Evidence map›Paper›PMID 37421448›Full record

ArticleAnnals of intensive care2023

Intermittent body composition analysis as monitoring tool for muscle wasting in critically ill COVID-19 patients.

Johannes Kolck, Zvonimir A Rako, Nick L Beetz, Timo A Auer, Laura K Segger, Christian Pille, Tobias Penzkofer, Uli Fehrenbach, Dominik Geisel

Open access · goldAbstract 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 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

9 citing papers in PubMed, 11 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

9 authors at 4 institutions in 1 country.

Johannes KolckDepartment of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany. Johannes.kolck@charite.de.ORCID http://orcid.org/0000-0001-9843-2247
Zvonimir A RakoDepartment of Pneumology and Intensive Care, Universities of Giessen and Giessen Lung Center (UGMLC), Member of the German Center for Lung Research (DZL), Berlin, Germany.
Nick L BeetzDepartment of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Timo A AuerDepartment of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Laura K SeggerDepartment of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Christian PilleDepartment of Anesthesiology and Intensive Care Medicine | CCM | CVK, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Tobias PenzkoferDepartment of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Uli Fehrenbach *Department of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Dominik Geisel *Department of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Charité - Universitätsmedizin Berlin · DEBerlin Institute of Health at Charité - Universitätsmedizin Berlin · DEGerman Center for Lung Research · DEHumboldt-Universität zu Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSARS-CoV-2 virus infection can lead to acute respiratory distress syndrome (ARDS), which can be complicated by severe muscle wasting. Until now, data on muscle loss of critically ill COVID-19 patients are limited, while computed tomography (CT) scans for clinical follow-up are available. We sought to investigate the parameters of muscle wasting in these patients by being the first to test the clinical application of body composition analysis (BCA) as an intermittent monitoring tool. MATERIALS: BCA was conducted on 54 patients, with a minimum of three measurements taken during hospitalization, totaling 239 assessments. Changes in psoas- (PMA) and total abdominal muscle area (TAMA) were assessed by linear mixed model analysis. PMA was calculated as relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan. Cox regression was applied to analyze associations with survival. Receiver operating characteristic (ROC) analysis and Youden index were used to define a decay cut-off.

resultsIntermittent BCA revealed significantly higher long-term PMA loss rates of 2.62% (vs. 1.16%, p < 0.001) and maximum muscle decay of 5.48% (vs. 3.66%, p = 0.039) per day in non-survivors. The first available decay rate did not significantly differ between survival groups but showed significant associations with survival in Cox regression (p = 0.011). In ROC analysis, PMA loss averaged over the stay had the greatest discriminatory power (AUC = 0.777) for survival. A long-term PMA decline per day of 1.84% was defined as a threshold; muscle loss beyond this cut-off proved to be a significant BCA-derived predictor of mortality.

conclusionMuscle wasting in critically ill COVID-19 patients is severe and correlates with survival. Intermittent BCA derived from clinically indicated CT scans proved to be a valuable monitoring tool, which allows identification of individuals at risk for adverse outcomes and has great potential to support critical care decision-making.

Indexed as

Artificial intelligenceBody composition analysisComputed tomographyCOVID-19Critical careMuscle wasting

Identifiers

PMID37421448
PMCPMC10329605
OpenAlexW4383620599

What OpenQuestion holds

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LicenceCC BY
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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.