The prevalence of severe refractory asthma.

BACKGROUND: Severe asthma is characterized by difficulty to achieve disease control despite high-intensity treatment. However, prevalence figures of severe asthma are lacking, whereas longstanding estimates vary between 5% and 10% of all asthmatic patients. Knowing the exact prevalence of severe refractory asthma as opposed to difficult-to-control asthma is important for clinical decision making, drug development, and reimbursement policies by health authorities. OBJECTIVE: We sought to estimate the prevalence of severe refractory asthma as defined by the Innovative Medicine Initiative consensus. METHODS: Adult patients with a prescription for high-intensity treatment (high-dose inhaled corticosteroids and long-acting ß2-agonists or medium- to high-dose inhaled corticosteroids combined with oral corticosteroids and long-acting ß2-agonists) were extracted from 65 Dutch pharmacy databases, representing 3% of the population (500,500 inhabitants). Questionnaires were sent to 5,002 patients, of which 2,312 were analyzed. The diagnosis of asthma and degree of asthma control were derived from questionnaires to identify patients with difficult-to-control asthma. Inhalation technique was assessed in a random sample of 60 adherent patients (prescription filling, ≥80%). Patients with difficult-to-control asthma, adherence to treatment, and a correct inhalation technique were qualified as having severe refractory asthma. Results were mirrored to the Dutch population. RESULTS: Of asthmatic adults, 3.6% (95% CI, 3.0% to 4.1%) qualified for a diagnosis of severe refractory asthma, representing 10.4 patients per 10,000 inhabitants. CONCLUSION: The prevalence of severe refractory asthma might be lower than estimated by expert opinion. This implies that currently recognized severe asthma subphenotypes could meet the criteria of rare diseases.

Clinical and inflammatory characteristics of the European U-BIOPRED adult severe asthma cohort.

U-BIOPRED is a European Union consortium of 20 academic institutions, 11 pharmaceutical companies and six patient organisations with the objective of improving the understanding of asthma disease mechanisms using a systems biology approach.This cross-sectional assessment of adults with severe asthma, mild/moderate asthma and healthy controls from 11 European countries consisted of analyses of patient-reported outcomes, lung function, blood and airway inflammatory measurements.Patients with severe asthma (nonsmokers, n=311; smokers/ex-smokers, n=110) had more symptoms and exacerbations compared to patients with mild/moderate disease (n=88) (2.5 exacerbations versus 0.4 in the preceding 12 months; p<0.001), with worse quality of life, and higher levels of anxiety and depression. They also had a higher incidence of nasal polyps and gastro-oesophageal reflux with lower lung function. Sputum eosinophil count was higher in severe asthma compared to mild/moderate asthma (median count 2.99% versus 1.05%; p=0.004) despite treatment with higher doses of inhaled and/or oral corticosteroids.Consistent with other severe asthma cohorts, U-BIOPRED is characterised by poor symptom control, increased comorbidity and airway inflammation, despite high levels of treatment. It is well suited to identify asthma phenotypes using the array of "omic" datasets that are at the core of this systems medicine approach.

Chest computed tomography and alveolar-arterial oxygen gradient as rapid tools to diagnose and triage mildly symptomatic COVID-19 pneumonia patients.

BACKGROUND: In the coronavirus disease 2019 (COVID-19) pandemic, rapid clinical triage is crucial to determine which patients need hospitalisation. We hypothesised that chest computed tomography (CT) and alveolar-arterial oxygen tension ratio (A-a) gradient may be useful to triage these patients, since they reflect the severity of the pneumonia-associated ventilation/perfusion abnormalities. METHODS: A retrospective analysis was performed in 235 consecutive patients suspected for COVID-19. The diagnostic protocol included low-dose chest CT and arterial blood gas analysis. In patients with CT-based COVID-19 pneumonia, the association between "need for hospitalisation" and A-a gradient was investigated by a multivariable logistic regression model. The A-a gradient was tested as a predictor for need for hospitalisation using receiver operating characteristic curve analysis and a logistic regression model. RESULTS: 72 out of 235 patients (mean±sd age 55.5±14.6 years, 40% female) screened by chest CT showed evidence for COVID-19 pneumonia. In these patients, A-a gradient was shown to be a predictor of need for hospitalisation, with an optimal decision level (cut-off) of 36.4 mmHg (95% CI 0.70-0.91, p<0.001). The A-a gradient was shown to be independently associated with need for hospitalisation (OR 1.97 (95% CI 1.23-3.15), p=0.005; A-a gradient per 10 points) from CT severity score (OR 1.13 (95% CI 0.94-1.36), p=0.191), National Early Warning Score (OR 1.19 (95% CI 0.91-1.57), p=0.321) or peripheral oxygen saturation (OR 0.88 (95% CI 0.68-1.14), p=0.345). CONCLUSION: Low-dose chest CT and the A-a gradient may serve as rapid and accurate tools to diagnose COVID-19 pneumonia and to select mildly symptomatic patients in need for hospitalisation.

Peripheral infiltration of remdesivir in 3 patients with COVID-19: Case series and discussion.

PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic resulted in accelerated market access to remdesivir worldwide. Therefore, data about complications experienced during use of the drug are limited. This is the first published case series (1 case report exists) to describe remdesivir infiltration in 3 patients with COVID-19. SUMMARY: In the first case, a 91-year-old woman experienced remdesivir infiltration resulting in edema, hematoma at the area of infiltration; on palpation, the affected area felt cooler than the surrounding areas. Swelling was still present after 6 weeks. In the second case, remdesivir infiltration occurred in a 72-year-old male, resulting in edema, hematoma, and pain at the area of infiltration. The hematoma lasted for 7 days. The third case concerned a 67-year-old woman, in whom remdesivir infiltration led to edema and a small hematoma. The hematoma regressed to a negligible size within 3 days. However, a week after infiltration, redness had reappeared. In 2 cases, the patient was immediately treated with hyaluronidase injections, but no specific treatments were provided in the other case. CONCLUSION: Based on the product information provided by remdesivir's manufacturer, we believe symptoms and signs observed in the 3 cases may have resulted from the low pH (~4) of the nonbuffered remdesivir solution, although the patients were not formally assessed for caustic injury. Previous experience with other noncytotoxic medications suggests that infusion-specific factors (eg, volume of leaked fluid) and patient-specific factors (eg, advanced age) may have a role in the outcome of remdesivir infiltration. The possibility of symptoms caused by cyclodextrins in the formulation or by intrinsic toxicity of remdesivir warrants exploration.

Developing and emerging clinical asthma phenotypes.

For more than a century, clinicians have attempted to subdivide asthma into different phenotypes based on triggers that cause asthma attacks, the course of the disease, or the prognosis. The first phenotypes that were described included allergic asthma, intrinsic or nonallergic asthma, infectious asthma, and aspirin-exacerbated asthma. These phenotypes are being reviewed elsewhere in this issue of the journal. The present article focuses on developing and emerging clinical asthma phenotypes. First, asthma phenotypes that are associated with environmental exposures (occupational agents, cigarette smoke, air pollution, cold dry air); second, asthma phenotypes that are associated with specific symptoms or clinical characteristics (cough, obesity, adult onset of disease); and third, asthma phenotypes that are based on biomarkers. This latter approach is the most promising because it attempts to identify asthma phenotypes with different underlying mechanisms so that therapies can be better targeted toward disease-specific features and disease outcomes can be improved.