Evidence map›Paper›PMID 34072716›Full record

ArticleDiagnostics (Basel, Switzerland)2021

Validation of Remote Dielectric Sensing (ReDS) in Monitoring Adult Patients Affected by COVID-19 Pneumonia.

Federico Mei, Alessandro Di Marco Berardino, Martina Bonifazi, Lara Letizia Latini, Lina Zuccatosta, Stefano Gasparini

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

4 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

6 authors at 2 institutions in 1 country.

Federico MeiRespiratory Diseases Unit, Azienda Ospedaliero-Universitaria "Ospedali Riuniti", 60126 Ancona, Italy.ORCID 0000-0003-1887-5377
Alessandro Di Marco BerardinoRespiratory Diseases Unit, Azienda Ospedaliero-Universitaria "Ospedali Riuniti", 60126 Ancona, Italy.
Martina BonifaziRespiratory Diseases Unit, Azienda Ospedaliero-Universitaria "Ospedali Riuniti", 60126 Ancona, Italy.
Lara Letizia LatiniRespiratory Diseases Unit, Azienda Ospedaliero-Universitaria "Ospedali Riuniti", 60126 Ancona, Italy.
Lina ZuccatostaRespiratory Diseases Unit, Azienda Ospedaliero-Universitaria "Ospedali Riuniti", 60126 Ancona, Italy.
Stefano GaspariniRespiratory Diseases Unit, Azienda Ospedaliero-Universitaria "Ospedali Riuniti", 60126 Ancona, Italy.ORCID 0000-0001-5689-9164
Azienda Ospedaliero Universitaria Ospedali Riuniti · ITMarche Polytechnic University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Remote dielectric sensing (ReDS) is a non-invasive electromagnetic wave technology which provides an accurate reading of lung fluid content, and it has been reported as a valid tool in monitoring heart failure patients. Considering that morphological alterations in COVID-19 include pulmonary edema, the purpose of the present study was to evaluate the reliability of ReDS technology in assessing the excess of lung fluid status in COVID-19 pneumonia, as compared to CT scans. In this pilot single center study, confirmed COVID-19 patients were enrolled on admission to an intermediate care unit. Measurements with the ReDS system and CT scans were performed on admission and at weeks 1 and 2. Eleven patients were recruited. The average change in ReDS was -3.1 ± 1.7 after one week (

Indexed as

computed tomographyCOVID-19 pneumoniafluid monitoringlung edemaremote dielectric sensing

Identifiers

PMID34072716
PMCPMC8226514
OpenAlexW3165346459

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.