Evidence map›Paper›PMID 38585676›Full record

ArticleCJC open2024

A Frailty Index to Predict Mortality, Resource Utilization and Costs in Patients Undergoing Coronary Artery Bypass Graft Surgery in Ontario.

Ana Johnson, Elizabeth Hore, Brian Milne, John Muscedere, Yingwei Peng, Daniel I McIsaac, Joel Parlow

Abstract read
In one paragraph

Article in CJC open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Ana JohnsonDepartment of Public Health Sciences, Queen's University, Kingston, Ontario, Canada.
Elizabeth HoreDepartment of Public Health Sciences, Queen's University, Kingston, Ontario, Canada.
Brian MilneDepartment of Anesthesiology and Perioperative Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, Ontario, Canada.
John MuscedereDepartment of Critical Care Medicine, Queen's University, Kingston, Ontario, Canada.
Yingwei PengDepartment of Public Health Sciences, Queen's University, Kingston, Ontario, Canada.
Daniel I McIsaacThe Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Joel ParlowDepartment of Anesthesiology and Perioperative Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: People living with frailty are vulnerable to poor outcomes and incur higher health care costs after coronary artery bypass graft (CABG) surgery. Frailty-defining instruments for population-level research in the CABG setting have not been established. The objectives of the study were to develop a preoperative frailty index for CABG (pFI-C) surgery using Ontario administrative data; assess pFI-C suitability in predicting clinical and economic outcomes; and compare pFI-C predictive capabilities with other indices. Methods: A retrospective cohort study was conducted using health administrative data of 50,682 CABG patients. The pFI-C comprised 27 frailty-related health deficits. Associations between index scores and mortality, resource use and health care costs (2022 Canadian dollars [CAD]) were assessed using multivariable regression models. Capabilities of the pFI-C in predicting mortality were evaluated using concordance statistics; goodness of fit of the models was assessed using Akakie Information Criterion. Results: As assessed by the pFI-C, 22% of the cohort lived with frailty. The pFI-C score was strongly associated with mortality per 10% increase (odds ratio [OR], 3.04; 95% confidence interval [CI], [2.83,3.27]), and was significantly associated with resource utilization and costs. The predictive performances of the pFI-C, Charlson, and Elixhauser indices and Johns Hopkins Aggregated Diagnostic Groups were similar, and mortality models containing the pFI-C had a concordance (C)-statistic of 0.784. Cost models containing the pFI-C showed the best fit. Conclusions: The pFI-C is predictive of mortality and associated with resource utilization and costs during the year following CABG. This index could aid in identifying a subgroup of high-risk CABG patients who could benefit from targeted perioperative health care interventions.

Identifiers

PMID38585676
PMCPMC10994976

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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.