Hemodynamic differences between women and men with elevated blood pressure in China: A non-invasive assessment of 45,082 adults using impedance cardiography.

BACKGROUND: Whether there are sex differences in hemodynamic profiles among people with elevated blood pressure is not well understood and could guide personalization of treatment. METHODS AND
RESULTS: We described the clinical and hemodynamic characteristics of adults with elevated blood pressure in China using impedance cardiography. We included 45,082 individuals with elevated blood pressure (defined as systolic blood pressure of ≥130 mmHg or a diastolic blood pressure of ≥80 mmHg), of which 35.2% were women. Overall, women had a higher mean systolic blood pressure than men (139.0 [±15.7] mmHg vs 136.8 [±13.8] mmHg, P<0.001), but a lower mean diastolic blood pressure (82.6 [±9.0] mmHg vs 85.6 [±8.9] mmHg, P<0.001). After adjusting for age, region, and body mass index, women <50 years old had lower systemic vascular resistance index (beta-coefficient [β] -31.7; 95% CI: -51.2, -12.2) and higher cardiac index (β 0.07; 95% CI: 0.04, 0.09) than men of their same age group, whereas among those ≥50 years old women had higher systemic vascular resistance index (β 120.4; 95% CI: 102.4, 138.5) but lower cardiac index (β -0.15; 95% CI: -0.16, -0.13). Results were consistent with a propensity score matching sensitivity analysis, although the magnitude of the SVRI difference was lower and non-significant. However, there was substantial overlap between women and men in the distribution plots of these variables, with overlapping areas ranging from 78% to 88%.
CONCLUSIONS: Our findings indicate that there are sex differences in hypertension phenotype, but that sex alone is insufficient to infer an individual's profile.

Introduction

Mean arterial pressure is determined by cardiac output (CO) and systemic vascular resistance (SVR), and there are important sex-specific differences in its regulation and the risk of developing hypertension [1-4]. Recent studies [5-7] have shown that, on average, women with hypertension have a higher SVR and a lower CO when compared with men. Such observations suggest that sex could serve as a proxy for the underlying hemodynamic phenotype among individuals with elevated blood pressure. Considering that tailoring antihypertensive treatment based on individuals’ hemodynamic profile may be associated with better blood pressure control [8-11], these sex differences on hemodynamic phenotypes could help to identify more personalized therapeutic approaches. However, current hypertension guidelines have no sex-specific recommendations on therapy–other than in pregnancy–due to a lack of evidence of benefit from sex-stratified therapies [12,13].

Most of the studies addressing these underlying hemodynamic sex differences have had small samples or focused exclusively on younger individuals [5,6], which limits the generalizability of their findings to a broader population that includes the elderly, among whom the hypertension burden is greater [14-16]. Particularly, after menopause, women experience a sharp increase in hypertension prevalence [17-19], eventually surpassing aged-matched men [20]. Thus, assessing the sex-specific differences in hemodynamic profiles across age groups can provide a better understanding on whether there are substantial hemodynamic differences by sex that could be used to guide therapy.

Accordingly, we used data from tens of thousands of individuals with elevated blood pressure from an outpatient setting in China to evaluate the overall patterns of sex differences in hemodynamic variables and to determine how these sex hemodynamic differences may vary with age. We also aimed to evaluate the distribution of these variables among women and men, and to what extent they overlap by sex. Furthermore, we stratified our analysis at the mean age of menopause in China because of its association with hemodynamic changes. Results from this study can advance our understanding of the association of sex with hemodynamic patterns in people with hypertension and suggest if sex could be used to guide therapy.

Methods

Data source

iKang Health Group provided the de-identified data used in this study to SJTU-Yale Joint Center for Biostatistics in Shanghai, China. This is where all data are stored and all analyses were performed. There are recent strict legal restrictions in publicly sharing data from China outside of its borders (see Personal Information Protection Law, November 2021). Requests can be sent to iKang Health at zhaohui.wang@ikang.com for consideration to share data in a legally compliant manner. The code used to analyze the data is publicly available at https://www.doi.org/10.5281/zenodo.5931975.

Study population

Between January 2012 and October 2018, 116,851 individuals (65,172 men and 51,679 women) underwent an impedance cardiography (ICG) test offered as part of the employee routine annual physical examination at 51 sites of iKang Health Checkup Centers throughout China. We excluded those younger than 20 years and those older than 80 years (n = 839). Then, we excluded 1,814 individuals with outlier values of weight, height, blood pressure, heart rate, stroke volume, and baseline thoracic impedance (). Of the 114,198 remaining individuals, we included 45,082 with elevated blood pressure, which was defined as a systolic blood pressure (SBP) of ≥130 mmHg or a diastolic blood pressure (DBP) of ≥80 mmHg, consistent with the 2017 American College of Cardiology/American Heart Association hypertension guidelines [12].

Study population flowchart.

Abbreviations: ICG, impedance cardiography; DBP, diastolic blood pressure; SBP, systolic blood pressure; SV, stroke volume; HR, heart rate; Z0, baseline impedance.

Data collection

At health centers, nurses collected information on the patient’s age, sex, geographical region, weight, height, SBP, and DBP. Weight was measured using a calibrated and standardized scale, rounded to the nearest 0.1 kg. Height was measured to the nearest 0.1 cm using a portable stadiometer (Omron HNJ-318; Omron Corporation, Kyoto, Japan) with patients standing without shoes and heels against the wall. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. After 5 minutes of resting in a seated position, blood pressure was measured once using an automated monitor (Omron HBP-9020; Omron Corporation, Kyoto, Japan) on the right arm.

Patients were then requested to lay supine and, after 3 minutes in this position, all hemodynamic parameters were measured using ICG. The ICG method that has been validated against invasive techniques for estimation of stroke volume and CO in both stable and high-risk populations [21-23], and has been shown to be a highly reproducible technique [24]. By applying a constant, low amplitude, high-frequency, alternating electrical current to the thorax, ICG device measures the corresponding voltage to detect beat-to-beat changes in thoracic electrical resistance, known as impedance, and with it stroke volume is estimated [25,26]. Then, using heart rate, mean arterial blood pressure, and BMI, other hemodynamic parameters are calculated, including CO, cardiac index (CI), SVR, and systemic vascular resistance index (SVRI) [27]. The ICG device used (CHM T3002/P3005, designed by Beijing Li-Heng Medical Technologies, Ltd, manufactured by Shandong Baolihao Medical Appliances, Ltd.) was developed based on improved hardware and advanced digital filtering algorithms [28], and has been validated versus both invasive thermodilution and non-invasive echocardiography in different settings [29-31].

Variable definitions

We described demographic characteristics and hemodynamic parameters of blood pressure in women and men overall and by age. Considering that the mean age of natural menopause in China is reported as approximately 50 years of age [32-34], we stratified our study population as <50 years old and ≥50 years old. We used the World Health Organization recommended cutoff values for BMI classification in Asian populations, defining underweight as <18.5 kg/m2, normal weight from 18.5 kg/m2 to <23 kg/m2, overweight from 23 kg/m2 to <27.5 kg/m2, and obesity as ≥27.5 kg/m2 [35]. We defined a predominantly vascular hypertension phenotype as high SVRI (>2400 dynes·sec·cm-5·m2) with a low or normal CI (<2.5 L/min/m2 or 2.5–4 L/min/m2, respectively), and predominantly cardiac hypertension phenotype as high CI (>4 L/min/m2) with low or normal SVRI (<2000 dynes·sec·cm-5·m2 or 2000–2400 dynes·sec·cm-5·m2, respectively) [11,36,37].

Statistical analysis

We calculated means with standard deviations (SD) for continuous variables and frequencies for categorical variables, and assessed for the significance of the inter-group differences using ANOVA and Chi-square test (with Yates’ correction), respectively. Next, the relationship between these parameters and age, BMI and SBP was evaluated using least squares method (LMS) curves [38]. To assess the association of sex with CO, CI, SVR, and SVRI we used unadjusted and sequential adjusted linear regression models and reported the female sex beta coefficient and its respective 95% confidence interval (95% CI) for the entire study population, among those <50 years old, and among those ≥50 years old. The sequential adjusted models were built as follows: adjusted model 1 included age and region; model 2 included variables from model 1 plus BMI. Finally, we used density plots to characterize the distribution of the hemodynamic parameters by sex across the different strata, estimating the percentage of the plot area that overlaps between women and men on each stratum. To account for potential residual confounding, we performed a nearest neighbor propensity score matching sensitivity analysis, using region, age, SBP, DBP, and BMI. Propensity score generation and 1:1 match for samples between men and women groups were performed using the MatchIt package in R [39]. For reproducibility and comparison with prior studies, and aligned with Chinese hypertension guidelines cutoff blood pressure values [40], we also performed a sensitivity analysis replicating these analyses on a subpopulation of individuals with SBP ≥140 mmHg or DBP ≥90 mmHg.

All statistical analyses were conducted using R, version 3.6.2 (The R Foundation for Statistical Computing). Statistical significance was defined as a 2-tailed P<0.05. Coauthors JG, HZ, and ZJM take responsibility for the analysis.

Ethics statement

This project received an exemption from review from the Institutional Review Board at Yale School of Medicine and at Shanghai Jiao Tong University College of Biotechnology as we used de-identified data provided by the iKang Health group. Given that the de-identified data were provided by a third party, we did not need to collect consent for participation.

Results

Age, body mass index, and hemodynamic variables and phenotypes by sex

We included 45,082 individuals with elevated blood pressure, of which 15,888 (35.2%) were women. Overall, women had a higher mean age than men (54.5 [±11.8] years vs 48.0 [±13.0] years, P<0.001) and were less likely to be obese (17.2% vs 23.5%, P<0.001) (Table 1). Women had a higher mean SBP than men (139.0 [±15.7] mmHg vs 136.8 [±13.8] mmHg, respectively, P<0.001), but a lower mean DBP (82.6 [±9.0] mmHg vs 85.6 [±8.9] mmHg, P< 0.001). Among those <50 years of age, women had lower mean SBP and DBP compared with men of the same age group (P<0.001 for each), whereas among those older than 50 years they had higher mean SBP and lower mean DBP than men (P<0.001 for each) ().

Table 1

Sex differences in clinical and hemodynamic variables by age group among adults with elevated blood pressure.

	All			<50 years old			≥50 years old
	WomenN = 15,888	MenN = 29194	P value	WomenN = 4,384	MenN = 15,512	P value	WomenN = 11,504	MenN = 13,682	P value
Age (years)	54.5 (11.8)	48.0 (13.0)	<0.001	39.3 (8.1)	38.0 (7.3)	<0.001	60.2 (6.9)	59.5 (7.2)	<0.001
BMI (kg/m2)	24.4 (3.5)	25.5 (3.2)	<0.001	23.5 (3.7)	25.7 (3.4)	<0.001	24.8 (3.3)	25.2 (3.0)	<0.001
Obesity*	2733 (17.2%)	6858 (23.49%)	<0.001	585 (13.34%)	4057 (26.15%)	<0.001	2148 (18.67%)	2801 (20.47%)	<0.001
Region			<0.001			<0.001			<0.001
East	5965 (37.54%)	13275 (45.47%)		1956 (20.86%)	7419 (79.14%)		4009 (40.64%)	5856 (59.36%)
North	3665 (23.07%)	4156 (14.24%)		779 (29.59%)	1854 (70.41%)		2886 (55.63%)	2302 (44.37%)
South	2737 (17.23%)	4317 (14.79%)		686 (22.66%)	2341 (77.34%)		2051 (50.93%)	1976 (49.07%)
Southwest	3521 (22.16%)	7446 (25.51%)		963 (19.81%)	3898 (80.19%)		2558 (41.89%)	3548 (58.11%)
Blood pressure (mmHg)
Systolic	139.0 (15.7)	136.7 (13.8)	<0.001	131.2 (13.2)	133.7 (12.2)	<0.001	142.0 (15.6)	140.1 (14.8)	<0.001
Diastolic	82.6 (9.00)	85.6 (8.9)	<0.001	83.3 (7.9)	85.3 (8.9)	<0.001	82.4 (9.4)	86.01 (9.0)	<0.001
Hypertension phenotype
Predominantly cardiac†	2559 (16.11%)	5185 (17.76%)	<0.001	1382 (31.52%)	3495 (22.53%)	<0.001	1177 (10.23%)	1690 (12.35%)	<0.001
Predominantly vascular‡	9780 (61.56%)	16396 (56.16%)	<0.001	1666 (38.00%)	7197 (46.40%)	<0.001	8114 (70.53%)	9199 (67.23%)	<0.001
Low/normal CI & low/normal SVRI	3531 (22.22)%	7548 (25.86%)	<0.001	1,330 (30.34%)	4,790(30.88%)	0.50	2,201 (19.13%)	2,758 (20.16%)	0.04
High CI & high SVRI	18 (0.11%)	65 (0.22%)	0.01	6 (0.14%)	30 (0.19%)	0.56	12 (0.10%)	35 (0.26%)	0.01
ICG parameters
Heart rate (bpm)	69.4 (11.4)	69.5 (11.3)	0.63	72.6 (11.9)	70.8 (11.1)	<0.001	68.2 (10.9)	68.0 (11.3)	0.15
Stroke volume (mL)	72.9 (18.6)	88.8 (21.5)	<0.001	80.0 (18.8)	93.0 (21.6)	<0.001	70.2 (17.7)	84.0 (20.5)	<0.001
CO (L/min)	5.0 (1.4)	6.1 (1.5)	<0.001	5.8 (1.4)	6.5 (1.4)	<0.001	4.7 (1.2)	5.6 (1.4)	<0.001
CI (L/min/m2)	3.2 (0.8)	3.3 (0.8)	<0.001	3.6 (0.9)	3.5 (0.7)	<0.001	3.0 (0.8)	3.2 (0.7)	<0.001
SVR (dynes·sec·cm-5)	1744 (523)	1433 (389)	<0.001	1471 (411)	1315 (324)	<0.001	1848 (524)	1565 (412)	<0.001
SVRI (dynes·sec·cm-5·m2)	2734.1 (809.9)	2596.3 (677.2)	<0.001	2326.0 (658.0)	2435.1 (598.6)	<0.001	2889.6 (808.3)	2779.2 (713.8)	<0.001

Data are presented as mean (SD) for continuous variables and n (%) for categorical variables.

* Obesity was defined as BMI ≥27.5 kg/m2.

† A predominantly cardiac hypertension phenotype was determined by high CI with low or normal SVRI.

‡ Predominantly vascular hypertension phenotype was determined by low or normal CI with high SVRI.

Abbreviations: SD = Standard Deviation, BMI = Body Mass Index, ICG = Impedance Cardiography, SVR = Systemic Vascular Resistance, SVRI = Systemic Vascular Resistance Index, CO = Cardiac Output, CI = Cardiac Index.

Overall, women had lower mean CO and CI and higher mean SVR and SVRI than men (P<0.001 for all). When stratified by age, women <50 years old had a higher mean CI and a lower mean SVRI than men (P< 0.001 for both), whereas, among those older than 50 years, women had a lower mean CI (P< 0.001) and a higher mean SVRI (P<0.001) (). Also, compared with men, women were more likely to have predominantly vascular hemodynamic hypertension phenotype (61.6% vs 56.2%, P<0.001) but only slightly less likely to have a predominantly cardiac phenotype (16.11% vs 17.8%, P<0.001). Compared with men of the same age, women <50 years old were less likely to have a predominantly vascular phenotype and more likely to have a predominantly cardiac phenotype (38% vs 46.4% and 31.5% vs 22.5%, respectively, P<0.001 for each comparison). Women older than 50 years, on the other hand, compared with men of the same age group, were more likely to have a predominantly vascular phenotype (70.5% vs 67.2%, P<0.001) and less likely to have a predominantly cardiac phenotype (10.2% vs 12.4%, P<0.001) (). Similar results were found in the sensitivity analysis among those with SBP ≥140 mmHg or DBP ≥90 mmHg, although in this subpopulation there was no significant difference in the mean CI and SVRI between men and women <50 years ().

Relationship of hemodynamic variables and age among women and men

Plots of median CO, CI, SVR, and SVRI with age are presented in . With age, median CO decreased for both sexes, being consistently lower among women (). Although median CI also decreased with age for both sexes, it was higher in women before age 50 than men of the same age, becoming similar afterwards (. On the other hand, SVR increased with age in both sexes, being consistently higher among women (). Although SVRI increased in both groups, it was lower among women compared with men among individuals <50 years old, having a steeper increase with age among young women and becoming similar between the 2 groups among individuals ≥50 years of age (. These results were consistent with those observed when analyzing individuals with SBP ≥140 mmHg or ≥90 mmHg only ().

Median Cardiac Output (A), Cardiac Index (B), Systemic Vascular Resistance (C), and Systemic Vascular Resistance Index (D) by Age Among Women and Men with Elevated Blood Pressure. Solid lines represent the median. Dashed lines represent the 25th and 75th percentile. Abbreviations: CO, cardiac output; CI, cardiac index; SVR, systemic vascular resistance; SVRI, systemic vascular resistance index.

Multivariable linear regression and propensity score matching sensitivity analysis

Unadjusted and sequentially-adjusted female sex beta coefficients (β) for CO, CI, SVR, and SVRI are presented in After adjusting for age, BMI, and region, female sex was associated with lower cardiac output overall (β = -0.78 [95% CI: -0.8, -0.75]), among those <50 years old (β = -0.59 [95% CI: -0.64, -0.54]), and among those ≥50 years old (β = -0.86 [95% CI: -0.89, -0.83]). However, female sex was positively associated with CI only among those <50 years (β = 0.07 [95% CI: 0.04, 0.09]), having a negative association overall (β = -0.08 [95% CI: -0.09, -0.06]) and among those ≥50 years of age (β = -0.15 [95% CI: -0.16, -0.13]). On the other hand, female sex was associated with higher SVR overall (β = 229 [95% CI: 221, 238]), among those <50 years (β = 140 [95% CI: 128, 151]), and among those ≥50 years of age (β = 274 [95% CI: 262, 285]). Lastly, female sex had a negative association with SVRI only among those <50 years old (β = -31.7 [95% CI: -51.2, -12.2]), having a positive association among those >50 years of age (β = 120.4 [95% CI: 102.4, 138.5]) and among the entire study population (β = 73.5 [95% CI: 60.3, 86.8]). The direction and magnitude of these findings were mostly consistent with the ones from the adjusted model that did not include BMI ().

These hemodynamic differences remained in the propensity score matching sensitivity analysis () and in the sensitivity analysis among those with SBP ≥140 mmHg or DBP ≥90 mmHg (), although the magnitude of the SVRI difference among those younger than 50 years was not significant.

Hemodynamic variables distribution overlap between women and men

Density plots of CO and CI, by sex and age are shown in Overall, the CO showed a distribution overlap of 52.1% between women’s and men’s density plots (). Among those younger than 50 years, women’s CO distribution was slightly shifted to the left compared to men’s, with a 65.4% overlap between sexes (). On the other hand, among those older than 50 years, CO distribution among women had higher kurtosis and was shifted to the left when compared with men, with an overlap between sexes of 55.6% (). The indexed variable (CI) distribution showed a greater overlap between sexes, reaching 79.6% overall, 80.8% among those <50 years old, and 82.6% among those ≥50 years old (, respectively).

Cardiac Output (A, B, and C) and Cardiac Index (D, E, and F) Density Plots Overlap Between Women And Men with Elevated Blood Pressure by Age Category. Abbreviations: CO, cardiac output; CI, cardiac index; OA, overlapping area.

Density plots of SVR and SVRI by sex and age are shown in Distribution of SVR showed an overlap between men and women of 56.7%, with women’s density plot having lower kurtosis and shifted to the right compared with men’s (). Among those <50 years old, women’s SVR distribution had less kurtosis and was slightly shifted to the right compared with men’s, with an overlap between sexes of 72.1% (). On the other hand, among those ≥50 years old, women’s SVR distribution was shifted to the right compared with men’s, with an overlap of 61.4% between the 2 groups (). The indexed variable (SVRI), also increased in overlap between both sexes, reaching 82.4%, 78.3%, and 87.7% among the entire study population, among those <50 years old, and among those ≥50 years old, respectively (, respectively).

Systemic Vascular Resistance (A, B, and C), and Systemic Vascular Resistance Index (D, E, and F) Density Plots Overlap Between Women And Men with Elevated Blood Pressure by Age Category. Abbreviations: SVR, systemic vascular resistance; SVRI, systemic vascular resistance index; OA, overlapping area.

When analyzing only those with SBP ≥140 mmHg or DBP ≥90 mmHg, the overlapping areas of the distribution of CO, CI, SVR, and SVRI were highly consistent with the ones from our main analysis ().

Discussion

In our study, we investigated sex differences in hemodynamic variables, mainly CI and SVRI, among adults presenting with elevated blood pressure. We found that, on average, young women have higher mean CI and lower SVRI than age-matched men, although the magnitude of the SVRI difference was significantly reduced when accounting for confounders. Notably, we also found that these hemodynamic differences between sexes were reversed among those older than 50 years of age, the mean age of menopause in China [34], with women having lower mean CI and higher mean SVRI than men. Nonetheless, a key finding of our study was that, despite these overall differences, there is substantial hemodynamic heterogeneity within individuals of the same sex and age: the overlapping area of the distribution plots of CI and SVRI ranged from nearly 80% among those younger than 50 years to nearly 90% among those older than 50 years.

Our results expand the existing knowledge in 2 major ways. First, while most studies have been performed on small samples or among young individuals [5-7], our study allowed us to describe the hemodynamic sex differences in a much larger sample of individuals with elevated blood pressure, including older individuals. To the best of our knowledge this is the largest study that has compared hemodynamic variables and phenotypes between women and men across different age groups. Doing so is instrumental in these studies because of the cardiovascular risk changes associated with menopause [18,19,34,41]. Second, our study is the first to estimate the full distribution of hemodynamic parameters by sex, rather than being limited to comparing the average values. This approach allowed us to describe for the first time that–besides significant average differences–sex is not a reliable indicator of the individual hemodynamic phenotype, particularly among those older than 50 years old where the distributions of CI and SVRI among women and men were almost identical.

Despite the geographical, sample size, and inclusion criteria differences, our results complement and are consistent with the findings from other studies in non-Asian populations [5-7] in which the authors found that, among hypertensive individuals, men had a higher CO and lower SVR than women. However, considering the well-known body composition differences between men and women [42], we analyzed the hypertension phenotype using the body surface area adjusted values (CI and SVRI) and stratified by age, increasing the comparability of these variables between sexes, consistent with our previous studies [43,44]. We found thatdespite the differences in mean CO and SVR, among those <50 years old hypertensive women were more likely to have a predominantly cardiac phenotype (high CI with normal/low SVRI) and less likely to have a predominantly vascular phenotype (high SVRI with normal/low CI) compared with men of the same age. Interestingly, among those older than 50 years, women were more likely to present a predominantly vascular phenotype than men. One plausible explanation for such an observation is that, along with hormonal and environmental factors [19], young women have a blunted alpha-adrenergic vasoconstriction response because of an increased beta-adrenergic vasodilatation [45] that disappears after menopause and that is absent in men [46]. This, however, does not fully explain the association between sex and blood pressure: compared with men, women have a steeper increase in SBP thorough life, even decades before menopause [47]. Altogether, such findings might suggest that the underlying mechanisms of elevated blood pressure might differ by sex, particularly among young individuals. The therapeutically implications of these sex differences are limited because of the high same-sex heterogeneity in these parameters that we observed. Beyond its potential implications for treatment adjustment or initiation [8-10], understanding if these differences in hypertension phenotypes are implicated in the known sex differences in terms of risk of subsequent cardiovascular outcomes [48] is still uncertain and deserves further investigation. Furthermore, there is also a need for longitudinal studies that help us to understand how chronic exposure to different hypertension phenotypes is associated with clinical outcomes, and if there are sex-differences in such associations.

Our study also has important implications for personalizing the care of patients presenting to an outpatient clinic with elevated blood pressure. As hypertension remains as one of the biggest public health challenges worldwide [49], there is urgency in determining possible ways of improving its treatment efficacy by using personalized therapies tailored to each patient’s characteristics. Although we and other studies have shown that, on average, there are significant hemodynamic differences by sex, we also found that there is substantial same-sex heterogeneity in the hemodynamic profile. Notably, as hypertension prevalence and arterial stiffening increases among women after menopause [15,18,50], the distribution of CI and SVRI among those older than 50 years was almost the same between women and men. Thus, our study indicates that sex alone is not a good proxy of the underlying hemodynamic patterns of patients with elevated blood pressure and should not be used clinically to assume the hypertension phenotype. Instead, it is necessary to measure these parameters directly if information about the hemodynamic profile is considered necessary to guide the antihypertensive therapy.

Limitations

The results from our study should be interpreted in light of the following limitations. First, our findings only represent a snapshot of an individual’s hemodynamic status, preventing us from assessing longitudinal clinical outcomes and pathologic adaptations that may occur with long-term exposure to a particular hypertension phenotype, including structural and physiological changes in heart and vessels [51,52].

Second, although we had highly detailed hemodynamic information of each individual, the sociodemographic and clinical information (including comorbidities that may affect hemodynamic status) available to our analyses was limited. Of great importance is the lack of information regarding current antihypertensive medications usage, which could alter the hemodynamic phenotype and inclusion criteria (e.g. beta-blockers lowering CO or a patient with controlled hypertension not being included). However, studies have shown that hypertension treatment and blood pressure control rates are low in China [53-55], though they are higher among women than in men, suggesting that the majority of the patients in our study would be untreated and that most individuals with hypertension would have been included. Nonetheless, our results represent participants’ hemodynamic status at the time of examination in an outpatient clinic, regardless of their medications, which could help guide the treatment initiation or adjustment based on the underlying hemodynamic derangement among patients with uncontrolled blood pressure. Additionally, although menopause is a key determinant of blood pressure regulation, we did not have this self-reported event from our participants. However, for our analysis we used the average age of menopause in China and the results were consistent with this hemodynamic shift among women around age 50 years. Lastly, we did not have information on participants’ smoking status or smoking history, factors associated with hypertension and increased arterial stiffness, although the latter is less certain [56,57]. Smoking is one of the major public health challenges among Chinese men, with a prevalence of nearly 1 in 2 among them and only around 2% among women [58,59]. The impact of smoking on the hypertension phenotype and if such an association is modified by sex remains to be studied in detail.

Third, a single BP measurement was recorded per participant, which could have affected the precision in this variable. However, all study centers followed the same standardized protocol for men and women, as described in the Methods section, to reduce inter-observer variability. Moreover, such a compromise in precision would most likely shift the observed sex differences towards the null rather than towards significance.

Fourth, although we performed a robust main analysis, which included adjustment for multiple confounders, and a sensitivity analysis that used propensity score matching, we cannot rule out that the differences observed between men and women were due to residual confounding.

Conclusions

Women and men with elevated blood pressure in China have differences in the average values of the hemodynamic determinants of blood pressure. However, the magnitude of such differences is significantly reduced with age and there is substantial overlap in the distribution of the hemodynamic variables. This indicates that sex alone is insufficient to infer the underlying hypertension phenotype.

Median cardiac output, cardiac index, systemic vascular resistance, and systemic vascular resistance index by age among women and men with systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg.

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Cardiac output and cardiac index density plots overlap between women and men with systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg, by age category.

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Systemic vascular resistance and systemic vascular resistance index density plots overlap between women and men with systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg, by age category.

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Sex differences in clinical and hemodynamic variables by age group among adults with systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg.

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Sex differences in clinical and hemodynamic variables by nearest neighbor propensity score matched subgroups.

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Unadjusted and sequentially-adjusted association of female sex with cardiac output, cardiac index, systemic vascular resistance, and systemic vascular resistance index, overall and by age categories among adults with systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg, by age category.

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6 Jan 2022

Hemodynamic Differences Between Women and Men with Elevated Blood Pressure in China

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Reviewer #1: Partly

Reviewer #2: Partly

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Reviewer #1: Yes

Reviewer #2: N/A

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Reviewer #1: No

Reviewer #2: No

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Reviewer #2: No

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5. Review Comments to the Author

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Reviewer #1: We have made a review for manuscript number: PONE-D-21-16564, entitled;

Hemodynamic Differences Between Women and Men with Elevated Blood Pressure in China. We have some important comments:

1- It should be clear in the title and abstract that the topic is about non invasive hemodynamic data assessment.

2- A flow chart is needed.

3- Thd authors should give strong reason of why there is a restriction on the availability of data.

4- In the methodology, the diagnosis of elevated blood pressure relies only on single blood pressure measurement. This is the major concern of the current analysis. Single measurement by automated device is not enough to classify patients regarding their blood pressure level. This point should be properly discussed and defended.

5- The authors should justify the use of ICG, the authors should mention the guidelines recommendations or FDA or international medical institutes that approve the use of ICG for such purposes.

6- In the results, there was significant difference in the age of women versus men (i.e., 54 vs 45, p <0.001). This significant difference still presents after subgroups analysis of <50 yr or > 50 yr (i.e., p<0.001). This important point should be defended and discuss as significant differences in age would be important confounder and obtaining reliable results needs proper adjustment of the analysis in regard to age.

7- The current manuscript does not have data regarding long term follow up to see if the current hemodynamic differences have clinical impact on long term prognosis or not. This point should be properly defended.

8- The clinical implications of the current study should be clear and practical.

Regards

Reviewer #2: -The cofounders missing some important factors as presence of diabetes , the types of hypertension ,the risk factors as dyslipidemia and the existence of chronic kidney disease .all these factors can contribute in risk stratification and further management of hypertension.

-the age 50 is not clear as not standard for old age as WHO recommendations.

- in table 1 what is meant by predominantly cardiac

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Reviewer #1: Yes: Rami Riziq Yousef Abumuaileq

Reviewer #2: No

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12 Apr 2022

Response To Reviewers

PONE-D-21-16564: Hemodynamic Differences Between Women and Men with Elevated Blood Pressure in China

We appreciate the academic editor’s and reviewers’ comments, which have helped us to improve our manuscript. We have responded to each comment (reproduced in bold) and detailed our changes to the manuscript. In this document, quoted text is presented indented and new additions (or relevant text when specified) underlined. The page and line numbers that we reference below are based on the clean version of our revised manuscript. New references are listed at the end of each response. We first addressed the academic editor’s comments and then each of the two reviewers.

ACADEMIC EDITOR

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Response: We have reviewed the style requirements and made the necessary adjustments.

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Response: Thank you. We modified our funding statement, as shown below (underlined text is new):

Source of funding:

The authors received no specific funding for this work.

3. Thank you for stating the following in the Competing Interests section:

"Yuan Lu is supported by the National Heart, Lung, and Blood Institute (K12HL138037) and the Yale Center for Implementation Science. She was a recipient of a research agreement, through Yale University, from the Shenzhen Center for Health Information for work to advance intelligent disease prevention and health promotion. Erica S. Spatz receives support from the Food and Drug Administration to support projects within the Yale-Mayo Clinic Center of Excellence in Regulatory Science and Innovation (CERSI); the National Institute on Minority Health and Health Disparities (U54MD010711-01) to study precision-based approaches to diagnosing and preventing hypertension; and the National Institute of Biomedical Imaging and Bioengineering (R01EB028106-01) to study a cuff-less blood pressure device. Xin Zheng is supported by the CAMS Innovation Fund for Medical Science (2016-I2M-1-006), the National Key Research and Development Program (2016YFE0103800) from the Ministry of Science and Technology of China. Hui Lu is supported by the National Key R&D Program of China (2018YFC0910500) and Neil Shen’s SJTU Medical Research Fund. Zheng J. Ma is affiliated with Beijing Li-Heng Medical Technologies, Ltd, which designed the ICG device used in this study. Harlan Krumholz works under contract with the Centers for Medicare & Medicaid Services to support quality measurement programs; was a recipient of a research grant, through Yale, from Medtronic and the U.S. Food and Drug Administration to develop methods for post-market surveillance of medical devices; was a recipient of a research grant with Medtronic and is the recipient of a research grant from Johnson & Johnson, through Yale University, to support clinical trial data sharing; was a recipient of a research agreement, through Yale University, from the Shenzhen Center for Health Information for work to advance intelligent disease prevention and health promotion; collaborates with the National Center for Cardiovascular Diseases in Beijing; receives payment from the Arnold & Porter Law Firm for work related to the Sanofi clopidogrel litigation, from the Ben C. Martin Law Firm for work related to the Cook IVC filter litigation, and from the Siegfried and Jensen Law Firm for work related to Vioxx litigation; chairs a Cardiac Scientific Advisory Board for UnitedHealth; was a participant/participant representative of the IBM Watson Health Life Sciences Board; is a member of the Advisory Board for Element Science, the Advisory Board for Facebook, and the Physician Advisory Board for Aetna; and is the founder of HugoHealth, a personal health information platform, and co-founder of Refactor Health, an enterprise healthcare AI-augmented data management company. The other co-authors report no potential competing interests."

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests). If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

Response: We reviewed the guide for authors and confirm that such competing interests do not alter our adherence to PLOS ONE policies on sharing data and materials. The revised disclosure now reads as below (underlined text is new):

DISCLOSURES

Yuan Lu is supported by the National Heart, Lung, and Blood Institute (K12HL138037) and the Yale Center for Implementation Science. Erica S. Spatz receives support from the Food and Drug Administration to support projects within the Yale-Mayo Clinic Center of Excellence in Regulatory Science and Innovation (CERSI); the National Institute on Minority Health and Health Disparities (U54MD010711-01) to study precision-based approaches to diagnosing and preventing hypertension; and the National Institute of Biomedical Imaging and Bioengineering (R01EB028106-01) to study a cuff-less blood pressure device. Xin Zheng is supported by the CAMS Innovation Fund for Medical Science (2016-I2M-1-006) and the National Key Research and Development Program (2016YFE0103800) from the Ministry of Science and Technology of China. Hui Lu is supported by the National Key R&D Program of China (2018YFC0910500) and Neil Shen’s SJTU Medical Research Fund. Zheng J. Ma is affiliated with Beijing Li-Heng Medical Technologies, Ltd, which designed the ICG device used in this study. This affiliation did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. In the past three years, Harlan Krumholz received expenses and/or personal fees from UnitedHealth, Element Science, Aetna, Reality Labs, Tesseract/4Catalyst, F-Prime, the Siegfried and Jensen Law Firm, Arnold and Porter Law Firm, and Martin/Baughman Law Firm. He is a co-founder of Refactor Health and HugoHealth, and is associated with contracts, through Yale New Haven Hospital, from the Centers for Medicare & Medicaid Services and through Yale University from Johnson & Johnson. Such competing interests do not alter our adherence to PLOS ONE policies on sharing data and materials. The other co-authors report no potential competing interests.

4. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For more information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

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We will update your Data Availability statement on your behalf to reflect the information you provide.

Response: We updated the data availability statement as shown below after discussion with, and guidance from, the PLOS One editorial office.

iKang Health Group provided the de-identified data used in this study to SJTU-Yale Joint Center for Biostatistics in Shanghai, China. This is where all data are stored and all analyses were performed. There are recent strict legal restrictions in publicly sharing data from China outside of its borders (see Personal Information Protection Law, November 2021). Requests can be sent to iKang Health at zhaohui.wang@ikang.com for consideration to share data in a legally compliant manner.

5. Please note that in order to use the direct billing option the corresponding author must be affiliated with the chosen institute. Please either amend your manuscript to change the affiliation or corresponding author, or email us at plosone@plos.org with a request to remove this option.

Response: We confirm that the corresponding author, Harlan M. Krumholz, is affiliated with Yale University with whom PLOS ONE has the direct billing option. We edited his affiliations in the title page.

6. Thank you for stating the following in the Financial Disclosure section: "This study was self-funded."

We note that one or more of the authors are employed by a commercial company: "iKang Healthcare Group, Inc., Shanghai, China and Beijing Li-Heng Medical Technologies, Ltd, Beijing, China.

a. Please provide an amended Funding Statement declaring this commercial affiliation, as well as a statement regarding the Role of Funders in your study. If the funding organization did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of authors' salaries and/or research materials, please review your statements relating to the author contributions, and ensure you have specifically and accurately indicated the role(s) that these authors had in your study. You can update author roles in the Author Contributions section of the online submission form.

Please also include the following statement within your amended Funding Statement.

“The funder provided support in the form of salaries for authors [insert relevant initials], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.”

If your commercial affiliation did play a role in your study, please state and explain this role within your updated Funding Statement.

b. Please also provide an updated Competing Interests Statement declaring this commercial affiliation along with any other relevant declarations relating to employment, consultancy, patents, products in development, or marketed products, etc.

Within your Competing Interests Statement, please confirm that this commercial affiliation does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests) . If this adherence statement is not accurate and there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include both an updated Funding Statement and Competing Interests Statement in your cover letter. We will change the online submission form on your behalf.

Response: We confirm that such affiliation did not have any role in the study design, data collection, data analysis, manuscript preparation, or decision to publish, nor was any author compensated for this project in any way.

The revised and updated disclosures are detailed in Comment 3 above.

7. Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as well.

Response: We have updated our ethics statement, as shown below.

Methods section, pages 6 and 7, lines 132-136 (underlined text is new):

Ethics statement

This project received an exemption for review from the Institutional Review Board at Yale School of Medicine and at Shanghai Jiao Tong University College of Biotechnology as we used de-identified data provided by the iKang Health group. Given that the de-identified data were provided by a third party, we did not need to collect consent for analysis.

REVIEWER 1

Comment 1: It should be clear in the title and abstract that the topic is about non invasive hemodynamic data assessment.

Response: Thank you for your suggestion. We modified the study title, as shown below (underlined text is new)

Title: Hemodynamic Differences Between Women and Men with Elevated Blood Pressure in China: A Non-Invasive Assessment of 45,082 Adults Using Impedance Cardiography

Comment 2: A flow chart is needed.

Response: Thank you for your suggestion. We moved the study population flowchart from the supporting information document to the main text as new Figure 1 (shown below):

Figure 1. Study population flowchart

Legend: Abbreviations: ICG, impedance cardiography; DBP, diastolic blood pressure; SBP, systolic blood pressure; SV, stroke volume; HR, heart rate; Z0, baseline impedance.

Comment 3: The authors should give strong reason of why there is a restriction on the availability of data.

Response: The data used in this study was provided by iKang Health Group to be analyzed by the SJTU-Yale Joint Center for Biostatistics in Shanghai, China. Although deidentified, data are from a third party and we are restricted from sharing it publicly. Data requests, however, can be submitted to iKang Health Group for consideration, and we made the code used to analyze the data publicly available (https://www.doi.org/10.5281/zenodo.5931975). We updated our data availability statement to reflect this, as below.

Methods, page 3, lines 51-56 (underlined text is new):

Data source

iKang Health Group provided the de-identified data used in this study to SJTU-Yale Joint Center for Biostatistics in Shanghai, China. This is where all data are stored and all analyses were performed. Requests for data can be submitted to the iKang Health Group at maozhen.zhang@ikang.com. The code used to analyze the data is publicly available at https://www.doi.org/10.5281/zenodo.5931975.

Comment 4: In the methodology, the diagnosis of elevated blood pressure relies only on single blood pressure measurement. This is the major concern of the current analysis. Single measurement by automated device is not enough to classify patients regarding their blood pressure level. This point should be properly discussed and defended.

Response: We recognize that using a single measurement is not ideal because of the possible measurement-to-measurement variability in a single individual. It is possible that we identified individuals as hypertensive based on the single measurement that would not have been included if an average of 2 or more measurements were used instead. However, we also performed a sensitivity analysis using higher blood pressure cutoffs (SBP≥140 mmHg, DBP≥90 mmHg), in which likelihood of inadequately identifying hypertensive individuals is decreased. The findings of this sensitivity analysis were consistent with those of the main analysis.

Furthermore, in all participating sites, blood pressure was measured following a standardized protocol. Although a single measurement may compromise the precision of an individual measurement, the impact of this limitation is reduced by the fact that all sites followed the same protocol with the same calibrated device, regardless of the participants’ sex. We have expanded the limitations, as shown below:

Discussion section, page 17, lines 340-344 (underlined text is new):

Third, a single BP measurement was recorded per participant, which could have affected the precision in this variable. However, all study centers followed the same standardized protocol for men and women, as described in the Methods section, to reduce inter-observer variability. Moreover, such a compromise in precision would most likely shift the observed sex differences towards the null rather than towards significance.

Comment 5: The authors should justify the use of ICG, the authors should mention the guidelines recommendations or FDA or international medical institutes that approve the use of ICG for such purposes.

Response: The non-invasive nature of ICG measurement makes it an ideal technology for monitoring hemodynamic parameters in clinics. We leveraged data in clinics where they were being routinely used.

Although there are no guideline recommendations for routine hemodynamic measurement using impedance cardiography, many devices that use ICG have been approved by the FDA for such purposes in different scenarios. Below are some of the FDA 510(k) premarket notifications that support the use of devices using ICG for hemodynamic assessment:

- Approval K080941: intended to use ICG among patients with cardiovascular disease who need cardiac assessment. Available from:

o https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K080941

- Approval K172196: intended to use ICG among patients who are expected to be intubated for less than 24 hours. Available from:

o https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K172196

- Approval K160899: intended to use ICG among patients with fluid-management disorders such as heart failure, chronic kidney disease, or who use diuretics. Available from:

o https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K160899

- Approval K041434: intended to use ICG among patients in hospital areas, including clinics. Available from:

o https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K041434

- Approval K110645: intended to use ICG for general hemodynamic monitoring. Available from:

o https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K110645

The device used in our study has been validated against invasive thermodilution and echocardiography in different scenarios, as mentioned in the methods section (see below).

Methods, page 5, lines 90-94:

The ICG device used (CHM T3002/P3005, designed by Beijing Li-Heng Medical Technologies, Ltd, manufactured by Shandong Baolihao Medical Appliances, Ltd.) was developed based on improved hardware and advanced digital filtering algorithms,[1] and has been validated versus both invasive thermodilution and non-invasive echocardiography in different settings.[2-4]

We defer to the editors whether to cite in the main text the FDA 510(k) documents listed above.

References:

1. Ma L. Development and application of the latest model of the cardiac hemodynamics monitoring system. International J Cardiovasc Med. 2009;10:11.

2. An X-g, Zhao Y, Gao J. Clinic evaluation of noninvasive hemodynamic monitoring in patients undergoing coronary artery surgery. Chin J Cardiovasc Rev. 2008;2:010.

3. Hong H, Jin X, Pan C, Gao X, Liu M, Jiang H, Ge J. Analysis of the correlation between non-invasive hemodynamic monitor and cardiac echocardiography on the evaluation of cardiac function. Chinese Journal of Medical Instrumentation. 2009;33:328-331.

4. Chen W, Huang D, Zeng J, Deng R, Deng G, Chen W, Zou Y. Application of noninvasive cardiac hemodynamic monitor for ICU critically ill patients. Hainan Medical Journal. 2018;29:15.

Comment 6: In the results, there was significant difference in the age of women versus men (i.e., 54 vs 45, p <0.001). This significant difference still presents after subgroups analysis of <50 yr or > 50 yr (i.e., p<0.001). This important point should be defended and discuss as significant differences in age would be important confounder and obtaining reliable results needs proper adjustment of the analysis in regard to age.

Response: Indeed, there were important differences in the mean age between women and men that could influence our findings. We believe, however, that we robustly accounted for such differences in 2 major ways, listed below:

1. We performed a sequentially adjusted linear regression, shown in Table 2. Age was included in Adjusted Model 1 and Adjusted Model 2, without significantly altering the association of female sex and the hemodynamic indicators (either overall or stratified at age 50). In these multivariable analyses, we found that women <50 years old had lower systemic vascular resistance index and higher cardiac index than men of their same age group, whereas among those ≥50 years old, women had higher systemic vascular resistance index but lower cardiac index. Please find Table 2 at the end of this document.

2. We also performed a sensitivity analysis using a nearest neighbor propensity score matching, using region, age, SBP, DBP, and BMI. In this sensitivity analysis, showed in S2 Table (also at the end of this document), findings in magnitude and direction of the multivariable linear regression were similar, with the exception of no significant difference in systemic vascular resistance index among those <50 years old.

Thus, the observed sex differences are not likely to arise just from differences in the mean age of our study sample. Nonetheless, it should be clear that although we found statistically significant differences in the mean of the hemodynamic variables studied, the main finding is the heterogeneity in their distribution such that sex was not determinative of the hemodynamic profile, as below:

Discussion section, pages 15-16, lines 299-311 (underlined relevant text):

Our study also has important implications for personalizing the care of patients presenting to an outpatient clinic with elevated blood pressure. As hypertension remains as one of the biggest public health challenges worldwide, there is urgency in determining possible ways of improving its treatment efficacy by using personalized therapies tailored to each patient’s characteristics. Although we and other studies have shown that, on average, there are significant hemodynamic differences by sex, we also found that there is substantial same-sex heterogeneity in the hemodynamic profile. Notably, as hypertension prevalence and arterial stiffening increases among women after menopause, the distribution overlap of CI and SVRI among those older than 50 years was almost the same between women and men. Thus, our study indicates that sex alone is not a good proxy of the underlying hemodynamic patterns of patients with elevated blood pressure and should not be used clinically to assume the hypertension phenotype. Instead, it is necessary to measure these parameters directly if information about the hemodynamic profile is considered necessary to guide the antihypertensive therapy.

Nonetheless, we added this as a limitation of our analysis, as shown below:

Discussion section, page 17, lines 345-348 (underlined text is new):

Fourth, although we performed a robust main analysis, which included adjustment for multiple confounders, and a sensitivity analysis that used propensity score matching, we cannot rule out that the differences observed between men and women were due to residual confounding.

Comment 7: The current manuscript does not have data regarding long term follow up to see if the current hemodynamic differences have clinical impact on long term prognosis or not. This point should be properly defended.

Response: Although we lack such information, we agree on the importance of investigating the long-term association of different hemodynamic phenotypes. However, such an objective is outside the scope of our study which, cross-sectional in design, aimed to evaluate the differences between men and women in hemodynamic profiles in an outpatient setting.

Discussion section, page 15, lines 289-298 (underlined text is new or edited):

Altogether, such findings might suggest that the underlying mechanisms of elevated blood pressure might differ by sex, particularly among young individuals. The clinical implications of these sex differences are limited because of the high same-sex heterogeneity in these parameters that we observed. Beyond its potential implications for treatment adjustment or initiation, understanding if these differences in hypertension phenotypes are implicated in the known sex differences in terms of risk of subsequent cardiovascular outcomes is still uncertain and deserves further investigation. Furthermore, there is a need for longitudinal studies that help understand how chronic exposure to different hypertension phenotypes is associated with clinical outcomes, and if there are sex differences in such associations.

We also edited our limitations to better express this, as shown below.

Discussion, page 16, lines 314-318 (underlined text is new):

The results from our study should be interpreted in light of the following limitations. First, our findings only represent a snapshot of individuals’ hemodynamic status, preventing us from assessing longitudinal clinical outcomes and pathological adaptations that may occur with long-term exposure to a particular hypertension phenotype, including structural and physiological changes in heart and vessels.

Comment 8: The clinical implications of the current study should be clear and practical.

Regards

Response: Thank you. We edited the clinical implications paragraph to made it clearer, as below.

Discussion section, pages 15 and 16, lines 299-311 (underlined text is new or edited):

Our study also has important implications for personalizing the care of patients presenting to an outpatient clinic with elevated blood pressure. As hypertension remains as one of the biggest public health challenges worldwide,[1] there is urgency in determining possible ways of improving its treatment efficacy by using personalized therapies tailored to each patient’s characteristics. Although we and other studies have shown that, on average, there are significant hemodynamic differences by sex, we also found that there is substantial same-sex heterogeneity. Notably, as hypertension prevalence and arterial stiffening increase among women after menopause,[2-4] the distribution overlap of CI and SVRI among those older than 50 years was almost complete between women and men. Thus, our study indicates that sex alone is not a good proxy of the underlying hemodynamic patterns of patients with elevated blood pressure and should not be used clinically to assume the hypertension phenotype. Instead, it is necessary to measure these parameters directly if information about the hemodynamic profile is considered necessary to guide the antihypertensive therapy.

References:

1. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet (London, England). 2018;392(10159):1923-94.

2. Cheng S, Xanthakis V, Sullivan LM, Vasan RS. Blood pressure tracking over the adult life course: patterns and correlates in the Framingham heart study. Hypertension. 2012;60(6):1393-9.

3. Zhou Y, Zhou X, Guo X, Sun G, Li Z, Zheng L, et al. Prevalence and risk factors of hypertension among pre- and post-menopausal women: a cross-sectional study in a rural area of northeast China. Maturitas. 2015;80(3):282-7.

4. Lu Y, Pechlaner R, Cai J, Yuan H, Huang Z, Yang G, et al. Trajectories of age-related arterial stiffness in Chinese men and women. Journal of the American College of Cardiology. 2020;75(8):870-80.

REVIEWER 2

Comment 1: The cofounders missing some important factors as presence of diabetes, the types of hypertension ,the risk factors as dyslipidemia and the existence of chronic kidney disease. All these factors can contribute in risk stratification and further management of hypertension.

Response: Our aim was to describe sex differences in a hemodynamic snapshot of people with elevated blood pressure who visited an outpatient setting, regardless of their current management or chronic conditions. This is a real-world, pragmatic study showing that among a large outpatient clinic, there is marked heterogeneity in profiles and that sex is significantly associated with those profiles—but that there is a lot of overlap of the profiles of men and women.

We added the lack of comorbidities to the study’s limitations, as shown below.

Limitations, page 16, lines 319-324 (underlined text is new):

Second, although we had highly detailed hemodynamic information about each individual, the sociodemographic and clinical information (including comorbidities that may affect hemodynamic status) available for our analyses was limited. Of great importance is the lack of information regarding current antihypertensive medication usage, which could alter the hemodynamic phenotype and inclusion criteria (e.g., beta-blockers lowering CO or a patient with controlled hypertension not being included).

Comment 2: the age 50 is not clear as not standard for old age as WHO recommendations.

Response: We used 50 years not because it represents the age at which people are consider elder, but because it is the mean age of menopause among women in China.[1-3] See below

Methods section, page 5, lines 96-103 (relevant text is underlined):

Variable definitions

We described demographic characteristics and hemodynamic parameters of blood pressure in women and men overall and by age. Considering that the mean age of natural menopause in China is reported as approximately 50 years of age, we stratified our study population as <50 years old and ≥50 years old. We used the World Health Organization recommended cutoff values for BMI classification in Asian populations, defining underweight as <18.5 kg/m2, normal weight from 18.5 kg/m2 to <23 kg/m2, overweight from 23 kg/m2 to <27.5 kg/m2, and obesity as ≥27.5 kg/m2.

To make it clearer, we mention it in the introduction as shown below.

Introduction section, pages 2 and 3, lines 41-48 (underlined text is new):

Accordingly, we used data from tens of thousands of individuals with elevated blood pressure from an outpatient setting in China to evaluate the overall patterns of sex differences in hemodynamic variables and to determine how these sex hemodynamic differences may vary with age. We also aimed to evaluate the distribution of these variables among women and men, and to what extent they overlap by sex. Furthermore, we stratified our analysis at the mean age of menopause in China because of its potential association with hemodynamic changes. Results from this study can advance our understanding of the association of sex with hemodynamic patterns in people with hypertension and suggest if sex could be used to guide therapy.

References:

1. Dorjgochoo T, Kallianpur A, Gao YT, Cai H, Yang G, Li H, et al. Dietary and lifestyle predictors of age at natural menopause and reproductive span in the Shanghai Women's Health Study. Menopause. 2008;15(5):924-33.

2. Wang M, Gong WW, Hu RY, Wang H, Guo Y, Bian Z, et al. Age at natural menopause and associated factors in adult women: Findings from the China Kadoorie Biobank study in Zhejiang rural area. PLoS One. 2018;13(4):e0195658.

3. Song L, Shen L, Li H, Liu B, Zheng X, Zhang L, et al. Age at natural menopause and hypertension among middle-aged and older Chinese women. J Hypertens. 2018;36(3):594-600.

Comment 3: in table 1 what is meant by predominantly cardiac

Response: As stated in the footnote of Table 1 (found at the end of this document) and in the methods section, we defined a predominantly cardiac phenotype as high cardiac index with low or normal systemic vascular resistance index. This definition is consistent with previous research.[1-3]

Methods section, page 5, lines 96-107 (relevant text is underlined):

Variable definitions

We described demographic characteristics and hemodynamic parameters of blood pressure in women and men overall and by age. Considering that the mean age of natural menopause in China is reported as approximately 50 years of age, we stratified our study population as <50 years old and ≥50 years old. We used the World Health Organization recommended cutoff values for BMI classification in Asian populations, defining underweight as <18.5 kg/m2, normal weight from 18.5 kg/m2 to <23 kg/m2, overweight from 23 kg/m2 to <27.5 kg/m2, and obesity as ≥27.5 kg/m2. We defined a predominantly vascular hypertension phenotype as high SVRI (>2400 dynes·sec·cm-5·m2) with a low or normal CI (<2.5 L/min/m2 or 2.5–4 L/min/m2, respectively), and predominantly cardiac hypertension phenotype as high CI (>4 L/min/m2) with low or normal SVRI (<2000 dynes·sec·cm-5·m2 or 2000–2400 dynes·sec·cm-5·m2, respectively).

References:

1. Lu Y, Wang L, Wang H, Gu J, Ma ZJ, Lian Z, et al. Effectiveness of an impedance cardiography guided treatment strategy to improve blood pressure control in a real-world setting: results from a pragmatic clinical trial. Open Heart. 2021;8(2): e001719.

2. Mahajan S, Gu J, Caraballo C, Lu Y, Spatz ES, Zhao H, et al. Relationship of age with the hemodynamic parameters in individuals with elevated blood pressure. Journal of the American Geriatrics Society. 2020;68(7):1520-1528.

3. Mahajan S, Gu J, Lu Y, Khera R, Spatz ES, Zhang M, et al. Hemodynamic phenotypes of hypertension based on cardiac output and systemic vascular resistance. The American Journal of Medicine. 2020;133(4):e127-e139.

Additional comment from the authors: please note that, for conciseness and consistency in the data reporting across text and tables, we edited the P values to express P values to 2 digits to the right of the decimal point, or to 3 digits if <0.01. During our thorough revision we also detected that a few P values in Table 1, Table S1, and Table S2 needed to be updated because of initial entry error. We apologize for the initial typographical errors, which have been corrected and tracked, and we confirm that none of the changes affect our findings or conclusions.

Tables

Table 1. Sex differences in clinical and hemodynamic variables by age group among adults with elevated blood pressure.

All < 50 years old ≥ 50 years old

Women

N=15,888 Men

N= 29194 P value Women

N = 4,384 Men

N = 15,512 P value Women

N = 11,504 Men

N = 13,682 P value

Age (years) 54.5 (11.8) 48.0 (13.0) <0.001 39.3 (8.1) 38.0 (7.3) <0.001 60.2 (6.9) 59.5 (7.2) <0.001

BMI (kg/m2) 24.4 (3.5) 25.5 (3.2) <0.001 23.5 (3.7) 25.7 (3.4) <0.001 24.8 (3.3) 25.2 (3.0) <0.001

Obesity* 2733 (17.2%) 6858 (23.49%) <0.001 585 (13.34%) 4057 (26.15%) <0.001 2148 (18.67%) 2801 (20.47%) <0.001

Region <0.001 <0.001 <0.001

East 5965 (37.54%) 13275 (45.47%) 1956 (20.86%) 7419 (79.14%) 4009 (40.64%) 5856 (59.36%)

North 3665 (23.07%) 4156 (14.24%) 779 (29.59%) 1854 (70.41%) 2886 (55.63%) 2302 (44.37%)

South 2737 (17.23%) 4317 (14.79%) 686 (22.66%) 2341 (77.34%) 2051 (50.93%) 1976 (49.07%)

Southwest 3521 (22.16%) 7446 (25.51%) 963 (19.81%) 3898 (80.19%) 2558 (41.89%) 3548 (58.11%)

Blood pressure (mmHg)

Systolic 139.0 (15.7) 136.7 (13.8) <0.001 131.2 (13.2) 133.7 (12.2) <0.001 142.0 (15.6) 140.1 (14.8) <0.001

Diastolic 82.6 (9.00) 85.6 (8.9) <0.001 83.3 (7.9) 85.3 (8.9) <0.001 82.4 (9.4) 86.01 (9.0) <0.001

Hypertension phenotype

Predominantly cardiac† 2559 (16.11%) 5185 (17.76%) <0.001 1382 (31.52%) 3495 (22.53%) <0.001 1177 (10.23%) 1690 (12.35%) <0.001

Predominantly vascular‡ 9780 (61.56%) 16396 (56.16%) <0.001 1666 (38.00%) 7197 (46.40%) <0.001 8114 (70.53%) 9199 (67.23%) <0.001

Low/normal CI & low/normal SVRI 3531 (22.22)% 7548 (25.86%) <0.001 1,330 (30.34%) 4,790(30.88%) 0.50 2,201 (19.13%) 2,758 (20.16%) 0.04

High CI & high SVRI 18 (0.11%) 65 (0.22%) 0.01 6 (0.14%) 30 (0.19%) 0.56 12 (0.10%) 35 (0.26%) 0.01

ICG parameters

Heart rate (bpm) 69.4 (11.4) 69.5 (11.3) 0.63 72.6 (11.9) 70.8 (11.1) <0.001 68.2 (10.9) 68.0 (11.3) 0.15

Stroke volume (mL) 72.9 (18.6) 88.8 (21.5) <0.001 80.0 (18.8) 93.0 (21.6) <0.001 70.2 (17.7) 84.0 (20.5) <0.001

CO (L/min) 5.0 (1.4) 6.1 (1.5) <0.001 5.8 (1.4) 6.5 (1.4) <0.001 4.7 (1.2) 5.6 (1.4) <0.001

CI (L/min/m2) 3.2 (0.8) 3.3 (0.8) <0.001 3.6 (0.9) 3.5 (0.7) <0.001 3.0 (0.8) 3.2 (0.7) <0.001

SVR (dynes·sec·cm-5) 1744 (523) 1433 (389) <0.001 1471 (411) 1315 (324) <0.001 1848 (524) 1565 (412) <0.001

SVRI (dynes·sec·cm-5·m2) 2734.1 (809.9) 2596.3 (677.2) <0.001 2326.0 (658.0) 2435.1 (598.6) <0.001 2889.6 (808.3) 2779.2 (713.8) <0.001

Table 2. Unadjusted and Sequentially-Adjusted Association of Female Sex with Cardiac Output, Cardiac Index, Systemic Vascular Resistance, and Systemic Vascular Resistance Index, Overall and by Age Categories.

Hemodynamic Variable

Female Sex β Coefficient (95% CI)

Unadjusted Model Adjusted Model 1* Adjusted Model 2†

Cardiac Output, (L/min)

Overall -1.07 (-1.1, -1.04) -0.79 (-0.82, -0.77) -0.78 (-0.8, -0.75)

<50 years old -0.73 (-0.78, -0.68) -0.67 (-0.71, -0.62) -0.59 (-0.64, -0.54)

≥50 years old -0.90 (-0.93, -0.87) -0.86 (-0.89, -0.83) -0.86 (-0.89, -0.83)

Cardiac Index, (L/min/m2)

Overall -0.15 (-0.16, -0.13) -0.01 (-0.03, 0)‡ -0.08 (-0.09, -0.06)

<50 years old 0.14 (0.12, 0.17) 0.19 (0.16, 0.21) 0.07 (0.04, 0.09)

≥50 years old -0.14 (-0.16, -0.12) -0.12 (-0.14, -0.1) -0.15 (-0.16, -0.13)

Systemic Vascular Resistance, (dynes·sec·cm-5)

Overall 312 (303, 320) 225 (216, 233) 230 (221, 238)

<50 years old 156 (144, 167) 138 (127, 149) 140 (128, 151)

≥50 years old 282 (271, 294) 271 (260, 282) 274 (262, 285)

Systemic Vascular Resistance Index, (dynes·sec·cm-5·m2)

Overall 137.8 (123.7, 151.8) 6.0 (-7.6, 19.7)§ 73.5 (60.2, 86.8)

<50 years old -109.1 (-129.7, -88.6) -146.9 (-166.6, -127.3) -31.7 (-51.2, -12.2)

≥50 years old 110.5 (91.7, 129.3) 88.5 (69.9, 107.2) 120.4 (102.4, 138.5)

S2 Table. Sex Differences in Clinical and Hemodynamic Variables by Nearest Neighbor Propensity Score Matched Subgroups.

All

1:1 Matching <50 years old

1:1 Matching ≥50 years old

1:1 Matching

Women

N=15,888 Men

N= 15,888 P value Women

N = 4,384 Men

N = 4,384 P value Women

N = 11,504 Men

N = 11,504 P value

Age, years mean (SD) 54.46 (11.83) 53.45 (12.72) <0.001 39.3 (8.07) 39.27 (7.5) 0.84 60.24 (6.9) 59.68 (7.24) <0.001

BMI (kg/m2), mean (SD) 24.4 (3.49) 24.53 (2.95) <0.001 23.49 (3.72) 23.65 (3.3) 0.04 24.75 (3.33) 24.97 (2.94) <0.001

Obese (BMI ≥27.5 kg/m2), n(%) 2733 (17.2%) 2284 (14.38%) <0.001 585 (13.34%) 483 (11.02%) <0.001 2148 (18.67%) 2086 (18.13%) 0.30

Region, n (%) <0.001 0.26 <0.001

East 5965 (48.74%) 6273 (51.26%) 1956 (50.46%) 1920 (49.54%) 4009 (46.58%) 4597 (53.42%)

North 3665 (51.84%) 3405 (48.16%) 779 (47.94%) 846 (52.06%) 2886 (55.98%) 2269 (44.02%)

South 2737 (50.39%) 2695 (49.61%) 686 (49.67%) 695 (50.33%) 2051 (52.32%) 1869 (47.68%)

South West 3521 (50.04%) 3515 (49.96%) 963 (51.06%) 923 (48.94%) 2558 (48.02%) 2769 (51.98%)

Blood pressure in mmHg, mean (SD)

Systolic 139.02 (15.71) 138 (13.98) <0.001 131.21 (13.19) 131.52 (11.06) 0.04 142 (15.57) 140.36 (14.57) <0.001

Diastolic 82.64 (9.00) 83.62 (8.39) <0.001 83.32 (7.85) 83.37 (8.05) 0.23 82.37 (9.38) 84.61 (8.32) <0.001

ICG parameters, mean (SD)

CO (L/min) 5.01 (1.35) 5.87 (1.43) <0.001 5.75 (1.41) 6.39 (1.42) <0.001 4.73 (1.21) 5.63 (1.35) <0.001

CI (L/min/m2) 3.19 (0.84) 3.31 (0.78) <0.001 3.64 (0.88) 3.59 (0.77) 0.013 3.02 (0.76) 3.18 (0.74) <0.001

SVR

(dynes·sec·cm-5) 1743.94 (523.42) 1475.6 (406.58) <0.001 1470.91 (411.34) 1306.85 (315.19) <0.001 1847.99 (524.09) 1552.76 (410.64) <0.001

SVRI

(dynes·sec·cm-5·m2) 2734.1 (809.92) 2606.44 (691.7) <0.001 2325.95 (658.03) 2322.25 (556.02) 0.78 2889.64 (808.27) 2741.28 (702.93) <0.001

SD= Standard Deviation, BMI= Body Mass Index, ICG= Impedance Cardiography, SVR= Systemic Vascular Resistance, SVRI= Systemic Vascular Resistance Index, CO= Cardiac Output, CI= Cardiac Index.

Propensity Score Generation Model: Gender ~ Age + BMI + SBP + DBP + Region

Submitted filename: PONE-D-21-16564_R1_Response_2022_02_11.docx

Click here for additional data file.

12 May 2022

Hemodynamic Differences Between Women and Men with Elevated Blood Pressure in China: A Non-Invasive Assessment of 45,082 Adults Using Impedance Cardiography

PLOS ONE

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20 May 2022

Please see the attached document for our responses in appropriate format. They are pasted also below.

Response To Comments

PONE-D-21-16564: Hemodynamic Differences Between Women and Men with Elevated Blood Pressure in China: A non-invasive assessment of 45,082 adults using impedance cardiography

We have responded to each comment (reproduced in bold) and detailed our changes to the manuscript. In this document, quoted text is presented indented and new additions (or relevant text when specified) underlined. The page and line numbers that we reference below are based on the clean version of our revised manuscript. New references are listed at the end of each response.

ACADEMIC EDITOR

Comment 1: Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The authors improved the manuscript but appear to have ignored comments of reviewer 2. If they respond sufficiently to these comments the manuscript can be accepted. Please check carefully once more the initial comments of reviewer 2 as listed below:

Response: We appreciate the academic editor comments and the opportunity to revise our work. This may be a misunderstanding. We did respond to the Reviewer 2 in our initial response letter and made some modifications to the manuscript accordingly. We apologize if our responses were somehow left out from the document that you reviewed. We reviewed each comment once more and included our responses below. Please note that we highlighted these changes in the attached tracked version of the manuscript.

Comment 2:

- The cofounders missing some important factors as presence of diabetes, the types of hypertension ,the risk factors as dyslipidemia and the existence of chronic kidney disease. All these factors can contribute in risk stratification and further management of hypertension.

Response: Our aim was to describe sex differences in a hemodynamic snapshot of people with elevated blood pressure who visited an outpatient setting, regardless of their current management or chronic conditions. This is a real-world, pragmatic study showing that among a large outpatient clinic, there is marked heterogeneity in profiles and that sex is significantly associated with those profiles—but that there is a lot of overlap of the profiles of men and women.

We added the lack of comorbidities to the study’s limitations, as shown below.

Limitations, page 16, lines 321-326 (underlined text is new):

Second, although we had highly detailed hemodynamic information about each individual, the sociodemographic and clinical information (including comorbidities that may affect hemodynamic status) available for our analyses was limited. Of great importance is the lack of information regarding current antihypertensive medication usage, which could alter the hemodynamic phenotype and inclusion criteria (e.g., beta-blockers lowering CO or a patient with controlled hypertension not being included).

- Comment 3: the age 50 is not clear as not standard for old age as WHO recommendations.

Response: We used 50 years not because it represents the age at which people are consider elder, but because it is the mean age of menopause among women in China.[1-3] See below

Methods section, page 5, lines 98-105 (relevant text is underlined):

Variable definitions

We described demographic characteristics and hemodynamic parameters of blood pressure in women and men overall and by age. Considering that the mean age of natural menopause in China is reported as approximately 50 years of age, we stratified our study population as <50 years old and ≥50 years old. We used the World Health Organization recommended cutoff values for BMI classification in Asian populations, defining underweight as <18.5 kg/m2, normal weight from 18.5 kg/m2 to <23 kg/m2, overweight from 23 kg/m2 to <27.5 kg/m2, and obesity as ≥27.5 kg/m2.

To make it clearer, we mention it in the introduction as shown below.

Introduction section, pages 2 and 3, lines 41-48 (underlined text is new):

Accordingly, we used data from tens of thousands of individuals with elevated blood pressure from an outpatient setting in China to evaluate the overall patterns of sex differences in hemodynamic variables and to determine how these sex hemodynamic differences may vary with age. We also aimed to evaluate the distribution of these variables among women and men, and to what extent they overlap by sex. Furthermore, we stratified our analysis at the mean age of menopause in China because of its potential association with hemodynamic changes. Results from this study can advance our understanding of the association of sex with hemodynamic patterns in people with hypertension and suggest if sex could be used to guide therapy.

References:

1. Dorjgochoo T, Kallianpur A, Gao YT, Cai H, Yang G, Li H, et al. Dietary and lifestyle predictors of age at natural menopause and reproductive span in the Shanghai Women's Health Study. Menopause. 2008;15(5):924-33.

2. Wang M, Gong WW, Hu RY, Wang H, Guo Y, Bian Z, et al. Age at natural menopause and associated factors in adult women: Findings from the China Kadoorie Biobank study in Zhejiang rural area. PLoS One. 2018;13(4):e0195658.

3. Song L, Shen L, Li H, Liu B, Zheng X, Zhang L, et al. Age at natural menopause and hypertension among middle-aged and older Chinese women. J Hypertens. 2018;36(3):594-600.

- Comment 4: in table 1 what is meant by predominantly cardiac

Response: As stated in the footnote of Table 1 (see underlined footnote in Table 1 below) and in the methods section, we defined a predominantly cardiac phenotype as high cardiac index with low or normal systemic vascular resistance index. This definition is consistent with previous research.[1-3]

Methods section, page 5, lines 98-109 (relevant text is underlined):

Variable definitions

We described demographic characteristics and hemodynamic parameters of blood pressure in women and men overall and by age. Considering that the mean age of natural menopause in China is reported as approximately 50 years of age, we stratified our study population as <50 years old and ≥50 years old. We used the World Health Organization recommended cutoff values for BMI classification in Asian populations, defining underweight as <18.5 kg/m2, normal weight from 18.5 kg/m2 to <23 kg/m2, overweight from 23 kg/m2 to <27.5 kg/m2, and obesity as ≥27.5 kg/m2. We defined a predominantly vascular hypertension phenotype as high SVRI (>2400 dynes·sec·cm-5·m2) with a low or normal CI (<2.5 L/min/m2 or 2.5–4 L/min/m2, respectively), and predominantly cardiac hypertension phenotype as high CI (>4 L/min/m2) with low or normal SVRI (<2000 dynes·sec·cm-5·m2 or 2000–2400 dynes·sec·cm-5·m2, respectively).

References:

1. Lu Y, Wang L, Wang H, Gu J, Ma ZJ, Lian Z, et al. Effectiveness of an impedance cardiography guided treatment strategy to improve blood pressure control in a real-world setting: results from a pragmatic clinical trial. Open Heart. 2021;8(2): e001719.

2. Mahajan S, Gu J, Caraballo C, Lu Y, Spatz ES, Zhao H, et al. Relationship of age with the hemodynamic parameters in individuals with elevated blood pressure. Journal of the American Geriatrics Society. 2020;68(7):1520-1528.

3. Mahajan S, Gu J, Lu Y, Khera R, Spatz ES, Zhang M, et al. Hemodynamic phenotypes of hypertension based on cardiac output and systemic vascular resistance. The American Journal of Medicine. 2020;133(4):e127-e139.

Table 1. Sex differences in clinical and hemodynamic variables by age group among adults with elevated blood pressure.

All < 50 years old ≥ 50 years old

Women

N=15,888 Men

N= 29194 P value Women

N = 4,384 Men

N = 15,512 P value Women

N = 11,504 Men

N = 13,682 P value

Age (years) 54.5 (11.8) 48.0 (13.0) <0.001 39.3 (8.1) 38.0 (7.3) <0.001 60.2 (6.9) 59.5 (7.2) <0.001

BMI (kg/m2) 24.4 (3.5) 25.5 (3.2) <0.001 23.5 (3.7) 25.7 (3.4) <0.001 24.8 (3.3) 25.2 (3.0) <0.001

Obesity* 2733 (17.2%) 6858 (23.49%) <0.001 585 (13.34%) 4057 (26.15%) <0.001 2148 (18.67%) 2801 (20.47%) <0.001

Region <0.001 <0.001 <0.001

East 5965 (37.54%) 13275 (45.47%) 1956 (20.86%) 7419 (79.14%) 4009 (40.64%) 5856 (59.36%)

North 3665 (23.07%) 4156 (14.24%) 779 (29.59%) 1854 (70.41%) 2886 (55.63%) 2302 (44.37%)

South 2737 (17.23%) 4317 (14.79%) 686 (22.66%) 2341 (77.34%) 2051 (50.93%) 1976 (49.07%)

Southwest 3521 (22.16%) 7446 (25.51%) 963 (19.81%) 3898 (80.19%) 2558 (41.89%) 3548 (58.11%)

Blood pressure (mmHg)

Systolic 139.0 (15.7) 136.7 (13.8) <0.001 131.2 (13.2) 133.7 (12.2) <0.001 142.0 (15.6) 140.1 (14.8) <0.001

Diastolic 82.6 (9.00) 85.6 (8.9) <0.001 83.3 (7.9) 85.3 (8.9) <0.001 82.4 (9.4) 86.01 (9.0) <0.001

Hypertension phenotype

Predominantly cardiac† 2559 (16.11%) 5185 (17.76%) <0.001 1382 (31.52%) 3495 (22.53%) <0.001 1177 (10.23%) 1690 (12.35%) <0.001

Predominantly vascular‡ 9780 (61.56%) 16396 (56.16%) <0.001 1666 (38.00%) 7197 (46.40%) <0.001 8114 (70.53%) 9199 (67.23%) <0.001

Low/normal CI & low/normal SVRI 3531 (22.22)% 7548 (25.86%) <0.001 1,330 (30.34%) 4,790(30.88%) 0.50 2,201 (19.13%) 2,758 (20.16%) 0.04

High CI & high SVRI 18 (0.11%) 65 (0.22%) 0.01 6 (0.14%) 30 (0.19%) 0.56 12 (0.10%) 35 (0.26%) 0.01

ICG parameters

Heart rate (bpm) 69.4 (11.4) 69.5 (11.3) 0.63 72.6 (11.9) 70.8 (11.1) <0.001 68.2 (10.9) 68.0 (11.3) 0.15

Stroke volume (mL) 72.9 (18.6) 88.8 (21.5) <0.001 80.0 (18.8) 93.0 (21.6) <0.001 70.2 (17.7) 84.0 (20.5) <0.001

CO (L/min) 5.0 (1.4) 6.1 (1.5) <0.001 5.8 (1.4) 6.5 (1.4) <0.001 4.7 (1.2) 5.6 (1.4) <0.001

CI (L/min/m2) 3.2 (0.8) 3.3 (0.8) <0.001 3.6 (0.9) 3.5 (0.7) <0.001 3.0 (0.8) 3.2 (0.7) <0.001

SVR (dynes·sec·cm-5) 1744 (523) 1433 (389) <0.001 1471 (411) 1315 (324) <0.001 1848 (524) 1565 (412) <0.001

SVRI (dynes·sec·cm-5·m2) 2734.1 (809.9) 2596.3 (677.2) <0.001 2326.0 (658.0) 2435.1 (598.6) <0.001 2889.6 (808.3) 2779.2 (713.8) <0.001

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31 May 2022

Hemodynamic Differences Between Women and Men with Elevated Blood Pressure in China: A Non-Invasive Assessment of 45,082 Adults Using Impedance Cardiography

PONE-D-21-16564R2

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3 Jun 2022

PONE-D-21-16564R2

Hemodynamic Differences Between Women and Men with Elevated Blood Pressure in China: A non-invasive assessment of 45,082 adults using impedance cardiography

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Table 2

Unadjusted and sequentially-adjusted association of female sex with cardiac output, cardiac index, systemic vascular resistance, and systemic vascular resistance index, overall and by age categories.

Hemodynamic Variable	Female Sex β Coefficient (95% CI)
	Unadjusted Model	Adjusted Model 1*	Adjusted Model 2†
Cardiac Output, (L/min)
Overall	-1.07 (-1.1, -1.04)	-0.79 (-0.82, -0.77)	-0.78 (-0.8, -0.75)
<50 years old	-0.73 (-0.78, -0.68)	-0.67 (-0.71, -0.62)	-0.59 (-0.64, -0.54)
≥50 years old	-0.90 (-0.93, -0.87)	-0.86 (-0.89, -0.83)	-0.86 (-0.89, -0.83)
Cardiac Index, (L/min/m2)
Overall	-0.15 (-0.16, -0.13)	-0.01 (-0.03, 0)‡	-0.08 (-0.09, -0.06)
<50 years old	0.14 (0.12, 0.17)	0.19 (0.16, 0.21)	0.07 (0.04, 0.09)
≥50 years old	-0.14 (-0.16, -0.12)	-0.12 (-0.14, -0.1)	-0.15 (-0.16, -0.13)
Systemic Vascular Resistance,(dynes·sec·cm-5)
Overall	312 (303, 320)	225 (216, 233)	230 (221, 238)
<50 years old	156 (144, 167)	138 (127, 149)	140 (128, 151)
≥50 years old	282 (271, 294)	271 (260, 282)	274 (262, 285)
Systemic Vascular Resistance Index, (dynes·sec·cm-5·m2)
Overall	137.8 (123.7, 151.8)	6.0 (-7.6, 19.7)§	73.5 (60.2, 86.8)
<50 years old	-109.1 (-129.7, -88.6)	-146.9 (-166.6, -127.3)	-31.7 (-51.2, -12.2)
≥50 years old	110.5 (91.7, 129.3)	88.5 (69.9, 107.2)	120.4 (102.4, 138.5)

* Model 1 was adjusted for age and region.

† Model 2 was adjusted for age, region, and body mass index.

‡P value = 0.16.

§P value = 0.39.

All other P values <0.001.