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External validation of an AI-based preoperative frailty index using real-world data.
Chen Bai1, Feifei Xiao2, Mohammad Al-Ani3
1Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, United States.
Summary
An artificial intelligence (AI)-based frailty index accurately predicts surgical risk in older adults. This AI tool, using electronic health records (EHR), identifies high-risk patients for better surgical care.
Area of Science:
- Geriatric Medicine
- Surgical Oncology
- Health Informatics
Background:
- Preoperative frailty assessment is vital for surgical risk stratification in older adults.
- Traditional frailty measures are often time-consuming and resource-intensive.
- This study validates an artificial intelligence (AI)-based frailty index using electronic health records (EHR).
Purpose of the Study:
- To externally validate an AI-based frailty index for preoperative risk stratification.
- To assess the index's association with postoperative outcomes.
- To compare general and service-specific AI frailty indices.
Main Methods:
- External validation of a previously developed AI frailty index.
- Analysis of a cohort of 1,523,364 surgical patients aged 65+.
- Examination of associations between predicted frailty and 30-day mortality, hospital stay, and discharge disposition.
Main Results:
- The AI frailty index showed a strong association with adverse postoperative outcomes.
- Highest frailty group (top 20%) had significantly higher odds of 30-day mortality (OR 4.33) and longer hospital stays (2.53x).
- General AI frailty index performed comparably to or better than service-specific indices.
Conclusions:
- The AI-based preoperative frailty index effectively predicts postoperative outcomes in a large external cohort.
- The index's efficiency and predictive performance can improve surgical risk stratification and patient outcomes.
- AI-driven frailty assessment offers a promising approach to enhance surgical care for older adults.
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