An adjudication algorithm for respiratory-related hospitalisation in idiopathic pulmonary fibrosis Article Swipe
YOU?
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· 2024
· Open Access
·
· DOI: https://doi.org/10.1183/23120541.00636-2023
Background There is no standard definition of respiratory-related hospitalisation, a common end-point in idiopathic pulmonary fibrosis (IPF) clinical trials. As diverse aetiologies and complicating comorbidities can present similarly, external adjudication is sometimes employed to achieve standardisation of these events. Methods An algorithm for respiratory-related hospitalisation was developed through a literature review of IPF clinical trials with respiratory-related hospitalisation as an end-point. Experts reviewed the algorithm until a consensus was reached. The algorithm was validated using data from the phase 3 ISABELA trials ( clinicaltrials.gov identifiers NCT03711162 and NCT03733444 ), by assessing concordance between nonadjudicated, investigator-defined, respiratory-related hospitalisations and those defined by the adjudication committee using the algorithm. Results The algorithm classifies respiratory-related hospitalisation according to cause: extraparenchymal (worsening respiratory symptoms due to left heart failure, volume overload, pulmonary embolism, pneumothorax or trauma); other (respiratory tract infection, right heart failure or exacerbation of COPD); “definite” acute exacerbation of IPF (AEIPF) (worsening respiratory symptoms within 1 month, with radiological or histological evidence of diffuse alveolar damage); or “suspected” AEIPF (as for “definite” AEIPF, but with no radiological or histological evidence of diffuse alveolar damage). Exacerbations (“definite” or “suspected”) with identified triggers (infective, post-procedural or traumatic, drug toxicity- or aspiration-related) are classed as “known AEIPF”; “idiopathic AEIPF” refers to exacerbations with no identified trigger. In the ISABELA programme, there was 94% concordance between investigator- and adjudication committee-determined causes of respiratory-related hospitalisation. Conclusion The algorithm could help to ensure consistency in the reporting of respiratory-related hospitalisation in IPF trials, optimising its utility as an end-point.
Related Topics
- Type
- article
- Language
- en
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- https://doi.org/10.1183/23120541.00636-2023
- https://openres.ersjournals.com/content/erjor/early/2023/11/09/23120541.00636-2023.full.pdf
- OA Status
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- Cited By
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- References
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- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4390755453Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1183/23120541.00636-2023Digital Object Identifier
- Title
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An adjudication algorithm for respiratory-related hospitalisation in idiopathic pulmonary fibrosisWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-01-01Full publication date if available
- Authors
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Paul Ford, Michael Kreuter, Kevin K. Brown, Wim Wuyts, Marlies Wijsenbeek, Dominique Israël‐Biet, Richard Hubbard, Steven D. Nathan, Hilario Nunès, Björn Penninckx, Niyati Prasad, Ineke Seghers, Paolo Spagnolo, Nadia Verbruggen, Nik Hirani, Jürgen Behr, Robert J. Kaner, Toby M. MaherList of authors in order
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https://doi.org/10.1183/23120541.00636-2023Publisher landing page
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https://openres.ersjournals.com/content/erjor/early/2023/11/09/23120541.00636-2023.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://openres.ersjournals.com/content/erjor/early/2023/11/09/23120541.00636-2023.full.pdfDirect OA link when available
- Concepts
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Medicine, Exacerbation, Intensive care medicine, Idiopathic pulmonary fibrosis, Respiratory failure, Algorithm, Respiratory system, Internal medicine, Lung, Computer scienceTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2025: 3Per-year citation counts (last 5 years)
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59Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| primary_location.raw_source_name | ERJ Open Research |
| primary_location.landing_page_url | https://doi.org/10.1183/23120541.00636-2023 |
| publication_date | 2024-01-01 |
| publication_year | 2024 |
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