Risk Prediction and Its Intelligent Assessment for Cognitive Impairment Among Community-dwelling Older Adults

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.

Study Overview

• Status: Completed
• Conditions: Cognitive Impairment; Aging; Predictive Model; Cohort

• Study Type: Observational
• Enrollment (Actual): 13228

Contacts and Locations

Study Locations

• China
  • Beijing, China, 100191
    • Peking University Six Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 65 years and older (Older Adult)
• Accepts Healthy Volunteers: Yes

• 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.

Description

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.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Training cohort; The training cohort will be used for model development.
Testing cohort; The testing cohort, a new cohort compared with the training cohort, will be used for model external validation.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AUC	the AUC of the prediciton model based on the test data	an average of 3 years after baseline assessement

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
sensitivity	the sensitivity of the prediciton model based on the test data	an average of 3 years after baseline assessement
specificity	the specificity of the prediciton model based on the test data	an average of 3 years after baseline assessement
positive predictive value	the positive predictive value of the prediciton model based on the test data	an average of 3 years after baseline assessement
negative predictive value	the negative predictive value of the prediciton model based on the test data	an average of 3 years after baseline assessement

Collaborators and Investigators

• Sponsor: Peking University Sixth Hospital
• Investigators: Study Director: Feifei Gao, Ph.D, Peking University Six Hospital

Study record dates

Study Major Dates

• Study Start (Actual): April 1, 2022
• Primary Completion (Actual): December 30, 2023
• Study Completion (Actual): December 30, 2023

Study Registration Dates

• First Submitted: May 11, 2022
• First Submitted That Met QC Criteria: May 17, 2022
• First Posted (Actual): May 23, 2022

Study Record Updates

• Last Update Posted (Actual): April 4, 2024
• Last Update Submitted That Met QC Criteria: April 2, 2024
• Last Verified: April 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Mental Disorders; Neurocognitive Disorders; Cognition Disorders; Cognitive Dysfunction
• Other Study ID Numbers: SHOUFA2020-3-4114

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No