Introduction Long COVID, a new condition whose origins and natural history are not yet fully established, currently affects 1.5 million people in the UK. Most do not have access to specialist long COVID services. We seek to optimise long COVID care both within and outside specialist clinics, including improving access, reducing inequalities, helping self-management and providing guidance and decision support for primary care. We aim to establish a ‘gold standard’ of care by systematically analysing current practices, iteratively improving pathways and systems of care. Methods and analysis This mixed-methods, multisite study is informed by the principles of applied health services research, quality improvement, co-design, outcome measurement and learning health systems. It was developed in close partnership with patients (whose stated priorities are prompt clinical assessment; evidence-based advice and treatment and help with returning to work and other roles) and with front-line clinicians. Workstreams and tasks to optimise assessment, treatment and monitoring are based in three contrasting settings: workstream 1 (qualitative research, up to 100 participants), specialist management in 10 long COVID clinics across the UK, via a quality improvement collaborative, experience-based co-design and targeted efforts to reduce inequalities of access, return to work and peer support; workstream 2 (quantitative research, up to 5000 participants), patient self-management at home, technology-supported monitoring and validation of condition-specific outcome measures and workstream 3 (quantitative research, up to 5000 participants), generalist management in primary care, harnessing electronic record data to study population phenotypes and develop evidence-based decision support, referral pathways and analysis of costs. Study governance includes an active patient advisory group. Ethics and dissemination LOng COvid Multidisciplinary consortium Optimising Treatments and servIces acrOss the NHS study is sponsored by the University of Leeds and approved by Yorkshire & The Humber—Bradford Leeds Research Ethics Committee (ref: 21/YH/0276). Participants will provide informed consent. Dissemination plans include academic and lay publications, and partnerships with national and regional policymakers. Trial registration number NCT05057260, ISRCTN15022307.

Deeper understanding of mold-induced cytokine signatures could promote advances in the diagnosis and treatment of invasive mycoses and mold-associated hypersensitivity syndromes. Currently, most T-cellular immunoassays in medical mycology require the isolation of mononuclear cells and have limited robustness and practicability, hampering their broader applicability in clinical practice. Therefore, we developed a simple, cost-efficient whole blood (WB) assay with dual α-CD28 and α-CD49d co-stimulation to quantify cytokine secretion in response to Aspergillus fumigatus antigens. Dual co-stimulation strongly enhanced A. fumigatus-induced release of T-cellular signature cytokines detectable by enzyme-linked immunosorbent assay (ELISA) or a multiplex cytokine assay. Furthermore, T-cell-dependent activation and cytokine response of innate immune cells was captured by the assay. The protocol consistently showed little technical variation and high robustness to pre-analytic delays of up to 8 h. Stimulation with an A. fumigatus lysate elicited at least 7-fold greater median concentrations of key T-helper cell signature cytokines, including IL-17 and the type 2 T-helper cell cytokines IL-4 and IL-5 in WB samples from patients with Aspergillus-associated lung pathologies versus patients with non-mold-related lung diseases, suggesting high discriminatory power of the assay. These results position WB-ELISA with dual co-stimulation as a simple, accurate, and robust immunoassay for translational applications, encouraging further evaluation as a platform to monitor host immunity to opportunistic pathogens.

Non-small cell lung cancer (NSCLC) frequently presents in advanced stages. A significant proportion of those with reportedly good ECOG performance status (PS) fail to receive planned multidisciplinary team (MDT) treatment, often for functional reasons, but an objective decline in physical performance is not well described. Sarcopenia, or loss of muscle mass, is an integral part of cancer cachexia. However, changes in both muscle mass and physical performance may predate clinically overt cachexia, and may be present even with normal body mass index. Physical fitness for treatment is currently subjectively assessed by means of the PS score, which may be inadequate in predicting tolerance to treatment. This study aims to evaluate whether measuring physical performance and muscle mass at baseline in NSCLC patients, in addition to PS score, is able to predict commencement and successful completion of MDT-planned treatment. This is a prospective, single-centre exploratory study of NSCLC patients attending a Rapid Access Lung Cancer clinic. Baseline data collected are (methods in brackets): physical performance (Short Physical Performance Battery), muscle mass (bioelectrical impedance ± dual energy x-ray absorptiometry), patient and physician-assessed PS (ECOG and Karnofsky), nutritional status and presence of cachexia. Longitudinal data consists of receipt and completion of MDT treatment plan. The primary outcome measure is commencement of MDT-planned treatment, and important secondary outcomes include successful completion of treatment, length of stay in surgical patients, and risk of chemotherapy- and radiotherapy-related side effects. A more comprehensive assessment of phenotype, particularly with regards to physical performance and muscle mass, will provide additional discriminatory information of patients’ fitness for treatment. If positive, this study has the potential to identify targets for early intervention in those who are at risk of deterioration. This will subsequently enable optimisation of performance of patients with NSCLC, in anticipation of systemic treatment.

Background: Long COVID (LC) is a multisystem clinical syndrome with functional disability and compromised overall health. Information on LC clinical severity types is emerging in cross-sectional studies. This study explored the pattern and consistency of long COVID (LC) clinical severity types over time in a prospective sample. Methods: Participants with LC completed the condition-specific outcome measure C19-YRSm (Yorkshire Rehabilitation Scale modified version) at two assessment time points. A cluster analysis for clinical severity types was undertaken at both time points using the k-means partition method. Results: The study included cross-sectional data for 759 patients with a mean age of 46.8 years (SD = 12.7), 69.4% females, and a duration of symptoms of 360 days (IQR 217 to 703 days). The cluster analysis at first assessment revealed three distinct clinical severity type clusters: mild (n = 96), moderate (n = 422), and severe (n = 241). Longitudinal data on 356 patients revealed that the pattern of three clinical severity types remained consistent over time between the two assessments, with 51% of patients switching clinical severity types between the assessments. Conclusions: This study is the first of its kind to demonstrate that the pattern of three clinical severity types is consistent over time, with patients also switching between severity types, indicating the fluctuating nature of LC.

The protracted form of COVID-19 known as ‘long covid’ was first described in 2020. Its symptoms, course and prognosis vary widely; some patients have a multi-system, disabling and prolonged illness. In 2021, ring-fenced funding was provided to establish 90 long covid clinics in England; some clinics were also established in Scotland and Wales. The NIHR-funded LOCOMOTION project implemented a UK-wide quality improvement collaborative involving ten of these clinics, which ran from 2021 to 2023. At regular online meetings held approximately 8-weekly, participants prioritized topics, discussed research evidence and guidelines, and presented exemplar case histories and clinic audits. A patient advisory group also held a priority-setting exercise, participated in quality meetings and undertook a service evaluation audit. The goal of successive quality improvement cycles aimed at changing practice to align with evidence was sometimes hard to achieve because definitive evidence did not yet exist in this new condition; many patients had comorbidities; and clinics were practically constrained in various ways. Nevertheless, much progress was made and a series of ‘best practice’ guides was produced, covering general assessment and management; breathing difficulties; orthostatic tachycardia and other autonomic symptoms; fatigue and cognitive impairment; and vocational rehabilitation. This paper summarises key findings with the front-line clinician in mind.

Background: Long COVID encompasses a heterogeneous set of ongoing symptoms that affect many individuals after recovery from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The underlying biological mechanisms nonetheless remain obscure, precluding accurate diagnosis and effective intervention. Complement dysregulation is a hallmark of acute COVID-19 but has not been investigated as a potential determinant of long COVID. Methods: We quantified a series of complement proteins, including markers of activation and regulation, in plasma samples from healthy convalescent individuals with a confirmed history of infection with SARS-CoV-2 and age/ethnicity/gender/infection/vaccine-matched patients with long COVID. Findings: Markers of classical (C1s-C1INH complex), alternative (Ba, iC3b), and terminal pathway (C5a, TCC) activation were significantly elevated in patients with long COVID. These markers in combination had a receiver operating characteristic predictive power of 0.794. Other complement proteins and regulators were also quantitatively different between healthy convalescent individuals and patients with long COVID. Generalized linear modeling further revealed that a clinically tractable combination of just four of these markers, namely the activation fragments iC3b, TCC, Ba, and C5a, had a predictive power of 0.785. Conclusions: These findings suggest that complement biomarkers could facilitate the diagnosis of long COVID and further suggest that currently available inhibitors of complement activation could be used to treat long COVID. Funding: This work was funded by the National Institute for Health Research (COV-LT2-0041), the PolyBio Research Foundation, and the UK Dementia Research Institute.