The relationship between morning blood pressure surge, serum anti-müllerian hormone level, and HOMA-IR score in patients with polycystic ovary syndrome

Abstract

In our study, we aimed to investigate the relationship between anti-müllerian hormone (AMH) and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) score, which are known to be increased in patients with polycystic ovary syndrome (PCOS), and morning blood pressure surge (MBPS), and whether these measurements are a marker for early cardiovascular disease risk in patients with PCOS. Forty patients aged between 18 and 65 years with hypertension (HT) and PCOS, 40 patients with HT but without PCOS, and 40 people representing the healthy control group were included in our prospective, cross-sectional study. All patients underwent ambulatory blood pressure measurement for 24 hours and MBPS was calculated. The study groups were divided into 3 groups as healthy control group (group 1), patient group with HT without PCOS (group 2), and patient group with HT and PCOS (group 3). MBPS was found to be statistically significantly higher in group 3. In linear regression analysis, AMH and HOMA-IR levels were found to be independently associated with MBPS. In patients with PCOS, AMH, and HOMA-IR levels were significantly higher in the group with MBPS > 25 mm Hg. Early diagnosis and treatment of PCOS and accompanying comorbidities can halt the progression of cardiac disorders and reduce cardiovascular mortality and morbidity. AMH level, HOMA-IR score, and MBPS measurement can be used in early detection and prediction of cardiovascular disease in PCOS patients.

1. Introduction

Eight to 10% of reproductive-age women suffer with polycystic ovarian syndrome (PCOS), making it one of the most prevalent endocrine illnesses in this population.^[1] Ovarian polycystic appearance, abnormal menstrual cycles, and hyperandrogenism in the clinic and lab are all symptoms experienced by patients. In addition to being an illness affecting the reproductive system, PCOS is also a metabolic disease. Compared to people without PCOS, women with PCOS have a higher risk of hyperlipidemia, hypertension (HT), glucose metabolism problems, cardiovascular diseases (CVD), and infertility.^[2]

Insulin resistance and compensatory hyperinsulinemia are significant features of PCOS pathogenesis. Insulin resistance is indicated by raised Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) values in peripheral tissues and a greater rate of impaired fasting glucose level in these patients. Evidence suggests that PCOS individuals are more likely to develop metabolic syndrome and CVD due to their elevated insulin resistance. There is a correlation between PCOS, insulin resistance, and excess androgens, which in turn increases the risk of metabolic syndrome and early atherosclerosis.^[3,4]

The gonodal tissue produces anti-müllerian hormone (AMH), and it is well-documented that PCOS patients have elevated levels of this hormone. Research has linked increased AMH levels to obesity, insulin resistance, and hyperandrogenism. Serum androgen levels are positively correlated with serum AMH levels in PCOS patients, according to the research.^[5] Although AMH elevation is not part of the diagnostic criteria for PCOS, it is useful for tracking the disease’s course and severity. Cardiovascular mortality and morbidity are both exacerbated when diagnoses are delayed.^[6]

Over the course of a day, blood pressure might fluctuate depending on the time of day. In contrast to the low readings recorded during the night, the blood pressure reading taken upon awakening in the morning reveals a significant rise. “Morning blood pressure surge” (MBPS) is the difference between the average blood pressure readings taken 2 hours after waking up and the lowest readings taken throughout the night. Regardless of the average blood pressure of the past 24 hours, MBPS remains a significant risk factor for CVDs. Studies have shown that the development of left ventricular hypertrophy, arterial stiffness, carotid atherosclerosis, and renal albuminuria, which are manifestations of HT, are independently predicted by elevated MBPS.^[7] As a result of elevated renin–angiotensin–aldosterone system activity, insulin resistance, and sympathetic hyperactivity, elevated MBPS is believed to occur.^[8]

We set out to determine whether elevated AMH and HOMA-IR scores, as well as MBPS, which is believed to rise due to insulin resistance and related processes, are indicators of early cardiovascular disease in PCOS patients, and if so, how these measurements relate to one another.

2. Material and methods

An ethical review board from Cukurova University’s medical school gave their stamp of approval to our study (Decision No: 101). The study does not contain any conflicts of interest.

2.1. Study population

We intended for our research to be a prospective, cross-sectional study with a single center. The study included a total of 120 participants from June 01, 2021 to May 31, 2022. Forty of whom had HT and PCOS phenotype 1 (hyperandrogenism + oligo-anovulation + polycystic ovarian morphology), 40 of whom had HT but no PCOS, and 40 of whom were healthy controls. The participants’ ages ranged from 18 to 65. The control group consisted of outpatient clinic applicants who were statistically identical to the patient group in terms of age, gender, and body mass index (BMI). According to the 2003 Rotterdam criteria, PCOS is diagnosed according to the presence of at least 2 of the following 3 criteria: oligo/anovulation (oligomenorrhea: menstrual cycle lasting more than 34 days; amenorrhea: absence of menstruation for 3 consecutive cycles or absence of menstruation for more than 6 months); hyperandrogenism with clinical and/or laboratory findings; polycystic ovaries (at least 1 ovarian volume > 10 mL or > 12 follicles 2–9 mm in at least 1 ovary). We used the criteria outlined in the 2018 ESC/ESH recommendations to select patients with a HT diagnosis for the case group. Liver illness, rheumatoid arthritis, hypothyroidism, heart failure, cancer, pregnancy, and smoking were all grounds for exclusion.

Before taking part in the trial, both the patients and the healthy controls were made aware of it. All participants were required to complete an informed consent form before they could be considered for the study. The Declaration of Helsinki was followed throughout the course of the research. All patients and healthy controls underwent thorough physical examinations and detailed medical histories.

Using an appropriate cuff, we measured blood pressure in both arms after 5 minutes of rest in a dark, silent room while also keeping an eye on the subjects’ pulses. The subjects were measured for their anthropometric body weight. Step one in taking a height measurement is to stand with your feet flat on the ground and your knees bent at a right angle to the measuring stick. BMI was determined by dividing the individual’s weight in kilograms by the square of their height in meters.

2.2. Ambulatory Holter measurements

The study’s participants all wore ambulatory blood pressure monitoring devices of the oscillometric type (DMS 300-3A Holter Recorder DM Softcare NV, USA). A 24-hour period of ambulatory blood pressure monitoring (ABPM) was conducted. Subjects were apprized of ABPM. All hours of the day and night, as well as MBPS, were tracked. 00 to 06 was thought of as the time for sleeping. The research did not include outpatient blood pressure data with systolic above 270 mm Hg and <70 mm Hg, or diastolic over 150 mm Hg and <40 mm Hg. Accurate data was defined as more than 14 during the day and more than 7 during the night. We asked patients about their day-to-day routines and tracked their heart rate to get an idea of their MBPS. To calculate MBPS, we calculated it as the difference between the mean blood pressure for 2 hours after waking up and the lowest blood pressure at night.

2.3. Laboratory measurements

Health Sciences University Adana Training and Research Hospital’s Biochemistry Laboratory conducted the study’s laboratory procedures. During regular controls, both the patients and the control group had their venous blood collected from the antecubital vein after fasting for at least 8 hours the night before. Both the patient’s medical records and the hospital’s automated system documented the patient’s gender, age, diagnosis, and the basic biochemical tests that were ordered during the diagnosis. Biochemical and hemogram values were assessed. Abbott Aeroset, located in Minnesota, USA, is an automated coupled chemistry analyzer that was used in conjunction with the proper commercial kits from Abbott to measure biochemical assays. The formula was used to construct the HOMA-IR index, which is [fasting blood glucose (mg/dL) × fasting insulin (μIU/mL)]/405. To be deemed significant, HOMA-IR has to be >2.5. An extra blood sample was taken from each participant using a gel tube with a yellow cap as part of their regular blood collection procedure. The samples were spun in a centrifuge at 4000 rpm for 10 minutes as soon as they were collected. The serum was then transferred to an ependorf tube and kept in cabinets at -80 °C till the study was conducted. The samples were transported to the Medical Microbiology Laboratory at Istanbul Bezmiâlem Vakif University under the right circumstances once the study was finished. After removing the samples from the deep freezer the day before the research, they were allowed to thaw at room temperature. The AMH kits (eBioscience, Europe/International, Austria) and the Enzyme-Linked Immunosorbent Assay (ELISA) technique were utilized to conduct the investigation.

2.4. Statistical analyses

We used SPSS 24.0 (Chicago, IL) for all of our statistical analysis. We checked for normality in the distribution of continuous variables using the Kolmogorov–Smirnov test. The mean ± standard deviation was used to express continuous variables in the group data. The numerical and percentage values for the categorical variables were used. When comparing groups with normally distributed continuous variables, either Student t test or one-way ANOVA was employed. When comparing continuous variables that did not follow a normal distribution, the Mann–Whitney U test was employed. To compare categorical variables, the chi-square (χ²) test was employed. To identify the parameters linked to MBPS in PCOS patients (n:40), a univariate correlation study was conducted using the Pearson–Spears correlation approach. In a multivariate model with parameters that were statistically significant, linear regression analysis was conducted. We identified the independent variables that have an effect on MBPS. Statistically significant parameters with a P value <.05 were used in the multivariate logistic regression analysis that followed the univariate model in the independent determination of patients with PCOS who had MBPS≥ 5 mm Hg. To find the cutoff value for the markers that were independent in recognizing patients with MBPS ≥ 25 mm Hg, a ROC curve analysis was run. The markers that were previously evaluated were reevaluated. To determine how precise the test was, the area under the curve was calculated. A P value <.05 was considered to be statistically significant.

3. Results

There were 3 groups in the study: patients with HT but no PCOS (group 2), patients with both PCOS and HT (group 3), and a healthy control group (group 1). Table 1 shows that when comparing the study groups, group 3 had a considerably higher BMI and alanine aminotransferase values than groups 1 and 2. When the groups were compared based on blood pressure measurements, it was discovered that groups 2 and 3 had significantly higher readings than group 1, including office systolic blood pressure (SBP), office diastolic blood pressure (DBP), daytime mean SBP, nighttime mean DBP, all mean SBP, all mean DBP, all mean DBP, and MBPS. Table 2 shows that MBPS was considerably greater in group 3 than in group 2. When comparing groups 2 and 3, group 3 had significantly higher values for BMI, alanine aminotransferase, LH/FSH ratio, dehydroepiandrosterone sulphate, total testosterone, AMH and HOMA-IR.

Table 1.

Demographic, clinical and laboratory findings of the study groups.

Variables	Healthy control group (group 1) n = 40	Patient with hypertension and without pcos group (group 2) n = 40	Patient with hypertension and pcos group (group 3) n = 40	P
Age (year)	28.0 ± 4.71	29.4 ± 3.84	29.2 ± 4.74	.292
Body mass index (kg/m2)	23.3 ± 1.67*	23.8 ± 3.48†	27.5 ± 7.74	.004
Basal heart rate (pulse/minute)	77.1 ± 7.38	80.1 ± 10.2	78.2 ± 9.70	.387
White blood cell (10³/µL)	6.83 ± 1.65	6.19 ± 1.30	6.25 ± 1.45	.213
Hemoglobin (g/dL)	12.8 ± 0.64	12.7 ± 0.89	13.0 ± 1.59	.493
Platelet (10³/µL)	290.8 ± 36.1	296.9 ± 66.4	274.0 ± 67.2	.221
Creatinine (mg/dL)	0.58 ± 0.13	0.58 ± 0.07	0.59 ± 0.08	.863
Sodium (mmol/L)	139.0 ± 2.06	138.7 ± 1.07	138.8 ± 1.16	.680
Potassium (mmol/L)	4.31 ± 0.35	4.40 ± 0.31	4.38 ± 0.30	.519
Aspartate aminotransferase (u/L)	17.3 ± 5.86	19.3 ± 4.31	20.4 ± 8.14	.103
Alanine aminotransferase (u/L)	16.3 ± 4.65*	14.9 ± 6.52†	19.4 ± 9.33	.021
Triglyceride (mg/dL)	105.6 ± 40.4	117.1 ± 76.2	120.3 ± 73.0	.573
High-density lipoprotein (mg/dL)	53.0 ± 12.0	54.0 ± 14.4	54.9 ± 14.5	.834
Low-density lipoprotein (mg/dL)	119.0 ± 26.1	115.9 ± 20.7	123..3 ± 36.5	.530
Calcium (mg/dL)	9.45 ± 0.52	9.64 ± 0.30	9.61 ± 0.35	.130
Glucose (mg/dL)	98.4 ± 5.45	98.8 ± 8.77	102.9 ± 13.4	.154
Thyroid stimulating hormone (mIU/L)	1.83 ± 0.80	1.98 ± 0.98	2.04 ± 1.06	.630
C-reactive protein (mg/L)	0.18 ± 0.10	0.23 ± 0.20	0.21 ± 0.17	.361

Bold values indicate significant P values.

Pcos = polycystic ovary syndrome.

^*The significant difference between group 1 and group 3.

^†The significant difference between group 2 and group 3.

Table 2.

Office and ambulatory blood pressure measurements of the study groups.

Variables	Healthy control group (group 1) n = 40	Patient with hypertension and without pcos group (group 2) n = 40	Patient with hypertension and pcos group (group 3) n = 40	P
Office SBP (mm Hg)	114.9 ± 4.97*,†	146.5 ± 16.7	148.7 ± 16.6	<.001
Office DBP (mm Hg)	78.3 ± 4.32*,†	101.9 ± 12.2	102.3 ± 14.7	<.001
Daytime mean SBP (mm Hg)	114.0 ± 4.14*,†	140.3 ± 24.4	142.8 ± 26.2	<.001
Daytime mean DBP (mm Hg)	75.7 ± 5.71*,†	95.5 ± 11.7	99.1 ± 15.0	<.001
Nighttime mean SBP (mm Hg)	113.3 ± 6.45*,†	127.5 ± 14.8	128.3 ± 19.0	<.001
Nighttime mean DBP (mm Hg)	75.9 ± 5.82*,†	83.5 ± 10.8	85.0 ± 14.5	<.001
All mean SBP (mm Hg)	115.6 ± 3.35*,†	143.5 ± 13.6	145.5 ± 17.0	<.001
All mean DBP (mm Hg)	73.1 ± 4.94*,†	95.2 ± 11.4	98.3 ± 14.8	<.001
MBPS (mm Hg)	16.0 ± 4.70*,†	20.4 ± 8.13‡	26.0 ± 10.8	<.001

Bold values indicate significant P values.

Pcos = polycystic ovary syndrome, SBP = systolic blood pressure, DBP = diastolic blood pressure, MBPS = morning blood pressure surge.

^*The significant difference between group 1 and group 2.

^†The significant difference between group 1 and group 3.

^‡The significant difference between group 2 and group 3.

For each group, researchers looked for associations between MBPS and a variety of clinical, demographic, and laboratory variables. It was discovered that the parameters linked to MBPS are HOMA-IR and AMH. We ran a linear regression analysis with the factors that had a strong connection with MBPS. There was an independent association between MBPS and AMH and HOMA-IR levels (Table 3, Figs. 1 and 2).

Table 3.

Parameters and linear regression analysis associated with morning blood pressure surge.

	Univariate analysis		Multivariate analysis
	P	r	P	β
HOMA-IR	.024	0.356	.015	7.484
AMH (ng/mL))	.005	0.438	.003	1.172

R² adjusted = 0.277. Bold values indicate significant P values.

AMH = anti-müllerian hormone, HOMA-IR = Homeostatic Model Assessment Insulin Resistance.

Figure 1.

Scatter plot diagram between morning blood pressure surge and HOMA-IR. HOMA-IR = Homeostatic Model Assessment of Insulin Resistance.

Figure 2.

Scatter plot diagram between morning blood pressure surge and anti-müllerian hormone.

Groups 2 and 3, who have HT were divided into 2 groups according to MBPS: MBPS < 25 mm Hg and MBPS ≥ 25 mm Hg. By comparing the 2 groups, it was discovered that the one with MBPS ≥ 25 mm Hg had considerably higher AMH and HOMA-IR values than the one with MBPS < 25 mm Hg.

A multivariate logistic regression analysis was conducted on the HT patient groups (groups 2 and 3), using parameters that were found to be statistically significant in the univariate analysis for patients with MBPS ≥ 25 mm Hg (P value < .05). In the patient group, the multivariate logistic regression analysis showed that the likelihood of MBPS ≥ 25 mm Hg increased 8.6 times for every 1 unit increase in serum HOMA-IR level (odds ratio: 8.667 confidence interval: 2.771–27.109 P < .001), 23% for every 1 ng/mL increase in serum AMH level (odds ratio: 1.237 confidence interval: 1.018–1.504 P: .033), and 5.7 times for having PCOS (odds ratio: 5.799 confidence interval: 1.055–31.894 P: .043).

Group 3, which consisted of patients diagnosed with PCOS and HT, was split into 2 categories: MBPS < 25 mm Hg and MBPS > 25 mm Hg. By comparing the 2 groups, it was discovered that the one with MBPS > 25 mm Hg had significantly greater levels of AMH and HOMA-IR compared to the one with MBPS < 25 mm Hg (Table 4).

Table 4.

Clinical and laboratory findings of group 3 according to morning blood pressure surge.

Variables	MBPS < 25 n = 16	MBPS ≥25 n = 24	P
Age (year)	28.9 ± 4.49	29.5 ± 4.98	.718
Body mass index (kg/m2)	28.8 ± 9.19	26.7 ± 6.65	.402
Basal heart rate (pulse/minute)	78.2 ± 11.4	78.3 ± 8.78	.971
White blood cell (10³/µL)	6.35 ± 1.56	6.18 ± 1.41	.726
Hemoglobin (g/dL)	13.5 ± 1.79	12.6 ± 1.36	.076
Platelet (10³/µL)	266.8 ± 59.4	278.8 ± 72.8	.588
Glucose (mg/dL)	104.3 ± 14.4	102.0 ± 13.0	.594
Creatinine (mg/dL)	0.58 ± 0.10	0.59 ± 0.07	.619
Sodium (mmol/L)	138.8 ± 1.05	138.9 ± 1.25	.759
Potassium (mmol/L)	4.43 ± 0.33	4.33 ± 0.28	.325
Calcium (mg/dL)	9.65 ± 0.25	9.59 ± 0.41	.617
Aspartate aminotransferase (u/L)	18.2 ± 6.25	21.8 ± 9.02	.170
Alanine aminotransferase (u/L)	20.3 ± 12.1	18.8 ± 7.07	.616
Triglyceride (mg/dL)	115.8 ± 50.0	123.6 ± 87.1	.750
High-density lipoprotein (mg/dL)	52.4 ± 12.5	56.8 ± 15.8	.364
Low-density lipoprotein (mg/dL)	121.9 ± 19.8	124.4 ± 45.4	.841
Thyroid stimulating hormone (mIU/L)	2.02 ± 0.79	2.06 ± 1.24	.913
C-reactive protein (mg/L)	0.23 ± 0.21	0.21 ± 0.13	.687
LH/FSH ratio	1.72 ± 0.69	1.77 ± 0.47	.820
Dehydroepiandrosterone sulfate (IU/mL)	425.8 ± 205.1	363.0 ± 136.5	.292
Total testosterone (pg/mL)	92.6 ± 15.4	92.2 ± 8.33	.930
Anti-müllerian hormone (ng/mL)	6.11 ± 3.28	8.80 ± 4.15	.035
HOMA-IR	2.31 ± 0.40	2.81 ± 0.47	.002

Bold values indicate significant P values.

FSH = follicule stimulating hormone, HOMA-IR = Homeostatic Model Assessment Insulin Resistance, LH = luteinizing hormone.

In order to determine whether PCOS patients had MBPS levels of 25 mm Hg or above, multivariate logistic regression analysis was carried out using parameters that had a P value <.05 and were shown to be statistically significant in the univariate analysis. The likelihood of MBPS ≥ 25 mm Hg increased 10.2 times for every 1 unit increase in serum HOMA-IR level in PCOS patients, as shown in Table 5, according to the multivariate logistic regression analysis.

Table 5.

Multivariate logistic regression analysis for detection of MBPS ≥ 25 mm Hg in patients with pcos (group 3).

Variables	Odds ratio	95% confidence interval	P
HOMA-IR	10.262	1.986–53.036	.005

HOMA-IR = Homeostatic Model Assessment Insulin Resistance, MBPS = morning blood pressure surge, Pcos = polycystic ovary syndrome.

Multivariate logistic regression analysis’s significant parameters were used to conduct ROC analysis. According to Table 6 and Figure 3, when the cutoff value for HOMA-IR was set at 2.28, it was discovered that it was 70.8% sensitive and 68.7% specific in identifying PCOS patients with MBPS ≥ 25 mm Hg.

Table 6.

Roc analysis of HOMA-IR identifying patients with MBPS ≥ 25 mm Hg in patients with pcos (group 3).

Variables	Area under the ROC curve	P	Cutoff	Sensitivity	Specificity
HOMA-IR	0.806 (0.665–0.947)	<.001	2.28	70.8%	68.7%

HOMA-IR = Homeostatic Model Assessment Insulin Resistance, Pcos = polycystic ovary syndrome.

Figure 3.

ROC curve of HOMA-IR level identifying patients with morning blood pressure surge ≥ 25 mm Hg in patients with polycystic ovary syndrome. HOMA-IR = Homeostatic Model Assessment of Insulin Resistance.

4. Discussion

Ovulatory dysfunction, excess androgens, and polycystic ovaries are the hallmarks of PCOS, a prevalent hormonal condition in women who have not yet reached menopause.^[1] The identification and treatment of any metabolic issues that may arise in the following years depends on the early detection and adequate treatment of patients with PCOS. Untreated PCOS has the potential to cause metabolic complications including hyperinsulinemia, glucose intolerance, type 2 diabetes mellitus (DM), dyslipidemia, obesity, HT and CVD in the long run.^[2] Studies have demonstrated that blood AMH levels rise in PCOS patients, suggesting that these levels could soon be used to diagnose PCOS and even indicate its severity.^[6] One way to calculate insulin resistance is using the HOMA-IR formula, although the hyperinsulemic euglycemic clamp test is the gold standard. Insulin resistance is elevated when the HOMA-IR score is more than 2.5. As a result of insulin resistance, dyslipidemia, HT, type 2 DM and CVD are more likely to occur in PCOS individuals. Patients with insulin resistance may have an increased risk of CVD and death in the future, which the HOMA-IR score might help us determine.^[4]

An significant indication of cardiovascular mortality, AMH and HOMA-IR levels have not been shown to be related in any studies involving PCOS and MBPS that we have examined in the literature. Our review of the literature indicates that PCOS and AMH have been the subject of numerous investigations. Nevertheless, the correlation between AMH and MBPS has not been investigated in any research. Biochemical hyperandrogenism, oligomenorrhea, and mean ovarian volume are closely linked to AMH. Thus, AMH has the makings of a biomarker for PCOS, and its application could render ultrasound exams obsolete. A high AMH level is not a diagnostic indicator in and of itself, but it is a good predictor of PCOS and a key measure in assessing the disease’s severity and, by extension, its comorbidities.^[9]

Wiweko et al included 71 non-PCOS subjects and 71 PCOS patients in their study. Patients were categorized into 4 groups based on their PCOS phenotype, and their serum AMH levels were assessed. The PCOS patients in this study were categorized based on their phenotypes, which differs from our study. Because phenotypic 1 polycystic ovary syndrome is so prevalent in our nation, we decided to include it in our study. The study concluded that serum AMH levels can be utilized as a diagnostic and predictive tool, and it also indicated that AMH levels were substantially higher in PCOS women compared to controls. Concurrently, insulin resistance was positively associated with serum AMH levels.^[6] Skalba et al also included 137 women in their study, with 87 of those women being PCOS sufferers and 50 serving as controls. The study’s findings showed that the PCOS group had much greater AMH levels than the control group. The levels of HOMA-IR, testosterone, and AMH were positively correlated with one another. Researchers found a favorable correlation between AMH levels and hyperandrogenism and insulin resistance. It is well-established that hyperandrogenism increases the risk of metabolic syndrome, atherosclerosis, and cardiovascular disease. Taken together, these results suggest that AMH level might be a novel cardiovascular risk factor for PCOS patients.^[10] To further understand how AMH levels relate to hyperandrogenism, lipid profiles, insulin resistance, metabolic syndrome, and CVD, as well as to employ AMH as a diagnostic and prognostic tool for PCOS, additional research is required. The risk of CVD was assessed in our study using MBPS. MBPS, more so than 24-hour mean blood pressure, is a major CVD risk factor. Different cutoffs for MBPS have been used in the studies. We used the value of 25 as a cutoff, which is seen to be a riskier value in terms of cardiovascular diseases in the studies conducted. The group with MBPS ≥ 25 mm Hg had significantly higher AMH levels when we separated PCOS patients into 2 groups: MBPS < 25 mm Hg and MBPS ≥ 25 mm Hg. In addition, we discovered that MBPS was independently correlated with AMH level. We found that AMH is a useful technique for predicting CVD risk.

Kadi H et al included 53 PCOS patients without comorbidities and 42 controls. Patients’ insulin resistance was assessed using the HOMA-IR score. Our study followed the use of ABPM to calculate MBPS. It was determined by subtracting the lowest blood pressure recorded throughout the night from the average blood pressure recorded 2 hours after awakening. Similar to our own findings, the control group and PCOS patients both had higher body mass indexes. Following previous research, this study confirmed that the PCOS group had greater HOMA-IR than the control group. The study found that MBPS was higher in PCOS-afflicted reproductive-aged women compared to non-PCOS-afflicted controls. Furthermore, insulin resistance and PCOS were identified as separate risk factors for elevated MBPS.^[8] Patients diagnosed with PCOS in our study also had HT. Only those diagnosed with HT were included in group 2. A increased MBPS value in HT patients relative to the control group is a predictable result. Despite the fact that all of the patient groups in our study had HT diagnoses, it is noteworthy to note that the group diagnosed with PCOS + HT had a substantially higher MBPS value than the group diagnosed with HT alone. Furthermore, the fact that MBPS independently correlates with AMH and HOMA-IR, and that the group with MBPS ≥ 25 mm Hg had greater levels of AMH and HOMA-IR than the group with MBPS < 25 mm Hg, suggests that disease-related AMH and HOMA-IR values could play a significant role in predicting the risk of CVD. Patients with MBPS ≥ 25 mm Hg were also found to be independently predicted by PCOS status and HOMA-IR score. While this study did show that insulin resistance is associated with MBPS, further research is required to determine the exact reasons of elevated MBPS, including any role that the sympathetic nervous system or the renin–angiotensin–aldosterone system may play.

A total of 81 patients with essential HT were included in the study by Abdel-Khalik MY et al, comprising 43 males and 38 females. ABPM was used to determine MBPS as in our study. Over the course of 36 months, all patients were monitored for any signs of cardiovascular problems. The MBPS was found to be considerably greater in 19 patients (23%) who had a cardiovascular incident during the follow-up period compared to individuals who did not. High MBPS was associated with an increased risk of cardiovascular events, according to this study.^[11] Amedeo et al conducted a related study in which they looked back at the records of 632 people with HT. Mortality from any cause was determined after a median duration of 50 months (46–54 months), and patients were split into 2 groups based on MBPS ≥ 41 mm Hg and MBPS < 41 mm Hg. ABPM was used to determine MBPS as in our study. The difference between the mean blood pressure during the 2 hours after waking and the lowest blood pressure at night was calculated. Our study classified the patient groups into MBPS over 25 mm Hg and below 25 mm Hg, in contrast to this study which divided the patient groups into MBPS ≥ 41 mm Hg (568 patients) and MBPS < 41 mm Hg (64 patients). Every single patient group in our study had HT, just like in this one. There was a statistically significant difference in the patient group with MBPS ≥ 41 mm Hg, and 19 deaths were noted during follow-up in this study by Amedeo et al to sum up, the results showed that MBPS and mortality were significantly different in hypertensive patients. Unfortunately, the study did not specify the patients’ causes of death, hence it cannot be accurately said that patients with high MBPS had an increased risk of death due to CVD. On the other hand, the study’s findings suggest that MBPS increases the risk of CVD by altering the vascular bed, which is why persistent elevation of MBPS is associated with a higher mortality rate.^[12] Our investigation confirmed previous findings that HT patients had considerably increased MBPS compared to the control group. Additionally, we observed a statistically significant increase in MBPS between the PCOS and HT groups and the HT group. Research on PCOS patients reveals elevated MBPS levels, albeit it is restricted in scope. Simultaneously, our study found that there was a statistically significant difference in AMH and HOMA-IR levels between the patient groups with MBPS ≥ 25 mm Hg and those with MBPS < 25 mm Hg. During the linear regression analysis in groups 2 and 3, specifically in the patient group, it was noted that the likelihood of having MBPS ≥ 25 mm Hg increased by 8.6 times for every 1 unit increase in HOMA-IR level and by 23% for every 1 ng/mL increase in serum AMH level. Because MBPS is a predictor of cardiovascular events on its own, and because elevated AMH and HOMA-IR levels promote cardiovascular events through several pathways, our study found that raised MBPS was associated with elevated AMH and HOMA-IR. We found only few research that found an increase in MBPS in PCOS patients, in contrast to the many studies that found an increase in MBPS in HT patients and its association with CVD risk. Because it demonstrates that MBPS is elevated in PCOS patients, our study is highly relevant to this area. Whether all 3 indicators may be utilized as a parameter to diagnose early CVD in PCOS patients is an important question that needs further research. Concurrently, additional research is required to determine the ideal MBPS threshold value, even if studies on CVD risk prediction using MBPS are ongoing.

The purpose of the study by Yoda et al was to examine the function of MBPS in the progression of vascular dysfunction in individuals with type 2 DM and the association between glycemic control and MBPS. Similar to our investigation, ABPM was utilized to ascertain MBPS in individuals with type 2 DM. As a result of the study, HOMA-IR score, HbA1c, and triglyceride levels showed significant and positive correlation with MBPS. This proved beyond a reasonable doubt that insulin resistance and MBPS are related. Establishing a connection between insulin resistance and MBPS is a critical aim of this research.^[13] Like DM type 2, PCOS starts with insulin resistance. We observed an independent association between HOMA-IR level and MBPS in our study. Our results showed that the group with MBPS ≥ 25 mm Hg had a higher HOMA-IR. The likelihood of developing MBPS ≥ 25 mm Hg rose by 10.2 times for every 1 unit increase in serum HOMA-IR level in PCOS individuals. Furthermore, for the PCOS patient group, we observed that HOMA-IR was 70.8% sensitive and 68.7% specific in identifying individuals with MBPS ≥ 25 mm Hg when the cutoff value was 2.28. We found a correlation between HOMA-IR and MBPS in our study; furthermore, HOMA-IR is a cheap and easy way to measure insulin resistance; hence, it could be a useful metric for identifying PCOS patients at risk for cardiovascular disease at an early stage.

5. Limitation

Our research has unique value since it is the first of its kind. Our study has some limitations. Patients with PCOS and HT diagnoses were both included in the research. Without comorbidities, we were unable to assess MBPS in PCOS patients. There has to be more research on MBPS in PCOS patients because there is a lack of it. Research on the correlation between AMH and HOMA-IR levels and other cardiovascular disease indicators in PCOS patients, other from MBPS, is urgently needed. A new study is required to determine the optimal MBPS threshold value; nonetheless, we used 25 mm Hg. We did not use phenotypic criteria to classify PCOS patients in this investigation. Our study had some limitations, such as a small sample size and the fact that it was limited to 1 facility. Our study’s topic necessitates additional multicenter trials with bigger patient numbers.

6. Conclusion

Our study indicated that PCOS patients had high levels of AMH, HOMA-IR score, and MBPS, all of which can be employed as predictive parameters for early diagnosis of CVDs. An additional association between MBPS and AMH and HOMA-IR levels was discovered. Stopping the progression of cardiac diseases and reducing cardiovascular mortality and morbidity can be achieved with early detection and treatment of PCOS and its associated comorbidities. HOMA-IR, an inexpensive and easy way to determine insulin resistance, may be a useful measurement in the early diagnosis of CVD in PCOS patients. It is possible to detect and predict CVDs in PCOS patients in the early stage by measuring AMH and HOMA-IR levels and MBPS.

Acknowledgments

There is no person, institution or company to acknowledge.

Author contributions

Conceptualization: Dilan Damla Ozturk, Huseyin Ali Ozturk, Fatih Necip Arici, Mehmet Can Erisen, Bercem Berent Kaya, Cahit Dincer, Hilmi Erdem Sumbul.

Data curation: Dilan Damla Ozturk, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Irfan Alisan, Cahit Dincer, Hilmi Erdem Sumbul.

Formal analysis: Dilan Damla Ozturk, Huseyin Ali Ozturk, Erdinc Gulumsek, Ahmet Gazi Mustan, Hilmi Erdem Sumbul.

Investigation: Dilan Damla Ozturk, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Mehmet Can Erisen, Bercem Berent Kaya, Irfan Alisan, Cahit Dincer, Ahmet Gazi Mustan.

Methodology: Dilan Damla Ozturk, Huseyin Ali Ozturk, Erdinc Gulumsek, Mehmet Can Erisen, Bercem Berent Kaya, Cahit Dincer, Hilmi Erdem Sumbul.

Project administration: Dilan Damla Ozturk, Huseyin Ali Ozturk, Cahit Dincer, Hilmi Erdem Sumbul.

Resources: Dilan Damla Ozturk, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Irfan Alisan, Cahit Dincer, Ahmet Gazi Mustan, Hilmi Erdem Sumbul.

Software: Dilan Damla Ozturk, Huseyin Ali Ozturk, Erdinc Gulumsek, Ahmet Gazi Mustan.

Supervision: Dilan Damla Ozturk, Erdinc Gulumsek, Mehmet Can Erisen, Bercem Berent Kaya, Cahit Dincer, Ahmet Gazi Mustan, Hilmi Erdem Sumbul.

Validation: Dilan Damla Ozturk, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Mehmet Can Erisen, Bercem Berent Kaya, Irfan Alisan, Cahit Dincer, Ahmet Gazi Mustan, Hilmi Erdem Sumbul.

Visualization: Dilan Damla Ozturk, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Mehmet Can Erisen, Bercem Berent Kaya, Irfan Alisan, Cahit Dincer, Hilmi Erdem Sumbul.

Writing – original draft: Dilan Damla Ozturk, Huseyin Ali Ozturk, Mehmet Can Erisen, Bercem Berent Kaya, Hilmi Erdem Sumbul.

Writing – review & editing: Dilan Damla Ozturk, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Mehmet Can Erisen, Bercem Berent Kaya, Irfan Alisan, Cahit Dincer, Ahmet Gazi Mustan, Hilmi Erdem Sumbul.