Clinical factors predicting the rate of cognitive decline in a US memory clinic: An electronic health record study

Abstract

INTRODUCTION

Dementia progression is heterogeneous and predicting who will decline quickly remains an open problem. Most work in this area has focused on volunteer-based cohorts, which are subject to recruitment biases. Instead, we examine predictors of rate of cognitive decline in cognitive assessment scores using electronic health record (EHR) data from a US memory clinic.

METHODS

Data include patients with their first memory clinic visit (baseline) between January 1, 2014 and May 31, 2024. We used a discrete-time model to identify significant predictors of baseline and 6 month change in Mini-Mental State Examination (MMSE) scores (Montreal Cognitive Assessment scores were converted to MMSE equivalents for analysis). Inverse probability weighting was used to account for selection and censoring biases and p values were adjusted for multiple comparisons.

RESULTS

The cohort included 9583 patients, of which 7113 had a baseline cognitive assessment. Average MMSE at baseline was 23.2. Variables associated with lower baseline MMSE included female sex, non-White race, Medicaid enrollment, baseline dementia diagnosis, and cholinesterase inhibitor prescription, while higher scores were associated with prior diagnoses of chronic pain or fatigue. Quicker post-baseline decline was associated with older age, dementia diagnoses, and cholinesterase inhibitor prescription, while slower decline was associated with a higher number of total prescriptions, distance from home to clinic, and Social Deprivation Index. Notably, rate of decline was not associated with mild cognitive impairment, other non-dementia cognitive impairment, or any of the comorbidities considered.

DISCUSSION

While several significant predictors were identified, the lack of associations with broad categories of comorbidities and social determinants of health suggest that finer grained predictors may be needed. Additionally, the finding that cholinesterase inhibitor prescriptions predicted quicker decline merits additional investigation in real-world samples. The model developed in this work may serve as a first step toward an EHR-based progression risk tool.

Highlights

• In a memory clinic setting, faster decline in Mini-Mental State Examination scores was associated with age, dementia diagnosis, and cholinesterase inhibitor or memantine prescription.
• Slower decline was associated with the patient's total number of prescriptions.
• Neither race nor ethnicity were associated with rate of decline, nor were baseline mild cognitive impairment, other non-dementia cognitive impairment, diabetes, hypertension, obesity, depression, anxiety, chronic pain/fatigue, or hearing loss.