Abstract
Abstract
Objectives
To investigate the association between systolic blood pressure time in target range (SBP-TTR) and the risk of all-cause mortality in patients with atherosclerotic cardiovascular disease (ASCVD).
Design
Analysis of data from a prospective cohort.
Setting
This study used data from the Kailuan Study. Participants diagnosed with ASCVD from 11 hospitals affiliated with the Kailuan Group in Tangshan, China were included in the analysis.
Participants
We included 6732 participants who developed ASCVD between 1 July 2006 and 31 December 2013, and who had two or more blood pressure measurements recorded between the ASCVD diagnosis date and 31 December 2017. All participants were followed up until 31 December 2022.
Outcome measures
SBP-TTR was defined as the proportion of time during which SBP remained within the target range, calculated using the linear interpolation method. Participants were stratified into five SBP-TTR categories: 0%, >0% to <25%, 25% to <50%, 50% to <75% and ≥75%. Associations between SBP-TTR categories and all-cause mortality were evaluated.
Results
When the target SBP range was defined as 120–140 mm Hg, compared with the SBP-TTR=0% group, the multivariable-adjusted HRs (95% CIs) for all-cause mortality were 0.92 (0.78 to 1.07), 0.82 (0.72 to 0.94), 0.79 (0.68 to 0.92) and 0.76 (0.65 to 0.89) for the SBP-TTR groups of <25%, 25% to <50%, 50% to <75% and ≥75%, respectively. For each SD increase in SBP-TTR, the risk of all-cause mortality decreased, with a multivariable-adjusted HR of 0.90 (95% CI 0.85 to 0.95). The inverse association between SBP-TTR and all-cause mortality was more pronounced in younger participants (aged <67 years) (p for interaction=0.008).
Conclusions
This study demonstrated a significant inverse association between SBP-TTR and all-cause mortality among patients with ASCVD. The association between maintaining SBP within the 120–140 mm Hg target range and reduced mortality was more evident in younger individuals. These findings suggest that sustained and stable blood pressure control may improve long-term survival in patients with ASCVD.
Trial registration number
ChiCTR-TNC-11001489.
Keywords: Blood Pressure, Cardiovascular Disease, Mortality
STRENGTHS AND LIMITATIONS OF THIS STUDY.
The study features a long-term follow-up period.
Blood pressure measurements were standardised, and comprehensive covariate data were collected.
Systolic blood pressure data were obtained from biennial physical examinations, resulting in a relatively long interval between measurements.
The observational design limits the strength of causal inferences.
Data on specific causes of death were not available.
Introduction
Atherosclerotic cardiovascular disease (ASCVD) is the second leading cause of mortality worldwide and the leading cause of death in China, accounting for approximately 25% of all-cause mortality.1 It remains a major contributor to premature mortality, reduced life expectancy, workforce attrition and increased healthcare costs.2 3 Despite extensive preventive measures, the prevalence of ASCVD continues to rise. This trend is attributable not only to increasing incidence but also to improved medical technologies that prolong survival in affected patients. Controlling risk factors and reducing mortality remain central to secondary prevention in ASCVD. Hypertension represents a particularly critical modifiable target, as both randomised controlled trials and clinical observational studies have consistently demonstrated that lowering systolic blood pressure (SBP) effectively reduces mortality risk in patients with ASCVD.4,7
Meta-analyses indicate that achieving blood pressure targets (SBP/diastolic blood pressure (DBP) <130/80 mmHg) is associated with a reduced mortality risk compared with not achieving these targets. Each 10 mm Hg reduction in SBP correlates with a 13% lower risk of all-cause mortality.8 Clinical observational studies further confirm that effective blood pressure control significantly reduces mortality risk in patients with myocardial infarction (MI) or stroke.8 9 Accordingly, major international guidelines consistently recommend a blood pressure target of <130/80 mm Hg for patients with established ASCVD.10 However, previous research has largely relied on single or short-term blood pressure measurements to assess control, whereas ASCVD patients typically require long-term, often lifelong, blood pressure management. Earlier studies primarily focused on absolute blood pressure values but often overlooked blood pressure variability over time. Doumas et al11 introduced the concept of time in target range (TTR), a metric that integrates both the average blood pressure and its variability across extended follow-up periods. This approach better reflects the sustainability and stability of blood pressure control in real-world clinical practice. Subsequent studies12,14 have established an inverse association between higher TTR and a lower risk of adverse outcomes, including ASCVD-related events. Notably, the specific relationship between SBP-TTR and all-cause mortality in patients with ASCVD remains unexplored. Therefore, using data from the Kailuan Study, this research aims to investigate the association between SBP-TTR and all-cause mortality in this patient population.
Methods
Study population
The Kailuan Study is a prospective cohort study investigating risk factors for cardiovascular and cerebrovascular diseases.15 In brief, the study recruited a total of 101 510 community-dwelling adults (aged 18–98 years; 81 110 men), all of whom completed a baseline survey between June 2006 and October 2007. Participants underwent questionnaire assessments, physical examinations and laboratory tests at 1 of 11 hospitals affiliated with the Kailuan Group. Follow-up assessments were conducted biennially, with annual documentation of chronic disease incidence (including cardiovascular events) and mortality. By 31 December 2022, eight complete follow-up cycles had been completed over the 16-year observation period.
This nested cohort study within the Kailuan Study included 10 930 participants who developed ASCVD between 1 July 2006 and 31 December 2013. ASCVD was defined as a history of MI, ischaemic stroke (IS) or prior coronary stent implantation (CSI). We applied the following exclusion criteria: (1) individuals who completed only one annual health examination between the date of ASCVD diagnosis and 31 December 2017 (n=3464) and (2) participants with fewer than two recorded SBP measurements during follow-up, despite having completed at least two annual health examinations (n=734). After exclusions, the final analytical cohort consisted of 6732 participants (online supplemental figure S1).
Blood pressure measurements and definition of TTR
Blood pressure measurements were conducted by trained healthcare professionals between 7:00 and 9:00 on the day of the health examination. Participants were instructed to rest in a comfortable position for at least 15 min prior to measurement and to remain quiet during the procedure. During the follow-up period from 2006 to 2012, a calibrated desktop mercury sphygmomanometer was used to measure blood pressure in the right brachial artery. SBP was recorded at the first Korotkoff sound, and DBP at the fifth Korotkoff sound. From the 2014 follow-up onward, an electronic sphygmomanometer (HEM-8102A; Omron Healthcare, Matsusaka, Japan) was used. SBP-mean refers to the average of all SBP measurements obtained during follow-up until 31 December 2022.
In accordance with current guidelines, SBP-TTR was defined as the proportion of time during which SBP remained within the target range of 120–140 mm Hg relative to the total exposure period. The total exposure period was calculated from the date of the first physical examination following an ASCVD diagnosis to the date of the 2016 annual examination. For participants with missing SBP data in 2016, the endpoint of the total exposure period was set as the date of the last available examination with valid SBP measurements prior to the 2016 assessment. TTR was estimated using linear interpolation.16 This method assumes a linear relationship between two consecutive blood pressure measurements and calculates the proportion of time during which the blood pressure remained within the target range. Participants were categorised into five SBP-TTR groups: 0%, >0% to <25%, 25% to <50%, 50% to <75% and ≥75%.
Covariates
Trained staff administered a standard questionnaire to collect information on sex, age, height, weight, waist circumference, occupational status and lifestyle habits including sleep patterns, smoking, alcohol consumption, physical activity and diet. Note that race and ethnicity were not included in the analysis since the Kailuan Study is a community-based cohort conducted in Tangshan, China, in which the vast majority of participants are of Han Chinese ethnicity, and race/ethnicity data were not systematically collected. The measurement protocols for height, weight and waist circumference have been described previously.15 17 Laboratory analyses were performed by the same team using an automated biochemical analyser (Hitachi 747; Hitachi, Tokyo, Japan) according to the manufacturer’s reagent instructions. Participants fasted for at least 8 hours before a 5 mL venous blood sample was collected at 7:00 AM. Serum was promptly separated and analysed within 4 hours. Measurements included fasting blood glucose (FBG), high-sensitivity C reactive protein (hs-CRP), serum creatinine (Scr), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C). Diabetes mellitus was defined as a self-reported history of diabetes, current use of insulin or oral hypoglycaemic agents, or an FBG level >126 mg/dL.18 The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.19 20 For males: eGFR=141 × min(Scr/κ, 1)ˆα×max(Scr/κ, 1)ˆ−1.209×0.993ˆage. For females: eGFR=141 × min(Scr/κ, 1)ˆα×max(Scr/κ, 1)ˆ−1.209×0.993ˆage×1.018.
Clinical outcomes and follow-up time
The primary endpoint of this study was all-cause mortality. Follow-up for all participants began on the date of their 2016 annual health examination (baseline) and continued until either death or the administrative censoring date of 31 December 2022, whichever occurred first. For participants whose SBP was not recorded at the 2016 examination, the follow-up start date was assigned as the date of the last available examination prior to 2016 that included a valid SBP measurement. Mortality data were validated annually by certified physicians using death certificates obtained from the provincial vital statistics office, ensuring consistent adjudication across the entire study cohort.
Statistical analysis
The normality of continuous variables was assessed through visual inspection of histograms and Q-Q plots, supplemented by formal statistical tests where appropriate. Continuous variables with an approximately normal distribution are presented as mean±SD, while skewed variables are summarised as median with IQR. Categorical variables are presented as counts and percentages. Missing data were handled using multiple imputation. To describe longitudinal trends, the mean SBP at each health examination during the exposure period was plotted. The association between SBP-TTR and all-cause mortality was evaluated using Cox proportional hazards regression models. Two models were constructed, both adjusted for the following confounders: Model 1 was adjusted for age and sex; Model 2 was further adjusted for baseline SBP, body mass index (BMI), LDL-C, HDL-C, FBG, hs-CRP, eGFR, smoking status, alcohol consumption, physical activity, education level and use of antihypertensive, hypoglycaemic or lipid-lowering medications. The restricted cubic spline models for all-cause mortality were displayed with three knots at the 10th, 50th and 90th percentiles of SBP-TTR.
Several sensitivity analyses were conducted to assess the robustness of the findings: (1) The SBP target range was redefined as 110–130 mm Hg to examine its association with all-cause mortality. (2) All-cause mortality events occurring within the first year of follow-up were excluded to minimise potential reverse causality. (3) To evaluate whether the association of SBP-TTR was independent of average SBP and its variability, SBP-mean and SBP-SD were separately added to the fully adjusted model. (4) To verify the robustness of the exposure period definition, an analysis was restricted to participants with complete SBP data at the 2016 examination. (5) To assess the potential impact of missing covariate data, a complete-case analysis was performed without imputation.
To examine whether the association between SBP-TTR and all-cause mortality varied across population subgroups, multiplicative interaction terms were introduced between SBP-TTR (per SD increase) and the following variables: age (above/below median), sex, diabetes status, exposure duration (above/below median), and ASCVD classification. Stratified Cox analyses were subsequently performed.
All statistical analyses were conducted using SAS V.9.4 (SAS Institute) and Stata V.16 (StataCorp). All p values were two-sided, with p<0.05 considered statistically significant.
Patient and public involvement
None.
Results
Study population characteristics
A total of 6732 participants were included in this analysis. Details regarding missing covariates are provided in online supplemental table S1. The mean age was 67.12±9.08 years, and 5847 participants (86.85%) were male. Among the cohort, 2978 (44.24%) had a history of MI or prior CSI, and 3754 (55.76%) had IS. The mean SBP was 146.57±21.26 mmHg, and the median number of blood pressure measurements recorded during the exposure period was 3 (IQR: 2, 4). The median SBP-TTR was 29% (IQR: 0%, 60%). Baseline characteristics are presented in table 1. Compared with participants with an SBP-TTR of 0%, those with an SBP-TTR≥75% were younger, had lower baseline levels of SBP, BMI, FBG, LDL-C, HDL-C and hs-CRP, and included a higher proportion of males.
Table 1. Baseline characteristics of participants according to SBP-TTR.
| Total | TTR=0% | 0%<TTR<25% | 25%≤TTR<50% | 50%≤TTR<75% | TTR≥75% | P value | |
|---|---|---|---|---|---|---|---|
| (N=6732) | (N=2348) | (N=768) | (N=1326) | (N=1160) | (N=1130) | ||
| Age (years) | 67.12±9.08 | 68.68±8.64 | 68.15±8.38 | 66.78±9.19 | 65.64±9.27 | 65.09±9.42 | <0.001 |
| Male (%) | 5847 (86.85) | 2047 (87.18) | 652 (84.90) | 1136 (85.67) | 1000 (86.21) | 1012 (89.56) | 0.016 |
| SBP (mm Hg) | 146.57±21.26 | 159.64±20.13 | 147.74±23.03 | 143.44±20.03 | 137.31±15.84 | 131.79±9.38 | <0.0001 |
| BMI (kg/m2) | 25.42±3.25 | 25.66±3.32 | 25.58±3.47 | 25.29±3.11 | 25.21±3.28 | 25.18±3.07 | <0.001 |
| FBG (mmol/L) | 6.39±2.13 | 6.56±2.21 | 6.36±2.14 | 6.36±2.13 | 6.30±2.11 | 6.14±2.02 | <0.001 |
| LDL-C (mmol/L) | 2.83±0.87 | 2.86±0.88 | 2.85±0.91 | 2.85±0.84 | 2.80±0.85 | 2.76±0.86 | 0.011 |
| HDL-C (mmol/L) | 1.41±0.43 | 1.41±0.43 | 1.42±0.43 | 1.42±0.44 | 1.40±0.41 | 1.38±0.42 | 0.063 |
| eGFR (mL/min·1.73 m2) | 82.05±18.20 | 79.00±18.69 | 81.85±17.84 | 82.37±18.09 | 85.25±17.03 | 84.86±17.67 | <0.0001 |
| Hs-CRP (mg/L) | 2.80±4.01 | 3.10±4.37 | 2.48±3.64 | 2.75±3.91 | 2.55±3.68 | 2.66±3.88 | <0.001 |
| Smoking (%) | 1746 (25.94) | 523 (22.27) | 203 (26.40) | 358 (27.00) | 332 (28.62) | 330 (29.23) | 0.0613 |
| Drinking (%) | 1473 (21.88) | 477 (20.32) | 164 (21.35) | 288 (21.72) | 283 (24.40) | 261 (23.10) | 0.067 |
| Exercising (%) | 1143 (16.98) | 387 (16.48) | 144 (18.75) | 210 (15.84) | 207 (17.84) | 195 (17.26) | 0.402 |
| High school and above (%) | 1115 (16.56) | 384 (16.35) | 105 (13.67) | 236 (17.80) | 184 (15.86) | 206 (18.23) | 0.064 |
| Take antihypertensive drug (%) | 1630 (24.21) | 755 (32.16) | 198 (25.78) | 286 (21.57) | 221 (19.05) | 170 (15.04) | <0.001 |
| Take hypoglycaemic drug (%) | 652 (9.69) | 240 (10.22) | 77 (10.03) | 129 (9.73) | 115 (9.91) | 91 (8.05) | 0.356 |
| Take lipid-lowering drug (%) | 550 (8.17) | 182 (7.75) | 62 (8.07) | 107 (8.07) | 108 (9.31) | 91 (8.05) | <0.001 |
| Take antiplatelet drug (%) | 1958 (29.08) | 704 (29.98) | 215 (27.96) | 359 (27.07) | 342 (29.48) | 338 (29.94) | 0.345 |
BMI, body mass index; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; hs-CRP, high-sensitivity C reactive protein; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; SBP-TTR, systolic blood pressure time in target range.
SBP-TTR and all-cause mortality
During a mean follow-up of 5.66±2.60 years, 1863 deaths from all causes occurred. Throughout the exposure period, participants who died had consistently higher SBP levels compared with those who survived (online supplemental figure S2). In analyses adjusted for multiple confounders, using the SBP-TTR=0% group as the reference, the HRs and 95% CIs for all-cause mortality were 0.92 (0.78 to 1.07) for SBP-TTR<25%, 0.82 (0.72 to 0.94) for SBP-TTR 25% to <50%, 0.79 (0.68 to 0.92) for SBP-TTR 50% to <75% and 0.76 (0.65 to 0.89) for SBP-TTR≥75%. Furthermore, each SD increase in SBP-TTR was associated with a reduction in all-cause mortality risk, with an adjusted HR of 0.90 (95% CI 0.85 to 0.95) (figure 1). The adjusted cubic spline curves fitted for the Cox model showed that SBP-TTR was inversely associated with the risk of all-cause death (figure 2).
Figure 1. Association of all-cause mortality with SBP-TTR model adjusted for age, sex, baseline SBP, BMI, FBG, LDL-C, HDL-C, hs-CRP, eGFR, smoking, drinking, exercising, education, take antihypertensive drug, take hypoglycaemic drug, take lipid-lowering drug and take antiplatelet drug. BMI, body mass index; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; hsCRP, high-sensitivity C reactive protein; LDL-C, low-density lipoprotein cholesterol; SBP-TTR, systolic blood pressure time in target range.
Figure 2. Restricted cubic spline curve between systolic blood pressure time in target range and the risk of all-cause mortality. Spline analysis was performed with 0% as the reference. The model was adjusted for age, sex, baseline SBP, BMI, FBG, LDL-C, HDL-C, hs-CRP, eGFR, smoking, drinking, physical activity, education level and use of antihypertensive, hypoglycaemic, lipid-lowering and antiplatelet medications. BMI, body mass index; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; hsCRP, high-sensitivity C reactive protein; LDL-C, low-density lipoprotein cholesterol; SBP-TTR, systolic blood pressure time in target range.
Effect modification and sensitivity analyses
No evidence of effect modification was observed for the association between SBP-TTR and all-cause mortality by sex, diabetes status, exposure duration or ASCVD classification. However, when stratified by age, the association was stronger among younger participants (<67 years). Specifically, the interaction between SBP-TTR and age was statistically significant (P for interaction <0.05) (table 2).
Table 2. Associations between SBP-TTR and all-cause mortality in subgroup analyses.
| Subgroup | HR (95% CI) | P value | P for interaction |
|---|---|---|---|
| Age <67 years (N=3362) | 0.86 (0.77 to 0.94) | 0.002 | 0.008 |
| Age ≥67 years (N=3370) | 0.92 (0.86 to 0.99) | 0.022 | |
| Male (N=5847) | 0.81 (0.65 to 1.01) | 0.056 | 0.521 |
| Female (N=885) | 0.91 (0.85 to 0.96) | 0.001 | |
| Exposure duration <6 years (N=3021) | 0.93 (0.87 to 1.00) | 0.056 | 0.185 |
| Exposure duration >6 years (N=3711) | 0.87 (0.79 to 0.94) | 0.002 | |
| Non-diabetics (N=5535) | 0.90 (0.85 to 0.95) | 0.001 | 0.770 |
| Diabetics (N=1197) | 0.89 (0.76 to 1.04) | 0.136 | |
| MI or CSI patients (N=2978) | 0.95 (0.87 to 1.03) | 0.235 | 0.312 |
| IS patients (N=3754) | 0.88 (0.82 to 0.95) | 0.001 |
Model adjusted for age, sex, baseline SBP, BMI, FBG, LDL-C, HDL-C, hs-CRP, eGFR, smoking, drinking, physical activity, education level and use of antihypertensive, hypoglycaemic, lipid-lowering and antiplatelet medications.
BMI, body mass index; CSI, coronary stent implantation; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; hsCRP, high-sensitivity C reactive protein; IS, ischaemic stroke; LDL-C, low-density lipoprotein cholesterol; MI, myocardial infarction; SBP-TTR, systolic blood pressure time in target range.
When the SBP target range was redefined as 110–130 mm Hg, the multivariable-adjusted HR (95% CI) for all-cause mortality were 0.82 (0.69 to 0.97) for SBP-TTR<25%, 0.93 (0.80 to 1.09) for 25%≤SBP TTR <50%, 0.82 (0.69 to 0.99) for 50%≤SBP TTR <75% and 0.87 (0.72 to 1.06) for SBP-TTR≥75%, respectively. Similarly, each SD increase in SBP-TTR was associated with a lower risk of all-cause mortality, with an adjusted HR of 0.93 (95% CI 0.88 to 0.99) (table 3).
Table 3. Associations between SBP-TTR and all-cause mortality in sensitivity analyses.
| TTR=0% | 0%<TTR<25% | 25%≤TTR<50% | 50%≤TTR<75% | TTR ≥75% | TTR-SD | |
|---|---|---|---|---|---|---|
| SBP-TTR at 110–130 mm Hg | ||||||
| Model | Ref. | 0.82 (0.69 to 0.97) | 0.93 (0.80 to 1.09) | 0.82 (0.69 to 0.99) | 0.87 (0.72 to 1.06) | 0.93 (0.88 to 0.99) |
| 1-year lagged analysis | ||||||
| Model | Ref. | 0.94 (0.79 to 1.13) | 0.80 (0.69 to 0.94) | 0.79 (0.67 to 0.94) | 0.79 (0.66 to 0.94) | 0.90 (0.85 to 0.96) |
| Adjusted SBP-mean | ||||||
| Model | Ref. | 1.01 (0.85 to 1.18) | 0.98 (0.85 to 1.14) | 0.97 (0.82 to 1.14) | 0.95 (0.79 to 1.13) | 0.98 (0.92 to 1.04) |
| Adjusted SBP-SD | ||||||
| Model | Ref. | 0.83 (0.71 to 0.98) | 0.75 (0.65 to 0.86) | 0.74 (0.64 to 0.87) | 0.77 (0.66 to 0.90) | 0.90 (0.85 to 0.95) |
| Only including participants with complete SBP data in 2016 | ||||||
| Model | Ref. | 0.81 (0.61 to 1.07) | 0.61 (0.46 to 0.60) | 0.63 (0.46 to 0.86) | 0.64 (0.46 to 0.90) | 0.83 (0.74 to 0.93) |
| No imputation for missing covariates | ||||||
| Model | Ref. | 0.90 (0.76 to 1.06) | 0.81 (0.71 to 0.94) | 0.79 (0.68 to 0.92) | 0.76 (0.64 to 0.89) | 0.90 (0.86 to 0.95) |
Model adjusted for age, sex, baseline SBP, BMI, FBG, LDL-C, HDL-C, hs-CRP, eGFR, smoking status, alcohol consumption, physical activity, education level, and use of antihypertensive, hypoglycaemic, lipid-lowering, and antiplatelet medications.
BMI, body mass index; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; hsCRP, high-sensitivity C reactive protein; LDL-C, low-density lipoprotein cholesterol; SBP-TTR, systolic blood pressure time in target range.
In sensitivity analyses, consistent results were obtained after excluding participants who died within the first year of follow-up. When SBP-SD was included in the model instead of baseline SBP, the inverse associations remained significant. However, when SBP-mean was included instead, the associations were no longer significant. Among participants with complete SBP data in 2016 and in analyses without imputation for missing covariates, a significant inverse relationship between SBP-TTR and all-cause mortality was consistently observed.
Discussion
In this large retrospective cohort study, we demonstrated that sustained blood pressure control within the target range was associated with a significant reduction in all-cause mortality among ASCVD patients, exhibiting a dose–response relationship. However, lowering the blood pressure target to 110–130 mm Hg did not provide additional survival benefit. Furthermore, the inverse association between SBP-TTR and all-cause mortality was stronger in younger ASCVD patients (<67 years) compared with older individuals.
Active and effective blood pressure management is crucial for improving long-term prognosis in ASCVD patients. The ISCHEMIA trial further highlights the central role of blood pressure control in secondary prevention, indicating that early initiation and sustained adherence to guideline-directed medical therapy, combined with multifactorial risk factor modification, significantly improves clinical outcomes in patients with chronic coronary disease. Notably, achieving SBP control was associated with the strongest protective effect on cardiovascular risk (99.7%), exceeding that of LDL-C target attainment (84.4%).21 Our analysis supports these findings, as deceased ASCVD patients exhibited consistently elevated SBP levels during follow-up, reinforcing the critical link between blood pressure control and clinical prognosis.
Relying on single or short-term blood pressure measurements inadequately reflects the quality of hypertension management. In contrast, SBP-TTR serves as an indicator of the persistence and stability of achieving blood pressure targets, and its prognostic significance has been verified in several studies. A post hoc analysis of the SPRINT trial further demonstrated that SBP-TTR could predict major adverse cardiovascular events (MACE) in hypertensive patients, with each 1-SD increase in SBP-TTR (calculated over 3-month monitoring intervals) associated with a 19% reduction in MACE risk.22 Similar findings were observed in the MID-hypertension subgroup within a Chinese veteran cohort study, and an inverse correlation between SBP-TTR and cardiovascular risk was also confirmed in a Chinese elderly cohort.23 Notably, most existing evidence originates from general hypertensive populations without a prior ASCVD diagnosis, leaving the prognostic value of SBP-TTR in established ASCVD patients insufficiently explored. Our study provides the first empirical evidence of an inverse association between SBP-TTR and all-cause mortality in ASCVD patients, demonstrating a 10% reduction in mortality risk per 1-SD increase in SBP-TTR. These findings suggest that SBP-TTR may serve as a novel prognostic marker for secondary prevention in ASCVD, offering clinical insights to optimise personalised antihypertensive strategies and follow-up care. Compared with traditional single-measurement approaches, SBP-TTR provides a more comprehensive evaluation of blood pressure control consistency and sustainability. We advocate integrating SBP-TTR assessment into routine clinical practice for ASCVD secondary prevention to achieve sustained long-term prognostic benefits.
The observed associations between SBP-TTR and all-cause mortality were no longer significant when SBP-mean, rather than SBP-SD, was adjusted for in the model. These findings align with those reported by Buckley et al.13 This suggests that the blood pressure control characteristics captured by SBP-TTR and SBP-mean may partially overlap. However, this does not diminish the clinical utility of SBP-TTR. Compared with SBP-mean, SBP-TTR additionally incorporates the temporal dimension of blood pressure control, placing greater emphasis on evaluating the continuity and stability of management over time. In clinical practice, blood pressure often exhibits considerable variability across different time points in patients, and achieving target levels in single or short-term measurements does not necessarily equate to optimal long-term control. In this context, SBP-TTR serves as a valuable complement to traditional mean blood pressure metrics.
Furthermore, we evaluated the predictive value of TTR using an intensive SBP target range of 110–130 mm Hg and found that each SD increase in SBP-TTR was associated with a 7% reduction in all-cause mortality risk, a slightly less pronounced effect than the 10% risk reduction observed with the 120–140 mm Hg SBP target range. This suggests that intensive blood pressure control may not substantially enhance survival benefit in ASCVD patients. Current guidelines, notably, do not emphasise intensive blood pressure management for this population. The European guidelines for secondary prevention of IS recommend a blood pressure target below 130/80 mmHg.24 Similarly, the American Heart Association/American College of Cardiology guidelines state that a target of 140/90 mm Hg is reasonable for patients with coronary artery disease, though a target below 130/80 mm Hg may be more appropriate for those with a history of stroke or transient ischaemic attack.25 Nevertheless, a meta-analysis of 10 randomised controlled trials involving 40 710 patients with stroke or TIA showed that, compared with standard blood pressure lowering, intensive lowering did not reduce all-cause mortality risk (RR: 0.97, 95% CI 0.91 to 1.04), though it significantly reduced recurrent stroke risk (RR: 0.83, 95% CI 0.78 to 0.88).26 These findings suggest that the benefits of intensive blood pressure lowering in ASCVD patients may lie more in preventing cardiovascular events and improving quality of life, rather than in prolonging survival.
Subgroup analyses indicated that the inverse association between SBP-TTR and mortality was more pronounced in younger than in older adults. A study by Huang et al involving 3194 heart failure patients similarly found a stronger inverse association between SBP-TTR and adverse cardiovascular outcomes among younger patients.14 Li et al reported that each 20 mm Hg increment in SBP was associated with 42% and 70% higher risks of all-cause mortality and CVD in participants aged ≤60 years, vs 9% and 12% in those aged >80 years.27 This underscores the more substantial impact of elevated blood pressure in younger and middle-aged populations, suggesting that long-term blood pressure control may confer greater preventive and long-term benefits in these groups. Therefore, future ASCVD secondary prevention strategies should fully account for age-specific effects on blood pressure management, with consideration of more rigorous and personalised control approaches for younger and middle-aged patients.
Strengths and limitations
The primary strength of this study is its systematic evaluation—the first of its kind—of the association between SBP-TTR and all-cause mortality risk in patients with ASCVD, providing new evidence to inform blood pressure management strategies for secondary prevention in this population. Additional strengths include a long follow-up period, standardised blood pressure measurement methods and comprehensive covariate data collection, which together help control for confounding and enhance the reliability of the findings. Several limitations should also be acknowledged. First, owing to the observational nature of the present study, the strength of causal inferences regarding the beneficial effects of SBP-TTR is limited. Second, the lack of data on specific causes of death limits our ability to analyse mortality by underlying cause in ASCVD patients. Third, SBP data were obtained from biennial physical examinations; the relatively long interval between measurements may affect the precision of TTR estimation. Nevertheless, the extended follow-up period remains valuable for examining the relationship between long-term blood pressure control and mortality risk. Fourth, although multiple confounders were adjusted for in the analysis, residual confounding cannot be ruled out. Fifth, because TTR was calculated from the period after ASCVD diagnosis, individuals who died shortly after onset were not included in TTR estimation, which may introduce some selection bias. Finally, given the high proportion of male participants (86.85%), the generalisability of these findings requires further validation in other populations.
Conclusions
In summary, a significant inverse association exists between SBP-TTR and all-cause mortality risk in patients with ASCVD, particularly evident among younger individuals. The findings of this study provide real-world evidence to inform blood pressure management strategies for secondary prevention in this population.
Supplementary material
Acknowledgements
The authors thank all participants and contributors to the Kailuan Study.
Footnotes
Funding: This study was supported by the Scientific Research Foundation of SUMHS (SSF-23-14-002), the Clinical Research Project of Health Consortium (ynlglht202402) and the Shanghai Key Clinical Research Center Fund (Grant No. 2023ZZ02006).
Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2025-110956).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Ethics approval: The studies involving human participants were reviewed and approved by the Ethics Committee of the Kailuan General Hospital ((2006) Approval No. 5). Participants gave informed consent to participate in the study before taking part.
Data availability free text: Data from the Kailuan Study are not publicly available.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Data availability statement
Data sharing is not applicable as no datasets were generated and/or analysed for this study.
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