Evidence map›Paper›PMID 40314855›Full record

Observational studyEuropean geriatric medicine2025

Validation of the hospital frailty risk score in China.

Yue Qiu, Weiqing Xiong, Xinyue Fang, Pei Li, Simon Conroy, Laia Maynou, Kenneth Rockwood, Xien Liu, Ji Wu, Andrew Street

Abstract readObservational StudyValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in European geriatric medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

10 authors.

Yue QiuTsinghua Medicine, Tsinghua University, Haidian District, Beijing, 100084, China.
Weiqing XiongTsinghua Medicine, Tsinghua University, Haidian District, Beijing, 100084, China.
Xinyue FangTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, 518055, China.
Pei LiTsinghua Medicine, Tsinghua University, Haidian District, Beijing, 100084, China.
Simon ConroyWolfson Institute of Population Health, Queen Mary University of London, Mile End Road, E1 4NS, London, UK.
Laia MaynouDepartment of Econometrics, Statistics and Applied Economics, Universitat de Barcelona, Barcelona, Spain.
Kenneth RockwoodDivision of Geriatric Medicine, Frailty Elder Care Network, Nova Scotia Health, Dalhousie University, Halifax, NS, B3H2E1, Canada.
Xien LiuDepartment of Electronic Engineering, Tsinghua University, Beijing, 100084, China.
Ji WuDepartment of Electronic Engineering, Tsinghua University, Beijing, 100084, China.
Andrew StreetDepartment of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, UK. a.street@lse.ac.uk.ORCID http://orcid.org/0000-0002-2540-0364

Funding

National Institute for Health and Care Research NIHR 203451
6 · The paper itself

Abstract

purposeTo validate the Hospital Frailty Risk Score (HFRS) in Chinese hospital settings, describing how patients are allocated to frailty risk groups and how frailty risk is associated with length of stay (LoS) and hospital costs.

designRetrospective observational study.

settingForty-eight hospitals in Lvliang City, Shanxi Province, China. SUBJECTS: Patients aged 75 years or older hospitalised between 1 January 2022 and 31 December 2023 (n = 34,731).

methodsA logistic regression model examined the association between long length of stay (LoS) and frailty risk. A generalised linear model assessed the association between hospital costs and frailty risk. Subgroup analyses of age group, sex, and hospital tiers were conducted.

results22.2% of patients were categorised as having zero risk, 62.4% as low risk, 15.3% as intermediate risk, and 0.08% as high risk. Compared to the zero risk group: for those with low risk, the probability of long LoS was 1.92 (95% CI 1.79-2.06) times higher and hospital costs were ¥1926 (95% CI 1655-2197) higher; for those with intermediate risk, the probability of long LoS was 2.7 (95% CI 2.49-2.96) times higher and hospital costs were ¥4284 (95% CI 3916-4653) higher; and for those with high risk, the probability of long LoS was 6.7 (95% CI 3.06-14.43) times higher and hospital costs were ¥16,613 (95% CI 12,827-20,399) higher. The explanatory power of the HFRS held across subgroups.

conclusionsCompared to patients aged 75 + elsewhere, those in China had lower frailty risk scores, likely reflecting a younger age structure and recording of fewer diagnosis codes. Even so, the HFRS is a powerful predictor of long length of stay and hospital costs in China.

Indexed as

Frail ElderlyFrailtyGeriatric AssessmentHospital CostsHospitalizationLength of StayAgedAged, 80 and overChinaFemaleHumansMaleRetrospective StudiesRisk AssessmentRisk FactorsFrailty risk assessmentHFRSHospital costsHospital frailty risk scoreLength of stay

Identifiers

PMID40314855
PMCPMC12378284

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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.