deduce the characteristic pulse diagram parameters of PCOS compared to normal women. The pulse diagnosis study of PCOS is non-invasive, convenient for screening, the samples can be collected on a large scale, and is cheaper than serological examination and ultrasonography. The findings would be helpful for screening and early intervention of PCOS. Moreover, it will offer an objective reference for TCM clinical diagnosis and treatment of PCOS.

2. Materials and methods

2.1. Research subjects

Compared to 113 women in the normal sample group with normal health examinations (Physical Examination Centre of Shuguang Hospital affiliated to Shanghai University of TCM), 165 female patients with PCOS from the Gynecological Department of Shuguang Hospital were selected in the study during the period of March–July 2021. All these patients were aged 15–45 (average, 30.82 ± 5.27) years and signed an informed consent form. The BMI of the PCOS group was 22.57 ± 1.96 kg/m², and that of the normal group was 22.32 ± 2.32 kg/m². No statistical difference was detected between the two groups (p < 0.05).

2.2. Case inclusion criteria

The 2003 Rotterdam diagnostic criteria (Rotterdam ESHRE/ASRM-Sponsored PCOS consensus workshop 21. group 2004) are as follows:

1. Sparse ovulation or anovulation;

2. Hyperandrogenic manifestations and(or) hyperandrogenism;

3. Ovarian polycystic changes: ultrasound revealed that one or both ovaries had ≥12 follicles with a diameter of 2–9 mm in one section, and(or) ovarian volume ≥10 mL;

The cases that met two of the above three items were included.

2.3. Case exclusion criteria

The exclusion criteria were as follows:

1. The cases did not meet the inclusion criteria of this study;

2. Other possible causes of hyperandrogenism, such as congenital adrenal hyperplasia, Cushing’s syndrome, and androgen-secreting tumours;

3. Other diseases that cause ovulation disorders, such as hyperprolactinaemia, premature ovarian failure, pituitary or hypophysis thalamic amenorrhoea and abnormal thyroid function;

4. Patients who used hormonal drugs (such as contraceptives, ovulation stimulators and glucocorticoid drugs) within the past month;

5. Patients had serious primary diseases in internal medicine and surgery;

6. Patients were unable to cooperate to complete the research plan, including a history of infectious diseases, mental illness and other diseases;

7. Patients with unstable pulse wave diagram.

2.4. Pulse diagram collection and analysis method

The collection and analysis methods were as follows:

1. The subjects were required to ensure that they did not stay up late into the night, and did not drink strong tea or coffee before the test. Exercising vigorously 1 h before the test was forbidden. They also needed to have a normal diet on the day of the test.

2. The subjects were breathing calmly, sitting upright, with the upper arms relaxed and the elbows bent about 120°. The forearms were naturally flat, the wrists were placed on the pulse pillow, and the palms were facing up. Simultaneously, the subjects should avoid speaking or shaking their body during the sampling process.

3. The sampler used the three-portions and nine pulse-taking methods to locate the most obvious position of the subject’s pulsation, and place the probe of the PDA-1 single-part pulse diagnosis instrument developed by our group. The best pressure point was corrected by referring to the waveform shown in the pulse acquisition software, which could automatically collect a single-part pulse diagram with a stable waveform of 30 s.

4. The qualitative result of the pulse condition was determined by the pulse classification standard in ‘Modern TCM Pulse Diagnosis’ (Fei 2003).

5. The time domain analysis method was used to interpret the meaning of each pulse diagram parameter (Fei 2003).

2.5. Statistical analysis

SPSS version 26.0 statistical software (SPSS Inc., Chicago, IL) was used for data analysis. The inspection level was α = 0.05. A two-sample t-test was employed for the comparison of BMI. Based on the qualitative pulse condition results, the different types of pulse conditions were expressed in digital form. The appearance was recorded as 1, and the absence was recorded as 0. The difference analysis was carried out using the χ² test. The areas under the curves (AUC) of receiver operating characteristic (ROC) provided the best cut-off value of the pulse diagram parameters. The 12 parameters of the pulse diagram (h₁, h₃, h₄, h₅, h₃/h₁, h₄/h₁, t, t₁, t₄, t₅, t₁/t and h₁/t₁) were included in single-factor analysis, which was also assessed by χ² test. Moreover, variable parameters that met p < 0.05 in the single-factor analysis were incorporated into the logistic regression model, and further multi-factor analysis was performed. The difference was statistically significant at p < 0.05.

3. Results

3.1. Qualitative results analysis of PCOS pulse condition

Pulse condition analysis is combined with the four major elements: position, number, shape and momentum. Therefore, in the qualitative analysis, the pulse condition was expressed as a compound pulse condition, i.e. concurrent pulse condition. In this study, the compound pulse conditions of PCOS patients were divided and counted individually. The pulse of plain pulse is even and fluent, which is the physiological state of normal people. The thin pulse is the main deficiency syndrome, and the pulse width is lower than the normal pulse. The string pulse is responsible for liver disease and pain, and the pulse diagram shows a broad main wave with a high trough. The smooth pulse is responsible for phlegm-dampness, and the pulse pattern is bimodal, and the pulse wave rises and falls smoothly. The rapid pulse dominates the heat syndrome, and the pulse rate is >90 beats/min (bpm). The abrupt pulse exhibits severe heat syndrome, and the pulse rate is >120 bpm. The moderate pulse governs spleen deficiency and phlegm dampness, with a pulse rate of 60–70 bpm. The forceful pulse is the main evidence, and the pulse width and pulse length are larger than the normal pulse. Irregular pulse indicates stagnation of Qi and blood and irregular pulse beat. The statistical results of the qualitative indicators of the pulse conditions showed that thin pulses had the highest frequency in PCOS patients (35.3%), followed by string, plain, rapid, smooth, irregular, moderate, abrupt and forceful pulses. Statistically significant differences were observed between plain pulse, thin pulse, string pulse and other types of pulse conditions (p < 0.05) (Supplementary Table 2 and Figure 2).

Figure 2. Comparisons in the numbers of different pulse-type cases in PCOS patients. PCOS: polycystic ovary syndrome. *: α = 0.05, there were significant differences in the number of cases between plain pulse and other pulse cases; ^#: α = 0.05, there were significant differences in the number of cases between thin pulse and other pulse cases; △: α = 0.05, there were significant differences in the number of cases between string pulse and other pulse cases.

3.2. ROC curve analysis of pulse diagram parameters for predicting the risk of PCOS

The pulse diagram parameters (h₁, h₃, h₄, h₅, h₃/h₁, h₄/h₁, t, t₁, t₄, t₅, t₁/t and h₁/t₁) were selected to predict the occurrence of PCOS. The best cut-off values were 8.315 mm, 5.15 mm, 2.49 mm, 0.415 mm, 0.525, 0.075, 0.815 s, 0.135 s, 0.355 s, 0.415 s, 0.085 and 2.92 mm/s, respectively. These 12 indicators had statistical differences (p < 0.05) and high diagnostic efficiencies (Table 1 and Figures 3 and 4).

Figure 3. ROC curves of h1, h3, h4, h5, h3/h1, h4/h1. ROC: receiver operating characteristic.

Figure 4. ROC curves of t, t1, t4, t5, t1/t, h1/t1. ROC: receiver operating characteristic.

Table 1. ROC curve analysis results of pulse diagram parameters.

Pulse diagram parameters	Cut-off values	AUC	p Value	95%CI
				Lower limit	Upper limit
h1	8.315 mm	0.781	≤0.001	0.729	0.834
h3	5.15 mm	0.797	≤0.001	0.747	0.848
h4	2.49 mm	0.714	≤0.001	0.653	0.776
h5	0.415 mm	0.63	≤0.001	0.559	0.701
t	0.815s	0.712	≤0.001	0.651	0.772
t1	0.135s	0.581	0.022	0.51	0.652
t4	0.355s	0.687	≤0.001	0.622	0.751
t5	0.415s	0.755	≤0.001	0.697	0.814
h3/h1	0.525	0.599	0.005	0.53	0.667
h1/t1	2.92 mm/s	0.77	≤0.001	0.716	0.824
h4/h1	0.075	0.348	≤0.001	0.283	0.413
t1/t	0.085	0.375	≤0.001	0.309	0.441

AUC: areas under the curves; ROC: receiver operating characteristic; CI: confidence interval

3.3. Single-factor analysis of pulse diagram parameters

Combining the cut-off values in Table 1, the study made relevant assignments to the pulse diagram parameters (Supplementary Table 3). The single-factor analysis results showed that h₁, h₃, h₄, h₅, h₃/h₁, h₁/t₁, t, t₁, t₄ and t₅ were related to PCOS occurrence (p < 0.05), as shown in Table 2.

Table 2. Single factor analysis of pulse diagram parameters.

Group	N	h1 (n, %)		h3 (n, %)		h4 (n, %)		h5 (n, %)		h3/h1 (n, %)		h4/h1 (n, %)		t (n, %)		t1 (n, %)		t4 (n, %)		t5 (n, %)		t1/t (n, %)		h1/t1 (n, %)
		≥8.315mm	<8.315mm	≥5.15mm	<5.15mm	≥2.49mm	<2.49mm	≥0.415mm	<0.415mm	≥0.525	<0.525	≥0.075	<0.075	≥0.815s	<0.815s	≥0.135s	<0.135s	≥0.355s	<0.355s	≥0.415s	<0.415s	≥0.085	<0.085	≥2.92mm/s	<2.92mm/s
PCOS	165	57 (34.5)	108 (65.5)	44 (26.7)	121 (73.3)	62 (37.6)	103 (62.4)	55 (33.3)	110 (66.7)	74 (44.8)	91 (55.2)	157 (95.3)	8 (4.8)	48 (29.1)	117 (70.9)	21 (12.7)	144 (87.3)	32 (19.4)	133 (80.6)	33 (20.0)	132 (80.0)	164 (99.4)	1 (0.6)	54 (32.7)	111 (67.3)
Normal	113	94 (83.2)	19 (16.8)	84 (74.3)	29 (25.7)	87 (77.0)	26 (23.0)	71 (62.8)	42 (37.2)	76 (67.3)	37 (32.7)	110 (97.3)	3 (2.7)	69 (61.1)	44 (38.9)	39 (34.5)	74 (65.5)	57 (50.4)	56 (49.6)	69 (61.1)	44 (38.9)	113 (100)	0 (0)	90 (79.6)	23 (20.4)
2 value		63.947		61.346		41.895		23.55		13.556		0.849		28.126		18.809		29.706		48.683		0.687		59.133
P value		≤0.001		≤0.001		≤0.001		≤0.001		≤0.001		0.357		≤0.001		≤0.001		≤0.001		≤0.001		0.407		≤0.001

PCOS: polycystic ovary syndrome

3.4. Multi-factor analysis of pulse parameters

Taking the univariate analysis with statistically significant pulse diagram parameters as independent variables, a forward likelihood ratio (LR) stepwise regression analysis was conducted and iteratively calculated 20 times to establish a logistic regression model: Logit(P)=3.97 − 1.547 × h₁−0.958 × h₅−1.42 × h₃/h₁−1.251 × t − 1.442 × t₁−1.295 × t₅, where h₁, h₅, h₃/h₁, t, t₁ and t₅ values were shown in Table 3. The model accuracy rate was 84.2%. The logistic multivariate analysis showed that h₁, h₅, h₃/h₁ and t₅ were independent predictors for distinguishing PCOS from healthy individuals (p < 0.05; Table 3).

Table 3. multiple factors analysis of pulse diagram parameters.

Independent variable	b	Sb	Waldꭕ^2	p value	OR value	95%CI
						Lower limit	Upper limit
h1	−1.547	0.357	18.723	≤0.001	0.213	0.106	0.429
h5	−0.958	0.389	6.086	0.014	0.384	0.179	0.821
h3/h1	−1.42	0.375	14.363	≤0.001	0.242	0.116	0.504
t	−1.251	0.329	14.452	≤0.001	0.286	0.15	0.546
t1	−1.442	0.414	12.127	≤0.001	0.236	0.105	0.532
t5	−1.295	0.334	14.995	≤0.001	0.274	0.142	0.528

OR: odds ratio; CI: confidence interval

4. Discussion

The oscillation of the blood vessel wall caused by the cardiac ejection is the key to the formation of the pulse. The blood is gradually transmitted from the aorta root to the branch vessels, forming a pulse wave (Shen et al. 2018). Factors, such as cardiac ejection activity, vascular wall elasticity, blood flow fluency and peripheral vascular resistance, can affect the pulse waveform (Zhang et al. 2019). The pulse data conversion showed (Li et al. 2018) that the differences in pulse information occurred with the changes in cardiovascular parameters, such as blood flow rate, vascular resistance and vascular elasticity. Most women with PCOS are known to present hyperandrogenemia and show signs of cardiovascular dysfunction (Wild et al. 2010). A previous study (Wang et al. 2012) evaluated the association between PCOS and echocardiographic parameters and showed that younger women with the syndrome exhibited higher left ventricular mass index and left atrial diameter than older women. Manti et al. (2020) showed left ventricular hypertrophy in women with PCOS, while structural changes were not accompanied by changes in blood pressure and metabolic abnormalities. Therefore, the cardiovascular function problems caused by PCOS could be manifested by the pulse condition.

In recent years, the objectification study of pulse diagnosis has gained extensive attention for its advantage of non-invasive diagnosis (Bi et al. 2020). Time-domain analysis is a method to evaluate pulse waveform characteristics by evaluating the correlation between pulse parameters (pulse diagram amplitude, time value, ratio and area) and pulse time phase. The method by Wang et al. (2011) was used to identify the internal correlation between these parameters and the pulse condition, which is valuable for clinical reference. In this study, logistic regression analysis comprehensively assessed multiple independent variables and successfully screened out independent risk factors of events (Nie and Li 2018). These findings also implied that logistic regression had achieved satisfactory results in medicine to currently analyse the influence factors of a specific disease (Jin et al. 2021).

In terms of TCM, PCOS could be classified as the gynaecological disease in the form of anemorrhagia, amenorrhoea, low menstrual volume, irregular menstruation, menometrorrhagia and infertility. According to the theory of TCM, the occurrence of PCOS is mainly the dysfunction of kidney-Tiangui-the chong and ren meridians-uterine axis and the dysfunction of the kidney, liver and spleen. The analysis of the qualitative indicators of pulse pattern of patients with PCOS revealed that the main pulse pattern of the female patients was thin pulse, followed by string pulse and plain pulse. The present results showed statistically significant differences among these three pulse types and other pulse types. The thin pulse suggests deficiency syndrome. Kidney and spleen deficiency causes blood vessels to lack enough blood, and hence the pulse is thin. In this study, thin pulse is the most common pulse condition, which supported the theory that PCOS is based on deficiency. Also, string pulse is a common clinical condition of patients with PCOS, suggesting liver and primary pain. According to the TCM theory, the liver stores blood and manages catharsis, which is reflected in the straight and long pulse-end like a hard chord. Therefore, liver depression is also the main pathological mechanism of PCOS, which is consistent with the conclusion of this study. In addition, some patients showed plain pulse on the pulse condition, which was termed the normal pulse. This indicates a lack of specificity in the early stages of PCOS, but has not affected the blood circulation, and the pulse condition is not reflected. Therefore, in the process of treating disease, we prevented disease before spreading. Thus, we should effectuate a comprehensive treatment based on syndrome differentiation of TCM clinical data.

Furthermore, this study carried out multi-factor analysis of the PCOS pulse parameters. The results showed that h₁, h₅, h₃/h₁, t, t₁ and t₅ are independent predictors of PCOS diagnosis. Herein, h₁ represents the amplitude of the main pulse of the pulse diagram, reflecting the left ventricular ejection function and aortic compliance; h₅ represents the amplitude of the dicrotic wave, reflecting the elasticity of the aorta and the function of the aorta; h₁ and h₅ values in the PCOS group are significantly lower than those in the normal group, suggesting a decrease in the left ventricular systolic function and the aortic compliance in the PCOS group; h₃/h₁ reflects the compliance and peripheral resistance of the vascular wall. Xu et al. (2010) pointed out that the vascular diameter increase index was positively correlated with h₃/h₁. The h₃/h₁ value of the PCOS group was lower than that of the normal group, which was used to identify the diameter of the carotid artery in the PCOS group, which was smaller than that in the normal group. t₅ is the time value from the dicrotic notch to the endpoints of the pulse diagram, corresponding to the diastolic phase of the left ventricle; t is the time value from the start point to the endpoint in the pulse diagram, corresponding to a cardiac cycle of the left ventricle; t₁ is the time value from the start point to the main peak point in the pulse diagram, corresponding to the rapid ejection period of the left ventricle; t₅ value in the PCOS group was lower than that in the normal group, suggesting a rapid heart rate in the PCOS group.

It is not difficult to find that PCOS has IR and a high risk of CVD by analysing its metabolic reasons. The effects of IR on the cardiovascular system of PCOS patients are manifested as increased systolic blood pressure, atherosclerotic plaque formation on the arterial wall, decreased blood flow velocity in the aortic valve area and the occurrence of coronary heart disease (Evanthia and Andrea 1996). Some studies have shown that women with PCOS have an increased prevalence of CVD, an increase in clinical and subclinical markers of early atherosclerosis, and an increase in carotid artery intima-media thickness. Then, the presence of carotid plaque increases coronary artery calcification (Moran and Teede 2009). In addition to insulin stimulation, ovarian androgen production reduces the production of liver sex hormone-binding globulin and increases total androgens and free androgens (Evanthia and Economou 2006). Another study showed that dehydroepiandrosterone level has an inverse correlation with health outcomes, such as CVD and atherosclerosis, in cross-sectional studies of young women (Arnold and Wu 2003). Preadipocytes have androgen receptors, and androgens regulate the function of adipocytes at the mechanical level. Increased androgens increase abdominal obesity, following which IR is increased (Hirokawa et al. 2016), which forms a vicious cycle of IR and hypernatremia and further leads to the occurrence of CVD.

No significant difference was detected in BMI between the experimental and control groups, suggesting that the influence of BMI on pulse characterisation parameters has been excluded when analysing the PCOS pulse characteristics. International evidence-based PCOS guidelines recommended that clinicians should consider racial differences in the presentation and presentation of PCOS (Teede et al. 2018). Asian women with PCOS have a lower mean BMI compared to other races. The mean BMI of East Asian patients ranged from 20 to 22 kg/m² (Chen et al. 2010, Nidhi et al. 2011, Kim et al. 2014), the mean BMI of American whites was 27.8 kg/m² (Carmina et al. 1992), and the mean BMI of British whites was 31.5 kg/m² (Mani et al. 2015), indicating that Asian women have a lower BMI than Caucasian patients such that PCOS can occur. This phenomenon is consistent with the conclusion that the average BMI of the patients in this study was within the normal BMI range, and no obvious overweight was detected. Strikingly, one of the manifestations of hyperandrogenism in PCOS is obesity (Rotterdam reference). Cui et al. (2016) suggested that the ratio parameters h₃/h₁ and h₄/h₁ could be used as the classification parameters of smooth pulse, which is consistent with the conclusion of this study that h₃/h₁ is an independent risk factor for PCOS. In this study, the proportion of the slippery pulse was 6.8%, which was lower than the proportion of the three most common pulse types mentioned above; this phenomenon agreement in line with the fact that the BMI of PCOS patients in Asia was common in the normal range. Feng et al. (2022) found that obese PCOS had lower pulse parameters h₁, h₃, h₄, h₅, h₄/h₁ than normal PCOS, suggesting that the left ventricular pumping function and arterial compliance were lower in obese than in normal PCOS patients. Obesity is responsible for the development of CVD and cardiovascular mortality independently of other cardiovascular risk factors (Lu et al. 2022). The study also suggested that obese patients with PCOS had poor left ventricular pumping function and arterial compliance than non-obese patients, and obese patients had lower peripheral resistance than non-obese patients; this phenomenon may be related to decreased myocardial contractility and cardiac function compensation in obese patients. The above understanding is consistent with the conclusion of this experiment.

Stener-Victorin et al. (2005) found that PCOS rats had significantly higher heart rates and increased sympathetic nerve activity than normal rats, suggesting that increased sympathetic nerve activity may have an impact on the mechanism of increased CVD risk in women with PCOS. Pei et al. (2013) demonstrated found that the resting heart rate of PCOS patients was significantly higher than that of normal women. These conclusions are consistent with the results of this study. Therefore, the effects of CVD risk due to PCOS were consistent with the conclusions of our pulse diagnosis experiment.

5. Conclusions

In summary, the probability of thin pulse is the highest, followed by string pulse and plain pulse in PCOS patients. This result is statistically significant using the testing method. In addition, the study implied that the early onset of PCOS is not fully manifested in the pulse condition, needing further exploration based on clinical data. Also, a logistic model was used to prove that the objective pulse diagnosis indicators h₁, h₅, h₃/h₁, t, t₁ and t₅ are independent predictors of the disease, indicating that the heart rate of PCOS patients is faster than that of healthy women. The ventricular systolic function and aortic compliance are also reduced. Concurrently, single-factor analysis showed that h₃, h₄, h₁/t₁ and t₄ are the factors influencing PCOS. However, multi-factor analysis cannot confirm this conclusion. Due to the small sample size, the model prediction effects might present bias. Thus, for a comprehensive analysis and optimal prediction result, a large sample size is required.

Ethics approval

This study was approved by the Medical Ethics Committee of Shuguang Hospital affiliated with the Shanghai University of TCM (authorization no. 2018-626-55-01) and was conducted in accordance with the Declaration of Helsinki.

Author contributions

Investigation: Weiying Wang, Weiwei Zeng, Xinmin Chen. Methodology: Xiuqi Yin, Jiatuo Xu. Analysis: Liping Tu, Weiying wang. Resources: Weiwei Zeng, Xiuqi Yin, Xiatuo Xu. Supervision: Liping Tu. Writing-original draft: Weiying Wang, Weiwei Zeng. Writing-review and editing: Weiying Wang, Weiwei Zeng, Xinmin Chen. All authors have read and approved the manuscript.

Disclosure statement

The authors declare that they have no conflicts of interest.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

Additional information

Funding

This study was funded by National Natural Science Foundation of China (no. 82004398).

This study was funded by the National Natural Science Foundation of China (no. 82004398).