PREsurgical Cognitive Evaluation Via Digital clockfacEdrawing
University of Florida
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. Machine learning algorithms will be applied to the hospital wide standard of care cognitive metric to identify risk for post-operative cognitive complications.
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.
Eligibility
- Age range
- 65+ years
- Sex
- All
- Healthy volunteers
- No
Inclusion Criteria: * \>/= 65 years of age * screening within the University of Florida (UF) Health Preoperative clinic * presurgical cognitive screening with the digital Clock Drawing Tool (dCDT) Exclusion Criteria: * \< 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)
Interventions
- Behavioraldigital cognitive testing
The digital testing is hypothesized to identify latent features for differentiating cognitively impaired presurgical patient subgroups
Location
- UF HealthGainesville, Florida