Evidence map›Paper›PMID 35505435›Full record

ArticleCritical care (London, England)2022

Comparison of the predictive ability of clinical frailty scale and hospital frailty risk score to determine long-term survival in critically ill patients: a multicentre retrospective cohort study.

Ashwin Subramaniam, Ryo Ueno, Ravindranath Tiruvoipati, Velandai Srikanth, Michael Bailey, David Pilcher

Abstract readMulticenter Study
In one paragraph

Article in Critical care (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

  1. Recognise, respond, reflect: A value-based framework for rapid response teams.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2026
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  12. Frailty in Pulmonary Hypertension: A Multidimensional Comorbidity.Annals of the American Thoracic Society · 2025
    Review
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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

6 authors.

Ashwin SubramaniamDepartment of Intensive Care, Frankston Hospital, Peninsula Health, 2 Hastings Road, VIC, 3199, Frankston, Australia. ashwin.subramaniam@monash.edu.
Ryo UenoAustralian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Ravindranath TiruvoipatiDepartment of Intensive Care, Frankston Hospital, Peninsula Health, 2 Hastings Road, VIC, 3199, Frankston, Australia.
Velandai SrikanthPeninsula Clinical School, Monash University, Frankston, VIC, Australia.
Michael BaileyAustralian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
David PilcherAustralian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Clinical Frailty Scale (CFS) is the most commonly used frailty measure in intensive care unit (ICU) patients. The hospital frailty risk score (HFRS) was recently proposed for the quantification of frailty. We aimed to compare the HFRS with the CFS in critically ill patients in predicting long-term survival up to one year following ICU admission.

methodsIn this retrospective multicentre cohort study from 16 public ICUs in the state of Victoria, Australia between 1st January 2017 and 30th June 2018, ICU admission episodes listed in the Australian and New Zealand Intensive Care Society Adult Patient Database registry with a documented CFS, which had been linked with the Victorian Admitted Episode Dataset and the Victorian Death Index were examined. The HFRS was calculated for each patient using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes that represented pre-existing conditions at the time of index hospital admission. Descriptive methods, Cox proportional hazards and area under the receiver operating characteristic (AUROC) were used to investigate the association between each frailty score and long-term survival up to 1 year, after adjusting for confounders including sex and baseline severity of illness on admission to ICU (Australia New Zealand risk-of-death, ANZROD).

results7001 ICU patients with both frailty measures were analysed. The overall median (IQR) age was 63.7 (49.1-74.0) years; 59.5% (n = 4166) were male; the median (IQR) APACHE II score 14 (10-20). Almost half (46.7%, n = 3266) were mechanically ventilated. The hospital mortality was 9.5% (n = 642) and 1-year mortality was 14.4% (n = 1005). HFRS correlated weakly with CFS (Spearman's rho 0.13 (95% CI 0.10-0.15) and had a poor agreement (kappa = 0.12, 95% CI 0.10-0.15). Both frailty measures predicted 1-year survival after adjusting for confounders, CFS (HR 1.26, 95% CI 1.21-1.31) and HFRS (HR 1.08, 95% CI 1.02-1.15). The CFS had better discrimination of 1-year mortality than HFRS (AUROC 0.66 vs 0.63 p < 0.0001).

conclusionBoth HFRS and CFS independently predicted up to 1-year survival following an ICU admission with moderate discrimination. The CFS was a better predictor of 1-year survival than the HFRS.

Indexed as

FrailtyAdultAgedCohort StudiesCritical IllnessFemaleHospitalsHumansMaleMiddle AgedProspective StudiesRetrospective StudiesRisk FactorsVictoria1-year survivalCFSClinical frailty scaleFrailtyHFRSHospital frailty risk scoreLong-term outcomes

Identifiers

PMID35505435
PMCPMC9063154

What OpenQuestion holds

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Registered trials

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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.