Key result
A prediction model using baseline CESD, physical self-maintenance, sleep, comorbidities, age, and weight predicted 2-year depression risk in MetS patients (AUC 0.775; 95% CI 0.750-0.800; P<0.001).
Why the study?
Although studies have explored the relationship between depression and metabolic syndrome, few studies have focused on the elderly in Chinese communities as China enters an aging society.
Population
2533 middle-aged and elderly patients with MetS in mainland China
Comparison
Depression (n = 938) vs non-depression groups (n = 1595)
Design
Longitudinal cohort study
Follow-up
7-year follow-up
Authors
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May support depression screening in Chinese MetS patients; leaves open external validation of the predictive model.
Cohort (n=2,533)
Yes
Effect estimate: AUC 0.775 (95% CI 0.750-0.800)
p-value: p=< 0.001
A predictive model using baseline clinical and demographic factors can effectively predict the 2-year risk of depression in middle-aged and elderly patients with metabolic syndrome.
Ma et al. (2024) conducted a cohort in Metabolic syndrome (n=2,533). Risk factors for depression (baseline CESD, Physical Self-Maintenance Scale, sleep duration, chronic diseases, age, weight) was evaluated on Risk of depression at 2-year follow-up (AUC 0.775, 95% CI 0.750-0.800, p=< 0.001). A prediction model using baseline CESD, physical self-maintenance, sleep, comorbidities, age, and weight predicted 2-year depression risk in MetS patients (AUC 0.775; 95% CI 0.750-0.800; P<0.001).
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