Evidence map›Paper›PMID 41788769›Full record

ArticleFrontiers in endocrinology2026

Hemoglobin A1c-systolic blood pressure index as a novel predictor of cardiovascular disease: evidence from three prospective cohorts.

Ruiqi Zhang, Xuelian Chen, Benjun Zhou, Boyang Xiang, Shushu Zhu

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Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ruiqi Zhang *Department of Radiology, Kunshan First People's Hospital Affiliated to Jiangsu University, Kunshan, China.
Xuelian Chen *Department of Radiology, Kunshan First People's Hospital Affiliated to Jiangsu University, Kunshan, China.
Benjun Zhou *Department of Cardiology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Boyang XiangDepartment of Cardiology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Shushu ZhuDepartment of Cardiology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hypertension and diabetes are major drivers of cardiovascular disease (CVD), and their coexistence confers excess risk. This study aimed to develop a hemoglobin A1c (HbA1c)-systolic blood pressure (SBP) index (HSI) to simultaneously capture glucose and blood pressure status and investigate the associations of baseline and cumulative HSI with incident CVD. Methods: Data were drawn from three population-based cohorts: the China Health and Retirement Longitudinal Study (CHARLS), the English Longitudinal Study of Ageing (ELSA), and the US Health and Retirement Study (HRS). Baseline HSI was calculated as HbA1c (%) × SBP (mmHg)/100. Cumulative HSI was derived from repeated measurements weighted by time intervals. Cause-specific Cox proportional hazards models were used to investigate linear associations of baseline and cumulative HSI with incident CVD. Additionally, restricted cubic splines were used to assess nonlinear relationships. Results: A total of 6,822 participants from CHARLS, 3,640 from ELSA, and 5,709 from HRS were included, with median follow-up of 9.0, 10.0, and 12.3 years, respectively. Across all three cohorts, the combination of elevated HbA1c and SBP was associated with the highest CVD risk. Higher baseline HSI were significantly associated with increased risks of CVD in the CHARLS (hazard ratio [HR] per 1 standard deviation [SD] increase =1.16, 95% confidence interval [CI] 1.11-1.22), ELSA (1.13, 95% CI 1.06-1.21), and HRS (1.14, 95% CI 1.10-1.19). Cumulative HSI levels were also significantly associated with elevated CVD risk (CHARLS: HR per 1 SD increase = 1.19, 95% CI 1.12-1.26; ELSA: 1.14, 95% CI 1.04-1.26; HRS, 1.15, 95% CI 1.08-1.22). No evidence of nonlinearity between baseline HSI and CVD was detected. The associations were almost consistent across demographic and clinical subgroups. The predictive performance of HSI was superior to HbA1c or SBP alone. Conclusions: HSI, a simple composite of HbA1c and SBP, was consistently associated with incident CVD across three international cohorts. Its predictive ability exceeded that of HbA1c or SBP alone, highlighting it as a pragmatic tool for integrated cardiometabolic risk assessment. The findings warrant further clinical validation.

Indexed as

Blood PressureCardiovascular DiseasesGlycated HemoglobinAgedChinaFemaleHumansHypertensionLongitudinal StudiesMaleMiddle AgedProspective StudiesRisk FactorsGlycated Hemoglobinhemoglobin A1c protein, humancardiovascular diseasediabetes mellitushemoglobin A1chypertensionpredictionsystolic blood pressure

Identifiers

PMID41788769
PMCPMC12956636

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.