Browsing by Author "Neffen, HE"

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    Concepts for the Development of Person-Centered, Digitally Enabled, Artificial Intelligence-Assisted ARIA Care Pathways (ARIA 2024)
    Bousquet, J; Schünemann, HJ; Sousa-Pinto, B; Zuberbier, T; Togias, A; Samolinski, B; Bedbrook, A; Czarlewski, W; Hofmann-Apitius, M; Litynska, J; Vieira, RJ; Anto, JM; Fonseca, JA; Brozek, J; Bognanni, A; Brussino, L; Canonica, GW; Cherrez-Ojeda, I; Cruz, AA; de las Vecillas, L; Dykewicz, M; Gemicioglu, B; Giovannini, M; Haahtela, T; Jacobs, M; Jacomelli, C; Klimek, L; Kvedariene, V; Larenas-Linnemann, DE; Louis, G; Lourenço, O; Leemann, L; Morais-Almeida, M; Neves, AL; Nadeau, KC; Nowak, A; Palamarchuk, Y; Palkonen, S; Papadopoulos, NG; Parmelli, E; Pereira, AM; Pfaar, O; Regateiro, FS; Savouré, M; Taborda-Barata, L; Toppila-Salmi, SK; Torres, MJ; Valiulis, A; Ventura, MT; Williams, S; Yepes-Nunez, JJ; Yorgancioglu, A; Zhang, L; Zuberbier, J; Latiff, AHA; Abdullah, B; Agache, I; Al-Ahmad, M; Al-Nesf, MA; Al Shaikh, NA; Amaral, R; Ansotegui, IJ; Asllani, J; Balotro-Torres, MC; Bergman, KC; Bernstein, JA; Bindslev-Jensen, C; Blaiss, MS; Bonaglia, C; Bonini, M; Bossé, I; Braido, F; Caballero-Fonseca, F; Camargos, P; Carreiro-Martins, P; Casale, T; Castillo-Vizuete, JA; Cecchi, L; Teixeira, MD; Chang, YS; Loureiro, CC; Christoff, G; Ciprandi, G; Cirule, I; Correia-de-Sousa, J; Costa, EM; Cvetkovski, B; de Vries, G; Del Giacco, S; Devillier, P; Dokic, D; Douagui, H; Durham, SR; Enecilla, ML; Fiocchi, A; Fokkens, WJ; Fontaine, JF; Gawlik, R; Gereda, JE; Gil-Mata, S; Giuliano, AFM; Gotua, M; Gradauskiene, B; Guzman, MA; Hossny, E; Hrubisko, M; Iinuma, T; Irani, C; Ispayeva, Z; Ivancevich, JC; Jartti, T; Jesenák, MS; Julge, K; Jutel, M; Kaidashev, I; Bennoor, KS; Khaltaev, N; Kirenga, B; Kraxner, H; Kull, I; Kulus, M; Kuna, P; Kupczyk, M; Kurchenko, A; La Grutta, S; Lane, S; Miculinic, N; Lee, SM; Tuyet, LLT; Lkhagvaa, B; Louis, R; Mahboub, B; Makela, M; Makris, M; Maurer, M; Melén, E; Milenkovic, B; Mohammad, Y; Moniuszko, M; Montefort, S; Moreira, A; Moreno, P; Mullol, J; Nadif, R; Nakonechna, A; Navarro-Locsin, CG; Neffen, HE; Nekam, K; Niedoszytko, M; Nunes, E; Nyembue, D; O'Hehir, R; Ollert, M; Ohta, K; Okamoto, Y; Okubo, K; Olze, H; Padukudru, MA; Palomares, O; Pali-Scholl, I; Panzner, P; Palosuo, K; Park, HS; Passalacqua, G; Patella, V; Pawankar, R; Pétré, B; Pitsios, C; Plavec, D; Popov, TA; Puggioni, F; Quirce, S; Raciborski, F; Ramonaité, A; Recto, M; Repka-Ramirez, S; Roberts, G; Robles-Velasco, K; Roche, N; Rodriguez-Gonzalez, M; Romualdez, JA; Rottem, M; Rouadi, PW; Salapatas, M; Sastre, J; Serpa, FS; Sayah, Z; Scichilone, N; Senna, G; Sisul, JC; Solé, D; Soto-Martinez, ME; Sova, M; Sozinova, O; Stevanovic, K; Ulrik, CS; Szylling, A; Tan, FM; Tantilipikorn, P; Todo-Bom, A; Tomic-Spiric, V; Tsaryk, V; Tsiligianni, I; Urrutia-Pereira, M; Rostan, MV; Sofiev, M; Valovirta, E; Van Eerd, M; Van Ganse, E; Vasankari, T; Vichyanond, P; Viegi, G; Wallace, D; Wang, DY; Waserman, S; Wong, G; Worm, M; Yusuf, OM; Zaitoun, F; Zidarn, M
    The 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. (c) 2024 The Authors. Published by Elsevier Inc. on behalf of the American Academy of Allergy, Asthma & Immunology. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
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    Development and validation of an electronic daily control score for asthma (e-DASTHMA): a real-world direct patient data study
    Sousa-Pinto, B; Jácome, C; Pereira, AM; Regateiro, FS; Almeida, R; Czarlewski, W; Kulus, M; Shamji, MH; Boulet, LP; Bonini, M; Brussino, L; Canonica, GW; Cruz, AA; Gemicioglu, B; Haahtela, T; Kupczyk, M; Kvedariene, V; Larenas-Linnemann, D; Louis, R; Niedoszytko, M; Nhan, PT; Puggioni, F; Romantowski, J; Sastre, J; Scichilone, N; Taborda-Barata, L; Ventura, MT; Vieira, RJ; Agache, I; Bedbrook, A; Bergmann, KC; Amaral, R; Azevedo, LF; Bosnic-Anticevich, S; Brusselle, G; Buhl, R; Cecchi, L; Charpin, D; Loureiro, CC; de Blay, F; Del Giacco, S; Devillier, P; Jassem, E; Joos, G; Jutel, M; Klimek, L; Kuna, P; Laune, D; Pech, JL; Makela, M; Morais-Almeida, M; Nadif, R; Neffen, HE; Ohta, K; Papadopoulos, NG; Papi, A; Pétré, B; Pfaar, O; Yeverino, DR; Cordeiro, CR; Roche, N; Sá-Sousa, A; Samolinski, B; Sheikh, A; Ulrik, CS; Usmani, OS; Valiulis, A; Vandenplas, O; Vieira-Marques, P; Yorgancioglu, A; Zuberbier, T; Anto, JM; Fonseca, JA; Bousquet, J
    Background Validated questionnaires are used to assess asthma control over the past 1-4 weeks from reporting. However, they do not adequately capture asthma control in patients with fluctuating symptoms. Using the Mobile Airways Sentinel Network for airway diseases (MASK-air) app, we developed and validated an electronic daily asthma control score (e-DASTHMA). Methods We used MASK-air data (freely available to users in 27 countries) to develop and assess different daily control scores for asthma. Data-driven control scores were developed based on asthma symptoms reported by a visual analogue scale (VAS) and self-reported asthma medication use. We included the daily monitoring data from all MASK-air users aged 16-90 years (or older than 13 years to 90 years in countries with a lower age of digital consent) who had used the app in at least 3 different calendar months and had reported at least 1 day of asthma medication use. For each score, we assessed construct validity, test-retest reliability, responsiveness, and accuracy. We used VASs on dyspnoea and work disturbance, EQ-5D-VAS, Control of Allergic Rhinitis and Asthma Test (CARAT), CARAT asthma, and Work Productivity and Activity Impairment: Allergy Specific (WPAI:AS) questionnaires as comparators. We performed an internal validation using MASK-air data from Jan 1 to Oct 12, 2022, and an external validation using a cohort of patients with physician-diagnosed asthma (the INSPIRERS cohort) who had had their diagnosis and control (Global Initiative for Asthma [GINA] classification) of asthma ascertained by a physician. Findings We studied 135 635 days of MASK-air data from 1662 users from May 21, 2015, to Dec 31, 2021. The scores were strongly correlated with VAS dyspnoea (Spearman correlation coefficient range 0.68-0.82) and moderately correlated with work comparators and quality-of-life-related comparators (for WPAI:AS work, we observed Spearman correlation coefficients of 0.59-0.68). They also displayed high test-retest reliability (intraclass correlation coefficients range 0.79-0.95) and moderate-to-high responsiveness (correlation coefficient range 0.69-0.79; effect size measures range 0.57-0.99 in the comparison with VAS dyspnoea). The best-performing score displayed a strong correlation with the effect of asthma on work and school activities in the INSPIRERS cohort (Spearman correlation coefficients 0.70; 95% CI 0.61-0.78) and good accuracy for the identification of patients with uncontrolled or partly controlled asthma according to GINA (area under the receiver operating curve 0.73; 95% CI 0.68-0.78). Interpretation e-DASTHMA is a good tool for the daily assessment of asthma control. This tool can be used as an endpoint in clinical trials as well as in clinical practice to assess fluctuations in asthma control and guide treatment optimisation. Funding None. Copyright (c) 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license.