Nomogram for predicting asymptomatic intracranial atherosclerotic stenosis in a neurologically healthy population

Asymptomatic intracranial atherosclerotic stenosis (aICAS) is a major risk factor for cerebrovascular events. The study aims to construct and validate a nomogram for predicting the risk of aICAS. Participants who underwent health examinations at our center from September 2019 to August 2023 were ret...

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Bibliographic Details
Published in:Scientific reports 2024-10, Vol.14 (1), p.24259-11, Article 24259
Main Authors: Li, Wenbo, Liu, Xiaonan, Liu, Yang, Liu, Jie, Guo, Qirui, Li, Jing, Zheng, Wei, Zhang, Longyou, Zhang, Ying, Hong, Yin, Wang, Anxin, Zheng, Huaguang
Format: Article
Language:English
Subjects:
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Adult
Aged
Arteriosclerosis
Asymptomatic
Asymptomatic Diseases
Asymptomatic intracranial atherosclerotic stenosis
Atherosclerosis
Blood Pressure
Calibration
Female
Humanities and Social Sciences
Humans
Hypertension
Hypertension - diagnosis
Hypertension - epidemiology
Intracranial Arteriosclerosis - diagnosis
Intracranial Arteriosclerosis - epidemiology
LASSO-Logistic regression
Male
Middle Aged
multidisciplinary
Neurologically healthy population
Nomogram
Nomograms
Population studies
Regression analysis
Retrospective Studies
Risk Factors
ROC Curve
Science
Science (multidisciplinary)
Stenosis
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Description
Summary:Asymptomatic intracranial atherosclerotic stenosis (aICAS) is a major risk factor for cerebrovascular events. The study aims to construct and validate a nomogram for predicting the risk of aICAS. Participants who underwent health examinations at our center from September 2019 to August 2023 were retrospectively enrolled. The participants were randomly divided into a training set and a testing set in a 7:3 ratio. Firstly, in the training set, least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were performed to select variables that were used to establish a nomogram. Then, the receiver operating curves (ROC) and calibration curves were plotted to assess the model’s discriminative ability and performance. A total of 2563 neurologically healthy participants were enrolled. According to LASSO-Logistic regression analysis, age, fasting blood glucose (FBG), systolic blood pressure (SBP), hypertension, and carotid atherosclerosis (CAS) were significantly associated with aICAS in the multivariable model (adjusted P  
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-74393-6