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

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 ac...

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Veröffentlicht in:Stroke (1970) 2021-09, Vol.52 (9), p.2874-2881
Hauptverfasser: Kilkenny, Monique F., Phan, Hoang T., Lindley, Richard I., Kim, Joosup, Lopez, Derrick, Dalli, Lachlan L., Grimley, Rohan, Sundararajan, Vijaya, Thrift, Amanda G., Andrew, Nadine E., Donnan, Geoffrey A., Cadilhac, Dominique A.
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container_end_page 2881
container_issue 9
container_start_page 2874
container_title Stroke (1970)
container_volume 52
creator Kilkenny, Monique F.
Phan, Hoang T.
Lindley, Richard I.
Kim, Joosup
Lopez, Derrick
Dalli, Lachlan L.
Grimley, Rohan
Sundararajan, Vijaya
Thrift, Amanda G.
Andrew, Nadine E.
Donnan, Geoffrey A.
Cadilhac, Dominique A.
description 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. 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. 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 (ORadjusted, 1.05 [95% CI, 1.04 to 1.06), 90-day mortality (HRadjusted, 1.04 [95% CI, 1.03 to 1.05]), readmissions (ORadjusted, 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. 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.
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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. 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 (&gt;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 (&gt;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. 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 (ORadjusted, 1.05 [95% CI, 1.04 to 1.06), 90-day mortality (HRadjusted, 1.04 [95% CI, 1.03 to 1.05]), readmissions (ORadjusted, 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. Greater frailty was associated with worse outcomes following stroke/transient ischemic attack. 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A 1-point increase in frailty (continuous variable) was associated with greater length of stay (ORadjusted, 1.05 [95% CI, 1.04 to 1.06), 90-day mortality (HRadjusted, 1.04 [95% CI, 1.03 to 1.05]), readmissions (ORadjusted, 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. Greater frailty was associated with worse outcomes following stroke/transient ischemic attack. 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source MEDLINE; American Heart Association Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection; Journals@Ovid Complete
subjects Aged
Aged, 80 and over
Female
Frailty - mortality
Hospitalization - statistics & numerical data
Hospitals - statistics & numerical data
Humans
Ischemic Attack, Transient - mortality
Length of Stay - statistics & numerical data
Male
Middle Aged
Outcome Assessment, Health Care
Quality of Life
Registries
Risk Factors
Stroke - mortality
title Utility of the Hospital Frailty Risk Score Derived From Administrative Data and the Association With Stroke Outcomes
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