Introduction and objectives: We aimed to build a national consensus to optimize the use of oral corticosteroids (OCS) in severe asthma in Portugal. Material and methods: A modified 3-round Delphi including 65 statements (topics on chronic systemic corticotherapy, therapeutic schemes, asthma safety and monitoring) was performed via online platform (October-November 2019). A five-point Likert-type scale was used (1-'strongly disagree'; 5-'strongly agree'). Consensus threshold was established as a percentage of agreement among participants ≥90% in the 1st round and ≥85% in the 2nd and 3rd rounds. The level of consensus achieved by the panel was discussed with the participants (face-to-face meeting). Results: Forty-eight expert physicians in severe asthma (specialists in allergology and pulmonology) participated in the study. Almost half of the statements (28/65; 43.1%) obtained positive consensus by the end of round one. By the end of the exercise, 12 (18.5%) statements did not achieve consensus. Overall, 87% of physicians agree that further actions for OCS cumulative risk assessment in acute asthma exacerbations are needed. The vast majority (91.7%) demonstrated a favorable perception for using biological agents whenever patients are eligible. Most participants (95.8%) are more willing to accept some degree of lung function deterioration compared to other outcomes (worsening of symptoms, quality of life) when reducing OCS dose. Monitoring patients' comorbidities was rated as imperative by all experts. Conclusions: These results can guide an update on asthma management in Portugal and should be supplemented by studies on therapy access, patients' adherence, and costs.

Introduction and objectives We aimed to build a national consensus to optimize the use of oral corticosteroids (OCS) in severe asthma in Portugal. Material and methods A modified 3-round Delphi including 65 statements (topics on chronic systemic corticotherapy, therapeutic schemes, asthma safety and monitoring) was performed via online platform (October-November 2019). A five-point Likert-type scale was used (1-‘strongly disagree’; 5-‘strongly agree’). Consensus threshold was established as a percentage of agreement among participants ≥90% in the 1st round and ≥85% in the 2nd and 3rd rounds. The level of consensus achieved by the panel was discussed with the participants (face-to-face meeting). Results Forty-eight expert physicians in severe asthma (specialists in allergology and pulmonology) participated in the study. Almost half of the statements (28/65; 43.1%) obtained positive consensus by the end of round one. By the end of the exercise, 12 (18.5%) statements did not achieve consensus. Overall, 87% of physicians agree that further actions for OCS cumulative risk assessment in acute asthma exacerbations are needed. The vast majority (91.7%) demonstrated a favorable perception for using biological agents whenever patients are eligible. Most participants (95.8%) are more willing to accept some degree of lung function deterioration compared to other outcomes (worsening of symptoms, quality of life) when reducing OCS dose. Monitoring patients’ comorbidities was rated as imperative by all experts. Conclusions : These results can guide an update on asthma management in Portugal and should be supplemented by studies on therapy access, patients’ adherence, and costs.

Introduction and objectives: Severe asthma management during the coronavirus disease 2019 (COVID-19) pandemic is a challenge and will continue to be, at least in the next few months, as herd immunity is still a mirage. A lot has to be learned about how COVID-19 affects underlying diseases, and severe asthma is no exception. Methods: Narrative review of papers available until February 2021 in PubMed and Google Scholar, relating severe asthma and COVID-19. Four main research topics were reviewed: SARS-CoV-2 infection: immunology and respiratory pathology; interrelationship of severe asthma endotypes and COVID-19 disease mechanisms; severe asthma epidemiology and COVID-19; and biologics for severe asthma in the context of COVID-19. Results: COVID-19 disease mechanisms start with upper respiratory cell infection, and afterwards several immunological facets are activated, contributing to disease severity, namely cell-mediated immunity and antibody production. Although infrequent in the COVID-19 course some patients develop a cytokine storm that causes organ damage and may lead to acute respiratory distress syndrome or multiorgan failure. Regarding severe asthma endotypes, type2-high might have a protective role both in infection risk and disease course. There is conflicting data regarding the epidemiological relationship between COVID-19 among severe asthma patients, with some studies reporting increased risk of infection and disease course, whereas others the other way round. Biologics for severe asthma do not seem to increase the risk of infection and severe COVID-19, although further evidence is needed. Conclusions: Globally, in the era of COVID-19, major respiratory societies recommend continuing the biologic treatment, preferably in a self-home administration program.

Bronchial asthma is a chronic disease that affects individuals of all ages. It has a high prevalence and is associated with high morbidity and considerable levels of mortality. However, asthma is not a single disease, and multiple subtypes or phenotypes (clinical, inflammatory or combinations thereof) can be detected, namely in aggregated clusters. Most studies have characterised asthma phenotypes and clusters of phenotypes using mainly clinical and inflammatory parameters. These studies are important because they may have clinical and prognostic implications and may also help to tailor personalised treatment approaches. In addition, various metabolomics studies have helped to further define the metabolic features of asthma, using electronic noses or targeted and untargeted approaches. Besides discriminating between asthma and a healthy state, metabolomics can detect the metabolic signatures associated with some asthma subtypes, namely eosinophilic and non-eosinophilic phenotypes or the obese asthma phenotype, and this may prove very useful in point-of-care application. Furthermore, metabolomics also discriminates between asthma and other "phenotypes" of chronic obstructive airway diseases, such as chronic obstructive pulmonary disease (COPD) or Asthma-COPD Overlap (ACO). However, there are still various aspects that need to be more thoroughly investigated in the context of asthma phenotypes in adequately designed, homogeneous, multicentre studies, using adequate tools and integrating metabolomics into a multiple-level approach.

Background: Previous studies have demonstrated the feasibility of using an asthma app to support medication management and adherence but failed to compare with other measures currently used in clinical practice. However, in a clinical setting, any additional adherence measurement must be evaluated in the context of both the patient and physician perspectives so that it can also help improve the process of shared decision making. Thus, we aimed to compare different measures of adherence to asthma control inhalers in clinical practice, namely through an app, patient self-report and physician assessment. Methods: This study is a secondary analysis of three prospective multicentre observational studies with patients (≥13 years old) with persistent asthma recruited from 61 primary and secondary care centres in Portugal. Patients were invited to use the InspirerMundi app and register their inhaled medication. Adherence was measured by the app as the number of doses taken divided by the number of doses scheduled each day and two time points were considered for analysis: 1-week and 1-month. At baseline, patients and physicians independently assessed adherence to asthma control inhalers during the previous week using a Visual Analogue Scale (VAS 0-100). Results: A total of 193 patients (72% female; median [P25-P75] age 28 [19-41] years old) were included in the analysis. Adherence measured by the app was lower (1 week: 31 [0-71]%; 1 month: 18 [0-48]%) than patient self-report (80 [60-95]) and physician assessment (82 [51-94]) (p < 0.001). A negligible non-significant correlation was found between the app and subjective measurements (ρ 0.118-0.156, p > 0.05). There was a moderate correlation between patient self-report and physician assessment (ρ = 0.596, p < 0.001). Conclusions: Adherence measured by the app was lower than that reported by the patient or the physician. This was expected as objective measurements are commonly lower than subjective evaluations, which tend to overestimate adherence. Nevertheless, the low adherence measured by the app may also be influenced by the use of the app itself and this needs to be considered in future studies.

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.

Background: Poor medication adherence is a major challenge in asthma and objective assessment of inhaler adherence is needed. InspirerMundi app aims to monitor inhaler adherence while turning it into a positive experience through gamification and social support. Objective: We assessed the medium-term feasibility of the InspirerMundi app to monitor inhaler adherence in real-world patients with persistent asthma (treated with daily inhaled medication). In addition, we attempted to identify the characteristics of the patients related to higher app use. Methods: Two real-world multicenter observational studies, with one initial face-to-face visit and a 4-month telephone interview, were conducted in 29 secondary care centers from Portugal. During an initial face-to-face visit, patients were invited to use the app daily to register their asthma medication intakes. A scheduled intake was considered taken when patients took a photo of the medication (inhaler, blister, or others) using the image-based medication detection tool. Medication adherence was calculated as the number of doses taken as a percentage of the number scheduled. Interacting with the app ≥30 days was used as the cut-off for higher app use. Results: A total of 114 patients {median 20 [percentile 25 to percentile 75 (P25-P75) 16-36] years, 62% adults} were invited, 107 (94%) installed the app and 83 (73%) completed the 4-month interview. Patients interacted with the app for a median of 18 [3-45] days, translated on a median use rate of 15 [3-38]%. Median inhaler adherence assessed through the app was 34 [4-73]% when considering all scheduled inhalations for the study period. Inhaler adherence assessed was not significantly correlated with self-reported estimates. Median adherence for oral and other medication was 41 [6-83]% and 43 [3-73]%, respectively. Patients with higher app use were slightly older (p = 0.012), more frequently taking medication for other health conditions (p = 0.040), and more frequently prescribed long-acting muscarinic antagonists (LAMA, p = 0.024). After 4 months, Control of Allergic Rhinitis and Asthma Test (CARAT) scores improved (p < 0.001), but no differences between patients interacting with the app for 30 days or less were seen. Conclusions: The InspirerMundi app was feasible to monitor inhaler adherence in patients with persistent asthma. The persistent use of this mHealth technology varies widely. A better understanding of characteristics related to higher app use is still needed before effectiveness studies are undertaken.

The Portuguese Severe Asthma Registry (Registo de Asma Grave Portugal, RAG) was developed by an open collaborative network of asthma specialists. RAG collects data from adults and pediatric severe asthma patients that despite treatment optimization and adequate management of comorbidities require step 4/5 treatment according to GINA recommendations. In this paper, we describe the development and implementation of RAG, its features, and data sharing policies. The contents and structure of RAG were defined in a multistep consensus process. A pilot version was pretested and iteratively improved. The selection of data elements for RAG considered other severe asthma registries, aiming at characterizing the patient's clinical status whilst avoiding overloading the standard workflow of the clinical appointment. Features of RAG include automatic assessment of eligibility, easy data input, and exportable data in natural language that can be pasted directly in patients' electronic health record and security features to enable data sharing (among researchers and with other international databases) without compromising patients' confidentiality. RAG is a national web-based disease registry of severe asthma patients, available at asmagrave.pt. It allows prospective clinical data collection, promotes standardized care and collaborative clinical research, and may contribute to inform evidence-based healthcare policies for severe asthma.

The Portuguese Severe Asthma Registry (Registo de Asma Grave Portugal, RAG) was developed by an open collaborative network of asthma specialists. RAG collects data from adults and pediatric severe asthma patients that despite treatment optimization and adequate management of comorbidities require step 4/5 treatment according to GINA recommendations. In this paper, we describe the development and implementation of RAG, its features, and data sharing policies. The contents and structure of RAG were defined in a multistep consensus process. A pilot version was pretested and iteratively improved. The selection of data elements for RAG considered other severe asthma registries, aiming at characterizing the patient's clinical status whilst avoiding overloading the standard workflow of the clinical appointment. Features of RAG include automatic assessment of eligibility, easy data input, and exportable data in natural language that can be pasted directly in patients' electronic health record and security features to enable data sharing (among researchers and with other international databases) without compromising patients' confidentiality. RAG is a national web-based disease registry of severe asthma patients, available at asmagrave.pt. It allows prospective clinical data collection, promotes standardized care and collaborative clinical research, and may contribute to inform evidence-based healthcare policies for severe asthma.

The Portuguese Severe Asthma Registry (Registo de Asma Grave Portugal, RAG) was developed by an open collaborative network of asthma specialists. RAG collects data from adults and pediatric severe asthma patients that despite treatment optimization and adequate management of comorbidities require step 4/5 treatment according to GINA recommendations. In this paper, we describe the development and implementation of RAG, its features, and data sharing policies. The contents and structure of RAG were defined in a multistep consensus process. A pilot version was pretested and iteratively improved. The selection of data elements for RAG considered other severe asthma registries, aiming at characterizing the patient's clinical status whilst avoiding overloading the standard workflow of the clinical appointment. Features of RAG include automatic assessment of eligibility, easy data input, and exportable data in natural language that can be pasted directly in patients' electronic health record and security features to enable data sharing (among researchers and with other international databases) without compromising patients' confidentiality. RAG is a national web-based disease registry of severe asthma patients, available at asmagrave.pt. It allows prospective clinical data collection, promotes standardized care and collaborative clinical research, and may contribute to inform evidence-based healthcare policies for severe asthma.