Cognitive DysfunctionPRECEDENCT03175302
PREsurgical Cognitive Evaluation Via Digital clockfacEdrawing
An observational study of Cognitive Dysfunction, run by University of Florida at 1 site in United States.
Trial summary
This study leverages a modernized digital version of a well-known cognitive screening tool to examine pre and post operative cognitive function after surgery in adults age 65 years or more. Read more about this study
- Who is it for?
- Ages 65 years and older
- Conditions the study is for
- Cognitive Dysfunction
- What is being tested?
- digital cognitive testing
- Type of treatment
- Lifestyle or therapy programme
- How many people
- 25,240 participants
- Where
- 1 siteUnited States
- Study dates
- 28 Jun 2018to 31 May 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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
- No healthy volunteers
- Older adult
Study population: Patients >/= 65 years of age scheduled for screening within the UF Health Preoperative clinic
Who may be able to join
- >/= 65 years of age
- screening within the University of Florida (UF) Health Preoperative clinic
- presurgical cognitive screening with the digital Clock Drawing Tool (dCDT)
Who cannot join
- < 65 years of age
- did not complete screening within the UF Health Preoperative clinic
- did not complete the presurgical cognitive screening with the digital Clock Drawing Tool (dCDT)
Trial locations and contacts
1 site in 1 country.
About this study
This study leverages a modernized digital version of a well-known cognitive screening tool to examine pre and post operative cognitive function after surgery in adults age 65 years or more. Machine learning algorithms will be applied to the hospital wide standard of care cognitive metric to identify risk for post-operative cognitive complications.
Read the detailed description
This proposal innovatively leverages a brief but informative digital test with machine learning to examine the subtlety of pre-surgery cognition within an extremely large number of older individuals screened preoperatively within an academic tertiary medical center. It also incorporates a unique group of well characterized non-surgery peers for demographic matching to assist with normal versus abnormal machine learning analyses.
- Conditions
- Cognitive Dysfunction
- Being tested
- digital cognitive testing
- Keywords
- cognitive processes, perioperative cognition, neurocognitive impairment
- Medical subject headings
- Cognitive Dysfunction
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
digital cognitive testingBehavioural
The digital testing is hypothesized to identify latent features for differentiating cognitively impaired presurgical patient subgroups
| Study group | Role | What they receive |
|---|---|---|
| Surgical group | Baseline preoperative digital cognitive testing performance in adults to predict frequency and severity of clinician reported outcomes within the first three months post-surgery. Receives: Behavioral: digital cognitive testing | |
| Control | Non-surgery matched peers with the same testing. Receives: Behavioral: digital cognitive testing |
What is being measured
The primary outcome is the main question the study is designed to answer.
Control and pre-surgery differences between digital behaviors
Measure range of digital outcome differences
Measured: up to one year
Secondary outcomes (4)
Predictive validity of digital behaviors on outcome
Digital tools will predict clinician reported events
Measured: up to 1 year
Change over time in digital behavior between groups
Surgery group and control group differences from baseline to 6-weeks
Measured: up to 6-weeks
Change over time in digital behavior between groups
Surgery group and control group differences from baseline to 3-months
Measured: up to 3-months
Change over time in digital behavior between groups
Surgery group and control group differences from baseline to one year
Measured: up to one year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Jun 2017
- Study start28 Jun 2018
- Primary completion31 May 2027 (estimated)
- Study completion31 May 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Cognitive DysfunctionStudies of the same condition, open and under way.
- More trials run by University of FloridaThe sponsor's other registered studies.
- 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
- Other
- Enrolment
- 25,240 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Florida
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute on Aging (NIA), National Center for Advancing Translational Sciences (NCATS)
- Responsible party
- Sponsor
- Investigators
- Catherine Price, Ph.D., Principal investigator, University of FloridaPatrick Tighe, MD, MS, Principal investigator, University of Florida
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03175302
- Sponsor's protocol ID
- IRB201700747-N
- Other IDs
- R01AG055337, OCR18881
- Acronym
- PRECEDE
- Status last verified
- Aug 2026
- First submitted
- 1 Jun 2017
- Last updated
- 17 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Bandyopadhyay S, Wittmayer J, Libon DJ, Tighe P, Price C, Rashidi P. Explainable semi-supervised deep learning shows that dementia is associated with small, avocado-shaped clocks with irregularly placed hands. Sci Rep. 2023 May 6;13(1):7384. doi: 10.1038/s41598-023-34518-9.
PubMed 37149670Bandyopadhyay S, Dion C, Libon DJ, Price C, Tighe P, Rashidi P. Variational autoencoder provides proof of concept that compressing CDT to extremely low-dimensional space retains its ability of distinguishing dementia. Sci Rep. 2022 May 14;12(1):7992. doi: 10.1038/s41598-022-12024-8.
PubMed 35568709
Study at a glance
From the registry record, last updated by the sponsor on 17 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- PREsurgical Cognitive Evaluation Via Digital clockfacEdrawing
- ClinicalTrials.gov ID
- NCT03175302
- Acronym / sponsor ID
- PRECEDE / IRB201700747-N
- Conditions
- Cognitive Dysfunction
- Keywords
- cognitive processes, perioperative cognition, neurocognitive impairment
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 25,240 participants (estimated)
- Lead sponsor
- University of FloridaUniversity, hospital or other
- Collaborators
- National Institute on Aging (NIA), National Center for Advancing Translational Sciences (NCATS)
- Study start
- 28 Jun 2018 (actual)
- Primary completion
- 31 May 2027 (estimated)
- Study completion
- 31 May 2027 (estimated)
- First posted
- 5 Jun 2017 (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.
This study leverages a modernized digital version of a well-known cognitive screening tool to examine pre and post operative cognitive function after surgery in adults age 65 years or more. Machine learning algorithms will be applied to the hospital wide standard of care cognitive metric to identify risk for post-operative cognitive complications.
Detailed description
This proposal innovatively leverages a brief but informative digital test with machine learning to examine the subtlety of pre-surgery cognition within an extremely large number of older individuals screened preoperatively within an academic tertiary medical center. It also incorporates a unique group of well characterized non-surgery peers for demographic matching to assist with normal versus abnormal machine learning analyses.
Study design
- Observational model
- Cohort
- Time perspective
- Other
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Surgical group | – | Behavioral: digital cognitive testingBaseline preoperative digital cognitive testing performance in adults to predict frequency and severity of clinician reported outcomes within the first three months post-surgery. |
| Control | – | Behavioral: digital cognitive testingNon-surgery matched peers with the same testing. |
Who may qualify
- Ages
- 65 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Older adult
- Study population
- Patients >/= 65 years of age scheduled for screening within the UF Health Preoperative clinic
Key inclusion criteria (3 listed)
- >/= 65 years of age
- screening within the University of Florida (UF) Health Preoperative clinic
- presurgical cognitive screening with the digital Clock Drawing Tool (dCDT)
Key exclusion criteria (3 listed)
- < 65 years of age
- did not complete screening within the UF Health Preoperative clinic
- did not complete the presurgical cognitive screening with the digital Clock Drawing Tool (dCDT)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| digital cognitive testingThe digital testing is hypothesized to identify latent features for differentiating cognitively impaired presurgical patient subgroups | Behavioural | Control, Surgical group |
Primary outcome
Control and pre-surgery differences between digital behaviors
Time frame: up to one year
Measure range of digital outcome differences
4 secondary outcomes
Predictive validity of digital behaviors on outcome
Time frame: up to 1 year
Change over time in digital behavior between groups
Time frame: up to 6-weeks
Change over time in digital behavior between groups
Time frame: up to 3-months
Change over time in digital behavior between groups
Time frame: up to one year
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Aug 2026.
- Derived from this study: PubMed 37149670Bandyopadhyay S, Wittmayer J, Libon DJ, Tighe P, Price C, Rashidi P. Explainable semi-supervised deep learning shows that dementia is associated with small, avocado-shaped clocks with irregularly placed hands. Sci Rep. 2023 May 6;13(1):7384. doi: 10.1038/s41598-023-34518-9.
- Derived from this study: PubMed 35568709Bandyopadhyay S, Dion C, Libon DJ, Price C, Tighe P, Rashidi P. Variational autoencoder provides proof of concept that compressing CDT to extremely low-dimensional space retains its ability of distinguishing dementia. Sci Rep. 2022 May 14;12(1):7992. doi: 10.1038/s41598-022-12024-8.
- Individual participant dataSharing planned: No
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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.
Catherine Price, Ph.D. principal investigator
University of Florida
Patrick Tighe, MD, MS principal investigator
University of Florida
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 Dysfunction, run by University of Florida at 1 site in United States.
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 3 inclusion and 3 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: under way, not looking for participants, as of the sponsor's last update on 17 Aug 2026. 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 United States. 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?
This study is still under way. Results are not available in the source record yet.
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?
Control and pre-surgery differences between digital behaviors (time frame: up to one year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03175302, which also lists 2 linked publications.
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 17 Aug 2026.