An automated electronic health‐record derived frailty index is associated with adverse events after endoscopy

Rejeski, Jared; Ted, Xiao,; Wheless, W.H.; Pajewski, Nicholas M.; Jensen, Elizabeth T.; Callahan, Kathryn E.

doi:10.1111/jgs.17537

Cited by 8 publications

(2 citation statements)

References 11 publications

(14 reference statements)

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“…Using frailty assessment tools based on EHRs may bridge the gap between frailty research and clinical frailty assessment. 47–49…”

Section: Discussionmentioning

confidence: 99%

“…Using frailty assessment tools based on EHRs may bridge the gap between frailty research and clinical frailty assessment. [47][48][49] Similarly, a formal quantification of frailty in patients with stroke could be helpful in the design, execution and analysis of clinical trials evaluating novel treatments for stroke, complementing the notion of chronological age with information about the clinical status of patients.…”

Section: Discussionmentioning

confidence: 99%

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Higher Hospital Frailty Risk Score Is Associated With Increased Risk of Stroke: Observational and Genetic Analyses

Renedo

Acosta

Koo

et al. 2023

Stroke

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Background: Frailty is a prevalent state associated with several aging-related traits and conditions. The relationship between frailty and stroke remains understudied. Here we aim to investigate whether the hospital frailty risk score (HFRS) is associated with the risk of stroke and determine whether a significant association between genetically determined frailty and stroke exists. Design: Observational study using data from All of Us research program and Mendelian Randomization analyses. Methods: Participants from All of Us with available electronic health records were selected for analysis. All of Us began national enrollment in 2018 and is expected to continue for at least 10 years. All of Us is recruiting members of groups that have traditionally been underrepresented in research. All participants provided informed consent at the time of enrollment, and the date of consent was recorded for each participant. Incident stroke was defined as stroke event happening on or after the date of consent to the All of Us study HFRS was measured with a 3-year look-back period before the date of consent for stroke risk. The HFRS was stratified into 4 categories: no-frailty (HFRS=0), low (HFRS ≥1 and <5), intermediate (≥5 and <15), and high (HFRS ≥15). Last, we implemented Mendelian Randomization analyses to evaluate whether genetically determined frailty is associated with stroke risk. Results: Two hundred fifty-three thousand two hundred twenty-six participants were at risk of stroke. In multivariable analyses, frailty status was significantly associated with risk of any (ischemic or hemorrhagic) stroke following a dose-response way: not-frail versus low HFRS (HR, 4.9 [CI, 3.5–6.8]; P <0.001), not-frail versus intermediate HFRS (HR, 11.4 [CI, 8.3–15.7]; P <0.001) and not-frail versus high HFRS (HR, 42.8 [CI, 31.2–58.6]; P <0.001). We found similar associations when evaluating ischemic and hemorrhagic stroke separately ( P value for all comparisons <0.05). Mendelian Randomization confirmed this association by indicating that genetically determined frailty was independently associated with risk of any stroke (OR, 1.45 [95% CI, 1.15–1.84]; P =0.002). Conclusions: Frailty, based on the HFRS was associated with higher risk of any stroke. Mendelian Randomization analyses confirmed this association providing evidence to support a causal relationship.

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“…Using frailty assessment tools based on EHRs may bridge the gap between frailty research and clinical frailty assessment. 47–49…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%