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Utility of the Hospital Frailty Risk Score Derived From Administrative Data and the Association With Stroke Outcomes

2021; Lippincott Williams & Wilkins; Volume: 52; Issue: 9 Linguagem: Inglês

10.1161/strokeaha.120.033648

1524-4628

Monique F. Kilkenny, Hoang Phan, Richard I. Lindley, Joosup Kim, Derrick Lopez, Lachlan L. Dalli, Rohan Grimley, Vijaya Sundararajan, Amanda G. Thrift, Nadine E. Andrew, Geoffrey A. Donnan, Dominique A. Cadilhac, Craig S. Anderson, Julie Bernhardt, Paul Bew, Christopher Bladin, Greg Cadigan, Helen Castley, Andrew Lee, Mark T. Mackay, Sandra Martyn, John S. McNeil, Sandy Middleton, Michael Pollack, Mark Simcocks, Frances D Simmonds, Helen M. Dewey, Steven Faux, Kelvin Hill, Christopher Levi, Christopher Price, P Bambery, T. S. Bates, Carolyn Beltrame, David Blacker, Ernie Butler, Sean Butler, Douglas E. Crompton, Vanessa Crosby, Carolyn De Wytt, David D. Douglas, Martin Dunlop, Paula Easton, Sharan Ermel, Nisal Gange, Richard Geraghty, Melissa Gill, Graham L. Hall, Peter J. Hand, Geoffrey Herkes, Karen Hines, Francis Hishon, James A. Hughes, Joel Iedema, Martin Jude, Thomas Kræmer, Paul Laird, Johanna Madden, Graham Mahaffey, Suzana Milosevic, Peter C. O’Brien, Stephen Read, Kristen Rowe, Fiona Ryan, Arman Sabet, Noel Saines, Eva Salud, Amanda Siller, Christopher Staples, R. L. White, Andrew Wong, Robin Armstrong, Leonid Churilov, A.R. Dias, Adele Gibbs, Brenda Grabsch, Francis Kung, Joyce Lim, Karen Moss, Kate Paice, Enna Stroil-Salama, Sabrina Small, Renee Stojanovic, Steven J. Street, Emma Tod, Kasey Wallis,

Acute Ischemic Stroke Management

Background and Purpose: Conditions associated with frailty are common in people experiencing stroke and may explain differences in outcomes. We assessed associations between a published, generic frailty risk score, derived from administrative data, and patient outcomes following stroke/transient ischemic attack; and its accuracy for stroke in predicting mortality compared with other measures of clinical status using coded data. Methods: Patient-level data from the Australian Stroke Clinical Registry (2009–2013) were linked with hospital admissions data. We used International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes with a 5-year look-back period to calculate the Hospital Frailty Risk Score (termed Frailty Score hereafter) and summarized results into 4 groups: no-risk (0), low-risk (1–5), intermediate-risk (5–15), and high-risk (>15). Multilevel models, accounting for hospital clustering, were used to assess associations between the Frailty Score and outcomes, including mortality (Cox regression) and readmissions up to 90 days, prolonged acute length of stay (>20 days; logistic regression), and health-related quality of life at 90 to 180 days (quantile regression). The performance of the Frailty Score was then compared with the Charlson and Elixhauser Indices using multiple tests (eg, C statistics) for predicting 30-day mortality. Models were adjusted for covariates including sociodemographics and stroke-related factors. Results: Among 15 468 adult patients, 15% died ≤90 days. The frailty scores were 9% no risk; 23% low, 45% intermediate, and 22% high. A 1-point increase in frailty (continuous variable) was associated with greater length of stay (OR adjusted , 1.05 [95% CI, 1.04 to 1.06), 90-day mortality (HR adjusted , 1.04 [95% CI, 1.03 to 1.05]), readmissions (OR adjusted , 1.02 [95% CI, 1.02 to 1.03]; and worse health-related quality of life (median difference, −0.010 [95% CI −0.012 to −0.010]). Adjusting for the Frailty Score provided a slightly better explanation of 30-day mortality (eg, larger C statistics) compared with other indices. Conclusions: Greater frailty was associated with worse outcomes following stroke/transient ischemic attack. The Frailty Score provides equivalent precision compared with the Charlson and Elixhauser indices for assessing risk-adjusted outcomes following stroke/transient ischemic attack.