Cognitive ImpairmentNCT05385874
Risk Prediction and Its Intelligent Assessment for Cognitive Impairment Among Community-dwelling Older Adults
An observational study of Cognitive Impairment and Predictive Model, run by Peking University Sixth Hospital at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 65 years and olderHealthy volunteers can take part
- Conditions the study is for
- Cognitive Impairment, Predictive Model, Aging
- How many people
- 13,228 participants
- Where
- 1 siteChina
- Study dates
- 1 Apr 2022to 30 Dec 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 65 years and older
- All sexes
- Healthy volunteers accepted
- Older adult
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.
Who may be able to join
- Aged 65 or over at baseline;
- With normal cognitive function at baseline (score ≥ 18 on the Chinese version of Mini-Mental State Examination, MMSE);
- Completed MMSE assessment three years later;
- Provided informed consent voluntarily.
Who cannot join
- Aged <65;
- had a history of dementia or MMSE score < 18 at baseline;
- lost to follow-up or without cognitive function assessment three years later;
- Refused to participate the survey.
Trial locations and contacts
1 site in 1 country.
About this study
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.
- Conditions
- Cognitive Impairment, Predictive Model, Aging, Cohort
- Medical subject headings
- Cognitive Dysfunction
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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 being measured
The primary outcome is the main question the study is designed to answer.
AUC
the AUC of the prediciton model based on the test data
Measured: an average of 3 years after baseline assessement
Secondary outcomes (4)
sensitivity
the sensitivity of the prediciton model based on the test data
Measured: an average of 3 years after baseline assessement
specificity
the specificity of the prediciton model based on the test data
Measured: an average of 3 years after baseline assessement
positive predictive value
the positive predictive value of the prediciton model based on the test data
Measured: an average of 3 years after baseline assessement
negative predictive value
the negative predictive value of the prediciton model based on the test data
Measured: an average of 3 years after baseline assessement
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 May 2022
- Study start1 Apr 2022
- Primary completion30 Dec 2023
- Study completion30 Dec 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Cognitive ImpairmentStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 13,228 participants (actual)
Sponsor and investigators
- Lead sponsor
- Peking University Sixth Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xiaozhen LV, Peking University Sixth Hospital
- Investigators
- Feifei Gao, Ph.D, Study director, Peking University Six Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05385874
- Sponsor's protocol ID
- SHOUFA2020-3-4114
- Status last verified
- Apr 2024
- First submitted
- 11 May 2022
- Last updated
- 4 Apr 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 4 Apr 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Risk Prediction and Its Intelligent Assessment for Cognitive Impairment Among Community-dwelling Older Adults
- ClinicalTrials.gov ID
- NCT05385874
- Acronym / sponsor ID
- SHOUFA2020-3-4114
- Conditions
- Cognitive Impairment, Predictive Model, Aging, Cohort
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 13,228 participants (actual)
- Lead sponsor
- Peking University Sixth HospitalUniversity, hospital or other
- Study start
- 1 Apr 2022 (actual)
- Primary completion
- 30 Dec 2023 (actual)
- Study completion
- 30 Dec 2023 (actual)
- First posted
- 23 May 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| 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. |
Who may qualify
- Ages
- 65 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Older adult
- 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.
Key inclusion criteria (4 listed)
- Aged 65 or over at baseline;
- With normal cognitive function at baseline (score ≥ 18 on the Chinese version of Mini-Mental State Examination, MMSE);
- Completed MMSE assessment three years later;
- Provided informed consent voluntarily.
Key exclusion criteria (4 listed)
- Aged <65;
- had a history of dementia or MMSE score < 18 at baseline;
- lost to follow-up or without cognitive function assessment three years later;
- Refused to participate the survey.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
AUC
Time frame: an average of 3 years after baseline assessement
the AUC of the prediciton model based on the test data
4 secondary outcomes
sensitivity
Time frame: an average of 3 years after baseline assessement
specificity
Time frame: an average of 3 years after baseline assessement
positive predictive value
Time frame: an average of 3 years after baseline assessement
negative predictive value
Time frame: an average of 3 years after baseline assessement
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Apr 2024.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Feifei Gao, Ph.D study director
Peking University Six Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Cognitive Impairment and Predictive Model, run by Peking University Sixth Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 4 Apr 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
AUC (time frame: an average of 3 years after baseline assessement). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 4 Apr 2024; AzTrials last refreshed its copy on 26 Oct 2026.