Evidence map›Paper›PMID 40215203›Full record

Observational studyInterdisciplinary cardiovascular and thoracic surgery2025

Three-dimensional tracheo-bronchial reconstruction to plan endoscopic stent insertion for malignant upper airway stenosis.

Beatrice Leonardi, Stefano Forte, Antonio Marella, Francesco Panini D'Alba, Giuseppe Vicario, Grazia Bergameo, Francesca Capasso, Francesco Leone, Noemi Maria Giorgiano, Davide Gerardo Pica and 10 more

Abstract readObservational Study
In one paragraph

Observational study in Interdisciplinary cardiovascular and thoracic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

20 authors.

Beatrice LeonardiThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.ORCID 0000-0002-5595-6849
Stefano ForteGenomics and Molecular Oncology Unit, Istituto Oncologico Mediterraneo, Viagrande, Italy.
Antonio MarellaThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Francesco Panini D'AlbaThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Giuseppe VicarioThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Grazia BergameoThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Francesca CapassoThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Francesco LeoneThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Noemi Maria GiorgianoThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Davide Gerardo PicaThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Emanuele MartoranaGenomics and Molecular Oncology Unit, Istituto Oncologico Mediterraneo, Viagrande, Italy.
Riccardo VillaGenomics and Molecular Oncology Unit, Istituto Oncologico Mediterraneo, Viagrande, Italy.
Maria MarvulliThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Riccardo MontiRadiology Department, University of Campania "Luigi Vanvitelli", Naples, Italy.
Gaetana MessinaThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.ORCID 0000-0001-5129-7201
Francesco FerrignoPneumology Unit, ASL Salerno, Salerno, Italy.
Marco MosellaPneumology Unit, ASL NA1, Naples, Italy.
Paolo ChiodiniDepartment of Medicine and Public Health, University of Campania Luigi Vanvitelli, Naples, Italy.
Giovanni VicidominiThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.
Alfonso FiorelliThoracic Surgery Unit, University of Campania "Luigi Vanvitelli", Naples, Italy.ORCID 0000-0002-0628-613X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMalignant central airway obstruction (MCAO) is a condition characterized by severe dyspnoea and high mortality. Tracheo-bronchial stents have emerged as an effective treatment to restore airway patency. Our study aimed to evaluate the efficacy of 3D reconstruction of the upper airways to plan tracheo-bronchial stent insertion for MCAO.

methodsThis was a retrospective, single-centre observational study. We analysed data of patients undergoing tracheo-bronchial stent insertion for MCAO from January 2012 to January /2024. Patients undergoing tracheo-bronchial stent insertion for MCAO with 3D reconstruction (3D Reconstruction Group) were compared with patients treated prior to the use of 3D reconstruction (Standard Group).

resultsA total of 136 patients were included in our study: 40 patients (29%) in the 3D Reconstruction Group and 96 patients (71%) in the Standard Group. Restore of airway patency was obtained in 96% of patients, without differences between groups (P = 0.48). Median operative time was 40 min in 3D Reconstruction Group vs 48 min in Standard Group, with a percentage reduction of 17% in the 3D Group (P = 0.03). Stent migration was less frequent in 3D Reconstruction Group than in Standard Group, being 5% vs 17% (P = 0.04). There were no significant differences in 30- and 90-day mortality.

conclusionsThree-dimensional reconstruction of the upper airways was associated with reduced operative time and stent migration rate in patients with MCAO. Reconstructing patients' anatomical features optimizes the procedure without any added cost or delay of the treatment.

Indexed as

Airway ObstructionBronchoscopyImaging, Three-DimensionalStentsTracheaTracheal StenosisAgedFemaleHumansMaleMiddle AgedRetrospective StudiesTreatment Outcomeendoscopythree-dimensional reconstructiontracheal stenosis

Identifiers

PMID40215203
PMCPMC12209832

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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.