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Integrating clinical and biochemical markers: a novel nomogram for predicting lacunes in cerebral small vessel disease.
- Source :
- Frontiers in Aging Neuroscience; 2024, p1-11, 11p
- Publication Year :
- 2024
-
Abstract
- Background: Lacunes, a characteristic feature of cerebral small vessel disease (CSVD), are critical public health concerns, especially in the aging population. Traditional neuroimaging techniques often fall short in early lacune detection, prompting the need for more precise predictive models. Methods: In this retrospective study, 587 patients from the Neurology Department of the Affiliated Hospital of Hebei University who underwent cranial MRI were assessed. A nomogram for predicting lacune incidence was developed using LASSO regression and binary logistic regression analysis for variable selection. The nomogram's performance was quantitatively assessed using AUC-ROC, calibration plots, and decision curve analysis (DCA) in both training (n = 412) and testing (n = 175) cohorts. Results: Independent predictors identified included age, gender, history of stroke, carotid atherosclerosis, hypertension, creatinine, and homocysteine levels. The nomogram showed an AUC-ROC of 0.814 (95% CI: 0.791-0.870) for the training set and 0.805 (95% CI: 0.782-0.843) for the testing set. Calibration and DCA corroborated the model's clinical value. Conclusion: This study introduces a clinically useful nomogram, derived from binary logistic regression, that significantly enhances the prediction of lacunes in patients undergoing brain MRI for various indications, potentially advancing early diagnosis and intervention. While promising, its retrospective design and single-center context are limitations that warrant further research, including multi-center validation. [ABSTRACT FROM AUTHOR]
- Subjects :
- RISK assessment
MEDICAL history taking
HOMOCYSTEINE
PREDICTION models
RESEARCH funding
RECEIVER operating characteristic curves
ACADEMIC medical centers
CREATININE
LACUNAR stroke
LOGISTIC regression analysis
FISHER exact test
BRAIN
SEX distribution
HYPERTENSION
MAGNETIC resonance imaging
DESCRIPTIVE statistics
RETROSPECTIVE studies
CHI-squared test
BIOCHEMISTRY
AGE distribution
CAROTID artery stenosis
LABORATORY test panels
LONGITUDINAL method
CEREBRAL small vessel diseases
RESEARCH
STROKE rehabilitation
COMPARATIVE studies
CONFIDENCE intervals
CALIBRATION
DATA analysis software
EARLY diagnosis
BIOMARKERS
REGRESSION analysis
SENSITIVITY & specificity (Statistics)
DISEASE risk factors
DISEASE complications
Subjects
Details
- Language :
- English
- ISSN :
- 16634365
- Database :
- Complementary Index
- Journal :
- Frontiers in Aging Neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- 179521236
- Full Text :
- https://doi.org/10.3389/fnagi.2024.1404836