Evidence map›Paper›PMID 40474893›Full record

ArticleEuropean heart journal open2025

Exploring breath metabolomics as a non-invasive tool for detecting pulmonary vascular disease.

Sarah Basler, Kai Fricke, Noriane A Sievi, Alexandra Arvaji, Felix Schmidt, Jonas Herth, Diego M Baur, Malcolm Kohler, Silvia Ulrich, Mona Lichtblau

Registry-linked trialAbstract read
In one paragraph

Article in European heart journal open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05458934 (Analysis of Exhaled Breath From Patients With Lung-/Airway Diseases), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

NCT05458934 recruitingnot on this map

Analysis of Exhaled Breath From Patients With Lung-/Airway Diseases (BigExBrESs)

TypeobservationalSponsorUniversity of ZurichRan2021 to 2030Enrolled5,000ConditionsLung-/Airway DiseasesArmsNo intervention
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

10 authors.

Sarah BaslerDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.
Kai FrickeDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.ORCID https://orcid.org/0009-0006-5238-372X
Noriane A SieviDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.
Alexandra ArvajiDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.
Felix SchmidtDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.
Jonas HerthDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.
Diego M BaurDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.ORCID https://orcid.org/0000-0002-1486-3603
Malcolm KohlerDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.
Silvia UlrichDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.ORCID https://orcid.org/0000-0002-5250-5022
Mona LichtblauDepartment of Pulmonology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland.ORCID https://orcid.org/0000-0003-4485-1758

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: The aim of this initial study was to explore whether prediction models based on breath metabolome profiles could detect differences between pulmonary vascular disease (PVD) patients and healthy controls. Additionally, we sought to investigate the potential to distinguish between two major subtypes of PVD-pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH)-to support early detection and targeted treatment. Methods and results: We used real-time breath analysis to compare the breath profiles of patients with PVD to healthy controls, and the metabolome of patients with PAH to those with CTEPH. Pathway enrichment analysis was conducted to reveal underlying metabolic pathways. Breath profiles of 75 patients (47 (62.7%) with PAH and 28 (37.3%) with CTEPH) were analysed and compared with those of 115 healthy controls. The prediction models identified PVD with an area under the curve of 0.917 and distinguished PAH from CTEPH with an AUC of 0.764. PVD patients showed significant metabolic alterations, particularly in Conclusion: Breath analysis shows potential as a non-invasive and real-time diagnostic tool by demonstrating detectable differences in breath profiles between PVD patients and healthy controls. Establishing these differences is a critical first step in assessing the feasibility of identifying breath markers for PVD and exploring further differentiation between PAH and CTEPH. Registration: Trial registration number: NCT05458934.

Indexed as

Breath analysisMetabolomicsPulmonary vascular disease

Identifiers

PMID40474893
PMCPMC12138245

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Registered trials

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.