Construction of a nomogram model to predict arteriosclerosis in middle-aged and elderly community dwellers: insights from a cohort study - Report - MDSpire
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Construction of a nomogram model to predict arteriosclerosis in middle-aged and elderly community dwellers: insights from a cohort study
Clinical Report: Development of a nomogram for predicting arteriosclerosis
Overview
This study developed a nomogram to predict arteriosclerosis in middle-aged and older adults, demonstrating good predictive accuracy. The model identified key risk factors, including age, BMI, and hypertension.
Background
Arteriosclerosis is a significant contributor to cardiovascular diseases, which remain a leading cause of mortality globally. Early identification of individuals at risk is crucial for timely intervention and management.
Data Highlights
Cohort
Area Under Curve (AUC)
95% Confidence Interval
Derivation
0.811
0.795–0.827
Validation
0.816
0.796–0.830
Key Findings
41.0% of participants were diagnosed with arteriosclerosis over an average follow-up of 3.25 years.
Independent risk factors identified include age, BMI, hypertension, triglyceride levels, glycosylated hemoglobin, sex, and fasting blood glucose.
The nomogram showed good predictive accuracy with AUC values of 0.811 and 0.816 for the derivation and validation cohorts, respectively.
Calibration curves indicated high consistency between predicted and observed results.
Decision curve analysis revealed favorable net benefits of the nomogram model.
Clinical Implications
Understanding the associated risk factors may assist healthcare providers in identifying individuals at risk for arteriosclerosis.
Conclusion
The predictive model for arteriosclerosis in middle-aged and older adults shows potential for identifying individuals at risk.
