Construction of a nomogram model to predict arteriosclerosis in middle-aged and elderly community dwellers: insights from a cohort study

Category	Detail
Condition	Arteriosclerosis
Key Mechanisms	Involves elastin fiber fragmentation, collagen deposition, and arterial wall calcification, leading to reduced vascular tone and compliance.
Target Population	Middle-aged and elderly individuals over 40 years of age.
Care Setting	Community healthcare settings.

41.0% of participants diagnosed with arteriosclerosis over an average follow-up of 3.25 years.
Independent risk factors include age, BMI, hypertension, triglyceride levels, glycosylated hemoglobin, sex, and fasting blood glucose.
The predictive model demonstrated good accuracy with AUC values of 0.811 and 0.816 for derivation and validation cohorts, respectively.
Calibration curves showed high consistency between predicted and observed results.
Decision curve analysis indicated favorable net benefits of the prediction model.

Increased risk of cardiovascular diseases and all-cause mortality associated with arteriosclerosis.

Individuals aged 40 and older in community settings.

Early identification and intervention may improve patient prognosis.

Utilize a nomogram for individualized prediction of arteriosclerosis risk.
Incorporate lifestyle modifications and management of risk factors in patient care.

Clinical Scorecard: Development of a nomogram for predicting arteriosclerosis in middle-aged and older adults in community settings: findings from a cohort analysis