Evidence map›Paper›PMID 35045122›Full record

ArticlePloS one2022

Beyond the revised cardiac risk index: Validation of the hospital frailty risk score in non-cardiac surgery.

Pishoy Gouda, Xiaoming Wang, Erik Youngson, Michael McGillion, Mamas A Mamas, Michelle M Graham

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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.

Pishoy GoudaUniversity of Alberta, Division of Cardiology and Mazankowski Alberta Heart Institute, Edmonton, Alberta, Canada.
Xiaoming WangResearch Facilitation, Alberta Health Services, Edmonton, Alberta, Canada.
Erik YoungsonResearch Facilitation, Alberta Health Services, Edmonton, Alberta, Canada.
Michael McGillionSchool of Nursing, Faculty of Health Sciences and Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada.
Mamas A MamasKeele Cardiovascular Research Group, Centre for Prognosis Research, Keele University, Keele, Newcastle, United Kingdom.
Michelle M GrahamUniversity of Alberta, Division of Cardiology and Mazankowski Alberta Heart Institute, Edmonton, Alberta, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Frailty is an established risk factor for adverse outcomes following non-cardiac surgery. The Hospital Frailty Risk Score (HFRS) is a recently described frailty assessment tool that harnesses administrative data and is composed of 109 International Classification of Disease variables. We aimed to examine the incremental prognostic utility of the HFRS in a generalizable surgical population. Using linked administrative databases, a retrospective cohort of patients admitted for non-cardiac surgery between October 1st, 2008 and September 30th, 2019 in Alberta, Canada was created. Our primary outcome was a composite of death, myocardial infarction or cardiac arrest at 30-days. Multivariable logistic regression was undertaken to assess the impact of HFRS on outcomes after adjusting for age, sex, components of the Charlson Comorbidity Index (CCI), Revised Cardiac Risk Index (RCRI) and peri-operative biomarkers. The final cohort consisted of 712,808 non-cardiac surgeries, of which 55·1% were female and the average age was 53·4 +/- 22·4 years. Using the HFRS, 86.3% were considered low risk, 10·7% were considered intermediate risk and 3·1% were considered high risk for frailty. Intermediate and high HFRS scores were associated with increased risk of the primary outcome with an adjusted odds ratio of 1·61 (95% CI 1·50-1.74) and 1·55 (95% CI 1·38-1·73). Intermediate and high HFRS were also associated with increased adjusted odds of prolonged hospital stay, in-hospital mortality, and 1-year mortality. The HFRS is a minimally onerous frailty assessment tool that can complement perioperative risk stratification in identifying patients at high risk of short- and long-term adverse events.

Indexed as

AdultAgedAlbertaCohort StudiesDatabases, FactualFemaleFrailtyGeneral SurgeryHospitalizationHospital MortalityHospitalsHumansLength of StayLogistic ModelsMaleMiddle Aged

Identifiers

PMID35045122
PMCPMC8769314

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.