Evidence map›Paper›PMID 33254065›Full record

ArticleEuropean journal of radiology2021

Temporal variations in the diagnostic performance of chest CT for Covid-19 depending on disease prevalence: Experience from North-Eastern France.

Mickaël Ohana, Joris Muller, François Severac, Pascal Bilbault, Martin Behr, Mathieu Oberlin, Pierre Leyendecker, Catherine Roy

Abstract read
In one paragraph

Article in European journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
–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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Thoracic imaging tests for the diagnosis of COVID-19.The Cochrane database of systematic reviews · 2022
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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

8 authors.

Mickaël OhanaHôpitaux Universitaires de Strasbourg, Service de Radiologie, Nouvel Hôpital Civil, Strasbourg, France. Electronic address: mickael.ohana@chru-strasbourg.fr.
Joris MullerHôpitaux Universitaires de Strasbourg, Service de Santé Publique, Nouvel Hôpital Civil, Strasbourg, France.
François SeveracHôpitaux universitaires de Strasbourg, Groupe Méthodes en Recherche Clinique (GMRC), Hôpital Civil, Strasbourg, France.
Pascal BilbaultHôpitaux Universitaires de Strasbourg, Service d'Accueil des Urgences, Nouvel Hôpital Civil, Strasbourg, France.
Martin BehrHôpitaux Universitaires de Strasbourg, Service d'Accueil des Urgences, Nouvel Hôpital Civil, Strasbourg, France.
Mathieu OberlinHôpitaux Universitaires de Strasbourg, Service d'Accueil des Urgences, Nouvel Hôpital Civil, Strasbourg, France.
Pierre LeyendeckerHôpitaux Universitaires de Strasbourg, Service de Radiologie, Nouvel Hôpital Civil, Strasbourg, France.
Catherine RoyHôpitaux Universitaires de Strasbourg, Service de Radiologie, Nouvel Hôpital Civil, Strasbourg, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RATIONALE AND

objectiveThe purpose of this work was to analyze temporal variations in the diagnostic performance of chest CT for Covid-19 throughout the first wave, depending on disease prevalence variations between the ascending, peak and descending phases of the epidemic in North-Eastern France. MATERIALS AND

methodsFrom March 6th to April 22nd 2020, all consecutive adult patients referred to the "Covid-19 clinic" of our Emergency Department with the availability of chest CT and of at least one RT-PCR result were retrospectively included in the present study. Chest CT was considered positive when typical Covid-19 lesions were observed (bilateral and predominantly peripheral and sub-pleural ground glass opacities and/or alveolar consolidations). RT-PCR results were considered as the reference standard. Ascending, peak and descending phases were determined based on the number of CT scans performed daily. CT diagnostic performance were calculated and variations between phases were tested for equivalence or difference using Bayesian methods.

results2194 consecutive chest CT were analyzed. Overall CT diagnostic performance was Se = 84.2 [82.0 ; 86.3], Sp = 86.6 [84.5 ; 88.5], PPV = 86.1 [84.0 ; 88.1], NPV = 84.7 [82.6 ; 86.7] and accuracy = 85.4 [83.9 ; 86.8], with no significant differences between chest and non-chest radiologists. Variations between the ascending (11 days, 281 chest CT, disease prevalence 37.0 %), the peak (18 days, 1167 chest CT, disease prevalence 64 %) and the descending phases (19 days, 746 chest CT, disease prevalence 32.2 %) were highest for PPV and NPV with a probability of difference >99.9 %, and smallest for accuracy and specificity with a probability of equivalence >98.8 %.

conclusionIn a homogenous cohort of 2194 consecutive chest CT performed over a 7-week epidemic wave, we observed significant variations of CT predictive values whereas CT specificity appeared marginally affected.

Indexed as

AdultBayes TheoremCohort StudiesCOVID-19Emergency Service, HospitalFemaleFranceHumansLungMaleMiddle AgedPrevalenceProbabilityRadiography, ThoracicReproducibility of ResultsRetrospective StudiesCovid-19Diagnostic imagingLung diseasesMultidetector computed tomographyReverse transcriptase polymerase chain reaction

Identifiers

PMID33254065
PMCPMC7836755

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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.