Evidence map›Paper›PMID 38748266›Full record

ArticleIntensive care medicine2024

Frailty, Outcomes, Recovery and Care Steps of Critically Ill Patients (FORECAST): a prospective, multi-centre, cohort study.

John Muscedere, Sean M Bagshaw, Michelle Kho, Sangeeta Mehta, Deborah J Cook, J Gordon Boyd, Stephanie Sibley, Han T Wang, Patrick M Archambault, Martin Albert and 10 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Intensive care medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
–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

39 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

20 authors.

John MuscedereDepartment of Critical Care Medicine, Kingston Health Sciences Center, Queen's University, 76 Stuart Street, Kingston, ON, K7L 2V7, Canada. John.Muscedere@kingstonhsc.ca.ORCID 0000-0002-9027-7198
Sean M BagshawDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, Edmonton, Canada.
Michelle KhoSchool of Rehabilitation Science, Faculty of Health Science, Physiotherapy Department, McMaster University, St. Joseph's Healthcare, Hamilton, ON, Canada.
Sangeeta MehtaInterdepartmental Division of Critical Care Medicine, Department of Medicine, Sinai Health System, University of Toronto, Toronto, ON, Canada.
Deborah J CookDepartments of Medicine, Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
J Gordon BoydDepartment of Medicine (Neurology) and Critical Care Medicine, Queen's University, Kingston, ON, Canada.
Stephanie SibleyDepartment of Critical Care Medicine, Kingston Health Sciences Center, Queen's University, 76 Stuart Street, Kingston, ON, K7L 2V7, Canada.
Han T WangDivision of Critical Care Medicine, Department of Medicine, Centre Hospitalier de L'Universite de Montreal, Montreal, QC, Canada.
Patrick M ArchambaultDepartment of Family Medicine and Emergency Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada.
Martin AlbertDivision of Critical Care Medicine, Department of Medicine, Hôpital du Sacré-Coeur de Montréal Research Center and Université de Montréal, Montreal, QC, Canada.
Oleksa G RewaDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, Edmonton, Canada.
Ian BallDepartment of Medicine and Department of Epidemiology and Biostatistics, Western University, London, ON, Canada.
Patrick A NormanKingston General Health Research Institute and Kingston Health Sciences Centre, Kingston, Canada.
Andrew G DayKingston General Health Research Institute and Kingston Health Sciences Centre, Kingston, Canada.
Miranda HuntDepartment of Critical Care Medicine, Kingston Health Sciences Center, Queen's University, 76 Stuart Street, Kingston, ON, K7L 2V7, Canada.
Osama LoubaniDepartment of Critical Care, Dalhousie University, Halifax, ON, Canada.
Tina MeleDepartment of Surgery, University of Western Ontario, London, ON, Canada.
Aimee J SartiDepartment of Critical Care, The Ottawa Hospital, Ottawa Hospital Research Institute, Ottawa, ON, Canada.
Jason ShahinDepartment of Medicine, McGill University, Montreal, Qc, Canada.
Canadian Critical Care Trials Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeFrailty is common in critically ill patients but the timing and optimal method of frailty ascertainment, trajectory and relationship with care processes remain uncertain. We sought to elucidate the trajectory and care processes of frailty in critically ill patients as measured by the Clinical Frailty Scale (CFS) and Frailty Index (FI).

methodsThis is a multi-centre prospective cohort study enrolling patients ≥ 50 years old receiving life support > 24 h. Frailty severity was assessed with a CFS, and a FI based on the elements of a comprehensive geriatric assessment (CGA) at intensive care unit (ICU) admission, hospital discharge and 6 months. For the primary outcome of frailty prevalence, it was a priori dichotomously defined as a CFS ≥ 5 or FI ≥ 0.2. Processes of care, adverse events were collected during ICU and ward stays while outcomes were determined for ICU, hospital, and 6 months.

resultsIn 687 patients, whose age (mean ± standard deviation) was 68.8 ± 9.2 years, frailty prevalence was higher when measured with the FI (CFS, FI %): ICU admission (29.8, 44.8), hospital discharge (54.6, 67.9), 6 months (34.1, 42.6). Compared to ICU admission, aggregate frailty severity increased to hospital discharge but improved by 6 months; individually, CFS and FI were higher in 45.3% and 50.6% patients, respectively at 6 months. Compared to hospital discharge, 18.7% (CFS) and 20% (FI) were higher at 6 months. Mortality was higher in frail patients. Processes of care and adverse events were similar except for worse ICU/ward mobility and more frequent delirium in frail patients.

conclusionsFrailty severity was dynamic, can be measured during recovery from critical illness using the CFS and FI which were both associated with worse outcomes. Although the CFS is a global measure, a CGA FI based may have advantages of being able to measure frailty levels, identify deficits, and potential targets for intervention.

Indexed as

Critical IllnessFrailtyGeriatric AssessmentIntensive Care UnitsAgedAged, 80 and overCohort StudiesCritical CareFemaleFrail ElderlyHumansMaleMiddle AgedPrevalenceProspective StudiesClinical Frailty ScaleFrailtyFrailty IndexOutcomesProcess measures

Identifiers

PMID38748266
PMCPMC11245420

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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.