Development of a risk factor nomogram prediction model for patients with acute coronary syndrome complicated by hypertension using LASSO regression analysis

A high-quality predictive nomogram model for assessing the risk of ACS in patients with hypertension has been developed. This model can assist clinicians in early diagnosis, personalized treatment, and prognostic evaluation.

Authors

Huimin Bai (ORCID: https://orcid.org/0000-0002-2062-5003)
Jumin Xie (ORCID: https://orcid.org/0000-0002-4493-4548)
Cheng Feng (ORCID: https://orcid.org/0000-0002-8785-2681)
Li Song (ORCID: https://orcid.org/0000-0002-8272-8665)
Zixuan Yang

Institutions

Hubei Polytechnic University (CN)
Huangshi Central Hospital (CN)

Publication Details

Journal: BMC Cardiovascular Disorders
Published: 2025-12-12
DOI: https://doi.org/10.1186/s12872-025-05317-z
Citations: 1
Primary Topic: Blood Pressure and Hypertension Studies
Type: article
Field-Weighted Citation Impact: 1.39

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article

Development of a risk factor nomogram prediction model for patients with acute coronary syndrome complicated by hypertension using LASSO regression analysis

Huimin Bai, Jumin Xie, Cheng Feng, Li Song et al.

Dec 12, 2025

1 citations

BMC Cardiovascular Disorders

Blood Pressure and Hypertension Studies

1.39

article

Development of a risk factor nomogram prediction model for patients with acute coronary syndrome complicated by hypertension using LASSO regression analysis

Huimin Bai, Jumin Xie, Cheng Feng, Li Song, Zixuan Yang

December 12, 2025article en

1 citations

Abstract

BMC Cardiovascular DisordersVol. 25(1)

Hubei Polytechnic University (CN), Huangshi Central Hospital (CN)

Openalex Percentile: Top 13%

Blood Pressure and Hypertension Studies

1.39

DOI Open Access PDF OpenAlex

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Development of a risk factor nomogram prediction model for patients with acute coronary syndrome complicated by hypertension using LASSO regression analysis — Huimin Bai, Jumin Xie, et al. · BMC Cardiovascular Disorders (2025) | TGRS Research Map | TGRS