Evidence map›Paper›PMID 36582133›Full record

ArticleArtificial organs2023

Evaluation of the discrimination and calibration of predictive scores of mortality in ECMO for patients with COVID-19.

Ivan Alfredo Huespe, Carolina Lockhart, Rahul Kashyap, Fernando Palizas, Malena Colombo, Maria Del Pilar Romero, Eduardo Prado, Christian A Casabella García, Marcos Las Heras, Indalecio Carboni Bisso

Open access · greenAbstract read
In one paragraph

Article in Artificial organs, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 48% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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

10 authors at 5 institutions in 2 countries.

Ivan Alfredo HuespeUnidad de Terapia Intensiva Adultos, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.ORCID https://orcid.org/0000-0003-3445-6981
Carolina LockhartUnidad de Terapia Intensiva Adultos, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.ORCID https://orcid.org/0000-0002-3888-8725
Rahul KashyapGlobal Clinical Scholars Research Trainee, Harvard Medical School, Boston, Massachusetts, USA.
Fernando PalizasUnidad de Terapia Intensiva Adultos, Clínica Bazterrica, Buenos Aires, Argentina.
Malena ColomboInstituto Universitario del Hospital Italiano, Buenos Aires, Argentina.
Maria Del Pilar RomeroInstituto Universitario del Hospital Italiano, Buenos Aires, Argentina.
Eduardo PradoUnidad de Terapia Intensiva Adultos, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.
Christian A Casabella GarcíaDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Marcos Las HerasUnidad de Terapia Intensiva Adultos, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.
Indalecio Carboni BissoUnidad de Terapia Intensiva Adultos, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.ORCID https://orcid.org/0000-0002-4834-4676
Hospital Italiano de Buenos Aires · ARInstituto Universitario Hospital Italiano · ARMayo Clinic · USEstudios Clínicos Latinoamérica · ARHarvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe criteria for the selection of COVID-19 patients that could benefit most from ECMO organ support are yet to be defined. In this study, we evaluated the predictive performance of ECMO mortality predictive models in patients with COVID-19. We also performed a cost-benefit analysis depending on the mortality predicted probability. We conducted a retrospective cohort study in COVID-19 patients who received ECMO at two tertiary care hospitals between March 2020 to July 2021. MATERIALS AND

methodsWe evaluated the discrimination (C-statistic), calibration (Cox calibration), and accuracy of the prediction of death due to severe ARDS in V-V ECMO score (PRESERVE), the Respiratory Extracorporeal Membrane Oxygenation Survival Score (RESP) score, and the PREdiction of Survival on ECMO Therapy-Score (PRESET) score. In addition, we compared the RESP score with Plateau pressure instead of Peak pressure.

resultsWe included a total of 36 patients, 29 (80%) of them male and with a median (IQR) APACHE of 10 (8-15). The PRESET score had the highest discrimination (AUROCs 0.81 [95%CI 0.67-0.94]) and calibration (calibration-in-the-large 0.5 [95%CI -1.4 to 0.3]; calibration slope 2.2 [95%CI 0.7/3.7]). The RESP score with Plateau pressure had higher discrimination than the conventional RESP score. The cost per QALY in the USA, adjusted to life expectancy, was higher than USD 100 000 in patients older than 45 years with a PRESET > 10.

conclusionThe PRESET score had the highest predictive performance and could help in the selection of patients that benefit most from this resource-demanding and highly invasive organ support.

Indexed as

COVID-19Extracorporeal Membrane OxygenationCalibrationHumansMaleRetrospective StudiesROC Curveacute respiratory distress syndromeCOVID-19extracorporeal life supportextracorporeal membrane oxygenationmortalitypredictionsurvival

Identifiers

PMID36582133
PMCPMC9880702
OpenAlexW4313312515

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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.