Evidence map›Paper›PMID 30977911›Full record

ArticleJournal of the American Geriatrics Society2019

Cumulative Prognostic Score Predicting Mortality in Patients Older Than 80 Years Admitted to the ICU.

Dylan W de Lange, Sylvia Brinkman, Hans Flaatten, Ariane Boumendil, Alessandro Morandi, Finn H Andersen, Antonio Artigas, Guido Bertolini, Maurizio Cecconi, Steffen Christensen and 16 more

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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

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  17. Frailty in Critical Care Medicine: A Review.Anesthesia and analgesia · 2020
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  18. Community-acquired pneumonia in critically ill very old patients: a growing problem.European respiratory review : an official journal of the European Respiratory Society · 2020
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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

26 authors.

Dylan W de LangeDepartment of Intensive Care Medicine, University Medical Center, University Utrecht, Utrecht, The Netherlands.ORCID 0000-0002-0191-7270
Sylvia BrinkmanDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Hans FlaattenDepartment of Clinical Medicine, University of Bergen, Bergen, Norway.
Ariane BoumendilAssistance Publique - Hôpitaux de Paris, Hôpital Saint-Antoine, Service de Réanimation Médicale, Paris, France.
Alessandro MorandiDepartment of Rehabilitation, Hospital Ancelle di Cremona, Cremona, Italy.
Finn H AndersenDepartment of Anaesthesia and Intensive Care, Ålesund Hospital, Ålesund, Norway.
Antonio ArtigasDepartment of Intensive Care Medecine, CIBER Enfermedades Respiratorias, Corporacion Sanitaria Universitaria Parc Tauli, Autonomous University of Barcelona, Sabadell, Spain.
Guido BertoliniLaboratorio di Epidemiologia Clinica, Centro di Coordinamento GiViTI Dipartimento di Salute Pubblica, IRCCS - Istituto di Ricerche Farmacologiche "Mario Negri", Ranica (Bergamo), Italy.
Maurizio CecconiSt George's University Hospital, London, United Kingdom.
Steffen ChristensenDepartment of Anaesthesia and Intensive Care Medicine, Aarhus University Hospital, Denmark.
Loredana FaraldiASST Grande Ospedale Metropolitano Niguarda, Milan, Italy.
Jesper FjølnerDepartment of Anaesthesia and Intensive Care Medicine, Aarhus University Hospital, Denmark.
Christian JungDepartment of Cardiology, Pulmonology and Angiology, University Hospital, Düsseldorf, Germany.
Brian MarshMater Misericordiae University Hospital, Dublin, Ireland.
Rui MorenoUnidade de Cuidados Intensivos Neurocriticos e Trauma, Hospital de São José, Centro Hospitalar Universitário de Lisboa Central Nova Medical School, Lisbon, Portugal.
Sandra OeyenDepartment of Intensive Care 1K12IC, Ghent University Hospital, Ghent, Belgium.
Christina Agvald ÖhmanKarolinska University Hospital, Stockholm, Sweden.
Bernardo Bollen PintoGeneva University Hospitals, Geneva, Switzerland.
Anne Marie G A de SmetDepartment of Critical Care, University Medical Center Groningen, University Groningen, Groningen, The Netherlands.
Ivo W SolimanDepartment of Intensive Care Medicine, University Medical Center, University Utrecht, Utrecht, The Netherlands.
Wojciech SzczeklikIntensive Care and Perioperative Medicine Division, Jagiellonian University Medical College, Kraków, Poland.
Andreas ValentinKardinal Schwarzenberg Hospital, Schwarzach, Austria.
Ximena WatsonSt George's University Hospital, London, United Kingdom.
Tilemachos ZafeiridisIntensive Care Unit, General Hospital of Larissa Tsakalof Larissa, Larissa, Greece.
Bertrand GuidetAssistance Publique - Hôpitaux de Paris, Hôpital Saint-Antoine, Service de Réanimation Médicale, Paris, France.
VIP1 Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo develop a scoring system model that predicts mortality within 30 days of admission of patients older than 80 years admitted to intensive care units (ICUs).

designProspective cohort study.

settingA total of 306 ICUs from 24 European countries.

participantsOlder adults admitted to European ICUs (N = 3730; median age = 84 years [interquartile range = 81-87 y]; 51.8% male). MEASUREMENTS: Overall, 24 variables available during ICU admission were included as potential predictive variables. Multivariable logistic regression was used to identify independent predictors of 30-day mortality. Model sensitivity, specificity, and accuracy were evaluated with receiver operating characteristic curves.

resultsThe 30-day-mortality was 1562 (41.9%). In multivariable analysis, these variables were selected as independent predictors of mortality: age, sex, ICU admission diagnosis, Clinical Frailty Scale, Sequential Organ Failure Score, invasive mechanical ventilation, and renal replacement therapy. The discrimination, accuracy, and calibration of the model were good: the area under the curve for a score of 10 or higher was .80, and the Brier score was .18. At a cut point of 10 or higher (75% of all patients), the model predicts 30-day mortality in 91.1% of all patients who die.

conclusionA predictive model of cumulative events predicts 30-day mortality in patients older than 80 years admitted to ICUs. Future studies should include other potential predictor variables including functional status, presence of advance care plans, and assessment of each patient's decision-making capacity.

Indexed as

Organ Dysfunction ScoresPrognosisAged, 80 and overEuropeFemaleHospitalizationHospital MortalityHumansIntensive Care UnitsMaleProspective StudiesRespiration, Artificialcritical caremodelolder adultspredictprognosis

Identifiers

PMID30977911
PMCPMC6850576

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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.