Abstract

Aims:Reduced pre-operative cognitive functioning in older adults is a risk factor for postoperative complications, but it is unknown if preoperative digitally-acquired clock drawing test (CDT) cognitive screening variables, which allow for more nuanced examination of patient performance, may predict lengthier hospital stay and greater cost of hospital care. This issue is particularly relevant for older adults undergoing transcatheter aortic valve replacement (TAVR), as this surgical procedure is chosen for intermediate-risk older adults needing aortic replacement. This proof of concept research explored if specific latency and graphomotor variables indicative of planning from digitally-acquired command and copy clock drawing would predict post-TAVR duration and cost of hospitalization, over and above age, education, American Society of Anesthesiologists (ASA) physical status classification score, and frailty.Methods:Form January 2018 to December 2019, 162 out of 190 individuals electing TAVR completed digital clock drawing as part of a hospital wide cognitive screening program. Separate hierarchical regressions were computed for the command and copy conditions of the CDT and assessed how a-priori selected clock drawing metrics (total time to completion, ideal digit placement difference, and hour hand distance from center; included within the same block) incrementally predicted outcome, as measured by R2 change significance values.Results:Above and beyond age, education, ASA physical status classification score, and frailty, only digitally-acquired CDT copy performance explained significant variance for length of hospital stay (9.5%) and cost of care (8.9%).Conclusions:Digital variables from clock copy condition provided predictive value over common demographic and comorbidity variables. We hypothesize this is due to the sensitivity of the copy condition to executive dysfunction, as has been shown in previous studies for subtypes of cognitive impairment. Individuals undergoing TAVR procedures are often frail and executively compromised due to their cerebrovascular disease. We encourage additional research on the value of digitally-acquired clock drawing within different surgery types. Type of cognitive impairment and the value of digitally-acquired CDT command and copy parameters in other surgeries remain unknown.

Highlights

  • Preoperative cognitive impairments are well known predictors of negative cognitive postoperative outcomes [1,2,3,4,5,6], it remains unknown if preoperative cognitive screening metrics provide valuable predictive information relevant to hospitals providing the care for older adults electing surgical procedures

  • transcatheter aortic valve replacement (TAVR) is associated with reduced mortality relative to standard surgical aortic valve replacement, the procedure can still be accompanied by negative complications impacting hospital cost and stay, e.g., Tilley and colleagues [8] reported that 23% of patients aged 60 years or older who underwent TAVR experience delirium, a preventative cause of cognitive impairment and dementia

  • Integrating preoperative cognitive biomarkers into the model is the logical research approach, given: (1) the abundance of research documenting the significance of preoperative cognition on postoperative outcome [6]; (2) that 54% of all surgical procedures are performed on older adults [13]; (3) prospective hospital-based studies show at least 20% of older adults electing surgical procedures have mild to moderate cognitive limitations on standardized screening metrics [14, 15]; and (4) general surgery guidelines strongly recommend at minimum preoperative cognitive screening for older adults electing surgery

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Summary

Introduction

Preoperative cognitive impairments are well known predictors of negative cognitive postoperative outcomes [1,2,3,4,5,6], it remains unknown if preoperative cognitive screening metrics provide valuable predictive information relevant to hospitals providing the care for older adults electing surgical procedures. Cognitive screenings could serve as a functional biomarker to predict which patients may benefit from improved care planning thereby reducing postoperative hospital costs and stay. It is important, to identify a screening tool that can be used by medical staff and provide rapid information yet remain sensitive to subtle effects of abnormal aging [14]

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