Impact of COVID-19 on people with asthma: a mixed methods analysis from a UK wide survey

IntroductionThe impact of acute COVID-19 on people with asthma appears complex, being moderated by multiple interacting disease-specific, demographic and environmental factors. Research regarding longer-term effects in this group is limited. We aimed to assess impacts of COVID-19 and predictors of persistent symptoms, in people with asthma.MethodsUsing data from an online UK-wide survey of 4500 people with asthma (median age 50–59 years, 81% female), conducted in October 2020, we undertook a mixed methods analysis of the characteristics and experience of those reporting having had COVID-19.ResultsThe COVID-19 group (n=471, 10.5%) reported increased inhaler use and worse asthma management, compared with those not reporting COVID-19, but did not differ by gender, ethnicity or household income. Among the COVID-19 group, 56.1% reported having long COVID, 20.2% were ‘unsure’. Those with long COVID were more likely than those without long COVID to describe: their breathing as worse or much worse after their initial illness (73.7% vs 34.8%, p<0.001), increased inhaler use (67.8% vs 34.8%, p<0.001) and worse or much worse asthma management (59.6% vs 25.6%, p<0.001). Having long COVID was not associated with age, gender, ethnicity, UK nation or household income.Analysis of free text survey responses identified three key themes: (1) variable COVID-19 severity, duration and recovery; (2) symptom overlap and interaction between COVID-19 and asthma; (3) barriers to accessing healthcare.ConclusionsPersisting symptoms are common in people with asthma following COVID-19. Measures are needed to ensure appropriate healthcare access including clinical evaluation and investigation, to distinguish between COVID-19 symptoms and asthma.

Reducing carbon footprint of inhalers: analysis of climate and clinical implications of different scenarios in five European countries

BackgroundInhaled therapies are key components of asthma and chronic obstructive pulmonary disease (COPD) treatments. Although the use of pressurised metered-dose inhalers (pMDIs) accounts for <0.1% of global greenhouse gas emissions, their contribution to global warming has been debated and efforts are underway to reduce the carbon footprint of pMDIs. Our aim was to establish the extent to which different scenarios led to reductions in greenhouse gas emissions associated with inhaler use, and their clinical implications.MethodsWe conducted a series of scenario analyses using asthma and COPD inhaler usage data from 2019 to model carbon dioxide equivalent (CO2e) emissions reductions over a 10-year period (2020–2030) in the UK, Italy, France, Germany and Spain: switching propellant-driven pMDIs for propellant-free dry-powder inhalers (DPIs)/soft mist inhalers (SMIs); transitioning to low global warming potential (GWP) propellant (hydrofluoroalkane (HFA)-152a) pMDIs; reducing short-acting β2-agonist (SABA) use; and inhaler recycling.ResultsTransition to low-GWP pMDIs and forced switching to DPI/SMIs (excluding SABA inhalers) would reduce annual CO2e emissions by 68%–84% and 64%–71%, respectively, but with different clinical implications. Emission reductions would be greatest (82%–89%) with transition of both maintenance and SABA inhalers to low-GWP propellant. Only minimising SABA inhaler use would reduce CO2e emissions by 17%–48%. Although significant greenhouse gas emission reductions would be achieved with high rates of end-of-life recycling (81%–87% of the inhalers), transition to a low-GWP propellant would still result in greater reductions.ConclusionsWhile the absolute contribution of pMDIs to global warming is very small, substantial reductions in the carbon footprint of pMDIs can be achieved with transition to low-GWP propellant (HFA-152a) inhalers. This approach outperforms the substitution of pMDIs with DPI/SMIs while preserving patient access and choice, which are essential for optimising treatment and outcomes. These findings require confirmation in independent studies.

Comparison of the airway microbiota in children with chronic suppurative lung disease

RationaleThe airway microbiota is important in chronic suppurative lung diseases, such as primary ciliary dyskinesia (PCD) and cystic fibrosis (CF). This comparison has not previously been described but is important because difference between the two diseases may relate to the differing prognoses and lead to pathological insights and potentially, new treatments.ObjectivesTo compare the longitudinal development of the airway microbiota in children with PCD to that of CF and relate this to age and clinical status.MethodsSixty-two age-matched children (age range 0.5–17 years) with PCD or CF (n=31 in each group) were recruited prospectively and followed for 1.1 years. Throat swabs or sputum as well as clinical information were collected at routine clinical appointments. 16S rRNA gene sequencing was performed.Measurements and main resultsThe microbiota was highly individual and more diverse in PCD and differed in community composition when compared with CF. While Streptococcus was the most abundant genus in both conditions, Pseudomonas was more abundant in CF with Haemophilus more abundant in PCD (Padj=0.0005). In PCD only, an inverse relationship was seen in the relative abundance of Streptococcus and Haemophilus with age.ConclusionsBacterial community composition differs between children with PCD and those with CF. Pseudomonas is more prevalent in CF and Haemophilus in PCD, at least until infection with Pseudomonas supervenes. Interactions between organisms, particularly members of Haemophilus, Streptococcus and Pseudomonas genera appear important. Study of the interactions between these organisms may lead to new therapies or risk stratification.

Efficacy and safety of as-needed albuterol/budesonide versus albuterol in adults and children aged ≥4 years with moderate-to-severe asthma: rationale and design of the randomised, double-blind, active-controlled MANDALA study

IntroductionUncontrolled asthma is associated with substantial morbidity. While fast-acting bronchodilators provide quick relief from asthma symptoms, their use as rescue fails to address the underlying inflammation. Combining a short-acting beta2-agonist, such as albuterol (salbutamol), with an inhaled corticosteroid, such as budesonide, in a single inhaler as rescue therapy could help control both bronchoconstriction and inflammation, and reduce the risk of asthma exacerbations.Methods and analysisThe Phase 3 MANDALA study was designed to determine the efficacy of albuterol in combination with budesonide (albuterol/budesonide 180/160 µg or 180/80 µg, two actuations of 90/80 µg or 90/40 µg, respectively) versus albuterol (180 µg, two actuations of 90 µg) as rescue therapy in adult, adolescent and paediatric patients with moderate-to-severe asthma. This event-driven study enrolled symptomatic patients (3000 adults/adolescents and 100 children aged 4–11 years) who experienced ≥1 severe asthma exacerbation in the previous year and were receiving maintenance therapy for ≥3 months prior to study entry. The primary efficacy endpoint was time-to-first severe asthma exacerbation.Ethics and disseminationThe study was conducted in accordance with the ethical principles that have their origin in the Declaration of Helsinki, and that are consistent with International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use and Good Clinical Practice and the applicable regulatory requirements.Trial registrationNCT03769090.

Implications of using the GLI-2012, GOLD and Australian COPD-X recommendations in assessing the severity of airflow limitation on spirometry among an Indigenous population with COPD: an Indigenous Australians perspective study

BackgroundAssessment of airflow limitation (AFL) is crucial in the clinical evaluation of patients with chronic obstructive pulmonary disease (COPD). However, in the absence of normative reference values among adult Australian Indigenous population, the implications of utilising the Global Lung Function Initiative (GLI-2012), Global Initiative for Chronic Obstructive Lung Disease (GOLD) and the Australian concise COPD-X recommended severity classifications is not known. Moreover, spirometry values (forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1)) are observed to be 20%–30% lower in an apparently healthy Indigenous population in comparison to Caucasian counterparts.MethodsAdult Indigenous patients diagnosed to have COPD on spirometry (postbronchodilator (BD) FEV1/FVC <0.7 ((GOLD, (COPD-X)) and ≤lower limit of normal (others/mixed reference equations) for GLI-2012) were assessed for AFL severity classifications on Post-BD FEV1 values (mild, moderate, severe, very severe) as per the recommended classifications.ResultsFrom a total of 742 unique patient records of Indigenous Australians, 253 were identified to have COPD via GOLD/COPD-X criteria (n=238) or GLI-2012 criteria (n=238) with significant agreeance between criteria (96%, κ=0.901). Of these, the majority were classified as having moderate or severe/very-severe AFL with significant variability across classification criteria (COPD-X (40%–43%), GOLD (33%–65%), GLI-2012 (18%–75%)). The FVC and FEV1 values also varied significantly between classification criterion (COPD-X/GOLD/GLI-2012) within the same AFL category, with COPD-X ‘moderate’ AFL almost matching ‘severe’ AFL categorisation by GOLD or GLI-2012.ConclusionsHealth professionals caring for Indigenous patients with COPD should be aware of the clinical implications and consequences of utilising various recommended AFL classifications in the absence of validated spirometry reference norms among adult Indigenous patients.

Long-term outcomes following severe COVID-19 infection: a propensity matched cohort study

BackgroundThere are limited data describing the long-term outcomes of severe COVID-19. We aimed to evaluate the long-term psychosocial and physical consequences of severe COVID-19 for patients.MethodsWe conducted a multicentre observational cohort study; between 3 and 7 months posthospital discharge, patients who had been admitted to critical care due to severe COVID-19 were invited to an established recovery service. Standardised questionnaires concerning emotional, physical and social recovery, including information on employment, were completed by patients. Using propensity score matching, we explored outcomes between patients admitted to critical care with and without COVID-19, using data from the same recovery programme.ResultsBetween July 2020 and December 2020, 93 patients who had been admitted to critical with COVID-19 participated. Emotional dysfunction was common: 46.2% of patients had symptoms of anxiety and 34.4% symptoms of depression. At follow-up 53.7% of previously employed patients had returned to employment; there was a significant difference in return to employment across the socio-economic gradient, with lower numbers of patients from the most deprived areas returning to employment (p=0.03). 91 (97.8%) COVID-19 patients were matched with 91 non-COVID-19 patients. There were no significant differences in any measured outcomes between the two cohorts.InterpretationEmotional and social problems are common in survivors of severe COVID-19 infection. Coordinated rehabilitation is required to ensure patients make an optimal recovery.

Predicting death from COVID-19 using pre-existing conditions: implications for vaccination triage

IntroductionGlobal shortages in the supply of SARS-CoV-2 vaccines have resulted in campaigns to first inoculate individuals at highest risk for death from COVID-19. Here, we develop a predictive model of COVID-19-related death using longitudinal clinical data from patients in metropolitan Detroit.MethodsAll individuals included in the analysis had a laboratory-confirmed SARS-CoV-2 infection. Thirty-six pre-existing conditions with a false discovery rate p<0.05 were combined with other demographic variables to develop a parsimonious prediction model using least absolute shrinkage and selection operator regression. The model was then prospectively validated in a separate set of individuals with confirmed COVID-19.ResultsThe study population consisted of 15 502 individuals with laboratory-confirmed SARS-CoV-2. The main prediction model was developed using data from 11 635 individuals with 709 reported deaths (case fatality ratio 6.1%). The final prediction model consisted of 14 variables with 11 comorbidities. This model was then prospectively assessed among the remaining 3867 individuals (185 deaths; case fatality ratio 4.8%). When compared with using an age threshold of 65 years, the 14-variable model detected 6% more of the individuals who would die from COVID-19. However, below age 45 years and its risk equivalent, there was no benefit to using the prediction model over age alone.DiscussionUsing a prediction model, such as the one described here, may help identify individuals who would most benefit from COVID-19 inoculation, and thereby may produce more dramatic initial drops in deaths through targeted vaccination.

Health economic analysis for the ‘CURE Project’ pilot: a hospital-based tobacco dependency treatment service in Greater Manchester

IntroductionTreating tobacco dependency in patients admitted to acute care National Health Service (NHS) trusts is a key priority in the NHS 10-year plan. This paper sets out the results of a health economic analysis for ‘The CURE Project’ pilot; a new hospital-based tobacco dependency service.MethodsA health economic analysis to understand the costs of the intervention (both for the inpatient service and postdischarge costs), the return on investment (ROI) and the cost per quality-adjusted life year (QALY) of the CURE Project pilot in Greater Manchester. ROI and cost per QALY were calculated using the European Study on Quantifying Utility of Investment in Protection from Tobacco and Greater Manchester Cost Benefit Analysis Tools.ResultsThe total intervention costs for the inpatient service in the 6-month CURE pilot were £96 224 with a cost per patient who smokes of £40.21. The estimated average cost per patient who was discharged on pharmacotherapy was £97.40. The cost per quit (22% quit rate for smokers at 12 weeks post discharge) was £475. The gross financial ROI ratio was £2.12 return per £1 invested with a payback period of 4 years. The cashable financial ROI ratio was £1.06 return per £1 invested with a payback period of 10 years. The public value ROI ratio was £30.49 per £1 invested. The cost per QALY for this programme was £487.DiscussionThe CURE Project pilot has been shown to be exceptionally cost-effective with highly significant ROI in this health economic analysis. This supports the NHS priority to embed high-quality tobacco addiction treatment services in acute NHS trusts, and the CURE Project provides a blueprint and framework to achieve this.

Ten-year prediction model for post-bronchodilator airflow obstruction and early detection of COPD: development and validation in two middle-aged population-based cohorts

BackgroundClassifying individuals at high chronic obstructive pulmonary disease (COPD)-risk creates opportunities for early COPD detection and active intervention.ObjectiveTo develop and validate a statistical model to predict 10-year probabilities of COPD defined by post-bronchodilator airflow obstruction (post-BD-AO; forced expiratory volume in 1 s/forced vital capacity<5th percentile).SettingGeneral Caucasian populations from Australia and Europe, 10 and 27 centres, respectively.ParticipantsFor the development cohort, questionnaire data on respiratory symptoms, smoking, asthma, occupation and participant sex were from the Tasmanian Longitudinal Health Study (TAHS) participants at age 41–45 years (n=5729) who did not have self-reported COPD/emphysema at baseline but had post-BD spirometry and smoking status at age 51–55 years (n=2407). The validation cohort comprised participants from the European Community Respiratory Health Survey (ECRHS) II and III (n=5970), restricted to those of age 40–49 and 50–59 with complete questionnaire and spirometry/smoking data, respectively (n=1407).Statistical methodRisk-prediction models were developed using randomForest then externally validated.ResultsArea under the receiver operating characteristic curve (AUCROC) of the final model was 80.8% (95% CI 80.0% to 81.6%), sensitivity 80.3% (77.7% to 82.9%), specificity 69.1% (68.7% to 69.5%), positive predictive value (PPV) 11.1% (10.3% to 11.9%) and negative predictive value (NPV) 98.7% (98.5% to 98.9%). The external validation was fair (AUCROC 75.6%), with the PPV increasing to 17.9% and NPV still 97.5% for adults aged 40–49 years with ≥1 respiratory symptom. To illustrate the model output using hypothetical case scenarios, a 43-year-old female unskilled worker who smoked 20 cigarettes/day for 30 years had a 27% predicted probability for post-BD-AO at age 53 if she continued to smoke. The predicted risk was 42% if she had coexistent active asthma, but only 4.5% if she had quit after age 43.ConclusionThis novel and validated risk-prediction model could identify adults aged in their 40s at high 10-year COPD-risk in the general population with potential to facilitate active monitoring/intervention in predicted ‘COPD cases’ at a much earlier age.