Using Informatics to Evaluate and Predict Cataract Surgery Impact on Alzheimer's Disease and Related Dementias and Mild Cognitive Impairment Outcomes

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PROJECT SUMMARY/ABSTRACT Background. Visual impairment has been strongly associated with Alzheimer’s disease and related dementias (ADRD) in numerous cross-sectional and longitudinal studies, and we have found that worse baseline vision is tied to increasingly higher risk of subsequent dementia. Neurosensory deprivation from visual impairment may place greater demands on cognitive resources, accelerating cognitive decline and increasing the incidence of cognitive impairment. Conversely, improving vision could improve cognitive outcomes by increasing neurosensory input and reducing cognitive demand for processing visual information. Cataracts are the most common cause of visual impairment—fortunately reversible with surgery, however, we have found that ADRD patients are only half as likely to undergo cataract surgery as those without ADRD. This may reflect concerns regarding less potential benefit and greater perceived risks. Objectives. Our long-term goal is to evaluate cataract surgery as a potential intervention to “bend the curve” for risk of ADRD onset and progression, including optimizing patient selection and timing for surgery. The objective of this proposal is to investigate how cataract surgery may affect incidence and progression of mild cognitive impairment (MCI) and ADRD, develop models to predict individual patients’ ADRD/MCI outcomes following cataract surgery, and identify key confounders, mediators, and effect modifiers. We hypothesize that cataract surgery is associated with (1) reduction in incidence of new MCI and ADRD and (2) reduced cognitive decline and impairment progression among patients with baseline MCI or ADRD, and that (3) we will be able to predict individual patient outcomes. We propose to use methods our group has developed to archive and analyze electronic health record (EHR) data, to develop a curated data set and achieve three Aims: (1) Determine impact of cataract surgery on ADRD and MCI incidence; (2) Determine impact of cataract surgery on cognitive decline and impairment among patients with baseline ADRD or MCI, and (3) Develop patient-level predictive models for ADRD and MCI outcomes after cataract surgery. Impact. EHR-based machine learning analysis has not been applied to ADRD research to date, and the influence of cataract surgery on cognitive outcomes is not yet known. Finding that a widely-available cataract surgery intervention improves cognitive outcomes would be transformative. We estimate a potential unmet need for cataract surgery affecting almost 350,000 patients annually—just among the subset of patients with existing Alzheimer’s disease. Results from this work will directly inform discussion of cataract surgery risks and benefits and will also facilitate future research, including pragmatic clinical trial design. By developing and disseminating open source EHR-based algorithms to identify and classify cognitive and visual impairment, this proposal will enable investigation of other ADRD risk factors and interventions, eye disease research, and a more precise approach to managing individual patients.