Evidence map›Paper›PMID 38907141›Full record

ReviewAnnals of intensive care2024

Prognosticating the outcome of intensive care in older patients-a narrative review.

Michael Beil, Rui Moreno, Jakub Fronczek, Yuri Kogan, Rui Paulo Jorge Moreno, Hans Flaatten, Bertrand Guidet, Dylan de Lange, Susannah Leaver, Akiva Nachshon and 5 more

Abstract readReview
In one paragraph

Review in Annals of intensive care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  16. [Ethical boundary decisions in intensive care medicine].Innere Medizin (Heidelberg, Germany) · 2024
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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

15 authors.

Michael BeilDepartment of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
Rui MorenoUnidade Local de Saúde São José, Hospital de São José, Lisbon, Portugal.
Jakub FronczekCenter for Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, Krakow, Poland.
Yuri KoganInstitute for Medical Biomathematics, Bene Ataroth, Israel.
Rui Paulo Jorge MorenoImperial College Business School, London, UK.
Hans FlaattenDepartment of Research and Development, Haukeland University Hospital, Bergen, Norway.
Bertrand GuidetINSERM, Institut Pierre Louis d'Epidémiologie Et de Santé Publique, AP-HP, Hôpital Saint Antoine, Sorbonne Université, Service MIR, Paris, France.
Dylan de LangeDepartment of Intensive Care Medicine, University Medical Center, University Utrecht, Utrecht, The Netherlands.
Susannah LeaverGeneral Intensive Care, St George's University Hospitals NHS Foundation Trust, London, UK.
Akiva NachshonGeneral Intensive Care Unit, Department of Anaesthesiology, Critical Care and Pain Medicine, Faculty of Medicine, Hebrew University and, Hadassah University Medical Center, Jerusalem, Israel.
Peter Vernon van HeerdenGeneral Intensive Care Unit, Department of Anaesthesiology, Critical Care and Pain Medicine, Faculty of Medicine, Hebrew University and, Hadassah University Medical Center, Jerusalem, Israel.
Leo JoskowiczSchool of Computer Science and Engineering and Center for Computational Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
Sigal SviriDepartment of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
Christian JungDepartment of Cardiology, Pulmonology and Vascular Medicine, Faculty of Medicine, Heinrich-Heine-University, University Duesseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany. christian.jung@med.uni-duesseldorf.de.ORCID http://orcid.org/0000-0001-8325-250X
Wojciech SzczeklikCenter for Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, Krakow, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prognosis determines major decisions regarding treatment for critically ill patients. Statistical models have been developed to predict the probability of survival and other outcomes of intensive care. Although they were trained on the characteristics of large patient cohorts, they often do not represent very old patients (age ≥ 80 years) appropriately. Moreover, the heterogeneity within this particular group impairs the utility of statistical predictions for informing decision-making in very old individuals. In addition to these methodological problems, the diversity of cultural attitudes, available resources as well as variations of legal and professional norms limit the generalisability of prediction models, especially in patients with complex multi-morbidity and pre-existing functional impairments. Thus, current approaches to prognosticating outcomes in very old patients are imperfect and can generate substantial uncertainty about optimal trajectories of critical care in the individual. This article presents the state of the art and new approaches to predicting outcomes of intensive care for these patients. Special emphasis has been given to the integration of predictions into the decision-making for individual patients. This requires quantification of prognostic uncertainty and a careful alignment of decisions with the preferences of patients, who might prioritise functional outcomes over survival. Since the performance of outcome predictions for the individual patient may improve over time, time-limited trials in intensive care may be an appropriate way to increase the confidence in decisions about life-sustaining treatment.

Indexed as

Critical careIntensive carePredictionVery old patients

Identifiers

PMID38907141
PMCPMC11192712

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.