Development and validation of a predictive model for carotid atherosclerosis in postmenopausal women

Bibliographic Details
Title: Development and validation of a predictive model for carotid atherosclerosis in postmenopausal women
Authors: Jing Liu, Xiaoyun Zeng, Jie Ruan, Yingnan Kang, Yao Lu, Siyi Li
Source: Scientific Reports, Vol 15, Iss 1, Pp 1-19 (2025)
Publisher Information: Nature Portfolio, 2025.
Publication Year: 2025
Collection: LCC:Medicine
LCC:Science
Subject Terms: Postmenopausal, Carotid atherosclerosis, Nomogram, Predictive modeling, Medicine, Science
More Details: Abstract With the global aging of the population, menopausal women face higher cardiovascular disease (CVD) risks, with carotid atherosclerosis as the primary pathological basis. However, no effective tools exist for assessing carotid atherosclerosis risk, and this study fills the gap in predictive tools in this field. Using data from 4,446 menopausal women in Shenzhen, we developed and validated a Nomogram model for carotid atherosclerosis risk. The sample was divided into training (2,178), internal validation (934), and external validation (1,334) sets. Variables were selected using logistic regression and LASSO, including age, systolic blood pressure (SBP), lipoprotein a (LPa), non-HDL cholesterol (Non-HDL-C), TC/HDL-C ratio, glycosylated hemoglobin (HbA1c), and blood glucose (GLU). Random Forest validation confirmed the model’s robustness. The Nomogram’s C-index was 0.706 (training), 0.664 (internal), and 0.668 (external), with Random Forest results of 0.721, 0.662, and 0.661, respectively. Calibration and decision curve analyses demonstrated the model’s accuracy and clinical utility. Additionally, a slight negative correlation between age and GLU (OR = 0.689, P = 0.068) suggested reduced glycemic risk with age. This model provides a scientific basis for early risk assessment and personalized interventions for menopausal women, guiding future research on related biological mechanisms.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-025-89098-7
Access URL: https://doaj.org/article/96bdfa5f9c3e453e8a9cad6c50fc890c
Accession Number: edsdoj.96bdfa5f9c3e453e8a9cad6c50fc890c
Database: Directory of Open Access Journals
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More Details
ISSN:20452322
DOI:10.1038/s41598-025-89098-7
Published in:Scientific Reports
Language:English