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International consensus statement on allergy and rhinology: Allergic rhinitis – 2023
Open accessAbstract
Background: In the 5 years that have passed since the publication of the 2018 International Consensus Statement on Allergy and Rhinology: Allergic Rhinitis (ICAR‐Allergic Rhinitis 2018), the literature has expanded substantially. The ICAR‐Allergic Rhinitis 2023 update presents 144 individual topics on allergic rhinitis (AR), expanded by over 40 topics from the 2018 document. Originally presented topics from 2018 have also been reviewed and updated. The executive summary highlights key evidence‐based findings and recommendation from the full document. Methods: ICAR‐Allergic Rhinitis 2023 employed established evidence‐based review with recommendation (EBRR) methodology to individually evaluate each topic. Stepwise iterative peer review and consensus was performed for each topic. The final document was then collated and includes the results of this work. Results: ICAR‐Allergic Rhinitis 2023 includes 10 major content areas and 144 individual topics related to AR. For a substantial proportion of topics included, an aggregate grade of evidence is presented, which is determined by collating the levels of evidence for each available study identified in the literature. For topics in which a diagnostic or therapeutic intervention is considered, a recommendation summary is presented, which considers the aggregate grade of evidence, benefit, harm, and cost. Conclusion: The ICAR‐Allergic Rhinitis 2023 update provides a comprehensive evaluation of AR and the currently available evidence. It is this evidence that contributes to our current knowledge base and recommendations for patient evaluation and treatment.
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Metadata
- Authors
- Wise, S. K., Damask, C., Roland, L. T., Ebert, C., Levy, J. M., Lin, S., Luong, A., Rodriguez, K., Sedaghat, A. R., Toskala, E., Villwock, J., Abdullah, B., Akdis, C., Alt, J. A., Ansotegui, I. J., Azar, A., Baroody, F., Benninger, M. S., Bernstein, J., Brook, C., Campbell, R., Casale, T., Chaaban, M. R., Chew, F. T., Chambliss, J., Cianferoni, A., Custovic, A., Davis, E. M., DelGaudio, J. M., Ellis, A. K., Flanagan, C., Fokkens, W. J., Franzese, C., Greenhawt, M., Gill, A., Halderman, A., Hohlfeld, J. M., Incorvaia, C., Joe, S. A., Joshi, S., Kuruvilla, M. E., Kim, J., Klein, A. M., Krouse, H. J., Kuan, E. C., Lang, D., Larenas‐Linnemann, D., Laury, A. M., Lechner, M., Lee, S. E., Lee, V. S., Loftus, P., Marcus, S., Marzouk, H., Mattos, J., McCoul, E., Melen, E., Mims, J. W., Mullol, J., Nayak, J. V., Oppenheimer, J., Orlandi, R. R., Phillips, K., Platt, M., Ramanathan, M., Raymond, M., Rhee, C., Reitsma, S., Ryan, M., Sastre, J., Schlosser, R. J., Schuman, T. A., Shaker, M. S., Sheikh, A., Smith, K. A., Soyka, M. B., Takashima, M., Tang, M., Tantilipikorn, P., Taw, M. B., Tversky, J., Tyler, M. A., Veling, M. C., Wallace, D., Wang, D. Y., White, A., & Zhang, L.
- Venue
- International Forum of Allergy & Rhinology
- Publisher
- Wiley
- Published
- 2023-03-06
- Volume
- 13
- Issue
- 4
- Pages
- 293-859
- ISSN
- 2042-6976 (ISSN-L)
- 2042-6984
- OpenAlex
- W4323304861
- Cited by
- 507
- References
- 504
- FWCI
- 75.84
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.