Browsing by Author "Amaral, Rita"
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- Adherence to treatment in allergic rhinitis during the pollen season in Europe: A MASK‐air StudyPublication . Bousquet, Jean; Amaral, RitaAdherence to rhinitis treatment has been insufficiently assessed. We aimed to use data from the MASK-airmHealth app to assess adherence to oral antihistamines (OAH), intra-nasal corticosteroids (INCS) or azelastine-fluticasone inpatients with allergic rhinitis. We included regular European MASK-air users with self-reported allergic rhinitis and reporting at least 1 day of OAH,INCS or azelastine-fluticasone. We assessed weeks during which patients answered the MASK-air questionnaire on all days. Werestricted our analyses to data provided between January and June, to encompass the pollen seasons across the different assessedcountries. We analysed symptoms using visual analogue scales (VASs) and the combined symptom-medication score (CSMS),performing stratified analyses by weekly adherence levels. Medication adherence was computed as the proportion of days inwhich patients reported rhinitis medication use. Sensitivity analyses were performed considering all weeks with at most 1 day ofmissing data and all months with at most 4 days of missing data. We assessed 8212 complete weeks (1361 users). Adherence (use of medication > 80% days) to specific drug classesranged from 31.7% weeks for azelastine-fluticasone to 38.5% weeks for OAH. Similar adherence to rhinitis medication was foundin users with or without self-reported asthma, except for INCS (better adherence in asthma patients). VAS and CSMS levelsincreased from no adherence to full adherence, except for INCS. A higher proportion of days with uncontrolled symptoms was observed in weeks with higher adherence. In full adherence weeks, 41.2% days reported rhinitis co-medication. The sensitivityanalyses displayed similar results. A high adherence was found in patients reporting regular use of MASK-air. Different adherence patterns werefound for INCS compared to OAH or azelastine-fluticasone that are likely to impact guidelines.
- AIRDOC: Smart mobile application for individualized support and monitoring of respiratory function and sounds of patients with chronic osbtructive diseasePublication . Almeida, Rute; Amaral, Rita; Jácome, Cristina; Martinho, Diogo; Vieira-Marques, Pedro; Jacinto, Tiago; Ferreira, Ana; Almeida, Ana; Martins, Constantino; Pereira, Mariana; Pereira, Ana; Valente, José; Almeida, Rafael; Vieira, Ana; Amaral, Rita; Sá-Sousa, Ana; Gonçalves, Ivânia; Rodrigues, Pedro; Alves-Correia, Magna; Freitas, Alberto; Marreiros, GoretiCurrent tools for self-management of chronic obstructive respiratory diseases (CORD) are difficult to use, not individualized and requiring laborious analysis by health professionals, discouraging their use in healthcare. There is an opportunity for cost-effective and easy-to-disseminate advanced technological solutions directed to patients and attractive to different stakeholders. The strategy of AIRDOC is to develop and integrate self-monitoring and self-managing tools, making use of the smartphone's presence in everyday life. AIRDOC intends to innovate on: i) technologies for remote monitoring of respiratory function and computerized lung auscultation; ii) coaching solutions, integrating psychoeducation, gamification and disease management support systems; and iii) management of personal health data, focusing on security, privacy and interoperability. It is expected that AIRDOC results will contribute for the innovation in CORD healthcare, with increased patient involvement and empowerment while providing quality prospective information for better clinical decisions, allowing more efficient and sustainable healthcare delivery.
- Allergen sensitization associates with worse lung function parametersPublication . Gonçalves, I.; Pereira, A. M.; Jacinto, Tiago; Amaral, Rita; Fonseca, J. de Almeida Lopes daTo assess the association between the number of allergen sensitizations and lung function variables in individuals with airway symptoms. Methods. Retrospective study with all individuals who performed lung function and skin-prick tests at CUF-Porto (01/2011-06/2016). Six allergen groups were considered. % predicted Pre-Bronchodilator test (BD) and % change after BD were analysed for spirometry and plethysmography parameters. Results. A total of 1293 individuals were included, 54% (n = 698) adults and 69% (n = 891) with sensitization to ≥ 1 allergen group. % FEV1 was significantly higher and % change in FEV1 significantly lower in non-sensitized individuals. % sRaw was higher in polysensitized (vs non-sensitized). Conclusions. The presence of allergen sensitizations was significantly associated with worse key lung function parameters.
- Associação entre o número de sensibilizações a aeroalergénios e parâmetros de função respiratóriaPublication . Gonçalves, I.; Pereira, A. M.; Jacinto, Tiago; Amaral, Rita; Fonseca, J. A.; Amaral, RitaO número de sensibilizações a aeroalergénios é importante na classificação fenotípica de indivíduos com patologia das vias aéreas, estando um maior número associado a maior gravidade da patologia (Amaral R et al, Allergy 2019). No entanto, a sua associação com a função respiratória não está ainda estudada.
- Automatic quality assessment of a forced expiratory manoeuvre acquired with the tablet microphonePublication . Almeida, Rute; Bernardo, Pinho; Jácome, Cristina; Teixeira, João Fonseca; Amaral, Rita; Gonçalves, Ivânia; Lopes, Filipa; Pinheiro, Ana Catarina; Jacinto, Tiago; Paixão, Cátia; Pereira, Mariana; Marques, Alda; Fonseca, João AlmeidaEvaluation of lung function is central to the management of chronic obstructive respiratory diseases. It is typically evaluated with a spirometer by a specialized health professional, who ensures the correct execution of a forced expiratory manoeuvre (FEM). Audio recording of a FEM using a smart device embedded microphone can be used to self-monitor lung function between clinical visits. The challenge of microphone spirometry is to ensure the validity and reliability of the FEM, in the absence of a health professional. In particular, the absence of a mouthpiece may allow excessive mouth closure, leading to an incorrect manoeuvre. In this work, a strategy to automatically assess the correct execution of the FEM is proposed and validated. Using 498 FEM recordings, both specificity and sensitivity attained were above 90%. This method provides immediate feedback to the user, by grading the manoeuvre in a visual scale, promoting the repetition of the FEM when needed.
- Automatic quality assessment of smart device microphone spirometryPublication . Pinho, B.; Almeida, R.; Jácome, C.; Teixeira, J. P.; Amaral, Rita; Lopes, F.; Jacinto, Tiago; Guedes, R.; Pereira, M.; Gonçalves, I.; Fonseca, J. A.; Amaral, RitaLung function tests are critical for diagnosis and monitoring of asthma and other respiratory diseases. Monitoring of lung function, in the absence of a healthcare professional, is very challenging but may be obtained through Smart Devices if automated quality assessment systems guarantee the proper technique during the forced expiratory manoeuvre. This paper describes the evaluation of one such system that uses the microphone of smart devices, regarding the initial effort of forced expiratory manoeuvres using the Back Extrapolated Volume. A health professional recorded microphone spirometry in 55 children (5-10 years), using a mobile game engineered for the purpose, and registered its quality. At least one acceptable manoeuvre was achieved for 96% of the children using a featured threshold. Using a stricter threshold of 5% of forced vital capacity, it was possible to ensure at least one acceptable manoeuvre for 69%. While the obtained results are comparable to findings in literature for regular spirometry in this age group, further work is required before we can determine whether the proposed algorithm is effective in real life.
- Combined image-based approach for monitoring the adherence to inhaled medicationsPublication . Vieira-Marques, Pedro; Teixeira, João Fonseca; Valente, José; Pinho, Bernardo; Guedes, Rui; Almeida, Rute; Jácome, Cristina; Pereira, Ana; Jacinto, Tiago; Amaral, Rita; Gonçalves, Ivânia; Sousa, Ana Sá; Couto, Mariana; Magalhães, Manuel; Bordalo, Diana; Silva, Luís Nogueira; Fonseca, J. AlmeidaThe adherence to inhaled controller medications is of critical importance to achieve good clinical results in patients with chronic respiratory diseases. To objectively verify the adherence, a detection tool was previously developed and integrated in the mobile application InspirerMundi, based on image processing methods. In this work, a new approach for enhanced adherence verification was developed. In a first phase template matching is employed to confirm the inhaler positioning and to locate the dose counter. In a second phase Google ML Kit framework is used for the detection of each numerical dose in the dose counter. The proposed approach was validated through a new detection tool pilot implementation, using a set of images collected by patients using the application in their daily life. Performance of each of the two phases was evaluated for a set of commonly used inhaler devices. Promising results were achieved showing the potential of mobile embedded sensors without the need for external devices.
- Comparison of hypothesis- and data-driven asthma phenotypes in NHANES 2007–2012: the importance of comprehensive data availabilityPublication . Amaral, Rita; Pereira, Ana M.; Jacinto, Tiago; Malinovschi, Andrei; Janson, Christer; Alving, Kjell; Fonseca, João A.Half of the adults with current asthma among the US National Health and Nutrition Examination Survey (NHANES) participants could be classified in more than one hypothesis-driven phenotype. A data-driven approach applied to the same subjects may allow a more useful classification compared to the hypothesis-driven one. To compare previously defined hypothesis-driven with newly derived data-driven asthma phenotypes, identified by latent class analysis (LCA), in adults with current asthma from NHANES 2007–2012. Adults (≥ 18 years) with current asthma from the NHANES were included (n = 1059). LCA included variables commonly used to subdivide asthma. LCA models were derived independently according to age groups: < 40 and ≥ 40 years old. Two data-driven phenotypes were identified among adults with current asthma, for both age groups. The proportions of the hypothesis-driven phenotypes were similar among the two data-driven phenotypes (p > 0.05). Class A < 40 years (n = 285; 75%) and Class A ≥ 40 years (n = 462; 73%), respectively, were characterized by a predominance of highly symptomatic asthma subjects with poor lung function, compared to Class B < 40 years (n = 94; 25%) and Class B ≥ 40 years (n = 170; 27%). Inflammatory biomarkers, smoking status, presence of obesity and hay fever did not markedly differ between the phenotypes. Both data- and hypothesis-driven approaches using clinical and physiological variables commonly used to characterize asthma are suboptimal to identify asthma phenotypes among adults from the general population. Further studies based on more comprehensive disease features are required to identify asthma phenotypes in population-based studies.
- A comparison of unsupervised methods based on dichotomous data to identify clusters of airways symptoms: latent class analysis and partitioning around medoids methodsPublication . Amaral, Rita; Jacinto, Tiago; Pereira, Ana; Almeida, Rute; Fonseca, JoãoLatent class analysis (LCA) and partitioning around medoids (PAM) are popular data-driven methods for partitioning objects based on dichotomous data, remaining not clear which is better for large epidemiological datasets. Hence, we compared these methods in the identification of clusters of subjects with airways symptoms, using a large population-based data from the U.S. National Health and Nutrition Examination Surveys (NHANES).
- Concepts for the Development of Person-Centered, Digitally Enabled, Artificial Intelligence–Assisted ARIA Care Pathways (ARIA 2024)Publication . Bousquet, Jean; Amaral, Rita; Amaral, RitaThe 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 digital care pathways for rhinitis and asthma multimorbidity and 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 Allergic Rhinitis and its Impact on Asthma (ARIA), a 2-decade journey, Grading of Recommendations, Assessment, Development and Evaluation (GRADE), the evidence-based model of guidelines in airway diseases, mHealth impact on airway diseases, .From guidelines to digital care pathways, Embedding Planetary Health, Novel classification of rhinitis and asthma, Embedding real-life data with population-based studies, The ARIA-EAACI (European Academy of Allergy and Clinical Immunology) strategy for the management of airway diseases using digital biomarkers, Artificial intelligence, The development of digitally enabled, ARIA person-centered care, and The political agenda. The ultimate goal is to propose ARIA 2024 guidelines centered around the patient to make them more applicable and sustainable.