SART and Individual Trial Mistake Thresholds: Predictive Model for Mobility Decline.

Area of Science:

• Gerontology
• Neuroscience
• Biostatistics

Background:

• The Sustained Attention to Response Task (SART) assesses neurocognitive function in older adults.
• Traditional SART analysis using averaged data may obscure crucial information and fail to link performance to clinical outcomes.
• A need exists for methods that capture individual trial SART data for better prediction of age-related decline.

Purpose of the Study:

• To introduce a novel visualization method for individual SART trial data.
• To assess the predictive power of this method for mobility and cognitive decline in older adults.
• To explore the association between SART performance and clinically meaningful outcomes in a large population-based study.

Main Methods:

• A cohort of 4864 participants aged 50+ in Ireland provided raw SART data.
• A thresholding method identified 'bad performance' (SART trials with ≥4 mistakes).
• Binary logistic regression models predicted mobility (Timed Up-and-Go) and cognitive (Mini-Mental State Examination) decline over 4 years.

Main Results:

• The 'bad performance' feature significantly predicted mobility decline (OR = 1.29) and new falls (OR = 1.11).
• This SART-derived feature was the most significant predictor for mobility decline and the only significant predictor for new falls.
• No SART-related variables predicted cognitive decline as measured by MMSE score changes.

Conclusions:

• A threshold-based approach to SART performance visualization offers valuable insights into older adult neurocognition.
• This novel method effectively identifies individuals at higher risk for future mobility decline and falls.
• The visualization technique can assist clinicians in forming hypotheses and managing age-related risks.