A detection model of cognitive impairment via the integrated gait and eye movement analysis from a large Chinese community cohort.

INTRODUCTION: Whether the integration of eye-tracking, gait, and corresponding dual-task analysis can distinguish cognitive impairment (CI) patients from controls remains unclear. METHODS: One thousand four hundred eighty-one participants, including 724 CI and 757 controls, were enrolled in this study. Eye movement and gait, combined with dual-task patterns, were measured. The LightGBM machine learning models were constructed. RESULTS: A total of 105 gait and eye-tracking features were extracted. Forty-six parameters, including 32 gait and 14 eye-tracking features, showed significant differences between two groups (P < 0.05). Of these, the Gait_3Back-TurnTime and Dual-task cost-TurnTime patterns were significantly correlated with plasma phosphorylated tau 181 (p-tau181) level. A model based on dual-task gait, dual-task smooth pursuit, prosaccade, and anti-saccade achieved the best area under the receiver operating characteristics curve (AUC) of 0.987 for CI detection, while combined with p-tau181, the model discriminated mild cognitive impairment from controls with an AUC of 0.824. DISCUSSION: Combining dual-task gait and dual-task eye-tracking analysis is feasible for the detection of CI. HIGHLIGHTS: This is the first study to report the efficiency of integrated parameters of dual-task gait and eye-tracking for cognitive impairment (CI) detection in a large cohort. We identified 46 gait and eye-tracking features associated with CI, and two were correlated to plasma phosphorylated tau 181. We constructed the model based on dual-task gait, smooth pursuit, prosaccade, and anti-saccade, achieving the best area under the curve of 0.987 for CI detection.

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.

Effectiveness of a Quality Improvement Intervention on Reperfusion Treatment for Patients With Acute Ischemic Stroke: A Stepped-Wedge Cluster Randomized Clinical Trial.

Importance: Reperfusion therapy is the most effective treatment for acute ischemic stroke but remains underused in China. Objective: To evaluate the effect of a problem-oriented, culturally adapted, targeted quality improvement intervention on reperfusion therapy for patients with acute ischemic stroke in China. Design, Setting, and Participants: In this stepped-wedge cluster randomized clinical trial, patients from 16 secondary and 33 tertiary hospitals in China with acute ischemic stroke within 6 hours of symptom onset were consecutively recruited between July 1, 2018, and June 30, 2020. Interventions: Hospitals were randomly assigned to 1 of 3 sequences to receive the targeted quality improvement intervention (n = 5689), in which workflow reconstruction was promoted to reduce in-hospital reperfusion treatment delays, or usual care (n = 6443), in which conventional stroke care was left to the discretion of the stroke team. Main Outcomes and Measures: The primary outcome was the reperfusion therapy rate, a composite outcome of intravenous recombinant tissue plasminogen activator (IV rtPA) or endovascular thrombectomy (EVT) for eligible patients who arrived within 3.5 or 4.5 hours of symptom onset. Secondary outcomes were the IV rtPA administration rate among eligible patients who arrived within 3.5 hours of symptom onset, the EVT rate among eligible participants who arrived within 4.5 hours of symptom onset, the proportion of patients with door-to-needle time within 60 minutes, the proportion of patients with door-to-puncture time within 90 minutes, in-hospital mortality, and 3-month disability as measured by a modified Rankin Scale score greater than 2. Results: All 12 132 eligible patients (mean [SD] age, 66 [12.1] years; 7759 male [64.0%]) completed the trial. The reperfusion rate was 53.5% (3046 of 5689) for the eligible patients in the intervention period and 43.9% (2830 of 6443) in the control period. No significant improvement in primary outcomes was found for the intervention after adjusting for cluster, period, and imbalanced baseline covariates (adjusted risk difference [ARD], 5.5%; 95% CI, -8.0% to 19.0%; adjusted odds ratio [AOR], 1.26; 95% CI, 0.72-2.21) or for the secondary outcomes. However, significant improvements were found in secondary hospitals for reperfusion therapy (1081 of 1870 patients [57.8%] vs 945 of 2022 patients [42.9%]; ARD, 19.0%; 95% CI, 6.4%-31.6%; AOR, 2.24; 95% CI, 1.29-3.88), IV rtPA administration (1062 of 1826 patients [58.2%] vs 916 of 2170 patients [42.2%]; ARD, 20.3%; 95% CI, 7.4%-33.1%; AOR, 2.37; 95% CI, 1.34-4.19), and EVT (51 of 231 patients [22.1%] vs 37 of 259 patients [14.3%]; ARD, 13.6%; 95% CI, 1.0%-26.3%; AOR, 3.03; 95% CI, 1.11-8.25) in subgroup analyses. Conclusions and Relevance: In this stepped-wedge cluster randomized clinical trial of patients with acute ischemic stroke in China, the use of a targeted quality improvement intervention compared with usual care did not improve the reperfusion therapy rate. However, the intervention may be effective in secondary hospitals. Trial Registration: ClinicalTrials.gov Identifier: NCT03578107.

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.