Why the study?
People living with frailty face poor outcomes and higher costs after CABG surgery, but frailty-defining instruments for population-level research in this setting have not been established.
Does a preoperative frailty index (pFI-C) derived from administrative data predict mortality, resource utilization, and costs in patients undergoing CABG surgery?
Does a preoperative frailty index (pFI-C) derived from administrative data predict mortality, resource utilization, and costs in patients undergoing CABG surgery?
A newly developed 27-item preoperative frailty index (pFI-C) using administrative data strongly predicts 1-year mortality, resource utilization, and healthcare costs in patients undergoing CABG.
Background: People living with frailty are vulnerable to poor outcomes and incur higher health care costs after coronary artery bypass graft (CABG) surgery. Frailty-defining instruments for population-level research in the CABG setting have not been established. The objectives of the study were to develop a preoperative frailty index for CABG (pFI-C) surgery using Ontario administrative data; assess pFI-C suitability in predicting clinical and economic outcomes; and compare pFI-C predictive capabilities with other indices. Methods: A retrospective cohort study was conducted using health administrative data of 50,682 CABG patients. The pFI-C comprised 27 frailty-related health deficits. Associations between index scores and mortality, resource use and health care costs (2022 Canadian dollars [CAD]) were assessed using multivariable regression models. Capabilities of the pFI-C in predicting mortality were evaluated using concordance statistics; goodness of fit of the models was assessed using Akakie Information Criterion. Results: As assessed by the pFI-C, 22% of the cohort lived with frailty. The pFI-C score was strongly associated with mortality per 10% increase (odds ratio [OR], 3.04; 95% confidence interval [CI], [2.83,3.27]), and was significantly associated with resource utilization and costs. The predictive performances of the pFI-C, Charlson, and Elixhauser indices and Johns Hopkins Aggregated Diagnostic Groups were similar, and mortality models containing the pFI-C had a concordance (C)-statistic of 0.784. Cost models containing the pFI-C showed the best fit. Conclusions: The pFI-C is predictive of mortality and associated with resource utilization and costs during the year following CABG. This index could aid in identifying a subgroup of high-risk CABG patients who could benefit from targeted perioperative health care interventions.
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Johnson et al. (2023) studied this question.
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