ArticlePloS one2016
Smelling the Diagnosis: The Electronic Nose as Diagnostic Tool in Inflammatory Arthritis. A Case-Reference Study.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 35 citations in OpenAlex.
- Measurement of immune cell-derived volatile organic compounds from ex vivo and in vitro cultures: a scoping review.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- Machine Learning Model Discriminate Ischemic Heart Disease Using Breathome Analysis.Biomedicines · 2024Article
- Volatilome is Inflammasome- and Lipidome-dependent in Ischemic Heart Disease.Current cardiology reviews · 2024Review
- Breathomics Detect the Cardiovascular Disease: Delusion or Dilution of the Metabolomic Signature.Current cardiology reviews · 2024Review
- The Versatility and Diagnostic Potential of VOC Profiling for Noninfectious Diseases.BME frontiers · 2023Article
- Two Beer(s) or Not Two Beer(s): The eNose as an Instrument to Pacify the World.Klinische Padiatrie · 2022Article
- Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose.PloS one · 2021Article
- Data preprocessing workflow for exhaled breath analysis by GC/MS using open sources.Scientific reports · 2020Article
- Odor Discrimination by Similarity Measures of Abstract Odor Factor Maps from Electronic Noses.Sensors (Basel, Switzerland) · 2018Article
- Cutting Edge Methods for Non-Invasive Disease Diagnosis Using E-Tongue and E-Nose Devices.Biosensors · 2017Review
- A Novel Medical E-Nose Signal Analysis System.Sensors (Basel, Switzerland) · 2017Article
- Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.Current rheumatology reports · 2017Review
- Factors Influencing Continuous Breath Signal in Intubated and Mechanically-Ventilated Intensive Care Unit Patients Measured by an Electronic Nose.Sensors (Basel, Switzerland) · 2016Article
- The electronic nose technology in clinical diagnosis: A systematic review.Porto biomedical journalReview
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate whether exhaled breath analysis using an electronic nose can identify differences between inflammatory joint diseases and healthy controls.
methodsIn a cross-sectional study, the exhaled breath of 21 rheumatoid arthritis (RA) and 18 psoriatic arthritis (PsA) patients with active disease was compared to 21 healthy controls using an electronic nose (Cyranose 320; Smiths Detection, Pasadena, CA, USA). Breathprints were analyzed with principal component analysis, discriminant analysis, and area under curve (AUC) of receiver operating characteristics (ROC) curves. Volatile organic compounds (VOCs) were identified by gas chromatography and mass spectrometry (GC-MS), and relationships between breathprints and markers of disease activity were explored.
resultsBreathprints of RA patients could be distinguished from controls with an accuracy of 71% (AUC 0.75, 95% CI 0.60-0.90, sensitivity 76%, specificity 67%). Breathprints from PsA patients were separated from controls with 69% accuracy (AUC 0.77, 95% CI 0.61-0.92, sensitivity 72%, specificity 71%). Distinction between exhaled breath of RA and PsA patients exhibited an accuracy of 69% (AUC 0.72, 95% CI 0.55-0.89, sensitivity 71%, specificity 72%). There was a positive correlation in RA patients of exhaled breathprints with disease activity score (DAS28) and number of painful joints. GC-MS identified seven key VOCs that significantly differed between the groups.
conclusionsExhaled breath analysis by an electronic nose may play a role in differential diagnosis of inflammatory joint diseases. Data from this study warrant external validation.
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