Key result
The prevalence of cognitive impairment among middle-aged and elderly individuals in Anhui Province was 12.6%, and a developed nomogram incorporating key risk factors demonstrated good predictive ability with an AUC of 0.845.
Cross-Sectional (n=3,059)
Yes
Effect estimate: AUC 0.845 (95% CI 0.822-0.868)
The prevalence of cognitive impairment among middle-aged and elderly individuals in Anhui Province is 12.6%, and a validated nomogram incorporating factors like age, sex, and comorbidities can effectively predict its occurrence.
Highlights risk factors for cognitive impairment in Anhui; leaves open causality and whether modifying them prevents decline.
Background The prevalence rate of CI among middle-aged and elderly individuals in Anhui Province was 12.6%. Female sex, elderly age, family history, low educational status, current smoking status, sleep disorders, hypertension, stroke, and diabetes were shown to be risk factors for CI, while exercise was shown to be a protective factor. Methods From May to June 2022, a multistage, stratified cluster-sampling method was used to select 3200 middle-aged and elderly people over 45 years old in Anhui Province for a questionnaire survey, and the Chinese version of the Mini-Mental State Examination (MMSE) was used to assess cognitive function. SPSS 25.0 was used for univariate and multivariate analyses, and R software was used to establish and validate the nomogram. Results A total of 3059 valid questionnaires were included, of which 384 were from participants who were diagnosed with CI, and the prevalence rate was 12.6%. Multivariate logistic analysis showed that female sex, advanced age, family history, etc., were closely related to the occurrence of CI. The AUC values in the modeling and validation groups were 0.845 (95% CI: 0.822-0.868) and 0.868 (95% CI: 0.835-0.902), respectively, indicating that the predictive ability of the model was good. The Hosmer‒Lemeshow test suggested that the model had good goodness-of-fit, and the decision-curve evaluation nomogram had a high benefit within the threshold, which had a certain clinical importance.
No takes yet. Share an insight, caveat, or question.
Cui et al. (2023) conducted a cross-sectional in Cognitive impairment (n=3,059). Risk factors for cognitive impairment (e.g., age, sex, family history, education, smoking, sleep disorders, hypertension, stroke, diabetes) vs. Individuals without these risk factors was evaluated on Predictive ability of the nomogram for cognitive impairment (AUC in modeling group) (AUC 0.845, 95% CI 0.822-0.868). The prevalence of cognitive impairment among middle-aged and elderly individuals in Anhui Province was 12.6%, and a developed nomogram incorporating key risk factors demonstrated good predictive ability with an AUC of 0.845.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: