A detection model for cognitive dysfunction based on volatile organic compounds from a large Chinese community cohort.

INTRODUCTION: We explored whether volatile organic compound (VOC) detection can serve as a screening tool to distinguish cognitive dysfunction (CD) from cognitively normal (CN) individuals. METHODS: The cognitive function of 1467 participants was assessed and their VOCs were detected. Six machine learning algorithms were conducted and the performance was determined. The plasma neurofilament light chain (NfL) was measured. RESULTS: Distinguished VOC patterns existed between CD and CN groups. The CD detection model showed good accuracy with an area under the receiver-operating characteristic curve (AUC) of 0.876. In addition, we found that 10 VOC ions showed significant differences between CD and CN individuals (p < 0.05); three VOCs were significantly related to plasma NfL (p < 0.005). Moreover, a combination of VOCs with NfL showed the best discriminating power (AUC = 0.877). DISCUSSION: Detection of VOCs from exhaled breath samples has the potential to provide a novel solution for the dilemma of CD screening.

The prevalence and risk factors study of cognitive impairment: Analysis of the elderly population of Han nationality in Hunan province, China.

OBJECTIVE: A large number of studies have found that the prevalence of cognitive impairment varies in different regions. However, data on cognitive impairment in the Chinese population is still lacking. The goal of this study was to assess the prevalence of cognitive impairment among the elderly in a region of China and explore the associated risk factors. METHODS: We performed a population-based cross-sectional survey from April to June 2022. Residents come from three villages and six urban communities in the county-level city of Liuyang in southern China (N = 3233) and the coverage rate of our study population reached 73%. Participants were assessed with a series of clinical examinations and neuropsychological measures. A total of 2598 participants were selected after filtering out those under 60 years old or with incomplete data. Patients with cognitive impairment included those with mild cognitive impairment (MCI) or dementia who met standard diagnostic criteria. RESULTS: The prevalence of cognitive impairment, MCI, and dementia among participants aged 60 years and older were 21.48% (95% CI, 19.90-23.10), 15.70% (95% CI, 14.30-17.10), and 5.77 (95% CI, 4.90-6.70), respectively. And residents in villagers were more likely to have cognitive impairment than in urban communities (p < 0.001). Age growth and education level were independent influencing factors for cognitive impairment in all populations (p < 0.001). For lifestyles factors, both smoking and drinking reduced the risk of cognitive impairment (p < 0.05), but when further quantified, the link disappeared. Moreover, having cerebrovascular disease and severe vision impairment were risk factors (p < 0.05). CONCLUSION: A representative prevalence of cognitive impairment, MCI, and dementia was found in the elderly Han Chinese population in Southern China. And we further explored the role of known risk factors, particularly in physical activity, smoking, and alcohol consumption.