Evidence map›Paper›PMID 34138945›Full record

ArticlePloS one2021

Reduced muscle mass as predictor of intensive care unit hospitalization in COVID-19 patients.

Chiara Giraudo, Giovanni Librizzi, Giulia Fichera, Raffaella Motta, Elisabetta Balestro, Fiorella Calabrese, Giovanni Carretta, Anna Maria Cattelan, Paolo Navalesi, Michela Pelloso and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 6 pooled it
4.9field-weighted citation impact, top 4% 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

25 citing papers in PubMed, 6 syntheses or guidelines pooled it, 49 citations in OpenAlex.

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  13. Sarcopenia and COVID-19 Outcomes.Clinical interventions in aging · 2023
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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 at 2 institutions in 1 country.

Chiara GiraudoDepartment of Medicine-DIMED, University of Padova, Padova, Italy.ORCID 0000-0003-0924-5883
Giovanni LibrizziDepartment of Medicine-DIMED, University of Padova, Padova, Italy.ORCID 0000-0002-2409-457X
Giulia FicheraDepartment of Medicine-DIMED, University of Padova, Padova, Italy.
Raffaella MottaDepartment of Medicine-DIMED, University of Padova, Padova, Italy.
Elisabetta BalestroRespiratory Disease Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Fiorella CalabresePathological Anatomy Section, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Giovanni CarrettaUnità Locale Socio Sanitaria-ULSS 3 Serenissima, Veneto Region, Italy.
Anna Maria CattelanDivision of Infectious and Tropical Diseases, Padova University Hospital, Padova, Italy.
Paolo NavalesiAnesthesiology and Intensive Care Unit, Department of Medicine-DIMED, University of Padova, Padova, Italy.
Michela PellosoDepartment of Laboratory Medicine, University Hospital of Padova, Padova, Italy.
Mario PlebaniDepartment of Laboratory Medicine, University Hospital of Padova, Padova, Italy.
Federico ReaThoracic Surgery, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Roberto VettorInternal Medicine, Department of Medicine-DIMED, University of Padova, Padova, Italy.
Andrea VianelloRespiratory Pathophysiology Division, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Roberto StramareDepartment of Medicine-DIMED, University of Padova, Padova, Italy.ORCID 0000-0002-1818-2290
University of Padua · ITRegione del Veneto · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate if reduced muscle mass, assessed with Computed Tomography (CT), is a predictor of intensive care unit (ICU) hospitalization in COVID-19 patients.

methodsIn this Institution Review Board approved study, we retrospectively evaluated COVID-19 patients treated in our tertiary center from March to November 2020 who underwent an unenhanced chest CT scan within three weeks from hospitalization.We recorded the mean Hounsfield Unit (Hu) value of the right paravertebral muscle at the level of the 12th thoracic vertebra, the hospitalization unit (ICU and COVID-19 wards), clinical symptoms, Barthel Index, and laboratory findings.Logistic regression analysis was applied to assess if muscle loss (Hu<30) is a predictor of ICU admission and outcome.Fisher's exact and Student's tests were applied to evaluate if differences between patients with and without muscle loss occurred (p<0.05).

resultsOne-hundred-fifty patients matched the inclusion criteria (46 females; mean age±SD 61.3±15 years-old), 36 treated in ICU. Patients in ICU showed significantly lower Hu values (29±24 vs 39.4±12, p = 0.001). Muscle loss was a predictor of ICU admission (p = 0.004).Patients with muscle loss were significantly older (73.4±10 vs 56.4±14 years), had lower Barthel Index scores (54.4±33 vs 85.1±26), red blood-cell count (3.9±1 vs 4.6±1×1012L-1), and Hb levels (11.5±2 vs 13.2±2g/l) as well as higher white blood-cell count (9.4±7 vs 7.2±4×109L-1), C-reactive protein (71.5±71 vs 44±48U/L), and lactate dehydrogenase levels (335±163 vs 265.8±116U/L) (p<0.05, each).

conclusionsMuscle loss seems to be a predictor of ICU hospitalization in COVID-19 patients and radiologists reporting chest CT at admission should note this finding in their reports.

Indexed as

AgedCOVID-19FemaleHospitalizationHumansIntensive Care UnitsMaleMiddle AgedMusclesReproducibility of ResultsRetrospective StudiesRisk FactorsROC CurveSARS-CoV-2Tomography, X-Ray Computed

Identifiers

PMID34138945
PMCPMC8211180
OpenAlexW3168449333

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.