Nazir I. Lone

Background: Acute COVID-19 alters the airway microbiota. Whether these changes persist post-COVID-19 and contribute to long COVID is unknown. We aimed to describe the microbiota by long COVID severity and subtype, and identify links with inflammation. Methods: Adults were prospectively recruited to the longitudinal UK Post-hospitalisation COVID-19 study (PHOSP-COVID). Patients were grouped by previously described “severity clusters” (of ongoing health impairments) and symptom subgroups. Oral and sputum microbiota (at 6 months post-discharge) were characterised through 16S ribosomal RNA gene amplicon sequencing, and microbiota diversity was assessed. Co-occurrence network analysis identified keystone taxa. Associations between keystone taxa and plasma inflammatory proteins were assessed through Spearman's rank correlations. Results: 771 participants had their microbiota assessed. Of participants with oral rinses and “severity cluster” assignment (mean age 57.5 years), 278 out of 722 (38.5%) were women. The “very severe” cluster, in which disease was predominantly pulmonary in nature, was associated with a distinct microbiota profile post-COVID-19. Reduced lung function was associated with a distinct oral microbiota profile. Persistent neurocognitive symptoms were associated with a distinct oral microbiota profile, while gastrointestinal symptoms were associated with a distinct sputum microbiota profile. Microbiota keystone taxa shifted to a higher prevalence of lactic acid bacteria associated with worse health outcomes. Lactic acid bacteria abundance was associated with elevated blood inflammatory proteins. Conclusion: Distinct oral and sputum microbiota profiles were associated with pulmonary function and with neurocognitive and gastrointestinal symptoms in long COVID. Shifts in keystone microbiota taxa linked with inflammation, based on worse health outcomes, suggest a potential role change for lactic acid bacteria, which may be associated with the host immune response.

Summary: Introduction: The optimal ICU sedation strategy to improve patient‐reported experience is unknown. In a planned secondary analysis of the A2B randomised trial, we evaluated the effect of sedation strategy (dexmedetomidine, clonidine or propofol) on recalled patient experience at 90 days post‐randomisation. Using mediation analyses, we explored plausible mediators of the relationship between sedation strategy and patient experience. Methods: We analysed data for all patients from A2B who completed the Intensive Care Experience Questionnaire (ICE‐Q) at 90 days. The primary outcome was patient‐recalled experience, measured by the four ICE‐Q domain scores (awareness, frightening memories, recall, satisfaction). Sedation strategy effect was evaluated using linear regression, adjusting for potential confounders. Mediation analyses were conducted for duration of mechanical ventilation; ICU stay; and days with pain behaviour, agitation and coma/delirium. Results: Of 1404 patients included in the primary trial analysis, 1009 (71.9%) were alive at 90 days post‐randomisation with ICE‐Qs completed by 289/1009 (28.6%). Compared with propofol, dexmedetomidine sedation was associated with higher awareness of surroundings (median score 32 vs. 28, adjusted mean difference 3.6, 95%CI 1.0–6.2, p = 0.01), but clonidine sedation had no association (difference 2.4, 95%CI ‐0.2–5.0, p = 0.07). No associations were found with other ICE‐Q domains. The contribution of the five potential mediators on the dexmedetomidine–awareness relationship was small. Discussion: Dexmedetomidine compared with propofol sedation strategy may be associated with increased recalled awareness of surroundings, which is considered a favourable indicator of ICU experience. Together with the primary A2B trial results, which showed no effect on ventilation duration, these hypothesis‐generating findings in a subgroup of the A2B cohort do not support the use of dexmedetomidine over propofol based on patient‐reported experience. Based on our findings, we advocate that a personalised approach to sedation strategies should continue to be used.

Background: Multimorbidity is common at cancer diagnosis, and both cancer and its treatment can lead to new long-term conditions. However, evidence on the prevalence of multimorbidity, particularly mental-physical multimorbidity, at both diagnosis and five years after cancer diagnosis remains limited. This study describes the prevalence of, and factors associated with, non-cancer multimorbidity in people newly diagnosed with cancer and those living with and beyond cancer. Methods: Retrospective cohort study of people aged 18 years and older diagnosed with, or surviving five years with one of breast, prostate, colorectal or lung cancer in 2018. For 46 long-term conditions, multimorbidity (≥ 2 non-cancer conditions), mental-physical multimorbidity (≥ 1 non-cancer physical and ≥ 1 mental health condition) and condition count (0 - ≥6 non-cancer conditions) were measured in incident and survivor cohorts, and examined by age, sex, deprivation and ethnicity. Odds of multimorbidity by cancer type was calculated using logistic regression, stratified by sex and adjusted for age, deprivation and ethnicity. Results: Analysis included 33,258 people with incident cancer and 16,807 people living with and beyond cancer (PLWBC). Multimorbidity ranged from 60 to 86% at cancer diagnosis to 70–90% in PLWBC, dependent on cancer type. Less than 20% had no additional long-term conditions at diagnosis (< 5.3% in lung cancer specifically) and less than 15% in PLWBC (< 2.3% in lung cancer). Mental-physical multimorbidity affected 24–39% at diagnosis and 27–44% in PLWBC. Both types of multimorbidity were higher in those living in the most deprived areas across all age groups. Compared with colorectal cancer, people with lung cancer had higher odds of multimorbidity at both diagnosis (in women adjusted OR 2.15 95%CI 1.86–2.49; in men aOR 1.71 95%CI 1.50–1.94) and in PLWBC (in women aOR 2.11 95%CI 1.45–3.12; in men, aOR 2.20 95%CI 1.51–3.30), whereas women with breast cancer and men with prostate cancer had lower odds. Conclusions: Most people with cancer have additional long-term conditions, with the highest prevalence in lung cancer. Clear socioeconomic inequalities in multimorbidity persist into survivorship. Cancer pathways need to ensure coordinated management of non-cancer long-term conditions between primary and secondary care across the whole cancer journey, from diagnosis through treatment and into survivorship.

Background: Services for patients with multiple long-term conditions (MLTC) operate within fragmented and poorly coordinated systems but how care experiences, perceptions, and behaviours emerge and adapt in response to service changes and increasing system complexity is poorly understood. Aim: To explore how experiences and perceptions of care for patients with MLTC and their carers emerge and evolve within a complex adaptive care system to identify opportunities for better care. Design and setting: Qualitative analysis of six focus groups with 28 patients with MLTC and carers in four Scottish integrated health and social care partnerships was undertaken. Method: Data were collected between February and May 2024. Abductive analysis informed by a complex adaptive systems lens was used. Results: Care for patients with MLTC emerged through dynamic, reciprocal interactions between patients, carers, professionals, and organisational structures. Service changes introduced to manage rising demand were often perceived as misaligned with patients’ complex needs, prompting patients and carers to modify their behaviours to navigate access barriers. Care experiences were unpredictable, shaped by reinforcing feedback loops in which small personal interactions had a disproportionate effect on trust and engagement. Informal care expanded to fill system gaps, with family members assuming coordination and advocacy roles. Clinical empathy and relational continuity of care acted as key stabilising influences within fragmented care systems. Conclusion: Service changes intended to improve care efficiency can inadvertently destabilise care and shift the burden onto patients with MLTC and their carers, affecting perceived care quality and relational continuity. The quality of interactions and relationships between agents shape patients’ perceptions of care and future engagement.

Background: Hospital ward transitions remain poorly understood despite their importance to patient flow and efficiency. Transition patterns are shaped by local policy and pathways, but in critically ill patients, transitions may also accumulate in response to clinical complexity. This study aimed to characterise patterns of ward transitions, identify determinants of ward transition frequency, and evaluate associations with adverse patient outcomes. Methods: This retrospective cohort study comprised patients admitted through the emergency department (ED) across three acute hospitals in a region of Scotland between 2017 and 2022 who experienced a critical care admission prior to hospital discharge. Ward transition patterns were characterised using descriptive statistics and frequency distributions. Regression analyses were conducted to identify factors associated with transition frequency and to examine associations with 7-day ED reattendance, 30-day emergency hospital readmission, 30-day post-discharge mortality, and hospital length of stay. Results: 12,836 critical care survivors were included. In univariable analyses, factors including age, comorbidity burden, smoking status, deprivation, and level of organ support were associated with transition frequency. Greater transition burden was associated with increased odds of 7-day ED reattendance (adjusted OR = 1.12, 99.89% CI: 1.07–1.17) and prolonged length of stay (adjusted beta coefficient 1.35, 99.89% CI: 1.34–1.36), but not 30-day readmission (adjusted OR = 1.01, 99.89% CI: 0.96–1.05) or 30-day mortality (adjusted OR = 0.99, 99.89% CI: 0.86–1.14). Conclusion: Increased ward transitions in critically ill patients mark clinical complexity. It is associated with longer hospital stays and may help identify those at greater risk of early ED reattendance.

The availability of electronic health records has facilitated data-driven approaches to the understanding of multimorbidity, with clustering becoming a common tool for uncovering relevant groups of associated conditions. Previous studies, however, have found challenges in their reproducibility, with wide disparity in the reported clusters. At the core of this issue lays a vagueness of the definition of a cluster, leading to a lack of standards in their methods and evaluation, while implementation details are often not completely reported or explicit in their assumptions. We present a methodological pipeline that can be adapted to different cluster definitions (e.g. multiple cluster membership or clusters where all nodes are mutually associated) and a set of scores that can be composed into an evaluation metric that explicitly incorporates assumptions that align with the research aims. We apply our pipeline to a healthcare dataset of over 7 million patients in England and show how clusters may drastically differ when varying the parameter choices, exposing the risks of reporting a single clustering realisation. Our methodological pipeline, evaluation framework, and tools for analysis and network visualisation serve as a reference to transparently explore and align methodological decisions to the aims of multimorbidity clustering, contributing to overcome the reproducibility challenges of the field.

Introduction: Prolonged time to asystole is a common barrier to successful organ donation after circulatory death, yet there have been few attempts to evaluate trends in its occurrence over time. This study investigated temporal trends in time to asystole among patients considered for donation after circulatory death in the UK (2014–2024). Methods: This observational study was conducted using NHS Organ Donation & Transplant (ODT) datasets. We analysed temporal trends in time to asystole and donation outcomes using descriptive statistics. Additionally, to explore evident impacts of the COVID-19 pandemic we performed pre-post comparisons and an interrupted time series (ITS) analysis. Results: Of 9466 participants, 58.5% proceeded to solid organ donation. Non-proceeding cases were primarily due to prolonged time to asystole (55.1%). Donation rates increased from 50% to 60% pre-2020 to consistently above 60% post-2022, whilst cases not proceeding due to prolonged time to asystole decreased from 25% to 20%. ITS analysis confirmed a significant post-pandemic reduction in time to asystole and a sustained drop in referrals, suggesting improved donation efficiency. Successful donors typically received higher levels of support and had lower neurological status compared to those with prolonged time to asystole. Discussion: The findings demonstrate reduced prolonged time to asystole occurrence and increased organ donation rates. Whilst there has been ongoing improvement over the study period there is evidence of a systemic change following the COVID-19 pandemic, which resulted in a smaller, more efficient referral pool. This may be attributed to better identification of suitable donors during the referral process, and while causation cannot be definitively established, the study supports ongoing evaluation and refinement of the donation pathways.

Background: Physical inactivity is a risk factor for severe COVID-19 and often worsens after hospitalisation. Clinicians need quick, accurate assessments to target interventions. We aimed to assess the validity of the General Practice Physical Activity Questionnaire (GPPAQ) in adults recovering one year after COVID-19 hospitalisation . Methods: Post-hospitalisation for COVID-19, adults attended a one-year-visit and completed the GPPAQ Physical Activity Index (PAI-4 active), 14-day wrist-worn accelerometry (Moderate-Vigorous PA [MVPA]- active), and other health outcomes. Validity was examined via : (i) internal consistency (factor analysis); (ii) measurement invariance across sex, age, and ethnicity using differential item functioning (DIF); (iii) convergent validity (GPPAQ sensitivity/specificity versus accelerometry); and (iv) construct validity (correlations with health outcomes). Results: 752 participants had GPPAQ and accelerometry (265 female, mean± sd age 60.9±11.6 years, MVPA 18.75 min·day ⁻¹ (IQR 7.55, 36.11), PAI-1 46.8%, PAI-2 15.6%, PAI-3 19.4%, PAI-4 18.2%. Factor analyses supported good internal consistency with two factors (daily activities, physical exercise). Confirmatory factor Index (CFI) showed excellent fit (CFI 0.965). DIF indicated moderate variability by sex and age. GPPAQ-PAI showed limited sensitivity (26.3%) for correctly classifying physically active individuals, but higher specificity (88.4%) for classifying physical inactivity, and weak-to-moderate correlations with health outcomes. Conclusions: GPPAQ demonstrates internal consistency, with construct and convergent validity in adults 1-year post-COVID-19 hospitalisation. GPPAQ effectively identifies inactive individuals to support clinical care; however, its sensitivity suggests underestimation of activity relative to accelerometry. Future pathways should combine GPPAQ with device-based assessment to optimise evaluation of physical activity to guide pulmonary rehabilitation and targeted interventions.

Background: Comorbidities can impact the whole cancer journey from diagnosis to survivorship. This study describes the prevalence of, and factors associated with non-cancer multimorbidity at diagnosis and among five-year cancer survivors. Methods: Cross-sectional study of people aged 18+ years diagnosed with, or surviving five years with one of breast, prostate, colorectal or lung cancer in 2018. For 46 long-term conditions, condition burden, multimorbidity (≥2 non-cancer conditions) and mental-physical multimorbidity (≥1 non-cancer physical and ≥1 mental health condition) were measured in incident and survivor cohorts. Odds of multimorbidity by cancer type was calculated using logistic regression, stratified by sex and adjusted for age, deprivation and ethnicity.Findings: Analysis included 33,258 people with incident cancer and 16,807 people living with and beyond cancer (PLWBC). Multimorbidity ranged from 60-86% at cancer diagnosis to 70-90% in PLWBC, dependent on cancer type. Less than 20% had no additional long-term conditions at cancer diagnosis and less than 15% in PLWBC. Age and deprivation were significant determinants of multimorbidity with a 13-28 percentage point difference in multimorbidity between the most and least deprived groups in those aged 18-59 years. Compared with colorectal cancer, people with lung cancer had higher odds of multimorbidity at both diagnosis (in women adjusted OR 2.15 95%CI 1.86-2.49; in men aOR 1.71 95%CI 1.50-1.94) and in PLWBC (in women aOR 2.11 95%CI 1.45-3.12; in men , aOR 2.20 95%CI 1.51-3.30), whereas women with breast cancer and men with prostate cancer had lower odds.Interpretation: Multimorbidity is very common in people with cancer. The burden is highest among people with lung cancer and clear socioeconomic inequalities exist. Cancer pathways need to ensure coordinated management of non-cancer long-term conditions between primary and secondary care across the whole cancer journey from diagnosis through treatment and into survivorship.