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Background: Respiratory syncytial virus (RSV) causes substantial winter pressure on adult services. In the UK, RSV vaccination currently targets adults aged ≥75 years and care home residents; it remains uncertain whether this age criterion alone meaningfully discriminates risk of poor outcome among adults hospitalised with RSV.

Methods: We pooled three UK hospital cohorts (one prospective, two retrospective) of adults admitted with acute respiratory infection (ARI) and PCR-confirmed RSV. The primary outcome was intensive care unit/high dependency unit (ICU/HDU) admission or all-cause mortality within 60 days. Prespecified predictors (age, sex and comorbidities) entered a least absolute shrinkage and selection operator (LASSO) penalised logistic regression; selected variables were refitted using standard logistic regression. Discrimination, calibration and decision-analytic performance were assessed using 1000-bootstrap internal validation and decision-curve analysis.

Results: Among 334 adults, 37 (11.1%) experienced the primary outcome. An age-only rule mirroring current UK vaccine age-eligibility (≥75 years) demonstrated only modest discrimination (optimism-adjusted area under the receiver operating characteristic curve (AUC) 0.58, 95% CI 0.48 to 0.65) and a compressed distribution of predicted risks. A four-predictor model-including age, COPD, active/previous cancer and dementia-achieved higher discrimination AUC (0.77 (0.69 to 0.85)), a wider spread of predicted risks and the greatest net benefit across clinically plausible escalation thresholds (5-20%).

Conclusions: In adults hospitalised with RSV-associated ARI, simple age-based heuristics-including the UK ≥75-year threshold-showed only modest ability to discriminate risk of ICU/HDU admission/60-day mortality once hospitalised. Comorbidity-inclusive approaches may provide more informative hospital-level risk stratification and warrant evaluation in future RSV vaccine-effectiveness and outcome studies. Any application requires external validation, more systematic RSV testing and comparison with physiology-based scores in larger, vaccinated cohorts.

Background: Obstructive sleep apnoea (OSA) and narcolepsy are estimated to affect approximately 4.8% and 0.047% of the UK population, respectively. We do not know how many people have been diagnosed or how this varies over time and by demographic factors.

Methods: We, therefore, conducted a historical population-based descriptive study estimating prevalence and incidence of diagnosed OSA and narcolepsy in England from 2000 to 2019 stratified by demographic factors, and compared estimates to Scotland, Wales and Northern Ireland. Data were from Clinical Practice Research Datalink (CPRD) primary care records linked to Hospital Episode Statistics (HES) admissions. The study population included people with ≥90 days follow-up between 1 January 2000 and 31 December 2019, no prior record of primary or central sleep apnoea, and aged ≥18 years (OSA only). Diagnoses were defined using the first coded record for each condition in CPRD or HES data. Annual prevalence was estimated at mid-year and directly age/sex-standardised to the national population. Incidence was estimated by dividing new diagnoses by total person-time at risk.

Results: In England, 2019 adult standardised diagnosed OSA prevalence was 1.40% (95% CI 1.40% to 1.41%) representing approximately 622 528 people; standardised narcolepsy prevalence was 0.020% (95% CI 0.019% to 0.021%) representing approximately 11 307 people. Despite increases over time, diagnosed incidence and prevalence remained substantially lower than published estimates of symptomatic frequency. Rates varied by age, sex, ethnicity and UK nation for both conditions, and urban-rural living, area-based deprivation and practice size for OSA.

Conclusion: Our results call for high-quality research to drive initiatives that increase diagnosis rates and address variation.

Background: Spirometry is a measure of lung function used to make clinical decisions regarding the diagnosis and management of respiratory conditions. The goal of spirometry interpretation is to relate impairments in mechanical lung function to pulmonary pathology. In many circumstances, interpretation of measured spirometric values relies on comparisons with a 'healthy' reference population. Such inferences assume that spirometric values in healthy populations follow a Gaussian distribution with impaired values concentrated in the lower tail.

Methods: We hypothesised that impairments in lung function mechanics generate spirometric values that follow a non-Gaussian distribution as predicted by extreme value analysis. We used a Gumbel distribution to model lung function impairment. We compared the Gaussian healthy distribution to the Gumbel impaired distribution to calculate the relative probability for impaired versus healthy values. The relative probability provides an objective measure of the likelihood that a particular spirometric value is within the healthy or impaired distribution.

Results: The potential usefulness of the relative probability was demonstrated in simulated cases, providing an objective delineation of the zone of uncertainty in the transition from normal to impaired lung function.

Conclusions: Considering the spirometric measures from people with lung function impairment as a separate distribution from people with healthy lung function provides a more analytic assessment of impairment. Applying extreme value analysis, the relative probability of a spirometric measurement being impaired versus healthy and a more precise definition of the zone of uncertainty potentially provides more objective discrimination of the intersection between the healthy and impaired lung function ranges.

Objective: Despite extensive research on the detrimental effects of air pollution on respiratory diseases like asthma and chronic obstructive pulmonary disease, the impact on people with cystic fibrosis (CF) remains understudied. Our study aimed to quantify the association between air pollution exposure and lung function decline in people with CF in London, UK.

Methods: Using 10 years (2008-2017) of UK Cystic Fibrosis Registry data, we conducted a longitudinal cohort study to evaluate the association between air pollution and the rate of decline in percent predicted forced expiratory volume in 1 second (ppFEV₁) among people with CF. Residential postcode exposure was based on high-resolution models of particulate matter with a diameter of less than 2.5 μm (PM_2.5) and nitrogen dioxide (NO₂) from the London Air Pollution Toolkit. We estimated the temporal decline in ppFEV₁ in high, medium and low exposure subgroups based on air pollutant concentration tertiles using linear mixed models with random intercepts.

Results: We used 3333 ppFEV₁ measurements of 393 people with CF (122 children, 271 adults). Over 40% of these people with CF lived in postcodes falling into the most deprived national quintile. For PM_2.5, the adjusted mean ppFEV₁ declined by 13.3% (95% CI -24.1% to -4.0%) over the study period in the high-exposure tertile compared with 8.5% (95% CI -11.7% to -6.4%) in the low-exposure tertile. Differences between the exposure groups were less consistent for NO₂. Children and people with CF with severe genotypes seemed particularly vulnerable.

Conclusions: This study provides novel evidence of the detrimental impact of air pollution on lung function in people with CF. Our findings highlight the importance of addressing air pollution as a modifiable risk factor to improve long-term outcomes of people with CF, and the need for national studies of the impact of environmental factors on CF in the UK.