Autor: |
Eisner, Ashley E., Witek, Lauren, Pajewski, Nicholas M., Taylor, Stephanie P., Bundy, Richa, Williamson, Jeff D., Jaeger, Byron C., Palakshappa, Jessica A. |
Předmět: |
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Zdroj: |
BMC Geriatrics; 11/29/2024, Vol. 24 Issue 1, p1-8, 8p |
Abstrakt: |
Background: New or worsening cognitive impairment or dementia is common in older adults following an episode of critical illness, and screening post-discharge is recommended for those at increased risk. There is a need for prediction models of post-ICU cognitive impairment to guide delivery of screening and support resources to those in greatest need. We sought to develop and internally validate a machine learning model for new cognitive impairment or dementia in older adults after critical illness using electronic health record (EHR) data. Methods: Our cohort included patients > 60 years of age admitted to a large academic health system ICU in North Carolina between 2015 and 2021. Patients were included in the cohort if they were admitted to the ICU for ≥ 48 h with ≥ 2 ambulatory visits prior to hospitalization and at least one visit in the post-discharge year. We used a machine learning model, oblique random survival forests (ORSF), to examine the multivariable association of 54 structured data elements available by 3 months after discharge with incident diagnoses of cognitive impairment or dementia over 1-year. Results: In this cohort of 8,299 adults, 22% died and 4.9% were diagnosed with dementia or cognitive impairment within one year. The ORSF model showed reasonable discrimination (c-statistic = 0.83) and stability with little difference in the model's c-statistic across time. Conclusion: Machine learning using readily available EHR data can predict new cognitive impairment or dementia at 1-year post-ICU discharge in older adults with acceptable accuracy. Further studies are needed to understand how this tool may impact screening for cognitive impairment in the post-discharge period. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
Externí odkaz: |
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