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 The phenotypic nature of multimorbidity in severe asthma is poorly understood. Our aims in this study were to define multimorbidity phenotypes and their characteristics in severe asthma across Europe by identifying and characterising co-aggregation of comorbidities. Methods Cross-sectional patient data were analysed from the pan-European Severe Heterogenous Asthma Research Collaboration: Patient Centred (SHARP) Central database of national severe asthma registries. Patients were grouped by four European regions (North, South, East, and West). Hierarchical clustering of comorbidities was applied to characterise the correlation structure of the ten commonest comorbidities within these geographical regions. Subsequent multimorbidity phenotypes (MMP) and their clinical features were then defined. Findings Data were available for 2690 severe asthma patients and 23 comorbidities from 11 countries. Three comorbidity clusters were consistently seen across the four European regions: 1) osteoporosis plus steroid-induced weight gain, 2) eczema plus rhinitis, and 3) chronic sinusitis plus nasal polyps. Four further comorbidities (obesity, bronchiectasis, gastro-oesophageal reflux disease, psychological factors) showed variable clustering. Multimorbidity was ubiquitous. Patients were assigned multimorbidity phenotypes (MMP) according to comorbidity cluster alignment. MMP sn (sinonasal-associated) and MMP u (no specific cluster alignment) were commonest. MMP ster (steroid-associated multimorbidity) had highest maintenance oral steroid (m-OCS) use, and Body Mass Index, plus worst lung function, asthma control, and asthma exacerbation frequency. MMP max (maximal multimorbidity) showed high prevalence of variably assigned comorbidities, higher m-OCS and biologic treatment needs. Interpretation Multimorbidity is common in severe asthma and can be classified into replicable novel phenotypes with characteristic clinical traits and outcomes. Recognising these phenotypes can guide better care of the ‘whole patient’ with severe asthma. Future clinical guidance should promote such understanding in order to support delivery of more effective personalised asthma care. Funding European Respiratory Society, pharmaceutical industry partners (Sanofi, TEVA, Novartis, GlaxoSmithKline, Chiesi).

Asthma is one of the commonest noncommunicable diseases worldwide. Poor clinical outcomes have been reported in asthma amongst ethnic minority groups (EMGs) and reasons are likely to be multifactorial. There is a suggestion that underlying disease may behave differently amongst EMGs, alongside other factors including deprivation, cultural, religious, social, literacy, patient beliefs, healthcare access, treatment adherence, alongside greater burden of multimorbidity. Multimorbidity (presence of ≥ 2 long-term health conditions) in asthma is increasingly known to contribute to greater asthma burden, with differences in multimorbidity burden and patterns seen across ethnicities with a tight association with deprivation. Earlier onset of multimorbidity with relatively reduced survival has been reported amongst EMG patients, particularly those from a deprived background compared to White patients. Data regarding asthma, multimorbidity and ethnicity are scant, but emerging data suggest that multimorbidity is heterogenous, and that ethnic background is associated with variations in asthma outcomes and multimorbidity phenotypes. What is currently lacking is population-based research with a joined-up interrogation of primary care and secondary care databases to determine the prevalence and patterns of T2 and non T2 multimorbidity in asthma amongst EMGs, and analysis of patterns of associations and link to socio-demographic variables and clinical outcomes. Deeper insight into views of EMG patients and their carers regarding lived experiences of asthma and multimorbidity management, as well as those of healthcare professionals is needed, to allow development of culturally tailored resources. These studies are likely to shape a holistic culturally tailored multidimensional and an equitable approach to management of asthma with multimorbidity amongst EMGs.

Abstract Background Cluster modelling has demonstrated asthma heterogeneity across disease severities, but contemporary data integrating difficult-to-treat and mild asthma with systematic assessment of comorbidity-focused treatable traits remain limited. Objective To identify and characterise difficult-to-treat and mild asthma clusters in two UK cohorts: Wessex AsThma CoHort of Difficult Asthma (WATCH-DA) and a mild-asthma cohort from the Epigenetics of Severe Asthma study (EOSA-MA). Methods Separate K-means clustering was applied to WATCH-DA ( n = 498; 11 variables) and EOSA-MA ( n = 67; 12 variables). Post-hoc comparisons evaluated demographic, inflammatory, physiological, comorbidity and patient-reported outcome profiles. Results Six difficult-to-treat and two mild asthma clusters were identified respectively, all Type-2 (T2)-predominant. Difficult-to-treat asthma clusters differed by sex, age of asthma-onset, body mass index (BMI) and comorbidities. Two clinically controlled clusters, cluster-1 (Early-onset atopic controlled) and cluster-4 (Late-adult-onset non-atopic controlled), showed distinct comorbidity patterns despite lower overall morbidity. Three severe, exacerbation-prone, adult-onset, female predominant difficult-to-treat clusters (Adult-onset eosinophilic exacerbator [cluster-2], Young-adult-onset high-risk exacerbator [cluster-5], Adult-onset obese multimorbid symptomatic [cluster-6]) varied by blood eosinophil counts (BEC), spirometry, BMI, treatment needs, comorbidities, and quality of life. An Adolescent-onset obese atopic obstructive (cluster-3) showed fewer exacerbations but high BEC with worst spirometry and poor asthma control. In mild asthma, cluster-1 (Early-onset atopic mild) showed worse pathophysiological indices and asthma control than cluster-2 (Adolescent-onset mild) but similarly high comorbidity prevalence. Conclusion Characterisation of difficult-to-treat and mild asthma clusters reveals diverse associated clinical traits and outcomes across the asthma severity spectrum. Recognition of these clusters and their associated comorbidities should prompt early personalised asthma management to address both airway-centric and comorbid disease aspects.

COPD remains a leading cause of morbidity and mortality, with outcomes stagnating relative to other long-term conditions. Current diagnostic pathways rely on spirometry, which detects airflow obstruction only after irreversible small airway and parenchymal damage has accrued, whereas pathogenic processes begin decades earlier. This review examines how understanding early pathogenic processes could inform alternative approaches to diagnosis and treatment. We highlight the contribution of developmental and environmental exposures, genetic susceptibility and epigenetic modification to disease initiation. We outline how these convergent mechanisms drive structural and functional abnormalities undetectable by conventional diagnostics but measurable with novel techniques. Advanced imaging-parametric response mapping, hyperpolarised gas magnetic resonance imaging and computed tomography-based vascular metrics-can detect emphysema, small airways disease and vascular pruning before spirometric thresholds are reached. Physiological tools including forced oscillation techniques and capnography show promise for early detection in primary care and may be scalable, affordable alternatives to spirometry. Biofluid-based platforms, including exhaled breath analysis, extracellular matrix neo-epitopes and blood-based inflammatory signatures, offer noninvasive phenotyping and risk stratification, though require validation and pathway integration. We argue for a shift from a spirometry-centric model to a multidimensional diagnostic framework integrating imaging, molecular, physiological and biomarker data. Recent longitudinal evidence, including diagnostic schemas combining imaging with symptom burden, indicates that such approaches identify high-risk individuals missed by spirometry alone. Proactive COPD detection in its earliest stages is therefore an essential step to altering disease trajectory and improving patient outcomes, and it is time our community looks beyond spirometry to deliver this.

Introduction:Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide and currently lacks effective disease-modifying therapies. Extracellular vesicles (EVs) are key mediators of intercellular communication and transport biologically active cargo, including microRNAs (miRNAs). We previously identified 8 differentially expressed EV miRNA (miR-223-3p, miR-2110, miR-182-5p, miR-200b-5p, miR-625-3p, miR-204-5p, miR-138-5p and miR-338-3p) that were differentially expressed in individuals with COPD compared with healthy volunteer ex-smoker controls (HV-ES). This study aimed to identify miRNA-mRNA interactions in diseased lung epithelium that may contribute to COPD pathogenesis. Methods:Gene expression was quantified by RNA sequencing of epithelial brushings obtained from 24 subjects with COPD and 20 HV-ES. In silico analyses were performed to identify target genes of the previously identified EV-derived miRNAs isolated from the same individuals. MiRNA-mRNA interactions were examined using negative correlation analysis and network-based approaches, and enrichment of biological processes was assessed using Cytoscape. Associations between computer tomography (CT) disease probability measures (DPM) and gene expression were assessed using Spearman correlation across the pooled cohort. Results:A total of 191 genes were differentially expressed in epithelial brushings from subjects with COPD compared with HV-ES. In silico analysis identified 121 miRNA-mRNA interactions involving these genes and the EV-associated miRNAs. Network analysis revealed miR-182-5p as a central hub, targeting multiple highly differentially expressed genes (DEGs). Expression of these DEGs correlated with CT DPM of emphysema and small airways disease (SAD). Exploratory pathway analyses suggested potential trends toward coordinated network regulation involving metabolic and immune -related processes; however, no biological processes remained significant after correction for multiple testing. Discussion:These findings highlight a potential role for EV-derived miRNA-mRNA regulatory networks in COPD pathogenesis, with miR-182-5p emerging as a putative regulator within this network. While exploratory analyses suggested possible associations with metabolic and immune-related pathways, these did not withstand multiple testing correction and should therefore be interpreted as hypothesis-generating. These findings support further mechanistic investigation of EV-derived miRNA-mRNA regulatory networks in COPD and may help inform future translational studies exploring their biological relevance.

BACKGROUND:Self-reported asthma control and lung function are key to evaluating asthma status, but they are not always concordant in patients with difficult-to-treat (difficult) asthma, indicating potential heterogeneity in patients' asthma perception. OBJECTIVE:To classify asthma perception phenotypes using both asthma control reported by patients and lung function, and to examine their associations with clinical characteristics in difficult asthma. METHODS:We classified 185 patients with difficult asthma who attended secondary care asthma clinics into four asthma perception phenotypes based on Asthma Control Questionnaire scores (six-item) (impaired cutoff of ≥1.5) and postbronchodilator FEV1 expressed as a percentage of predicted values (impaired cutoff of <80% predicted), measured via spirometry. We performed bivariate analyses and multinomial logistic regression analyses to examine the associations of asthma perception phenotypes with clinical characteristics. RESULTS:Only about 55% of patients showed concordant perceived asthma control and lung function. Regardless of lung function, patients with perceived poorer asthma control reported lower quality of life, more depressive symptoms, and more OCS courses. The most-impaired asthma perception phenotype (characterized by both impaired perceived asthma control and lung function) was associated with male sex, low medication adherence, and comorbidity diagnoses of chronic obstructive pulmonary disease, obesity, and depression. CONCLUSIONS:We identified concordant and discordant asthma perception phenotypes in difficult asthma and highlighted their clinical relevance. A holistic approach to identifying and addressing low medication adherence, comorbid chronic obstructive pulmonary disease, obesity, and depression may provide key targets in clinical practice to improve difficult asthma outcomes, such as asthma control, lung function, and psychosocial functioning.

Extracellular matrix (ECM) dysregulation is a key process in the pathology of COPD. However, an inability to characterise ECM remodelling in vivo has limited our understanding of its relationship with functional decline and disease mechanisms. We aimed to quantify in vivo ECM remodelling using probe-based confocal laser endomicroscopy (pCLE) and determine associations with physiological, radiological, histological, and serological markers of COPD. 16 patients with COPD and 20 controls underwent pulmonary function testing, CT imaging, bronchoscopy, and pCLE. Alveolar morphometrics and elastin linearity scores (ELS) were quantified using a novel automated algorithm. Bronchial biopsies were analysed for elastin and collagen content. Serum biomarkers of elastin and collagen turnover were measured in a combined cohort of 54 COPD patients and 61 controls. Compared with never-smoking controls, current smokers without airflow obstruction demonstrated larger alveolar dimensions including increased alveolar opening area (AOA) (46,282 ± 16,805 vs. 33,549 ± 2,595 μm², p = 0.003). Alveolar dimensions were further increased in COPD, with larger AOA (56,468 ± 11,079 vs. 46,282 ± 16,805 μm², p < 0.001) compared with all controls. COPD was also associated with greater elastin fibre disorganisation (ELS 54.9 ± 6.0 vs. 47.5 ± 10.7, p = 0.032). Across the cohort, ELS correlated with airflow obstruction and surrogate markers of small airway disease. Airway collagen content was increased in COPD and correlated with ELS (r = 0.665, p = 0.005). COPD was associated with higher circulating elastin and collagen degradation biomarkers, including ELP-3, C1M, C6M, and EL-CG (all p < 0.05), which correlated with pCLE morphometrics. Using an innovative lung imaging technique, we provide the first objective quantification of in vivo airway elastic fibre disorganisation and demonstrate quantifiable lung microstructural changes that may precede abnormalities detected by established techniques. These quantifiable signals relate to biomarkers of lung ECM turnover, offering a new platform for early disease detection and mechanistic understanding of COPD.

Background Cluster modelling has demonstrated the heterogeneity of asthma but has previously focused mainly on severe disease with limited assessment of mild disease or treatable traits like comorbidities. Objective To identify and characterise difficult-to-treat and mild asthma clusters in two UK cohorts: Wessex AsThma CoHort of Difficult Asthma (WATCH-DA) and a mild-asthma cohort from the Epigenetics of Severe Asthma study (EOSA-MA). Methods Separate K-means clustering was applied to WATCH-DA (n = 498; 11 variables) and EOSA-MA (n = 67; 12 variables). Post-hoc comparisons evaluated demographic, inflammatory, physiological, comorbidity and patient-reported outcome profiles. Results Six difficult-to-treat and two mild asthma clusters were identified respectively, all Type-2 (T2)-predominant. Difficult-to-treat asthma clusters differed by sex, age of asthma-onset, body mass index (BMI) and comorbidities. Two clinically-controlled clusters, cluster-1 (early-onset–clinically-controlled–atopic disease) and cluster-4 (adult-onset–clinically-controlled–least-atopic disease), showed distinct comorbidity patterns despite lower overall morbidity. Three severe, exacerbation-prone, adult-onset, female predominant difficult-to-treat clusters (cluster-2, cluster-5, cluster-6) varied by blood eosinophil counts (BEC), spirometry, BMI, treatment needs, comorbidities, and quality of life. An adolescent-onset–obese–atopic–airflow-obstructive disease (cluster-3) showed fewer exacerbations but high BEC with worst spirometry and poor asthma control. In mild asthma, cluster-1 (early-onset-atopic-mild-asthma) showed worse pathophysiological indices and asthma control than cluster-2 (adolescent-onset-mild-asthma) but similarly high comorbidity prevalence. Conclusion Characterisation of difficult-to-treat and mild asthma clusters reveals diverse associated clinical traits and outcomes across the asthma severity spectrum. Recognition of these clusters and their associated comorbidities should prompt early personalised asthma management to address both airway-centric and comorbid disease aspects.

Background:Multimorbidity refers to the presence of multiple coexisting conditions, but is often underappreciated in the context of severe asthma (SA) management. We sought to identify differences in approaches to multimorbidity management in SA, variability in access to multidisciplinary team (MDT) resources, and whether physician perspectives on multimorbidity differ between SA specialists and general respiratory physicians. Methods:The Severe Heterogeneous Asthma Registry, Patient-centred (SHARP) Clinical Research Collaboration circulated an online physician survey via European national respiratory societies to assess 1) available resources to address multimorbidity and 2) physician perspectives on multimorbidity in SA. Results:495 responses from 25 European countries included 48% SA specialists and 52% general respiratory physicians. SA specialists had more experience with SA patients (20% were seeing >60 patients per month) compared to general respiratory physicians. SA specialists had greater access to multidisciplinary care - including better access to MDTs, allied health professionals and referrals to external specialists, and therefore more routinely assessed comorbidities and considered them greater influences on their practice. They also considered multimorbidity to a greater degree and rated its impact on their patients' asthma outcomes (and general health outcomes) as more substantial. Conclusions:Alongside more experience of treating SA, SA specialists have increased awareness of multimorbidity and better resources to manage it. However, access to MDTs remains a significant gap for both SA specialists and general respiratory physicians. Furthermore, both groups identified a high need for further education and training about multimorbidity. These findings highlight key areas for improvement in clinical practice, resources and training.

Introduction:Early in the COVID-19 pandemic, CT was demonstrated as a sensitive tool for diagnosing COVID-19. We undertook a detailed study of CT scans in COVID-19 patients to characterise disease distribution within lung parenchyma, respiratory airways, and pulmonary vasculature, aiming to delineate underlying disease processes. Methods:We characterised acute phase chest CT of 40 participants with COVID-19 from the REACT study, 31 with CT pulmonary angiography (CTPA), 4 with intravenous contrast enhanced CT and 5 with non-intravenous contrast enhanced CT. Participants had neither been vaccinated nor received systemic steroids. We further correlated the distribution of lung parenchymal damage on CT with contemporaneous chest radiographs. Results:Parenchymal lung damage was found in all subjects. However, airways inflammation was present in only 23% (9) and limited to small areas. Notably, vascular abnormalities were dominant and characterised by dilated peripheral pulmonary vessels supplying areas of lung damage in a gravity-dependent distribution bilaterally in 95% (38), basally in 90% (36), peripherally in 92.5% (37), and posteriorly in 90% (36). Macrothrombosis was demonstrated in 23% (7) of CTPAs. Wedge-shaped peripheral lung damage, resembling areas of pulmonary vascular congestion, were distinct in 53% (21) with or without visible macrothrombosis. Pleural effusions were seen in 28% (11). Notably, lung opacification distribution in 98% of the plain radiographs matched distribution on CT (39). Conclusion:Our study frames COVID-19 as a pulmonary vasculopathy rather than a more conventional pneumonia which may be important not only for guiding mechanistic study design but also for the development of novel targeted therapeutics.

BACKGROUND:Multimorbidity (ie, co-existence of two or more health conditions) is highly prevalent in patients with difficult-to-treat asthma. However, it remains unclear how multimorbidity correlates with disease severity and adverse health outcomes in these patients and which comorbidities are most important. We aimed to address this knowledge gap by developing a patient-centred, clinically descriptive multimorbidity score for difficult-to-treat asthma. METHODS:We used data from the UK-based Wessex Asthma Cohort of Difficult Asthma (WATCH; n=500, data collected between April 22, 2015, and April 1, 2020) to develop the Multimorbidity in Difficult Asthma Score (MiDAS). Initially, we created a modified Asthma Severity Scoring System (m-ASSESS) in WATCH. We then conducted univariate association analysis to test the association between the 13 commonest comorbidities and m-ASSESS in WATCH and used a branch-and-bound approach to select the most relevant comorbidities for inclusion in MiDAS. We calculated MiDAS values for all patients with complete information in WATCH (n=319) and assessed them for correlation with components of m-ASSESS, proinflammatory biomarkers, and St George's Respiratory Questionnaire (SGRQ) score, a quality-of-life measure. We also assessed the association of MiDAS with multiple clinical outcomes in four international cohorts: two from Australia (n=236, data collected between June 14, 2014, and April 1, 2022; and n=140, Aug 6, 2012, to Oct 18, 2016), one from southeast Asia (n=151, March 21, 2017, to Jan 16, 2024), and one from the USA (n=100, July 9, 2021, to Dec 14, 2023). FINDINGS:We selected seven common comorbidities (ie, rhinitis, gastro-oesophageal reflux disease, breathing pattern disorder, obesity, bronchiectasis, non-steroidal anti-inflammatory drug-exacerbated respiratory disease, and obstructive sleep apnoea) for inclusion in MiDAS on the basis of the branch-and-bound analysis and combined them using multivariate linear regression to derive a MiDAS model associated with m-ASSESS in WATCH. The range of MiDAS scores was 9·6-16·2. In WATCH members, mean MiDAS value was 11·97 (SD 1·21) and MiDAS was nominally correlated with m-ASSESS components of poor asthma control (τ=0·31 [95% CI 0·24-0·38]) and exacerbations (τ=0·16 [0·08-0·24]). MiDAS was also correlated with worse total SGRQ score (r=0·39 [95% 0·28-0·49], p<0·0001) and with the proinflammatory plasma cytokines interleukin (IL)-4 (r=0·19 [95% CI 0·06-0·31], p=0·0036), IL-5 (r=0·35 [0·24-0·46], p<0·0001), and leptin (r=0·29 [0·17-0·40], p<0·0001) in WATCH. MiDAS values across the four international cohorts were similar to those of WATCH (UK cohort), with mean values of 12·33 (SD 1·47) and 12·31 (1·37) in the Australian cohorts, 11·80 (1·20) in the USA cohort, and 11·55 (1·23) in the Singapore cohort. In these cohorts, MiDAS correlated with worse asthma control, worse quality of life, anxiety, depression, and increased inflammation. INTERPRETATION:MiDAS highlights the co-occurrence of multimorbidity with the worst outcomes in difficult-to-treat asthma. These findings strongly indicate that an airway-centric approach is inadequate and that holistic and multidisciplinary care is imperative. This clinical score could help clinicians to identify patients most at risk from their multimorbidity. FUNDING:UK National Institute for Health and Care Research, Australian National Health and Medical Research Council, Hunter Medical Research Institute, University of Newcastle (Australia), and John Hunter Hospital Charitable Trust.

The human respiratory tract virome is an underexplored component of the microbiome that includes eukaryotic viruses, bacteriophages and archaeal viruses. The respiratory virome represents a dynamic and heterogeneous ecosystem, shaped by host, environmental and microbial factors. Advances in metagenomic sequencing have expanded our understanding of virome composition, dynamics and potential roles in health and disease. Despite increasing interest, virome research remains fragmented and often secondary to bacteriome studies. Challenges in study design, genomic characterisation and interpretation limit consistent conclusions. This review summarises current knowledge of the respiratory virome in health and across acute and chronic respiratory diseases, including acute respiratory infection, asthma, COPD, cystic fibrosis and bronchiectasis. While each condition is distinct, they share features of airway inflammation and immune dysregulation where the virome may act as a modifier or marker. Across these syndromes, emerging evidence highlights the consistent detection of respiratory viruses including potential commensals, such as Anelloviridae, and the often-overlooked role of bacteriophages. We also discuss the concept of viral dark matter, where large proportions of sequence data remain unclassified, potentially representing novel viral taxa. Technical and conceptual challenges are evaluated, alongside recent methodological innovations such as meta-transcriptomics and viral enrichment protocols. We outline how standardised, multi-omic and longitudinal approaches are urgently needed to clarify the virome's functional role, interactions with immunity and microbial communities and its utility as a biomarker or therapeutic target.

Human rhinovirus (HRV), a non-enveloped RNA virus, was first identified more than 70 years ago. It is highly infectious and easily transmitted through aerosols and direct contact. The advent of multiplex PCR has enhanced the detection of a diverse range of respiratory viruses, and HRV consistently ranks among the most prevalent respiratory pathogens globally. Circulation occurs throughout the year, with peak incidence in autumn and spring in temperate climates. Remarkably, during the SARS-CoV-2 pandemic, HRV transmission persisted, demonstrating its resistance to stringent public health measures aimed at curbing viral transmission. HRV is characterised by its extensive genetic diversity, comprising three species and more than 170 genotypes. This diversity and substantial number of concurrently circulating strains allows HRVs to frequently escape the adaptive immune system and poses formidable challenges for the development of effective vaccines and antiviral therapies. There is currently a lack of specific treatments. Historically, HRV has been associated with self-limiting upper respiratory infection. However, there is now extensive evidence highlighting its significant role in severe lower respiratory disease in adults, including exacerbations of chronic airway diseases, such as asthma and chronic obstructive pulmonary disease (COPD), as well as pneumonia. These severe manifestations can occur even in immunocompetent individuals, broadening the clinical impact of this ubiquitous virus. Consequently, the burden of rhinovirus infections extends across various healthcare settings, from primary care to general hospital wards and intensive care units. The impact of HRV in adults, in terms of morbidity and healthcare utilisation, rivals that of the other major respiratory viruses, including influenza and respiratory syncytial virus. Recognition of this substantial burden underscores the critical need for novel treatment strategies and effective management protocols to mitigate the impact of HRV infections on public health. This review examines the epidemiology, clinical manifestations, and risk factors associated with severe HRV infection in adults. By drawing on contemporary literature, we aim to provide a comprehensive overview of the virus’s significant health implications. Understanding the scope of this impact is essential for developing new, targeted interventions and improving patient outcomes in the face of this persistent and adaptable pathogen.

Background Respiratory viral infections (RVIs) are a significant cause of morbidity and hospital admission worldwide. However, the management of most viral infection-associated diseases remains primarily supportive. The recent COVID-19 pandemic has underscored the urgent need for a deeper understanding of RVIs to improve patient outcomes and develop effective treatment strategies. The Understanding Infection, Viral Exacerbation and Respiratory Symptoms at Admission-Longitudinal Study is an observational study which addresses this need by investigating the heterogeneity of RVIs in hospitalised adults, aiming to identify clinical and biological predictors of adverse outcomes. This study aims to bridge critical knowledge gaps in the clinical course and the economic impact of RVIs by characterising the phenotypic diversity of these infections and their recovery patterns following hospital admission and thus assisting with the optimal design of future interventional studies.Methods and analysis This prospective longitudinal observational study (V.6, 20 September 2023) will be conducted across multiple UK secondary care sites from August 2022 onwards, with an aim to enrol 1000 participants testing positive for RVI. Adults admitted with respiratory symptoms who test positive for RVIs via the BioFire® FilmArray® System or other validated diagnostic PCR tests will be enrolled. The data collected include patient demographics, clinical history, comorbidities and symptoms experienced prior to, during and after hospitalisation with follow-up after discharge at weeks 1, 2, 4, 8, 12 and 26. In addition, biological samples are collected at multiple time points during the hospital stay. The primary endpoints are to study the impact of different RVIs and identify predictors of disease progression and length of stay. Secondary endpoints include time to recovery and healthcare cost. Exploratory endpoints focus on biomarker profiles associated with virus type and clinical outcomes.Ethics and dissemination The study protocol received ethical approval from the relevant committees (English Ethics Reference Number: 22/WM/0119; Scottish Ethics Reference Number: 22-SS-0101, 20/09/2023). For patients who lack the capacity to consent, the study complies with the Mental Capacity Act 2005, using a consultee process where a family member, carer or an independent clinician may provide assent on behalf of the patient. Data from all the study centres will be analysed together and disseminated through peer-reviewed journals, conference presentations and workshops. The study group will ensure that participants and their families are informed of the study findings promptly and in an accessible format.Trial registration number ISRCTN49183956.