Objective:

To create and verify a tool for forecasting arteriosclerosis in middle-aged and elderly individuals within the community, including its validation.

Approach:

Key Findings:

• 41.0% of subjects were diagnosed with arteriosclerosis over an average follow-up of 3.25 years, defined as baPWV ≥ 1400 cm/s.
• Independent risk factors identified include age, BMI, hypertension, triglyceride levels, glycosylated hemoglobin, sex, and fasting blood glucose.
• The area under the receiver operating characteristic curve was 0.811 for the derivation cohort and 0.816 for the validation cohort.

Interpretation:

The predictive model may assist in identifying arteriosclerosis in middle-aged and elderly individuals, aiding in early detection and intervention.

Limitations:

• The study was limited to community settings and may not be generalizable to other populations.
• The follow-up duration and sample size may affect the robustness of the findings.

Conclusion:

The predictive model established in this study holds promise for identifying arteriosclerosis in middle-aged and elderly individuals.

Attribution Notice

This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.