Surgical complications are common, costly, and deadly. Older patients are at high risk of adverse surgical outcomes, especially when they exhibit frailty. Frailty is a state of decreased physiologic reserve and loss of capacity to adapt to stressors. Over the past decade, while frailty has been increasingly recognized as an important risk factor for poor surgical outcomes, integration of a standardized frailty metric into clinical care has not been achieved. A key barrier is that existing frailty assessments are not standardized, objective, or widely available, limiting their routine application in surgical decision-making. With the long-term goal of improving surgical care for older adults, we will evaluate two ?e-frailty? metrics that can be automatically derived from electronic or digital data that are already collected as part of routine clinical care. These e-frailty metrics include, first, granular patient profiles of electronic health record (EHR) data (risk scores based on claims data or on physiologic and laboratory values), and second, muscle loss assessed from pre-surgical computed tomography (CT) scans (low skeletal muscle mass, known as sarcopenia, and fatty infiltration into muscle indicative of reduced physical function, known as myosteatosis).
In Aim 1, we will calculate these two e-frailty metrics among a diverse population of over 41,000 abdominal surgical patients; characterize the overlap between patients designated as frail by the two e-frailty metrics; and evaluate their associations with 30-day readmission and other adverse surgical outcomes (30-day and 1-year mortality, complications, non-home discharge, and length of stay >7 days).
In Aim 2, we will compare the performance of e-frailty metrics for predicting 30-day readmission and other adverse surgical outcomes to that of standard risk stratification tools (acute and chronic illness severity metrics) already embedded in EHRs today using cross-validation and an independent validation dataset of over 14,000 more recent abdominal surgeries.
In Aim 3, we will examine whether e-frailty metrics modify the benefits that patients derive from achieving postoperative targets -including early and sustained mobilization- in one of the largest Enhanced Recovery After Surgery (ERAS) programs in the nation. We will examine e-frailty metrics as salient indicators of biologic age for predicting morbidity and mortality. In sum, e-frailty metrics show great promise for identifying high-risk patients in the surgical domain, but they need to be integrated within clinical workflows to be scalable and sustainable. This proposal will compute standardized e-frailty metrics automatically derived from EHR data and provide new information regarding the potential value of these e-frailty metrics for improving surgical care for older adults. This study will also lay the groundwork for future prospective interventions integrating e-frailty metrics into clinical care to improve risk stratification and counseling of patients considering surgery and enhance perioperative care for frail surgical patients.

Public Health Relevance

Patient frailty increases the risk for surgical complications, which are common, costly, and deadly, especially for older Americans. To improve surgical care for older adults, we will investigate whether electronic measures of frailty can help reduce complications by identifying which patients are likely to be readmitted to the hospital or die soon after surgery.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project (R01)
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Biomedical Computing and Health Informatics Study Section (BCHI)
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Salive, Marcel
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Kaiser Foundation Research Institute
United States
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