Evidence map›Paper›PMID 34070021›Full record

ArticleBiomedicines2021

Predict Score: A New Biological and Clinical Tool to Help Predict Risk of Intensive Care Transfer for COVID-19 Patients.

Mickael Gette, Sara Fernandes, Marion Marlinge, Marine Duranjou, Wijayanto Adi, Maelle Dambo, Pierre Simeone, Pierre Michelet, Nicolas Bruder, Regis Guieu and 1 more

Abstract read
In one paragraph

Article in Biomedicines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Mickael GetteLaboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
Sara FernandesCenter for Research and Studies on Health Services and Quality of Life, Aix-Marseille University, 13005 Marseille, France.
Marion MarlingeLaboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
Marine DuranjouLaboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
Wijayanto AdiLaboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
Maelle DamboLaboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
Pierre SimeoneDepartment of Anesthesiology and Intensive Care, Timone University Hospital, Aix Marseille University APHM, 13005 Marseille, France.ORCID 0000-0002-0682-9405
Pierre MicheletINSERM, INRAE, C2VN, Aix-Marseille University, 13005 Marseille, France.
Nicolas BruderDepartment of Anesthesiology and Intensive Care, Timone University Hospital, Aix Marseille University APHM, 13005 Marseille, France.
Regis GuieuLaboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.ORCID 0000-0002-3824-0814
Julien FromonotLaboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.ORCID 0000-0001-6726-9125

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 crisis has strained world health care systems. This study aimed to develop an innovative prediction score using clinical and biological parameters (PREDICT score) to anticipate the need of intensive care of COVID-19 patients already hospitalized in standard medical units.

methodsPREDICT score was based on a training cohort and a validation cohort retrospectively recruited in 2020 in the Marseille University Hospital. Multivariate analyses were performed, including clinical, and biological parameters, comparing a baseline group composed of COVID-19 patients exclusively treated in standard medical units to COVID-19 patients that needed intensive care during their hospitalization.

resultsIndependent variables included in the PREDICT score were: age, Body Mass Index, Respiratory Rate, oxygen saturation, C-reactive protein, neutrophil-lymphocyte ratio and lactate dehydrogenase. The PREDICT score was able to correctly identify more than 83% of patients that needed intensive care after at least 1 day of standard medical hospitalization.

conclusionsThe PREDICT score is a powerful tool for anticipating the intensive care need for COVID-19 patients already hospitalized in a standard medical unit. It shows limitations for patients who immediately need intensive care, but it draws attention to patients who have an important risk of needing intensive care after at least one day of hospitalization.

Indexed as

biologyCOVID-19intensive carescore

Identifiers

PMID34070021
PMCPMC8157884

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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.