ABSTRACT
Abnormal LV geometrics implied higher cardiovascular risk for hypertensive patients. Ethnicity‐specific cardiographic criteria classified more accurately the left ventricular (LV) geometric patterns for Chinese than international guideline. We hypothesized that the influences of achieved blood pressure on prognosis varied by different LV geometrics based on ethnicity‐specific echocardiographic criteria. We enrolled participants from a nationwide public health research project in China and categorized into four groups including normal geometry (NG), concentric remoldeling (CR), eccentric remodeling (ER), and concentric hypertrophy (CH) based on LV geometrics. The cumulative cardiovascular risks across different LV geometric patterns and achieved SBP subgroups were analyzed using survival analysis and Cox regression. The LV geometric patterns based on ethniticy‐specific diagnostic thresholds from the EMINICA study distinguished accurately the cardiovascular risks for Chinese hypertensive patients. Notably, a lower achieved SBP of below 130 mmHg conferred significantly additional benefits to subjects with CH (Multivariable HR = 0.342 for primary endpoint, 95%CI 0.162–0.719, p = 0.005). An achieved SBP below 130 mmHg elevates slightly but significantly the risk of coronary artery disease (CAD) in patients with concentric remodeling (Multivaribale HR = 2.351 for hospitalization of CAD, 95%CI 1.145–4.830, p = 0.010). The influence of achieved SBP on prognosis varied by different LV structural patterns based on ethnicity‐specific diagnostic thresholds. The achieved SBP below 130mHg might bring additional benefits for patients with CH.
Keywords: blood pressure, cardiovascular risk stratification, echocardiogram, hypertensive heart disease, left ventricular geometrics
Abbreviations
- CAD
Coronary Artery Disease
- CH
Concentric Hypertrophy.
- CR
Concentric Remodeling
- EH
Eccentric Hypertrophy
- HHD
Hypertensive Heart Disease
- LVH
Left Ventricular Hypertrophy
- LVMI
Left Ventricular Mass Index
- NG
Normal Geometry
- RWT
Relative Wall Thickness
- SBP
Systolic Blood Pressure
1. Introduction
Determining the optimal blood pressure (BP) target for hypertensive patients across different cardiovascular risk strata remains a pivotal challenge. Large‐scale trials such as SPRINIT and STEP have demonstrated that intensive antihypertensive therapy reduced major adverse cardiovascular events, especially in high‐risk populations [1, 2]. However, the intensive therapy may not be universally suitable, especially for frail and low‐risk hypertensive patients, due to the risks such as postural hypotension and renal injuries [3]. Therefore, a refined understanding of how achieved systolic BP influenced prognosis across diverse clinical subgroups is needed.
Echocardiography provides vaulable insights into hypertension‐related organ damage. Hypertensive heart disease (HHD), characterized of left ventricular hypertrophy (LVH) or remodeling defined by echocardiogphic criteria, is a well‐established marker of increased cardiovascular risk [4, 5]. Numerous studies affirmed that alterations in LV geometric patterns in response to the hemodynamic irregularities of hypertension correlate with escalated cardiovascular risks [6, 7, 8]. Based on metrics like the left ventricular mass index (LVMI) and relative wall thickness (RWT), LV geometry can be classified into four patterns: normal geometry (NG), concentric remodeling (CR), eccentric hypertrophy (EH), and concentric hypertrophy (CH) [9, 10]. While SPRINT and ACCORD‐BP trials have reported LVH regression in with intensive anti‐hypertensive therapy using electrocardiography (ECG) criteria [11, 12], and LIFE study further corroborated that LVH regression defined by ECG is strongly correlated with reduction of major adverse cardiovascular and cerebrovascular events (MACCEs) in hypertensive patients [13, 14], ECG lack detailed assessment of cardiovascular risks based on LV geometric patterns. Consequently, the optimal achieved SBP for patients with distinct LV geometric subtypes remains unclear. We hypothesized that intensive BP control may confer greater benefit in patients with abnormal LV geometry than in those with NG.
Using the Guangdong Provincial cohort of the China Patient‐centered Evaluative Assessment of Cardiac Events Million Persons Project (PEACE MPP) [15, 16, 17], we analyzed 7680 hypertensive individuals to evaluate the impact of achieved systolic BP on cardiovascular outcomes across LV geometric patterns. Recognizing that echocardiographic norms may vary by ethnicity [18, 19, 20, 21], we applied both the international ASE/EACVI criteria and the ethnicity‐specific thresholds from the EMINCA study to assess whether ethnicity‐specific thresholds better stratifies cardiovascular risk in a Chinese hypertensive population. Finally, we adopted ethnicity‐specific echocardiographic diagnostic thresholds for grouping and conducted the retrospective study to elucidate whether the optimal achieved SBP target for minimizing the MACCEs differs by LV geometric patterns in Chinese hypertensive patients.
2. Methods
2.1. Study Populations
This study was conducted using data from the PEACE MPP, a nationwide public‐health research project led by the Chinese National Center for Cardiovascular Diseases (NCCD) focusing on investigation of the cardiovascular risk factors of rural and urban residents in China [15, 16]. This provincial sub‐study complied with Declaration of Helsinki and approved by Research Ethics Committee of Guangdong Provincial People's Hospital (Guangdong Academy of Medical Science) (No.GDREC2016438H‐R2). Informed consents were gotten from all participants.
Detailed methodologies of this project have been documented in previous studies [15, 16]. Participants for this study were recruited from nine distinct locations in Guangdong province, encompassing towns and districts across cities such as Guangzhou (Canton), Dongguan, Shenzhen, Zhongshan, Foshan, and Zhuhai. Between 2016 and 2019, all participants underwent assessments and recordings of 12 cardiovascular risk factors. Data collection was executed through in‐person interviews adhering to standard procedures and was cataloged using electronic questionnaires with real‐time validation capabilities. A total of 20 921 participants were identified as high cardiovascular risk individuals based on predefined criteria as following: (1) individuals with a estimated 10‐year risk of cardiovascular higher than 20% according to the 2019 World Health Organization cardiovascular risk evaluation guideline for Eastern Asian Population [22]; (2) Certain medical history including previous myocardial infarction, stroke, percutaneous coronary intervention and coronary artery bypass grafting;(3)The systolic BP greater than 160 mmHg or diastolic BP greater than 110 mmHg, low‐density lipoprotein‐cholesterol (LDL‐C) greater than 4.1 mmol/L (160 mg/dl) or high‐density lipoprotein‐cholesterol (HDL‐C) less than 0.78 mmol/L (30 mg/dl) [15]. Of these, 11 511 were diagnosed with hypertension, and 7969 had accessible follow‐up BP data. After applying specific exclusion criteria (mentioned in Inclusion and Exclusion Criteria), 7680 hypertensive participants with both follow‐up BP readings and baseline echocardiographic data were included. Figure 1 provides a comprehensive breakdown of the participant recruitment process.
FIGURE 1.
Flowchart of the Prospective Cohort Study.
All high‐risk participants underwent medical examinations such as 12‐lead electrocardiograms, transthoracic echocardiographic exams, and carotid ultrasonography as per the national survey's standard procedures. Given the subsequent community‐based medical interventions, short‐term interviews, and long‐term follow‐ups, this investigation is best characterized as a prospective cohort study aiming to understand the relationship between achieved BP and cardiovascular outcomes across varied left ventricular (LV) geometric conditions within the Chinese populace.
2.2. Inclusion and Exclusion Criteria
In the study, we primarily selected the individuals based on several inclusion criteria as following: (1) Hypertensive patients who need to anti‐hypertensive therapy, including self‐reported hypertensive cases and unknown hypertensive patients who were diagnosed based on office BP in the survey; (2) Defined as individuals with high risks of cardiovascular diseases in the study according to three criteria mentioned above; (3) Echocardiographic data at baseline in the survey were available; (4) The achieved BP values measured three months later were available. The exclusion criteria included as following: (1) With evidence of previous ST‐segment elevated myocardial infraction (MI), including self‐reported previous MI and with obvious pathological q wave shown in adjacent leads discovered by electrocardiogram testing; (2) Complicated with structural heart diseases, including cardiomyopathy, valvular heart diseases (medium‐severe mitral/aortic valvular stenosis and regurgitation) and adult congenital heart disease; (3) Individuals with atrial flutter and fibrillation; (4) Self‐report of heart failure, or with EF lower than 40% measured by baseline transthoracic echocardiographic examination; (5) Regional wall systolic dysfunction and LV aneurysm discovered by baseline echocardiographic examination.
2.3. Intervention and Follow‐Up
Medical interventions, grounded in the community medical system, comprised disease awareness initiatives, health education, lifestyle interventions, and community‐centered drug regimens targeting cardiovascular risk factors [15, 16]. General practitioners offered tailored advice and personalized antihypertensive prescription for all hypertensive patients, integrating clinical guidelines and patient preferences. Scheduled follow‐ups included a preliminary personal interview after three months and subsequent annual check‐ins. These sessions encapsulated comprehensive cardiovascular assessments, including real achieved BP readings, lipid and glucose testing, and recording of any cardiovascular events. And the achieved systolic BP in this article was defined as the average value of SBP at the first interview and every annual interviews. Annual follow‐up plan for high‐risk individuals enrolled in this cohort study were performed according to protocols issued by the Chinese NCCD [15, 16].
2.4. Echocardiographic Examination
LV parameters were ascertained using 2D echocardiography, in alignment with the guidelines from the American Society of Echocardiography and the European Association of Cardiovascular Imaging (ASE/EACVI) [10]. Interventricular septal end‐diastolic thickness (IVSTd), LV posterior wall end‐diastolic thickness (LVPWTd), and LV end‐diastolic diameter (LVEDD) were recorded from the parasternal long‐axis view at the level of the mitral valve leaflet tips. The LV ejection fraction (LVEF) was calculated based on modified biplane Simpson's method. LV mass (LVM) was calculated as: LVM = 0.8* 1.04 *[(IVSTd + LVEDD + LVPWTd)3 – LVEDD3] + 0.6 g [10]. RWT was calculated as: RWT = (LVPWTd*2)/LVEDD [10]. The echocardiographic value of LVM was indexed to body surface area (BSA) according to the ASE/EACVI guideline recommendation [10]. LVM index was calculated as: LVM/body surface area2(BSA2). According to ASE/EACVI guideline recommendation, LV hypertrophy (LVH) was defined with a value of LMVI>115 g/m2 for men and > 95 g/m2 for women. LVH with or without RWT > 0.42 was defined CH and eccentric hypertrophy (EH) respectively. Merely RWT > 0.42 was considered concentric remodeling. According to the data from Echocardiographic Measurements in Normal Chinese Adults (EMINCA) study, LV hypertrophy (LVH) was defined with a value of LMVI > 109 g/m2 for men and >105 g/m2 for women. LVH with or without RWT > 0.51 was defined concentric hypertrophy (CH) and eccentric hypertrophy (EH) respectively. Merely RWT > 0.51 was considered concentric remodeling [18]. Based on the presence of concentric remodeling and LVH, LV geometry was classified into NG, concentric remodeling, CH, and eccentric hypertrophy.
2.5. Endpoints
The primary endpoint encompassed the onset of MACCEs during the follow‐up period, including the cardiovascular death, MI, stroke, hospitalization for coronary artery diseases (CAD) and heart failure (HF). Secondary endpoints considered incidences of first stroke, initial hospitalizations due to CADs and heart failure. Mortality data and causes of death were sourced from the Guangdong Provincial Center for Disease Control and Prevention, and other outcomes were retrieved from the electronic medical record system managed by the Health Commission of Guangdong Province, China.
2.6. Statistical Analysis
The SPSS 24.0 version was used for statistical analysis. Quantitative data were presented as either Mean (SD) or Median (IQR) based on their distribution. Statistical tests such as the Student's t‐test, One‐way ANOVA, rank‐sum test were used for the comparison of continuous variables among four subgroups based on LV geometric patterns The comparison of cardiovascular outcomes among four subgroups was analyzed using survival analysis and Log‐Rank test. Multifactor Cox regression model were employed to the Confounding Factors Included Age, Sex, Obesity, Current Smoking, Intake of Alcohol, Hyperlipidemia, Diabetes, and Low Metabolic Equivalent in the multivariable Cox regression model. A significance level of p < 0.05 was used for all statistical tests.
3. Results
3.1. Baseline Characteristics and LV Geometry Patterns
7680 hypertensive individuals at high cardiovascular disease risk were recruited, with a median follow‐up of 3.5 years. Participants were categorized into four LV geometry groups: NG, concentric remodeling (CR), eccentric hypertrophy (EH), and CH using the PEACE MPP dataset from Guangdong province, China. Continuous variables displayed a skewed distribution and are presented as Median (IQR). Baseline characteristics showcased based on EMINCA and ASE/EACVI typing in Table 1 and Supplementary Table 1, respectively. Significant differences of variables were observed among groups, except for total cholesterol levels using EMINCA diagnostic thresholds, aligning with ASE/EACVI guideline recommendation.
TABLE 1.
Baseline characteristics and cardiovascular risk factors of chinese participants based on EMINCA diagnostic thresholds.
| EMINCA typing | Data type | Total (N = 7680) |
EMINCA typing NR (N = 5225) |
EMINCA typing CR (N = 598) |
EMINCA typing EH (N = 1502) |
EMINCA typing CH (N = 355) |
p value |
|---|---|---|---|---|---|---|---|
| Age, years | Median (IQR) | 61.0 (53.0–66.0) | 59.0 (52.0–65.0) | 62.0 (56.0–68.0) | 63.0 (55.0–68.0) | 63.0 (56.0–67.0) | <0.001 |
| Body‐mass index (BMI), kg/m2 | Median (IQR) | 25.1 (23.0–27.4) | 25.0 (22.9–27.2) | 25.3 (23.2–27.5) | 25.5 (23.4–28.0) | 25.7 (23.6–27.9) | <0.001 |
| Waist circumference, cm | Median (IQR) | 88.0 (81.7–94.0) | 87.0 (81.0–93.0) | 89.0 (82.0–95.0) | 89.0 (82.5–95.0) | 90.0 (84.8–96.0) | <0.001 |
| Systolic BP, mmHg | Median (IQR) | 160.0 (144.5–166.0) | 159.5 (144.0–165.0) | 160.0 (146.0–166.0) | 161.0 (148.0–168.5) | 162.0 (145.0–170.5) | <0.001 |
| Diastolic BP, mmHg | Median (IQR) | 90.5 (81.5–99.5) | 90.5 (81.5–99.0) | 92.0 (82.5–101.0) | 90.0 (81.0–99.0) | 91.5 (83.0–100.5) | 0.001 |
| Total cholesterol, mmol/L | Median (IQR) | 5.1 (4.2–6.3) | 5.2 (4.2–6.3) | 5.0 (4.2–6.2) | 5.0 (4.2–6.1) | 5.0 (4.2–6.0) | 0.011 |
| Fasting blood glucose (FBG), mmol/L | Median (IQR) | 5.9 (5.2–6.8) | 5.9 (5.2–6.7) | 6.1 (5.2–7.3) | 5.8 (5.2–6.8) | 6.2 (5.6–7.4) | <0.001 |
| Overweight, defined as 24≦BMI≦28 kg/m2, (n,%) | 0 | 2743 (35.7) | 1952 (37.4) | 198 (33.1) | 486 (32.4) | 107 (30.1) | <0.001 |
| 1 | 4937 (64.3) | 3273 (62.6) | 400 (66.9) | 1016 (67.6) | 248 (69.9) | ||
| Obesity, defined as BMI > 28 kg/m2 (n,%) | 0 | 6103 (79.5) | 4238 (81.1) | 466 (77.9) | 1132 (75.4) | 267 (75.2) | <0.001 |
| 1 | 1577 (20.5) | 987 (18.9) | 132 (22.1) | 370 (24.6) | 88 (24.8) | ||
| Total cholesterol > 5.0 mmol/L (n,%) | 0 | 3579 (46.6) | 2386 (45.7) | 300 (50.2) | 723 (48.1) | 170 (47.9) | 0.088 |
| 1 | 4101 (53.4) | 2839 (54.3) | 298 (49.8) | 779 (51.9) | 185 (52.1) | ||
| Fast blood glucose > 7.0 mmol/L (n,%) | 0 | 5934 (77.3) | 4112 (78.7) | 408 (68.2) | 1168 (77.8) | 246 (69.3) | <0.001 |
| 1 | 1746 (22.7) | 1113 (21.3) | 190 (31.8) | 334 (22.2) | 109 (30.7) | ||
| Current smoking (n,%) | 0 | 6264 (81.6) | 4312 (82.5) | 476 (79.6) | 1202 (80.0) | 274 (77.2) | 0.009 |
| 1 | 1416 (18.4) | 913 (17.5) | 122 (20.4) | 300 (20.0) | 81 (22.8) | ||
| Alcohol use (n,%) | 0 | 7176 (93.4) | 4921 (94.2) | 538 (90.0) | 1394 (92.8) | 323 (91.0) | <0.001 |
| 1 | 504 (6.6) | 304 (5.8) | 60 (10.0) | 108 (7.2) | 32 (9.0) | ||
| Low physical activity (%) | 0 | 4633 (60.3) | 3224 (61.7) | 352 (58.9) | 850 (56.6) | 207 (58.3) | 0.003 |
| 1 | 3047 (39.7) | 2001 (38.3) | 246 (41.1) | 652 (43.4) | 148 (41.7) |
Note: Data are presented as either median (IQR) or n (%). A p‐value of < 0.05 denotes statistical significance.
3.2. Risk Stratification of MACCEs Using EMINICA and ASE/EACVI Diagnostic Thresholds
Survival analysis were used for determining whether LV geometric patterns based on different diagnostic thresholds of echocardiographic parameters is the independent risk factors cardiovascular events in the hypertensive patients. The LV geometrics based on ethnicity‐specific and ASE/EACVI guideline criteria both was associated with the cumulative risk of the primary endpoints (Figures 2A and 2B). Differences of cumulative incidence in the whole secondary endpoints were statistically significant with EMINCA‐derived LV geometry patterns (Log‐rank test, p < 0.05) (Figure S1 A‐C). In contrast, differences of incidence were not significant in the stroke under ASE/EACVI (Figure S2 A‐C). Multivariable Cox regression models further confirmed the statistical significances for primary endpoints and all secondary endpoints based on EMINCA typing (Table 2). However, the cumulative incidence of stroke and CAD hospitalization was not independently associated with LV geometries based on ASE/EACVI typing, which demonstrated EMINCA typing is superior in the risk stratification for secondary endpoints in the Chinese hypertensive patients compared to ASE/EACVI typing (Table S2).
FIGURE 2.
Survival curves for primary outcomes across different LV geometry patterns based on EMINCA and ASE/EACVI diagnostic thresholds. The log‐rank test was utilized to compare median survival times. A p‐value of < 0.05 denotes statistical significance.
TABLE 2.
Univariate and multivariable hazard ratios of outcomes for four LV geometry patterns based on EMINCA diagnostic thresholds.
| Outcomes | EMINCA typing | N (%) | HR (univariable) | HR (multivariable) | |
|---|---|---|---|---|---|
| Primary outcome | Incidence of composite endpoints | NG | 5225 (68.0) | − | − |
| CR | 598 (7.8) | 1.458 (1.168–1.818, p = 0.001) | 1.225 (0.981–1.530, p = 0.074) | ||
| EH | 1502 (19.6) | 1.349 (1.166–1.561, p < 0.001) | 1.169 (1.009–1.354, p = 0.037) | ||
| CH | 355 (4.6) | 2.291 (1.833–2.864, p < 0.001) | 1.902 (1.519–2.382, p < 0.001) | ||
| Secondary outcomes | Incidence of stroke | NG | 5225 (68.0) | — | — |
| CR | 598 (7.8) | 1.544 (1.175–2.030, p = 0.002) | 1.371 (1.041–1.806, p = 0.025) | ||
| EH | 1502 (19.6) | 1.188 (0.982–1.437, p = 0.077) | 1.045 (0.862–1.267, p = 0.654) | ||
| CH | 355 (4.6) | 2.012 (1.504–2.692, p < 0.001) | 1.761 (1.315–2.359, p < 0.001) | ||
| Incidence of hospitalization for HF | NG | 5225 (68.0) | — | — | |
| CR | 598 (7.8) | 1.399 (0.838–2.334, p = 0.199) | 0.994 (0.690–1.432, p = 0.973) | ||
| EH | 1502 (19.6) | 1.659 (1.217–2.262, p = 001) | 1.213 (0.971–1.515, p = 0.090) | ||
| CH | 355 (4.6) | 3.519 (2.314–5.352, p < 0.001) | 1.655 (1.167–2.347, p = 0.005) | ||
| Incidence of hospitalization for CAD | NG | 5225 (68.0) | — | — | |
| CR | 598 (7.8) | 1.254 (0.872–1.803, p = 0.222) | 1.110 (0.663–1.860, p = 0.690) | ||
| EH | 1502 (19.6) | 1.450 (1.163–1.807, p = 0.001) | 1.386 (1.013–1.895, p = 0.041) | ||
| CH | 355 (4.6) | 2.198 (1.561–3.095, p < 0.001) | 2.614 (1.709–3.999, p < 0.001) |
Note: Hazard ratios are represented with point estimates and a 95% confidence interval. Multivariable analysis was adjusted for confounding factors, including age, sex, fasting blood glucose, total cholesterol, obesity status, smoking habits, alcohol consumption, and physical activity levels. A p‐value of < 0.05 signifies statistical significance.
Abbreviations: CAD, Coronary Artery Disease; CH, Concentric Hypertrophy; CR, Concentric Remodeling; EH, Eccentric Remodeling; H, Hazard ratios; HF, Heart Failure; MI, Myocardial Infarction; NG, Normal Geometry.
3.3. Influence of Achieved BP on Prognosis by Different LV Geometry
We intend to clarify whether a lower achieved SBP could improve outcomes in the patients with different LV geometries. We further divided hypertensive patients into three groups by average follow‐up SBP (over 140 mmHg, 130∼140 mmHg, below 130 mmHg) respectively.
For individuals with NG and EH, we did not detect the significant correlation between achieved SBP and cumulative incidence of primary endpoint, which might be attributed to the relatively short follow‐up period and lower intrinsic cardiovascular risks (Figure 3A and 3C based on the EMINICA typing and Figure 4A and 4C based on the ASE/EACVI typing). For individuals with CH, multivariable Cox regression demonstrated that the cumulative incidence of primary endpoint reduced significantly in the group achieving a SBP below 130 mmHg compared to other three groups (Figure 3D based on the EMINCA typing and Figure 4D based on the ASE/EACVI typing). Unexpectedly, we found that the cumulative incidence of primary endpoint events and hospitalization for CAD was significantly increased in the individuals with an achieved SBP below 130 mmHg than other groups for CR group (Figure 3B based on the EMINICA typing and Figure 4B based on the guideline‐recommended typing).
FIGURE 3.
Forest plot showing adjusted hazard ratios for primary outcomes in individuals with hierarchically achieved systolic BP across four groups using EMINCA diagnostic thresholds. Adjusted hazard ratios are depicted with point estimates and a 95% confidence interval. Multivariable analysis was conducted, adjusting for confounding factors such as age, sex, fasting blood glucose, total cholesterol, obesity status, smoking habits, alcohol consumption, and physical activity levels. A p‐value of < 0.05 signifies statistical significance.
FIGURE 4.
Forest plot displaying adjusted hazard ratios for primary outcomes in individuals with hierarchically achieved systolic BP across four groups using ASE/EACVI diagnostic thresholds. Adjusted hazard ratios are depicted with point estimates and a 95% confidence interval. Multivariate analysis was conducted, adjusting for confounding factors such as age, sex, fasting blood glucose, total cholesterol, obesity status, smoking habits, alcohol consumption, and physical activity levels. A p‐value of < 0.05 signifies statistical significance.
Then we calculated the hazard ratios (HRs) of primary and secondary endpoints of individuals with different achieved SBP in four LV geometric groups categorized by EMINCA and ASE/EACVI‐guided diagnostic thresholds (Table 3, 4, 5, 6 and Table S3, respectively). We obtained similar findings, demonstrating that a significant reduction in primary endpoint events and stroke of patients whose achieved systolic BP fell below 130 mmHg could only be observed in the subgroup with CH (Multivariable HR = 0.342 for primary endpoint, 95%CI 0.162–0.719; HR = 0.279 for stroke 95% CI 0.099–0.788) (Table 6). However, an achieved SBP lower than 130 mmHg was associated higher risk of primary endpoints in the patients with CR, which mainly was ascribed to the increase of hospitalization of CAD (Table 4).
TABLE 3.
Univariate and multivariable hazard ratios of outcomes for hierarchical achieved SBP for NG based on EMINCA diagnostic thresholds.
| Outcomes | Achieved BP level | Event count | N (%) | HR (univariable) | HR (multivariable) | |
|---|---|---|---|---|---|---|
| Primary outcome | Incidence of composite endpoints | SBP > 140 mmHg | 623 | 2692 (51.6) | — | — |
| 130 < SBP ≤ 140 mmHg | 1371 (26.2) | 1.028 (0.853–1.238, p = 0.770) | 1.112 (0.922–1.341, p = 0.267) | |||
| SBP ≤ 130 mmHg | 1162 (22.2) | 0.917 (0.748–1.123, p = 0.401) | 1.024 (0.835–1.257, p = 0.819) | |||
| Secondary outcomes | Incidence of stroke | SBP > 140 mmHg | 388 | 2692 (51.6) | — | — |
| 130 < SBP ≤ 140 mmHg | 1371 (26.2) | 0.975 (0.770–1.236, p = 0.837) | 1.051 (0.829–1.333, p = 0.681) | |||
| SBP ≤ 130 mmHg | 1162 (22.2) | 0.819 (0.629–1.065, p = 0.136) | 0.895 (0.687–1.168, p = 0.415) | |||
| Incidence of hospitalization for HF* | SBP > 140 mmHg | 117 | 2692 (51.6) | — | — | |
| 130 < SBP ≤ 140 mmHg | 1371 (26.2) | 1.316 (0.861–2.010, p = 0.205) | 1.371 (0.892–2.109, p = 0.151) | |||
| SBP ≤ 130 mmHg | 1162 (22.2) | 1.160 (0.729–1.844, p = 0.531) | 1.303 (0.815–2.082, p = 0.269) | |||
| Incidence of hospitalization for CAD | SBP > 140 mmHg | 243 | 2692 (51.6) | — | — | |
| 130 < SBP ≤ 140 mmHg | 1371 (26.2) | 1.110 (0.820–1.502, p = 0.498) | 1.207 (0.889–1.638, p = 0.227) | |||
| SBP ≤ 130 mmHg | 1162 (22.2) | 1.141 (0.833–1.563, p = 0.412) | 1.330 (0.969–1.826, p = 0.077) | |||
Note: Hazard ratios (HR) are provided with point estimates and a 95% confidence interval. The multivariable analysis methodology mirrors the one previously described. A p‐value of < 0.05 indicates statistical significance.
TABLE 4.
Univariate and multivariable hazard ratios of outcomes for hierarchical achieved SBP for concentric remodeling based on EMINCA diagnostic thresholds.
| Outcomes | Achieved BP level | Event count | N (%) | HR (univariable) | HR (multivariable) | |
|---|---|---|---|---|---|---|
| Primary outcome | Incidence of composite endpoints | SBP > 140 mmHg | 98 | 308 (51.5) | — | — |
| 130 < SBP ≤ 140 mmHg | 146 (24.4) | 1.191 (0.719–1.973, p = 0.496) | 1.246 (0.750–2.072, p = 0.395) | |||
| SBP ≤ 130 mmHg | 144 (24.1) | 1.637 (1.034–2.591, p = 0.035) | 1.832 (1.153–2.911, p = 0.010) | |||
| Secondary outcomes | Incidence of stroke | SBP > 140 mmHg | 60 | 308 (51.5) | — | — |
| 130 < SBP ≤ 140 mmHg | 146 (24.4) | 0.998 (0.527–1.890, p = 0.996) | 1.060 (0.558–2.016, p = 0.858) | |||
| SBP ≤ 130 mmHg | 144 (24.1) | 1.117 (0.607–2.058, p = 0.722) | 1.219 (0.658–2.255, p = 0.529) | |||
| Incidence of hospitalization for HF | SBP > 140 mmHg | 17 | 308 (51.5) | — | — | |
| 130 < SBP ≤ 140 mmHg | 146 (24.4) | 0.328 (0.069–1.561, p = 0.161) | 0.324 (0.066–1.581, p = 0.163) | |||
| SBP ≤ 130 mmHg | 144 (24.1) | 0.664 (0.197–2.238, p = 0.509) | 0.707 (0.206–2.427, p = 0.582) | |||
| Incidence of hospitalization for CAD | SBP > 140 mmHg | 42 | 308 (51.5) | — | — | |
| 130 < SBP ≤ 140 mmHg | 146 (24.4) | 1.284 (0.574–2.874, p = 0.543) | 1.293 (0.571–2.931, p = 0.538) | |||
| SBP ≤ 130 mmHg | 144 (24.1) | 2.082 (1.023–4.238, p = 0.043) | 2.351 (1.145–4.830, p = 0.020) | |||
Note: HR are provided with point estimates and a 95% confidence interval. A p‐value of < 0.05 indicates statistical significance.
TABLE 5.
Univariate and multivariable hazard ratios of outcomes for hierarchical achieved SBP for ER based on EMINCA diagnostic thresholds.
| Outcomes | Achieved BP level | Event count | N (%) | HR (univariable) | HR (multivariable) | |
|---|---|---|---|---|---|---|
| Primary outcome | Incidence of composite endpoints | SBP > 140 mmHg | 256 | 872 (58.0) | — | — |
| 130 < SBP ≤ 140 mmHg | 354 (23.6) | 0.928 (0.684–1.259, p = 0.630) | 0.949 (0.698–1.290, p = 0.737) | |||
| SBP ≤ 130 mmHg | 276 (18.4) | 0.993 (0.719–1.373, p = 0.968) | 0.984 (0.710–1.362, p = 0.921) | |||
| Secondary outcomes | Incidence of stroke | SBP > 140 mmHg | 148 | 872 (58.0) | — | — |
| 130 < SBP ≤ 140 mmHg | 354 (23.6) | 0.907 (0.611–1.347, p = 0.628) | 0.957 (0.642–1.425, p = 0.827) | |||
| SBP ≤ 130 mmHg | 276 (18.4) | 0.749 (0.473–1.186, p = 0.218) | 0.752 (0.473–1.196, p = 0.228) | |||
| Incidence of hospitalization for HF | SBP > 140 mmHg | 65 | 872 (58.0) | — | — | |
| 130 < SBP ≤ 140 mmHg | 354 (23.6) | 1.037 (0.571–1.884, p = 0.905) | 1.130 (0.622–2.054, p = 0.688) | |||
| SBP ≤ 130 mmHg | 276 (18.4) | 0.991 (0.519–1.892, p = 0.978) | 0.897 (0.464–1.737, p = 0.748) | |||
| Incidence of hospitalization for CAD | SBP > 140 mmHg | 114 | 872 (58.0) | — | — | |
| 130 < SBP ≤ 140 mmHg | 354 (23.6) | 1.133 (0.722–1.778, p = 0.586) | 1.180 (0.751–1.855, p = 0.473) | |||
| SBP ≤ 130 mmHg | 276 (18.4) | 1.325 (0.834–2.105, p = 0.233) | 1.294 (0.811–2.063, p = 0.279) | |||
Note: HR are provided with point estimates and a 95% confidence interval. A p‐value of < 0.05 indicates statistical significance.
TABLE 6.
Univariate and multivariable hazard ratios of outcomes for hierarchical achieved SBP for CH based on EMINCA diagnostic thresholds.
| Outcomes | Achieved BP level | Event count | N (%) | HR (univariable) | HR (multivariable) | |
|---|---|---|---|---|---|---|
| Primary outcome | Incidence of composite endpoints | SBP > 140 mmHg | 88 | 205 (57.7) | — | — |
| 130 < SBP ≤ 140 mmHg | 84 (23.7) | 0.791 (0.477–1.312, p = 0.364) | 0.874 (0.523–1.460, p = 0.607) | |||
| SBP ≤ 130 mmHg | 66 (18.6) | 0.384 (0.184–0.805, p = 0.011) | 0.342 (0.162–0.719, p = 0.005) | |||
| Secondary outcomes | Incidence of stroke | SBP > 140 mmHg | 52 | 205 (57.7) | — | — |
| 130 < SBP ≤ 140 mmHg | 84 (23.7) | 0.540 (0.261–1.118, p = 0.097) | 0.551 (0.264–1.152, p = 0.113) | |||
| SBP ≤ 130 mmHg | 66 (18.6) | 0.305 (0.109–0.857, p = 0.024) | 0.279 (0.099–0.788, p = 0.016) | |||
| Incidence of hospitalization for HF | SBP > 140 mmHg | 27 | 205 (57.7) | — | ||
| 130 < SBP ≤ 140 mmHg | 84 (23.7) | 0.669 (0.248–1.801, p = 0.426) | 0.741 (0.274–2.005, p = 0.555) | |||
| SBP ≤ 130 mmHg | 66 (18.6) | 0.737 (0.249–2.181, p = 0.582) | 0.604 (0.201–1.815, p = 0.369) | |||
| Incidence of hospitalization for CAD | SBP > 140 mmHg | 38 | 205 (57.7) | — | — | |
| 130 < SBP ≤ 140 mmHg | 84 (23.7) | 1.218 (0.589–2.518, p = 0.595) | 1.352 (0.646–2.829, p = 0.424) | |||
| SBP ≤ 130 mmHg | 66 (18.6) | 0.594 (0.204–1.725, p = 0.338) | 0.547 (0.187–1.601, p = 0.271) | |||
Note: HR are provided with point estimates and a 95% confidence interval. A p‐value of < 0.05 indicates statistical significance.
3.4. Subgroup Analysis: Impact of BP on Prognosis of Patients With LV Concentric Remodeling
For preliminary interpretation of the reason why lower achieved SBP increase the cumulative incidence of CAD hospitalization in the patients with CR, we performed further review via subgroup analysis in the individuals with CR, which revealed a significant correlation between lower achieved SBP and higher CAD hospitalization was pronounced in those aged over 65, without diabetes, and females, but absent in younger, diabetic, or male patients (Figure 5).
FIGURE 5.
Adjusted hazard ratios for the primary outcome in patients with concentric remodeling across various interventional systolic BP levels in subgroup analysis.
4. Discussion
From the Guangdong provincial data sourced from the Chinese nationwide prospective cohort study, we deduced that the influence of achieved SBP on cardiovascular cumulative risks was differential based on LV geometry patterns using ethnicity‐specific echocardiographic criteria from the EMINICA study.
4.1. Ethnicity‐Specific Criteria of LV Geometrics
Two cohort studies in China (the EMINCA and WASE studies) have already identified the significant differences in the normal reference values for LV measurements across different ethnic and national groups [23, 24]. The definition of LVH and LV geometry patterns relies on echocardiographic parameters and the accurate diagnostic thresholds are ethnicity‐specific.
How to define the diagnostic thresholds for LVH is a decisive issue among specific races and populations？Sheng et al. have reported the remarkable differences in the normal reference values of major echocardiographic parameters between Chinese and western populations in the EMINCA study, including the LVM indexed to BSA, LAV index to BSA and RWT, signfied that the ethnic difference could bring the physiological variance in the echocardiographic measurement. Current thresholds set by the American Society of Echocardiography (ASE) and the European Association of Cardiovascular Imaging (EACVI) overestimated the proportion of CR and CH in the Chinese population [18]. Because Chinese healthy volunteers have smaller values of LVEDD and larger values of LVPWTd compared to the Caucasian whose data were used to establish the international guideline criteria, the cut‐off value of RWT is higher in Chinese than Caucasian.
In our study, we found that the proportion of individuals with NG was 68.0% (5225/7680) based on ethnicity‐specific diagnostic thresholds for the Chinese population, while the proportion of those with abnormal LV geometry was 32.0% (2455/7680), CH accounted for 4.6% of these (355/7680). In contrast, based on the international guideline criteria, the proportion of individuals with NG was 31.8% (2445/7680), while the proportion of those with abnormal LV geometry was 68.2% (5235/7680), with CH comprising 24.8% (1906/7680), in line with the previous reports [18]. Evidently, the international guidelines overestimate the proportion of individuals with abnormal LV geometry for hypertensive Chinese adults, which might lead to a misestimation of the overall cardiovascular risk for the Chinese hypertensive population.
A recent study reported that the prevalence of LVH in the Chinese population differs substantially by Chinese ethnicity‐specific or international guideline reference values. LVH defined by Chinese ethnicity‐specific reference values demonstrated a stronger association with cardiovascular mortality compared to international guideline reference values (HR 1.55, p < 0.001 vs. HR 1.31, p = 0.047) [19]. Therefore, we hypothesized that ethnicity‐specific echocardiographic criteria might be more apt for the Chinese hypertensive populace, especially in the cardiovascular risk stratification. Indeed, we verified firstly that the ethnicity‐specific criteria for LV measurement improved the risk discrimination of secondary endpoints compared to ASE/EAVCI guideline, underscoring its suitability in risk stratification of cardiovascular diseases for the Chinese population.
4.2. The Different Influences of Achieved BP on Prognosis by Four Distinct LV Geometrics
Then, we discussed the differences among influences of achieved SBP on prognosis by distinct LV geometrics based ethnicity‐specific criteria in Chinese. Contrarily, our findings could not correlate significantly a lower achieved SBP with reduced cardiovascular risks in patients with NR, CR, and EH, perhaps because of the limited follow‐up duration and the relatively lower intrinsic cardiovascular risks in these sub‐populations. The results of HRs are roughly similar regardless of the diagnostic thresholds from EMINCA study or ASE/EACVI guidelines. The diagnostic thresholds according to ASE/EACVI guidelines overestimated the frequencies of LV concentric remodeling and CH in Chinese population [20], resulting in relatively compromised but still significant HR values of primary endpoints compared to the ethnicity‐specific typing in CH and CR groups. In CR group, subjects might be more vulnerable to organ hypoperfusion due to the immoderate anti‐hypertensive therapy possibly. The results of HRs about the influence of achieved SBP on the secondary cardiovascular outcomes in EH group is erratic based on the ASE/EACVI diagnostic threshold, which might hint that the ASE/EACVI guideline‐recommended diagnostic threshold for the LV geometry typing could not be preferably appropriate for Chinese and even East Asians populations.
Our baseline data highlighted significant differences in conventional cardiovascular risk factors among four groups based on EMINICA categorization. CH patients exhibited higher proportions of hyperglycemia and obesity. Numerous studies have also proven that the advanced cardiac remolding and myocardial hypertrophy was also associated with the metabolic abnormality, included obesity and diabetes [25, 26, 27]. This correlation between LV CH and metabolic abnormalities suggests that individuals with both hypertension and metabolic dysfunction might benefit significantly from intensive hypertension treatments targeting lower SBP, in line with previous study that proved that the hypertensive patients with diabetes and obesity could profit from intensive anti‐hypertensive treatment for lower SBP target [28]. Meanwhile, although numerous clinical trials have affirmed the benefits from intensive anti‐hypertensive therapy and lower BP target (below 130/80 mmHg) in recent years, based on our data, the intensive anti‐hypertensive therapy brought benefits merely in the high‐risk patients with CH and it should be considered more vigorously in the high‐risk hypertensive patients defined by echocardiographic examination or other clinical conditions (such as obesity and diabetes).
4.3. The Imbalance Between Maintenance Vital Organ Perfusion and Benefits From Intensive Anti‐Hypertensive Strategy
In‐depth analyses regarding impact of achieved SBP on cardiovascular outcomes in CR patients yielded surprising findings: lower achieved SBP was inversely correlated with higher risks of primary endpoints and hospitalization for CAD. This might suggest potential side effects from hypotension, which might be involved in the vital organ hypoperfusion and relative ischemia because of increased requirement of coronary physical perfusion pressure and imbalance of oxygen demand and supply [29]. In CLARIFY registry study, for the patients with hypertension and stable CAD, both systolic BP of more than 140 mmHg and less than 120 mmHg disease would bring a increase of primary outcomes including cardiovascular death, myocardial infarction and stroke [30]. The observational study illustrated the J‐curve association of BP with cardiovascular outcomes in the patients with CAD, suggesting that the intensive anti‐hypertensive therapy should be prudent and conservative in patients with CAD, which support partially our deduction that hypotension might result in organ hypoperfusion and relative myocardial ischemia. Our results revealed that not all hypertensive patients should obtain a benefit from lower achieved SBP. Intriguingly, sub‐analyses revealed that younger individuals, males, and diabetic patients exhibit no these inverse correlations. These subsets of patients with CR were immune from the side‐effects from lower achieved SBP, maybe because males and diabetic patients were relatively high‐risk subpopulations and could benefit from lower achieved SBP more likely than low‐risk ones. Older patients are more vulnerable to hypotension and organ hypoperfusion. In previous post‐hoc analysis for some randomized clinical trials about the outcomes of older hypertensive patients who received the intensive anti‐hypertensive treatment, intensive treatment might bring more incidence of renal hypoperfusion and acute kidney failure [31, 32]. Meanwhile, CR were associated with extracardiac organ damage, including formation carotid plaque and sub‐clinical vascular alterations [33, 34, 35, 36]. These individuals might be more susceptible to organic hypoperfusion Another consideration for the cause is that follow‐up period of the study is relatively short. Therefore, the likelihood that lower achieved SBP is beneficial for long‐term cardiovascular outcomes is not entirely negated according to our data, especially in those patients with reversal of LVH eventually, which should be further explored afterward in the large‐scale, long‐term, prospective studies, and randomized clinical trials.
There are inherent limitations in our study. Firstly, while the study aim to analyze the varying impacts of achieved systolic BP on prognosis based on different LV geometry patterns, the choice of anti‐hypertensive drugs was not considered due to insufficient data. Some drugs, like angiotensin‐converting enzyme inhibitors and angiotensin receptor blockers, may offer additional benefits for patients with advanced LV hypertrophy. Secondly, our data is a retrospective analysis from a prospective cohort study. Thus, the main conclusion that a lower achieved SBP target benefits exclusively patients with CH requires further validation through a randomized controlled trial (RCT). Thirdly, the observed inverse correlation between achieved systolic BP and cardiovascular outcomes in patients with concentric remodeling is preliminary, and the statistical significance is relatively narrow. Future studies with larger sample sizes for CR patients are recommended. Fourthly, single measurement of follow‐up BP was a limitation of the current study. Time in Range (TIR) for achieved blood pressure (a SBP of below 130 mmHg) by Home blood pressure monitoring (HBPM) or ambulatory BP should be considered to a more ideal indicator for BP level in the future.
5. Conclusion
The article concluded two vital points as following: (1) Because of superior ability of cardiovascular risk stratification for secondary outcomes, we further clarify that the ethnicity‐specific echocardiographic criteria for definition of LV geometrics might be more appropriate for Chinese and even eastern Asian population; (2) LV geometrics based on ethnicity‐specific criteria should be applied to evaluate the eligibility for lower achieved SBP and intensive antihypertensive therapy.
5.1. Clinical Perspectives
Several clinical perspectives could be listed as following from our study:
1. Firstly, the study clarified further that the significance of ethnicity‐specific diagnostic thresholds for definition of abnormal LV geometrics in the hypertensive individuals, which could preferably stratify the cardiovascular risks for Chinese and even eastern Asian populations.
2. Secondly, according to the study, we primarily put forward a concept that lower achieved SBP could bring exclusively additional benefits for those with CH and higher cardiovascular disease risk, defined by accessible cardiovascular imaging tool. Meanwhile, we unexpectedly discovered that the individuals with CR might be more likely to suffer intolerance owing to lower achieved SBP. Therefore, the study emphasized the significance of evaluation of LV geometric patterns by echocardiographical examination for the individualized decision of achieved SBP in the hypertensive therapeutics.
3. Thirdly, randomized control trial about intensive anti‐hypertensive therapy strategy should be given more attention for hypertensive patients with different LV geometric patterns in the future.
Disclosure
The authors have nothing to report.
Conflicts of Interest
The authors declare no conflict of interest.
Supporting information
Supporting Information: jch70275‐sup‐0001‐SupMat.doc
Acknowledgment
We sincerely appreciated the funding provided by the Guangzhou Municipal Science and Technology Bureau Basic Research Program Project (2023A04J0510) and the General Project from National Natural Science Foundation of China (82570592) and Chinese National Key Research and Development Program (2018YFC1312404, 2017YFC1310803, 2017YFC1310801) from the Ministry of Science and Technology, Ministry of Finance, and the National Health Commission of China. Our gratitude extends to the working team of the China Patient‐centered Evaluative Assessment of Cardiac Events Million Persons Project (PEACE MPP) and assistance from the Chinese National Center for Cardiovascular Diseases (NCCD). We are indebted to the Health Commission of Guangdong Province and the Guangdong Provincial Center for Disease Control and Prevention for facilitating access to endpoint event data. Lastly, we extend our heartfelt thanks to all the staff and general practitioners from the nine recruitment locations in Guangdong Province, China, for their dedication.
Data Availability Statement
The raw data about the endpoint events underlying this article cannot be shared publicly due to or the privacy of individuals and public policy that participated in the study. The data will be shared on reasonable request to the corresponding author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting Information: jch70275‐sup‐0001‐SupMat.doc
Data Availability Statement
The raw data about the endpoint events underlying this article cannot be shared publicly due to or the privacy of individuals and public policy that participated in the study. The data will be shared on reasonable request to the corresponding author.