Systolic Blood Pressure Burden: A Novel Metric for Predicting Cardiovascular Outcomes in High Cardiovascular Risk Patients – Insights from the SPRINT Study

Moran Li, Jieying Shi, Minghui Chen, Qiaorui He, Bo Wang, Song Zhao, Yan Li, Yifan Zhao, Yi Zhang

PULSE · 2026-yil

Annotatsiya

Introduction: Conventional systolic blood pressure (SBP) indices, such as mean SBP or variability indices, fail to capture control consistency. SBP time in target range (TTR) improves risk prediction by measuring SBP control duration. However, it neglects the magnitude of SBP elevation, treating minor and severe elevations equally. We developed and validated the SBP burden, a novel metric integrating both the duration and magnitude of SBP elevation, to enhance cardiovascular risk prediction. Methods: This post hoc analysis of the SPRINT included 9,017 high-risk, nondiabetic participants (age, 67.0 [61.0–76.0] years; 64.7% men). SBP burden was calculated as the proportion of the over-target time multiplied by the over-target part proportion of SBP area under the curve [AUC] during that time, using SBP records in months 0–6 (target: 130 mm Hg). Its prediction performance was compared with mean SBP, SBP standard deviation (SD), SBP average real variability (ARV), SBP TTR, and SBP AUC. The primary outcome was the first occurrence of major adverse cardiovascular events (MACEs), including cardiovascular death (CVD death), myocardial infarction, stroke, and heart failure (HF) hospitalization. Results: Over a median follow-up of 3.89 years, 568 MACEs occurred. After adjusting for traditional risk co-variables, the SBP burden showed an independent linear association with MACEs (hazard ratio [HR], 95% confidence interval [CI]: 1.17, 1.09–1.26; p < 0.01) and this association remained even after further adjustment for SBP SD and ARV. Mean SBP (HR, 95% CI: 1.13, 1.03–1.23; p < 0.01), SBP SD (HR, 95% CI: 1.10, 1.01–1.19; p = 0.03), SBP ARV (HR, 95% CI: 1.10, 1.01–1.18; p = 0.02), SBP AUC (HR, 95% CI: 1.15, 1.05–1.26; p < 0.01), and SBP TTR (HR, 95% CI: 0.88, 0.80–0.97; p = 0.01) were also independent risk predictors. Further, we confirmed SBP burden acheived the greatest improvement in discrimination and reclassification (Net reclassification improvement as 0.12 [0.03–0.22]; integrated discrimination improvement as 0.0032 [0.0006–0.0076]), and feature importance (relative informativeness and LASSO ranking as top 1) among tested SBP indices. Conclusion: In high-risk, nondiabetic patients, SBP burden is an independent predictor of cardiovascular outcomes. It overcomes the limitations of SBP TTR, outperforming other SBP indices in predictive performance and feature importance for cardiovascular outcomes.

Maqola ma’lumotlari
MualliflarMoran Li, Jieying Shi, Minghui Chen, Qiaorui He, Bo Wang, Song Zhao, Yan Li, Yifan Zhao, Yi Zhang
JurnalPULSE
NashriyotPROFI университетининг
ISSN2074-1855, 2235-8668
Nashr sanasi2026-04-16
Jild14
Son1
Betlar93-104
TilIngliz
Ilmiy sohaPsixologiya
DOI10.1159/000551995
Indeksga qo‘shilgan2026-09-02

DOI: 10.1159/000551995 · Maqolaning asl sahifasi · PDF

Ilmiy soha

Psixologiya

Iqtibos keltirish

APAMoran Li, Jieying Shi, Minghui Chen, Qiaorui He, Bo Wang, Song Zhao, Yan Li, Yifan Zhao, & Yi Zhang (2026). Systolic Blood Pressure Burden: A Novel Metric for Predicting Cardiovascular Outcomes in High Cardiovascular Risk Patients – Insights from the SPRINT Study. PULSE, 14(1), 93-104. https://doi.org/10.1159/000551995
GOST (OAK)Moran Li va b. Systolic Blood Pressure Burden: A Novel Metric for Predicting Cardiovascular Outcomes in High Cardiovascular Risk Patients – Insights from the SPRINT Study // PULSE. – 2026. – T. 14, № 1. – P. 93-104. – DOI: 10.1159/000551995.
MLAMoran Li, Jieying Shi, Minghui Chen, Qiaorui He, Bo Wang, Song Zhao, Yan Li, Yifan Zhao, and Yi Zhang. “Systolic Blood Pressure Burden: A Novel Metric for Predicting Cardiovascular Outcomes in High Cardiovascular Risk Patients – Insights from the SPRINT Study.” PULSE, 14(1), 93-104, 2026. https://doi.org/10.1159/000551995
ChicagoMoran Li, Jieying Shi, Minghui Chen, Qiaorui He, Bo Wang, Song Zhao, Yan Li, Yifan Zhao, and Yi Zhang. “Systolic Blood Pressure Burden: A Novel Metric for Predicting Cardiovascular Outcomes in High Cardiovascular Risk Patients – Insights from the SPRINT Study.” PULSE, 14(1), 93-104 (2026). https://doi.org/10.1159/000551995
HarvardMoran Li, Jieying Shi, Minghui Chen, Qiaorui He, Bo Wang, Song Zhao, Yan Li, Yifan Zhao, and Yi Zhang (2026) ‘Systolic Blood Pressure Burden: A Novel Metric for Predicting Cardiovascular Outcomes in High Cardiovascular Risk Patients – Insights from the SPRINT Study’, PULSE, 14(1), 93-104. https://doi.org/10.1159/000551995
BibTeX
@article{moranli2026,
  title = {Systolic Blood Pressure Burden: A Novel Metric for Predicting Cardiovascular Outcomes in High Cardiovascular Risk Patients – Insights from the SPRINT Study},
  author = {Moran Li and Jieying Shi and Minghui Chen and Qiaorui He and Bo Wang and Song Zhao and Yan Li and Yifan Zhao and Yi Zhang},
  journal = {PULSE},
  year = {2026},
  volume = {14},
  number = {1},
  pages = {93-104},
  doi = {10.1159/000551995},
  url = {https://doi.org/10.1159/000551995}
}

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