Personalized pollen-related symptom-forecast information services for allergic rhinitis patients in Europe

Berger, Uwe; Karatzas, Kostas; Jaeger, S.; Voukantsis, Dimitris; Sofiev, M.; Brandt, Oliver; Zuberbier, Torsten; Bergmann, Karl‐Christian

doi:10.1111/all.12181

Cited by 32 publications

(21 citation statements)

References 8 publications

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“…39 The immune system reacts with symptoms to allergens, 40 which are carried and released by pollen. The natural variability across Europe of how much allergen is carried by grass pollen was unknown.…”

Section: Discussionmentioning

confidence: 99%

Variation of the group 5 grass pollen allergen content of airborne pollen in relation to geographic location and time in season

Buters

Prank

Sofiev

et al. 2015

Journal of Allergy and Clinical Immunology

160

107

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Section: Discussionmentioning

confidence: 99%

Variation of the group 5 grass pollen allergen content of airborne pollen in relation to geographic location and time in season

Buters

Prank

Sofiev

et al. 2015

Journal of Allergy and Clinical Immunology

160

107

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“…The COST action ES0603, for the first time, established a multidisciplinary forum that critically reviewed the existing information on pollen production, release and transport in Europe (13,18). The development and widespread clinical use of electronic personalized hay fever diaries (19) in AIT trials have allowed the opportunity to combine such information with pollen data in a wide variety of patients and to evaluate the importance of this information.…”

Section: The Regulatory and Academic Viewmentioning

confidence: 99%

“…The selection of the amounts of different pollen was based on existing threshold values for symptom development (14), the comparison between pollen data from the European Aeroallergen Network (EAN) database (https://ean.polleninfo.eu/) and 'reallife' data as reported by patients using the online patient's hay-fever diary (https://www.pollendiary.com/) and the Pollen App 4.1 (https://www.pollenwarndienst.at/de/gratis-polle n-app.html) to document their actual (daily) symptoms on eyes, nose and bronchi during pollen exposure within the season (19,52). As such, these definitions have been elaborated by the TF experts based on data belonging to central and southern Europe, well knowing that values used in the definitions might need adaptation to different biogeographical regions.…”

Section: Proposed Definitionsmentioning

confidence: 99%

Defining pollen exposure times for clinical trials of allergen immunotherapy for pollen‐induced rhinoconjunctivitis – an EAACI position paper

Pfaar

Bastl

Berger

et al. 2017

Allergy

Self Cite

134

155

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Underlying principles in measuring pollen exposure and associated methodological problems and limitations were considered to achieve a consensus. Results: The Task Force achieved a comprehensive position in defining pollen exposure times for different pollen types. Definitions are presented for 'pollen season', 'high pollen season' (or 'peak pollen period') and 'high pollen days'. Conclusion: This EAACI position paper provides definitions of pollen exposures for different pollen types for use in AIT trials. Their validity as standards remains to be tested in future studies.

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“…Airborne pollen are monitored in Europe by a network of about 400 Hirst-type pollen traps [17]. However, there is a need for more rapid, preferably instantaneous, online reporting of airborne pollen concentrations in addition to alleviating the workload of manual operation.…”

Section: Introductionmentioning

confidence: 99%

Automatic and Online Pollen Monitoring

Oteros¹,

Pusch²,

Weichenmeier³

et al. 2015

Int Arch Allergy Immunol

132

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Background: Pollen are monitored in Europe by a network of about 400 pollen traps, all operated manually. To date, automated pollen monitoring has only been feasible in areas with limited variability in pollen species. There is a need for rapid reporting of airborne pollen as well as for alleviating the workload of manual operation. We report our experience with a fully automated, image recognition-based pollen monitoring system, BAA500. Methods: The BAA500 sampled ambient air intermittently with a 3-stage virtual impactor at 60 m³/h in Munich, Germany. Pollen is deposited on a sticky surface that was regularly moved to a microscope equipped with a CCD camera. Images of the pollen were constructed and compared with a library of known samples. A Hirst-type pollen trap was operated simultaneously. Results: Over 480,000 particles sampled with the BAA500 were both manually and automatically identified, of which about 46,000 were pollen. Of the automatically reported pollen, 93.3% were correctly recognized. However, compared with manual identification, 27.8% of the captured pollen were missing in the automatic report, with most reported as unknown pollen. Salix pollen grains were not identified satisfactorily. The daily pollen concentrations reported by a Hirst-type pollen trap and the BAA500 were highly correlated (r = 0.98). Conclusions: The BAA500 is a functional automated pollen counter. Its software can be upgraded, and so we expected its performance to improve upon training. Automated pollen counting has great potential for workload reduction and rapid online pollen reporting.

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Personalized pollen-related symptom-forecast information services for allergic rhinitis patients in Europe

Abstract: We report on the development of personalized pollen‐related information services that include sensitivity categorization, threshold identification, and symptom forecasting, addressing patients with allergic rhinitis in Europe.

Cited by 32 publications

References 8 publications

Variation of the group 5 grass pollen allergen content of airborne pollen in relation to geographic location and time in season

Variation of the group 5 grass pollen allergen content of airborne pollen in relation to geographic location and time in season

Defining pollen exposure times for clinical trials of allergen immunotherapy for pollen‐induced rhinoconjunctivitis – an EAACI position paper

Automatic and Online Pollen Monitoring

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