Evidence map›Paper›PMID 36511440›Full record

ArticleAustralasian journal on ageing2023

Comparison of a multidomain frailty index from routine health data with the hospital frailty risk score in older patients in an Australian hospital.

Kenji Fujita, Sarita Y Lo, Ruth E Hubbard, Danijela Gnjidic, Sarah N Hilmer

Open access · hybridAbstract read
In one paragraph

Article in Australasian journal on ageing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Neural embedding of frailty in cognitively unimpaired aging and dementia across Latin America.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  3. Article
  4. Observational
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Kenji FujitaDepartments of Clinical Pharmacology and Aged Care, Faculty of Medicine and Health, The University of Sydney, Kolling Institute, Royal North Shore Hospital, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0001-7876-6004
Sarita Y LoDepartments of Clinical Pharmacology and Aged Care, Faculty of Medicine and Health, The University of Sydney, Kolling Institute, Royal North Shore Hospital, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-5272-9958
Ruth E HubbardCentre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-8688-5836
Danijela GnjidicSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-9404-3401
Sarah N HilmerDepartments of Clinical Pharmacology and Aged Care, Faculty of Medicine and Health, The University of Sydney, Kolling Institute, Royal North Shore Hospital, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-5970-1501
The University of Sydney · AUThe University of Queensland · AU

Funding

The Australian National Health and Medical Research Council Targeted Call for Research into Frailty in Hospital Care (APP 1174447)
6 · The paper itself

Abstract

backgroundFrailty is an important determinant of health-care needs and outcomes for people in hospital.

objectivesTo compare characteristics and predictive ability of a multidomain frailty index derived from routine health data (electronic frailty index-acute hospital; eFI-AH) with the hospital frailty risk score (HFRS).

methodsThis retrospective study included 6771 patients aged ≥75 years admitted to an Australian metropolitan tertiary referral hospital between October 2019 and September 2020. The eFI-AH and the HFRS were calculated for each patient and compared with respect to characteristics, agreement, association with age and ability to predict outcomes.

resultsMedian eFI-AH was 0.17 (range 0-0.66) whilst median HFRS was 3.2 (range 0-42.9). Moderate agreement was shown between the tools (Pearson's r 0.61). After adjusting for age and gender, both models had associations with long hospital stay, in-hospital mortality, unplanned all-cause readmission and fall-related readmission. Specifically, the eFI-AH had the strongest association with in-hospital mortality (adjusted odds ratio (aOR) 2.81, 95% confidence intervals (CI) 2.49-3.17), whilst the HFRS was most strongly associated with long hospital stay (aOR 1.20, 95% CI 1.18-1.21). Both tools predicted hospital stay >10 days with good discrimination and calibration.

conclusionsAlthough the eFI-AH and the HFRS did not consistently identify the same inpatients as frail, both were associated with adverse outcomes and they had comparable predictive ability for prolonged hospitalisation. These two constructs of frailty may have different implications for clinical practice and health service provision and planning.

Indexed as

Frail ElderlyFrailtyAgedAustraliaGeriatric AssessmentHospitalsHumansRetrospective StudiesRisk Factorsfrail elderlyfrailtyhospitalslength of stayrisk assessment

Identifiers

PMID36511440
PMCPMC10946514
OpenAlexW4311287569

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.