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Development of a risk factor nomogram prediction model for patients with acute coronary syndrome complicated by

Jumin Xie1, Li Song2, Zixuan Yang2

  • 1Hubei Key Laboratory of Renal Disease Occurrence and Intervention, Medical School, Hubei Polytechnic University, Huangshi, Hubei, 435003, China. xiejumin@hbpu.edu.cn.

BMC Cardiovascular Disorders
|December 13, 2025
PubMed

Insights

This study developed a nomogram to predict acute coronary syndrome (ACS) risk in hypertensive patients. The model aids clinicians in early diagnosis, personalized treatment, and prognosis for cardiovascular disease management.

Area of Science:

  • Cardiology
  • Medical Informatics
  • Public Health

Background:

  • Cardiovascular disease (CVD) is a leading global cause of death.
  • Acute coronary syndromes (ACS) incidence is rising worldwide.
  • Hypertension is a significant risk factor for ACS.

Purpose of the Study:

  • To develop a predictive nomogram model for ACS risk in hypertensive patients.
  • To provide a tool for early diagnosis and personalized treatment strategies.
  • To enhance prognostic evaluation for ACS patients with hypertension.

Main Methods:

  • Retrospective data collection from 980 ACS patients (2018-2023).
  • Inclusion of patient demographics, medical history, and clinical data.
  • Development of a nomogram using LASSO and logistic regression analysis.

Main Results:

  • The study included 682 hypertensive ACS patients (69.59%).
  • Significant differences observed between hypertensive and non-hypertensive groups in various clinical and laboratory parameters.
  • A high-quality nomogram model was constructed and validated.

Conclusions:

  • A validated nomogram model for predicting ACS risk in hypertensive patients was developed.
  • The model demonstrates high predictive accuracy and clinical utility.
  • This tool supports improved clinical decision-making for ACS management in hypertensive individuals.
Abstract

Keywords:
Acute coronary syndromesHypertensionLASSONomogram model

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