Institution-free days after critical illness: A multicenter retrospective study

Prashanti Marella; Kevin B Laupland; Kiran Shekar; Alexis Tabah; Felicity Edwards; Mahesh Ramanan

doi:10.1016/j.jcrc.2023.154253

Institution-free days after critical illness: A multicenter retrospective study

J Crit Care. 2023 Apr:74:154253. doi: 10.1016/j.jcrc.2023.154253. Epub 2023 Jan 12.

Authors

Prashanti Marella¹, Kevin B Laupland², Kiran Shekar³, Alexis Tabah⁴, Felicity Edwards⁵, Mahesh Ramanan⁶

Affiliations

¹ Intensive Care Unit, Caboolture Hospital, Metro North Hospital and Health Services, Queensland, Australia; Mater Clinical Unit, University of Queensland, Brisbane, Australia.
² Queensland University of Technology (QUT), Brisbane, Queensland, Australia; Department of Intensive Care Services, Royal Brisbane and Womens hospital, Brisbane, Queensland, Australia.
³ The Prince Charles Hospital, Brisbane, Queensland, Australia; Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia.
⁴ Queensland University of Technology (QUT), Brisbane, Queensland, Australia; Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia; Intensive Care Unit, Redcliffe Hospital, Metro North Hospital and Health Services, Queensland, Australia.
⁵ Queensland University of Technology (QUT), Brisbane, Queensland, Australia.
⁶ Intensive Care Unit, Caboolture Hospital, Metro North Hospital and Health Services, Queensland, Australia; The Prince Charles Hospital, Brisbane, Queensland, Australia; Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia; Critical Care Division, The George Institute for Global Health, University of New South Wales, Sydney, Australia. Electronic address: Mahesh.Ramanan@health.qld.gov.au.

PMID: 36640478
DOI: 10.1016/j.jcrc.2023.154253

Abstract

Background: Patient-centered outcomes beyond mortality such as institution-free days (IFD) are becoming increasingly relevant in critical care trials.

Methods: We calculated IFD using three definitions which differed in the way death and censoring of after-hospital deaths were handled analysing data from adult patient databases admitted to four ICUs of North Brisbane, Australia. Differences in distribution of IFD using different definitions were explored with descriptive statistics and histograms. Six pre-specified variables (age, illness severity, comorbidities index, elective status, surgical/medical admission and treatment limitations) were assessed and reported as determinants of IFDs for the proposed definitions.

Results: Data from 25,371 ICU admissions was analysed. The density distribution of IFD was bimodal with a peak at 0 days and a variable right-sided peak depending on the definition used. The mean IFD varied from 253 (standard deviation(SD) 151.3) to 295 (SD 116.2) depending on definition used. Multivariable zero-inflated negative binomial regression modelling showed that the six pre-specified variables had significant associations with IFD and their magnitude of effect varied with the definition used.

Conclusions: IFD is a simple, easily measurable patient-centered outcome that varies depending on the definition used. Patient input should be sought to define the optimum definition and clinical use of IFD.

Keywords: Critical care; Determinants; Institution-free days; Patient-centred outcomes.

Publication types

Multicenter Study
Research Support, Non-U.S. Gov't

MeSH terms

Adult
Critical Care
Critical Illness*
Humans
Intensive Care Units*
Outcome Assessment, Health Care
Retrospective Studies