Evidence map›Paper›PMID 38091131›Full record

ArticleAnnals of intensive care2023

Frailty's influence on 30-day mortality in old critically ill ICU patients: a bayesian analysis evaluating the clinical frailty scale.

Bernhard Wernly, Raphael Romano Bruno, Michael Beil, Hans Flaatten, Malte Kelm, Sviri Sigal, Wojciech Szczeklik, Muhammed Elhadi, Michael Joannidis, Andreas Koköfer and 8 more

Abstract read
In one paragraph

Article in Annals of intensive care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
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  7. Characteristics and temporality of the ventilatory techniques in the management of acute respiratory distress syndrome: A scoping review.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 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

18 authors.

Bernhard WernlyInstitute of General Practice, Family Medicine and Preventive Medicine, Paracelsus Medical University of Salzburg, 5020, Salzburg, Austria.
Raphael Romano BrunoMedical Faculty, Department of Cardiology, Pulmonology and Vascular Medicine, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany.
Michael BeilDepartment of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, 91120, Jersualem, Israel.
Hans FlaattenDepartment of Clinical Medicine, University of Bergen, Department of Anaestesia and Intensive Care, Haukeland University Hospital, 5021, Bergen, Norway.
Malte KelmMedical Faculty, Department of Cardiology, Pulmonology and Vascular Medicine, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany.
Sviri SigalDepartment of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, 91120, Jersualem, Israel.
Wojciech SzczeklikCenter for Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, 31-008, Krakow, Poland.
Muhammed ElhadiFaculty of Medicine, University of Tripoli, R6XF+46G, Tripoli, Libya.
Michael JoannidisDivision of Intensive Care and Emergency Medicine, Department of Internal Medicine, Medical University Innsbruck, 6020, Innsbruck, Austria.
Andreas KoköferDepartment of Anaesthesiology, Perioperative Medicine and Intensive Care, Paracelsus Medical University of Salzburg, 5020, Salzburg, Austria.
Sandra OeyenDepartment of Intensive Care 1K12IC, Ghent University Hospital, 9000, Ghent, Belgium.
Brian MarshMater Misericordiae University Hospital, Dublin, D07 R2WY, Ireland.
Rui MorenoCentro Hospitalar de Lisboa Central, Faculdade de Ciências Médicas de Lisboa, Nova Medical School, Lisboa, Portugal.
Sarah WernlyDepartment of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, 5020, Salzburg, Austria.
Susannah LeaverGeneral Intensive Care, St. George´S University Hospital NHS Foundation Trust, London, SW17 0QT, UK.
Dylan W De LangeDepartment of Intensive Care Medicine, University Medical Center, University Utrecht, 3584 CX, Utrecht, Utrecht, The Netherlands.
Bertrand GuidetInserm, Service de'Réanimation, Sorbonne Université, Hôpital Saint-Antoine, Institut Pierre-Louis d'épidémiologie Et de Santé Publique, AP-HP, 184, Rue du Faubourg-Saint-Antoine, 75012, Paris, France.
Christian JungMedical Faculty, Department of Cardiology, Pulmonology and Vascular Medicine, Heinrich-Heine-University Duesseldorf, 40225, Düsseldorf, Germany. christian.jung@med.uni-duesseldorf.de.ORCID http://orcid.org/0000-0001-8325-250X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionFrailty is widely acknowledged as influencing health outcomes among critically ill old patients. Yet, the traditional understanding of its impact has predominantly been through frequentist statistics. We endeavored to explore this association using Bayesian statistics aiming to provide a more nuanced understanding of this multifaceted relationship.

methodsOur analysis incorporated a cohort of 10,363 older (median age 82 years) patients from three international prospective studies, with 30-day all-cause mortality as the primary outcome. We defined frailty as Clinical Frailty Scale ≥ 5. A hierarchical Bayesian logistic regression model was employed, adjusting for covariables, using a range of priors. An international steering committee of registry members reached a consensus on a minimal clinically important difference (MCID).

resultsIn our study, the 30-day mortality was 43%, with rates of 38% in non-frail and 51% in frail groups. Post-adjustment, the median odds ratio (OR) for frailty was 1.60 (95% CI 1.45-1.76). Frailty was invariably linked to adverse outcomes (OR > 1) with 100% probability and had a 90% chance of exceeding the minimal clinically important difference (MCID) (OR > 1.5). For the Clinical Frailty Scale (CFS) as a continuous variable, the median OR was 1.19 (1.16-1.22), with over 99% probability of the effect being more significant than 1.5 times the MCID. Frailty remained outside the region of practical equivalence (ROPE) in all analyses, underscoring its clinical importance regardless of how it is measured.

conclusionsThis research demonstrates the significant impact of frailty on short-term mortality in critically ill elderly patients, particularly when the Clinical Frailty Scale (CFS) is used as a continuous measure. This approach, which views frailty as a spectrum, enables more effective, personalized care for this vulnerable group. Significantly, frailty was consistently outside the region of practical equivalence (ROPE) in our analysis, highlighting its clinical importance.

Identifiers

PMID38091131
PMCPMC10719192

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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.