R. Louis

University of Liège

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Florence Schleich

University of Liège

Monique Henket

University of Liège

Guy Joos

Ghent University Hospital

Virginie Paulus

University of Liège

Violeta Kvedarienė

Vilnius University

Torsten Zuberbier

Charité - Universitätsmedizin Berlin

Anna Bedbrook

Hôpital Arnaud de Villeneuve

Jean Bousquet

Charité - Universitätsmedizin Berlin

Bolesław Samoliński

Medical University of Warsaw

Ratko Djukanović

University of Southampton

Cooperative Institutions

Charité - Universitätsmedizin Berlin

Inserm

University of Liège

ENT and Allergy

Centre Hospitalier Universitaire de Liège

Imperial College London

Municipal Institute for Medical Research

Humboldt-Universität zu Berlin

Hospital Del Mar

Centre Hospitalier Universitaire de Montpellier

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Heterogeneity of phenotypes in severe asthmatics. The Belgian Severe Asthma Registry (BSAR)

Respiratory Medicine (2014)

Florence Schleich Guy Brusselle R. Louis Olivier Vandenplas Alain Michils

Interquartile range

10.1016/j.rmed.2014.10.007

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Citations (243)

Integrated care pathways for airway diseases (AIRWAYS-ICPs)

European Respiratory Journal (2014)

Jean Bousquet Antonio Addis Ian M. Adcock Ioana Agache Àlvar Agustí

The objective of Integrated Care Pathways for Airway Diseases (AIRWAYS-ICPs) is to launch a collaboration to develop multi-sectoral care pathways for chronic respiratory diseases in European countries and regions.AIRWAYS-ICPs has strategic relevance to the European Union Health Strategy and will add value to existing public health knowledge by: 1) proposing a common framework of care pathways for chronic respiratory diseases, which will facilitate comparability and trans-national initiatives; 2) informing cost-effective policy development, strengthening in particular those on smoking and environmental exposure; 3) aiding risk stratification in chronic disease patients, using a common strategy; 4) having a significant impact on the health of citizens in the short term (reduction of morbidity, improvement of education in children and of work in adults) and in the long-term (healthy ageing); 5) proposing a common simulation tool to assist physicians; and 6) ultimately reducing the healthcare burden (emergency visits, avoidable hospitalisations, disability and costs) while improving quality of life.In the longer term, the incidence of disease may be reduced by innovative prevention strategies.AIRWAYS-ICPs was initiated by Area 5 of the Action Plan B3 of the European Innovation Partnership on Active and Healthy Ageing.All stakeholders are involved (health and social care, patients, and policy makers).@ERSpublications AIRWAYS-ICPs: launch of a collaboration to develop multi-sectoral integrated care pathways for respiratory disease

Action plan

10.1183/09031936.00014614

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Citations (165)

La thermoplastie bronchique dans le traitement de l’asthme sévère de l’adulte

Revue des Maladies Respiratoires (2014)

Pascal Chanez Louis‐Philippe Boulet Pierre‐Yves Brillet Guy Joos M. Laviolette

10.1016/j.rmr.2014.09.009

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Citations (6)

Abnormal Vascular Tone, Defective Oxygen Transport And Myocardial Failure In Human Septic Shock

Annals of Surgery (1967)

John H. Siegel Mark Greenspan R. Louis DEL GUEHCIO

SIEGEL, JOHN H. M.D.; GREENSPAN, MARK M.D.; LOUIS, R. M.; GUEHCIO, DEL M.D. Author Information

Vascular tone

Tone (literature)

10.1097/00000658-196704000-00002

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Citations (291)

Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests

European Respiratory Journal (2019)

Marko Topalovic Nilakash Das Pierre‐Régis Burgel Marc Daenen Eric Derom

The interpretation of pulmonary function tests (PFTs) to diagnose respiratory diseases is built on expert opinion that relies on the recognition of patterns and the clinical context for detection of specific diseases. In this study, we aimed to explore the accuracy and interrater variability of pulmonologists when interpreting PFTs compared with artificial intelligence (AI)-based software that was developed and validated in more than 1500 historical patient cases.120 pulmonologists from 16 European hospitals evaluated 50 cases with PFT and clinical information, resulting in 6000 independent interpretations. The AI software examined the same data. American Thoracic Society/European Respiratory Society guidelines were used as the gold standard for PFT pattern interpretation. The gold standard for diagnosis was derived from clinical history, PFT and all additional tests.The pattern recognition of PFTs by pulmonologists (senior 73%, junior 27%) matched the guidelines in 74.4±5.9% of the cases (range 56-88%). The interrater variability of κ=0.67 pointed to a common agreement. Pulmonologists made correct diagnoses in 44.6±8.7% of the cases (range 24-62%) with a large interrater variability (κ=0.35). The AI-based software perfectly matched the PFT pattern interpretations (100%) and assigned a correct diagnosis in 82% of all cases (p<0.0001 for both measures).The interpretation of PFTs by pulmonologists leads to marked variations and errors. AI-based software provides more accurate interpretations and may serve as a powerful decision support tool to improve clinical practice.

Pulmonologists

10.1183/13993003.01660-2018

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Citations (162)

Overuse of Short Acting Beta-2 Agonist (SABA) in asthmatics: relationship with lung function and airway inflammation

05.02 - Monitoring airway disease (2024)

France Louis Virginie Paulus Françoise Guissard Geneviève Philippe R. Louis

BETA (programming language)

10.1183/13993003.congress-2024.pa3996

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Citations (0)

Prior ICS use may protect from lung parenchymal involvement in asthmatics and COPD patients affected by COVID-19

05.02 - Monitoring airway disease (2024)

Doriane Calmés Virginie Paulus Françoise Guissard Nathalie Maes Laurence Seidel

Parenchyma

2019-20 coronavirus outbreak

10.1183/13993003.congress-2024.pa3989

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Citations (0)

Artificial intelligence improves experts in reading pulmonary function tests

Marko Topalovic Nilakash Das Pierre‐Régis Burgel Marc Daenen Eric Derom

Introduction: The use of pulmonary function tests (PFT) is built on an expert opinion. PFT interpretation relies on the recognition of patterns but scarcely leads to a specific respiratory disease diagnosis. We aimed to explore the accuracy and inter-rater variability of pulmonologists when: 1/ interpreting PFT's, 2/ suggesting a respiratory disease diagnosis based on clinical info and PFT's. We compared it with artificial intelligence (AI)-based software developed on 1430 historical patient cases. Methods: 6000 interpretations of complete PFT (spirometry, body box and diffusion) and clinical info were made by 120 pulmonologists from 16 European hospitals on 50 patient cases. ATS/ERS guidelines were used as the gold standard for test interpretation. The gold standard diagnosis was derived from clinical history, PFT and all additional tests, and finally confirmed by an expert panel. AI software examined the same cases. Results: The interpretations of pulmonologists (senior 73%, junior 27%) matched the guidelines in 74.4% (±5.9) of the cases (range: 56-88%). Inter-rater variability of 0.67 pointed to a common agreement. Readers were able to correctly appoint the primary disease diagnosis in only 44.6% (±8.7) of the cases (range: 24-62%). Inter-rater variability of 0.35 indicates a common disagreement between readers. AI-based software perfectly (100%) matched the interpretation of ATS/ERS guidelines while it assigned a correct diagnosis in 82% of cases. Conclusions: Interpreting PFTs and suggesting primary respiratory disease diagnosis by expert clinicians contains discrepancy and incorrectness. The AI-based software provides a powerful decision support tool to improve current clinical practice.

Pulmonologists

Gold standard (test)

Second opinion

10.1183/13993003.congress-2018.pa5290

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Citations (0)

From Molecular Science to the Treatment of Allergy

International Archives of Allergy and Immunology (1999)

Bradley J. Undem Dawn D. Hunter Mark Liu Mary Haak‐Frendscho Angela Oakragly

for each drug for any change in indications and dosage and for added warnings and precautions.This is particularly important when the recommended agent is a new and/or infrequently employed drug.

10.1159/000024035

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Citations (0)

Exhaled nitric oxide thresholds associated with a sputum eosinophil count >=3% in a cohort of unselected patients with asthma

Thorax (2010)

Florence Schleich Laurence Seidel J. Sele Maïté Manise Valérie Quaedvlieg

It has been claimed that exhaled nitric oxide (FeNO) could be regarded as a surrogate marker for sputum eosinophil count in patients with asthma. However, the FeNO threshold value that identifies a sputum eosinophil count ≥3% in an unselected population of patients with asthma has been poorly studied.This retrospective study was conducted in 295 patients with asthma aged 15–84 years recruited from the asthma clinic of University Hospital of Liege. Receiver-operating characteristic (ROC) curve and logistic regression analysis were used to assess the relationship between sputum eosinophil count and FeNO, taking into account covariates such as inhaled corticosteroids (ICS), smoking, atopy, age and sex.Derived from the ROC curve, FeNO ≥41 ppb gave 65% sensitivity and 79% specificity (AUC=0.777, p=0.0001) for identifying a sputum eosinophil count ≥3%. Using logistic regression analysis, a threshold of 42 ppb was found to discriminate between eosinophilic and non-eosinophilic asthma (p<0.0001). Patients receiving high doses of ICS (≥1000 μg beclometasone) had a significantly lower FeNO threshold (27 ppb) than the rest of the group (48 ppb, p<0.05). Atopy also significantly altered the threshold (49 ppb for atopic vs 30 ppb for non-atopic patients, p<0.05) and there was a trend for a lower threshold in smokers (27 ppb) compared with non-smokers (46 ppb, p=0.066). Age and sex did not affect the relationship between FeNO and sputum eosinophilia. When combining all variables into the logistic model, FeNO (p<0.0001), high-dose ICS (p<0.05) and smoking (p<0.05) were independent predictors of sputum eosinophilia, while there was a trend for atopy (p=0.086).FeNO is able to identify a sputum eosinophil count ≥3% with reasonable accuracy and thresholds which vary according to dose of ICS, smoking and atopy.

Atopy

10.1136/thx.2009.124925

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Citations (140)