Evidence map›Paper›PMID 39281132›Full record

ArticleQuantitative imaging in medicine and surgery2024

Proposal for a computed tomography score to predict major complications requiring hospitalization after percutaneous lung biopsy: a single-center retrospective study.

Satcha Ortmans, Fabien de Oliveira, Chris Serrand, Tarek Kammoun, Joel Greffier, Djamel Dabli, Hélène de Forges, Cécile Rieux, Jean-Paul Beregi, Julien Frandon

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Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Satcha OrtmansDepartment of Medical Imaging, PRIM Platform, Nîmes University Hospital, University of Montpellier, Medical Imaging Group Nîmes, IMAGINE, Nîmes, France.
Fabien de OliveiraDepartment of Medical Imaging, PRIM Platform, Nîmes University Hospital, University of Montpellier, Medical Imaging Group Nîmes, IMAGINE, Nîmes, France.
Chris SerrandDepartment of Biostatistics, Clinical Epidemiology, Public Health, and Innovation in Methodology (BESPIM), Hospital University Center, Nîmes, France.
Tarek KammounDepartment of Medical Imaging, PRIM Platform, Nîmes University Hospital, University of Montpellier, Medical Imaging Group Nîmes, IMAGINE, Nîmes, France.
Joel GreffierDepartment of Medical Imaging, PRIM Platform, Nîmes University Hospital, University of Montpellier, Medical Imaging Group Nîmes, IMAGINE, Nîmes, France.
Djamel DabliDepartment of Medical Imaging, PRIM Platform, Nîmes University Hospital, University of Montpellier, Medical Imaging Group Nîmes, IMAGINE, Nîmes, France.
Hélène de ForgesDepartment of Medical Imaging, PRIM Platform, Nîmes University Hospital, University of Montpellier, Medical Imaging Group Nîmes, IMAGINE, Nîmes, France.
Cécile RieuxDepartment of Pneumology, Hospital University Center of Nîmes, Hôpital Caremeau, Rue du Pr Debré, Nîmes Cedex, France.
Jean-Paul BeregiDepartment of Medical Imaging, PRIM Platform, Nîmes University Hospital, University of Montpellier, Medical Imaging Group Nîmes, IMAGINE, Nîmes, France.
Julien FrandonDepartment of Medical Imaging, PRIM Platform, Nîmes University Hospital, University of Montpellier, Medical Imaging Group Nîmes, IMAGINE, Nîmes, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Image-guided percutaneous lung biopsy (PLB) may lead to major complications requiring hospitalization. This study aims to evaluate the rate of major PLB complications and determine a predictive computed tomography (CT) score to define patients requiring hospitalization due to these complications. Methods: This single-center retrospective study included all PLBs performed from July 2019 to December 2020 in Nimes University Hospital, France. Patients who were undergoing thermo-ablation during the same procedure or for whom PLB procedure data were not available were excluded. All major complications leading to hospitalization were recorded. A Percutaneous Image-guided Lung biopsy In/out Patient score (PILIP) based on variables significantly associated with major complications was calculated by multivariate analysis. Results: A total of 240 consecutive patients (160 men, 80 women; mean age: 67.3±10.5 years) were included. The major complication rate was 10.4%. Length of lung parenchyma traversed <20 Conclusions: PLB showed a major complication rate of 10.4%. The PILIP is an easy-to-use CT score for differentiating patients at a low or high risk of complications requiring hospitalization.

Indexed as

Computed tomography (CT)interventional radiologypercutaneous lung biopsy (PLB)predictive score

Identifiers

PMID39281132
PMCPMC11400643

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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.