Clinical trial NCT05385874: Risk Prediction and Its Intelligent Assessment for Cognitive Impairment Among Community-dwelling Older Adults
Official title: Risk Prediction and Its Intelligent Assessment for Cognitive Impairment Among Community-dwelling Older Adults
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Cognitive Impairment
Predictive Model
Aging
Cohort
Lead sponsor: Peking University Sixth Hospital
Sponsor class: OTHER
First posted: 2022-05-23
Enrollment: 13228
Sex: ALL
Minimum age (years): 65
Standard ages: OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study population of this project was those community-dwelling older adults with normal cognitive function at baseline and completed cognitive function assessment three years later.

Brief summary: Cognitive impairment is one of the core early signs of dementia, and it is also a key stage for community-based dementia prevention. Accurate and convenient prediction of cognitive impairment can help the community to identify and manage the high-risk population of dementia. Previous studies had developed several dementia predicting models, but such models may be not suitable for cognitive impairment prediction. Based on the national representative follow-up data of Chinese Longitudinal Healthy Longevity Survey (CLHLS), this project aims to develop and validate a brief cognitive impairment prediction algorithm among the community-dwelling elderly, using machine learning methods (such as Logistic regression, Naïve Bayes model, Extreme Gradient Boosting Tree and so on). Finally, based on the constructed model, an easy-to-use online intelligent assessment tool for predicting cognitive impairment risk will be developed. The general practitioners, social workers and the elderly would be invited to use the tool and we will revise the tool according to their suggestions and comments. This project is expected to provide scientific basis and technical support for community-based dementia prevention, and will also be useful for the elderly to easily understand their cognitive health.


Eligibility criteria: Inclusion Criteria:

1. Aged 65 or over at baseline;
2. With normal cognitive function at baseline (score ≥ 18 on the Chinese version of Mini-Mental State Examination, MMSE);
3. Completed MMSE assessment three years later;
4. Provided informed consent voluntarily.

Exclusion Criteria:

1. Aged \<65;
2. had a history of dementia or MMSE score \< 18 at baseline;
3. lost to follow-up or without cognitive function assessment three years later;
4. Refused to participate the survey.

Primary outcomes:
measure: AUC
timeFrame: an average of 3 years after baseline assessement
Secondary outcomes:
measure: sensitivity
timeFrame: an average of 3 years after baseline assessement
measure: specificity
timeFrame: an average of 3 years after baseline assessement
measure: positive predictive value
timeFrame: an average of 3 years after baseline assessement
measure: negative predictive value
timeFrame: an average of 3 years after baseline assessement
Other outcomes:
Locations:
city: Beijing
country: China
facility: Peking University Six Hospital
Study officials:
affiliation: Peking University Six Hospital
name: Feifei Gao, Ph.D
role: STUDY_DIRECTOR
References: