Assessment of thunderstorm-induced asthma using Google Trends

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UCRAID (Ukrainian Citizen and refugee electronic support in Respiratory diseases, Allergy, Immunology and Dermatology) action plan.

Eight million Ukrainians have taken refuge in the European Union. Many have asthma and/or allergic rhinitis and/or urticaria, and around 100,000 may have a severe disease. Cultural and language barriers are a major obstacle to appropriate management. Two widely available mHealth apps, MASK-air® (Mobile Airways Sentinel NetworK) for the management of rhinitis and asthma and CRUSE® (Chronic Urticaria Self Evaluation) for patients with chronic spontaneous urticaria, were updated to include Ukrainian versions that make the documented information available to treating physicians in their own language. The Ukrainian patients fill in the questionnaires and daily symptom-medication scores for asthma, rhinitis (MASK-air) or urticaria (CRUSE) in Ukrainian. Then, following the GDPR, patients grant their physician access to the app by scanning a QR code displayed on the physician's computer enabling the physician to read the app contents in his/her own language. This service is available freely. It takes less than a minute to show patient data to the physician in the physician's web browser. UCRAID-developed by ARIA (Allergic Rhinitis and its Impact on Asthma) and UCARE (Urticaria Centers of Reference and Excellence)-is under the auspices of the Ukraine Ministry of Health as well as European (European Academy of Allergy and Clinical immunology, EAACI, European Respiratory Society, ERS, European Society of Dermatologic Research, ESDR) and national societies

Mobile Technology in Allergic Rhinitis : Evolution in Management or Revolution in Health and Care?

Smart devices and Internet-based applications (apps) are largely used in allergic rhinitis and may help to address some unmet needs. However, these new tools need to first of all be tested for privacy rules, acceptability, usability, and cost-effectiveness. Second, they should be evaluated in the frame of the digital transformation of health, their impact on health care delivery, and health outcomes. This review (1) summarizes some existing mobile health apps for allergic rhinitis and reviews those in which testing has been published, (2) discusses apps that include risk factors of allergic rhinitis, (3) examines the impact of mobile health apps in phenotype discovery, (4) provides real-world evidence for care pathways, and finally (5) discusses mobile health tools enabling the digital transformation of health and care, empowering citizens, and building a healthier society. (C) 2019 American Academy of Allergy, Asthma & ImmunologyPeer reviewe

Development and validation of combined symptom‐medication scores for allergic rhinitis*

Background: Validated combined symptom-medication scores (CSMSs) are needed to investigate the effects of allergic rhinitis treatments. This study aimed to use real-life data from the MASK-air® app to generate and validate hypothesis- and data-driven CSMSs. Methods: We used MASK-air® data to assess the concurrent validity, test-retest reliability and responsiveness of one hypothesis-driven CSMS (modified CSMS: mCSMS), one mixed hypothesis- and data-driven score (mixed score), and several data-driven CSMSs. The latter were generated with MASK-air® data following cluster analysis and regression models or factor analysis. These CSMSs were compared with scales measuring (i) the impact of rhinitis on work productivity (visual analogue scale [VAS] of work of MASK-air® , and Work Productivity and Activity Impairment: Allergy Specific [WPAI-AS]), (ii) quality-of-life (EQ-5D VAS) and (iii) control of allergic diseases (Control of Allergic Rhinitis and Asthma Test [CARAT]). Results: We assessed 317,176 days of MASK-air® use from 17,780 users aged 16-90 years, in 25 countries. The mCSMS and the factor analyses-based CSMSs displayed poorer validity and responsiveness compared to the remaining CSMSs. The latter displayed moderate-to-strong correlations with the tested comparators, high test-retest reliability and moderate-to-large responsiveness. Among data-driven CSMSs, a better performance was observed for cluster analyses-based CSMSs. High accuracy (capacity of discriminating different levels of rhinitis control) was observed for the latter (AUC-ROC = 0.904) and for the mixed CSMS (AUC-ROC = 0.820). Conclusion: The mixed CSMS and the cluster-based CSMSs presented medium-high validity, reliability and accuracy, rendering them as candidates for primary endpoints in future rhinitis trials

Development and validation of combined symptom-medication scores for allergic rhinitis*

Background Validated combined symptom-medication scores (CSMSs) are needed to investigate the effects of allergic rhinitis treatments. This study aimed to use real-life data from the MASK-air(R) app to generate and validate hypothesis- and data-driven CSMSs. Methods We used MASK-air(R) data to assess the concurrent validity, test-retest reliability and responsiveness of one hypothesis-driven CSMS (modified CSMS: mCSMS), one mixed hypothesis- and data-driven score (mixed score), and several data-driven CSMSs. The latter were generated with MASK-air(R) data following cluster analysis and regression models or factor analysis. These CSMSs were compared with scales measuring (i) the impact of rhinitis on work productivity (visual analogue scale [VAS] of work of MASK-air(R), and Work Productivity and Activity Impairment: Allergy Specific [WPAI-AS]), (ii) quality-of-life (EQ-5D VAS) and (iii) control of allergic diseases (Control of Allergic Rhinitis and Asthma Test [CARAT]). Results We assessed 317,176 days of MASK-air(R) use from 17,780 users aged 16-90 years, in 25 countries. The mCSMS and the factor analyses-based CSMSs displayed poorer validity and responsiveness compared to the remaining CSMSs. The latter displayed moderate-to-strong correlations with the tested comparators, high test-retest reliability and moderate-to-large responsiveness. Among data-driven CSMSs, a better performance was observed for cluster analyses-based CSMSs. High accuracy (capacity of discriminating different levels of rhinitis control) was observed for the latter (AUC-ROC = 0.904) and for the mixed CSMS (AUC-ROC = 0.820). Conclusion The mixed CSMS and the cluster-based CSMSs presented medium-high validity, reliability and accuracy, rendering them as candidates for primary endpoints in future rhinitis trials.Peer reviewe

Google Trends terms reporting rhinitis and related topics differ in European countries

Google Trends (GT) searches trends of specific queries in Google and reflects the real-life epidemiology of allergic rhinitis. We compared Google Trends terms related to allergy and rhinitis in all European Union countries, Norway and Switzerland from 1 January 2011 to 20 December 2016. The aim was to assesswhether the same terms could be used to report the seasonal variations of allergic diseases. Using the Google Trend 5-year graph, an annual and clear seasonality of queries was found in all countries apart from Cyprus, Estonia, Latvia, Lithuania and Malta. Different terms were found to demonstrate seasonality depending on the country - namely 'hay fever', 'allergy' and 'pollen' - showing cultural differences. A single set of terms cannot be used across all European countries, but allergy seasonality can be compared across Europe providing the above three terms are used. Using longitudinal data in different countries and multiple terms, we identified an awareness-related spike of searches (December 2016)

Electronic Clinical Decision Support System for allergic rhinitis management : MASK e-CDSS

Background: Allergic rhinitis (AR) management has changed in recent years following the switch from the concept of disease severity to the concept of disease control, publication of the AR clinical decision support system (CDSS) and development of mobile health (m-health) tools for patients (eg Allergy Diary). The Allergy Diary Companion app for healthcare providers is currently being developed and will be launched in 2018. It incorporates the AR CDSS to provide evidence-based treatment recommendations, linking all key stakeholders in AR management. Objective: To produce an electronic version of the AR CDSS (e-CDSS) for incorporation into the Allergy Diary Companion, to describe the app interfaces used to collect information necessary to inform the e-CDSS and to summarize some key features of the Allergy Diary Companion. Methods: The steps involved in producing the e-CDSS and incorporating it into the Allergy Diary Companion were (a) generation of treatment management scenarios; (b) expert consensus on treatment recommendations; (c) generation of electronic decisional algorithms to describe all AR CDSS scenarios; (d) digitization of these algorithms to form the e-CDSS; and (e) embedding the e-CDSS into the app to permit easy user e-CDSS interfacing. Results: Key experts in the AR field agreed on the AR CDSS approach to AR management and on specific treatment recommendations provided by Allergy Diary Companion. Based on this consensus, decision processes were developed and programmed into the Allergy Diary Companion using Titanium Appcelerator (JavaScript) for IOS tablets. To our knowledge, this is the first time the development of any m-health tool has been described in this transparent and detailed way, providing confidence, not only in the app, but also in the provided management recommendations. Conclusion: The Allergy Diary Companion for providers provides guideline and expert-endorsed AR management recommendations. [MASK paper No 32].Peer reviewe

The ARIA-MASK-air® approach

Funding Information: The authors thank Ms Véronique Pretschner for submitting the paper. MASK‐air has been supported by Charité Universitätsmedizin Berlin, EU grants (EU Structural and Development Funds Languedoc Roussillon and Region PACA; POLLAR: EIT Health; Twinning: EIP on AHA; Twinning DHE: H2020; Catalyse: Horizon Europe) and educational grants from Mylan‐Viatris, ALK, GSK, Novartis, Stallergènes‐Greer and Uriach. None for the study. ® Publisher Copyright: © 2023 The Authors. Clinical and Translational Allergy published by John Wiley & Sons Ltd on behalf of European Academy of Allergy and Clinical Immunology.MASK-air®, a validated mHealth app (Medical Device regulation Class IIa) has enabled large observational implementation studies in over 58,000 people with allergic rhinitis and/or asthma. It can help to address unmet patient needs in rhinitis and asthma care. MASK-air® is a Good Practice of DG Santé on digitally-enabled, patient-centred care. It is also a candidate Good Practice of OECD (Organisation for Economic Co-operation and Development). MASK-air® data has enabled novel phenotype discovery and characterisation, as well as novel insights into the management of allergic rhinitis. MASK-air® data show that most rhinitis patients (i) are not adherent and do not follow guidelines, (ii) use as-needed treatment, (iii) do not take medication when they are well, (iv) increase their treatment based on symptoms and (v) do not use the recommended treatment. The data also show that control (symptoms, work productivity, educational performance) is not always improved by medications. A combined symptom-medication score (ARIA-EAACI-CSMS) has been validated for clinical practice and trials. The implications of the novel MASK-air® results should lead to change management in rhinitis and asthma.publishersversionpublishe

Concepts for the Development of Person-Centered, Digitally Enabled, Artificial Intelligence–Assisted ARIA Care Pathways (ARIA 2024)

Funding Information: This work has received funding from ARIA (Allergic Rhinitis and its Impact of Asthma); CATALYSE (Climate Action To Advance HeaLthY Societies in Europe), the European Union\u2019s Horizon Europe research and innovation program under grant agreement no. 101057131; FRAUNHOFER Institute for Translational Medicine and Pharmacology (ITMP), Immunology and Allergology, Berlin, Germany; University of Porto, Portugal; and MASK-air, which has been supported by EU grants (Impact of air Pollution on Asthma and Rhinitis [POLLAR] project of the European Institute of Innovation and Technology Health; Structural and Development Funds, R\u00E9gion Languedoc Roussillon and Provence-Alpes-C\u00F4te d\u2019Azur; Twinning, European Innovation Partnership on Active and Healthy Ageing, DG Sant\u00E9 and DG Connect); educational grants from Mylan-Viatris, Allergologisk Laboratorium K\u00F8benhavn, GlaxoSmithKline, Novartis, Stallerg\u00E8nes-Greer, and Noucor; and funding from Breathing Together Onlus Association (Associazione Respiriamo Insieme Onlus), Italy; Esp\u00EDritu Santo University, Samborond\u00F3n, Ecuador; Finnish Anti-Tuberculosis Association Foundation and Tampere Tuberculosis Foundation; GA 2 LEN; German Allergy Society AeDA (\u00C4rzteverband Deutscher Allergologen); IPOKRaTES (International Postgraduate Organization for Knowledge transfer, Research and Teaching Excellent Students) Lithuania Fund; Polish Society of Allergology (POLSKIE TOWARZYSTWO ALLERGOLOGICZNE); and University of Li\u00E8ge, Belgium. Funding Information: Conflicts of interest: J. Bousquet reports personal fees from Cipla, Menarini, Mylan, Novartis, Purina, Sanofi-Aventis, Teva, Noucor, other from KYomed-Innov, and other from Mask-air-SAS, outside the submitted work. M. Blaiss reports personal fees from Sanofi, personal fees from Regeneron, personal fees from ALK, personal fees from Merck, personal fees from AstraZeneca, personal fees from GSK, personal fees from Prollergy, personal fees from Lanier Biotherapeutics, and nonfinancial support from Bryn Phama, outside the submitted work. J. Lity\u0144ska reports personal fees from Evidence Prime Sp. z o.o., outside the submitted work. T. Iinuma reports grants from Sanofi, outside the submitted work. P. Tantilipikorn reports grants from Abbott, other from GSK, and other from Sanofi Aventis, outside the submitted work. T. Haahtela reports personal fees from Orion Pharma, outside the submitted work. Publisher Copyright: © 2024 The AuthorsThe traditional healthcare model is focused on diseases (medicine and natural science) and does not acknowledge patients’ resources and abilities to be experts in their own lives based on their lived experiences. Improving healthcare safety, quality, and coordination, as well as quality of life, is an important aim in the care of patients with chronic conditions. Person-centered care needs to ensure that people's values and preferences guide clinical decisions. This paper reviews current knowledge to develop (1) digital care pathways for rhinitis and asthma multimorbidity and (2) digitally enabled, person-centered care.1 It combines all relevant research evidence, including the so-called real-world evidence, with the ultimate goal to develop digitally enabled, patient-centered care. The paper includes (1) Allergic Rhinitis and its Impact on Asthma (ARIA), a 2-decade journey, (2) Grading of Recommendations, Assessment, Development and Evaluation (GRADE), the evidence-based model of guidelines in airway diseases, (3) mHealth impact on airway diseases, (4) From guidelines to digital care pathways, (5) Embedding Planetary Health, (6) Novel classification of rhinitis and asthma, (7) Embedding real-life data with population-based studies, (8) The ARIA-EAACI (European Academy of Allergy and Clinical Immunology) strategy for the management of airway diseases using digital biomarkers, (9) Artificial intelligence, (10) The development of digitally enabled, ARIA person-centered care, and (11) The political agenda. The ultimate goal is to propose ARIA 2024 guidelines centered around the patient to make them more applicable and sustainable.proofinpres

ARIA digital anamorphosis : Digital transformation of health and care in airway diseases from research to practice

Digital anamorphosis is used to define a distorted image of health and care that may be viewed correctly using digital tools and strategies. MASK digital anamorphosis represents the process used by MASK to develop the digital transformation of health and care in rhinitis. It strengthens the ARIA change management strategy in the prevention and management of airway disease. The MASK strategy is based on validated digital tools. Using the MASK digital tool and the CARAT online enhanced clinical framework, solutions for practical steps of digital enhancement of care are proposed.Peer reviewe