Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease.

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain-gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials.

Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma.

RATIONALE: Volatile organic compounds (VOCs) in asthmatic breath may be associated with sputum eosinophilia. We developed a volatile biomarker-signature to predict sputum eosinophilia in asthma. METHODS: VOCs emitted into the space above sputum samples (headspace) from severe asthmatics (n=36) were collected onto sorbent tubes and analysed using thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Elastic net regression identified stable VOCs associated with sputum eosinophilia ≥3% and generated a volatile biomarker signature. This VOC signature was validated in breath samples from: (I) acute asthmatics according to blood eosinophilia ≥0.3x109cells/L or sputum eosinophilia of ≥ 3% in the UK EMBER consortium (n=65) and U-BIOPRED-IMI consortium (n=42). Breath samples were collected onto sorbent tubes (EMBER) or Tedlar bags (U-BIOPRED) and analysed by gas-chromatography-mass spectrometry (GC×GC-MS -EMBER or GC-MS -U-BIOPRED). MAIN RESULTS: The in vitro headspace identified 19 VOCs associated with sputum eosinophilia and the derived VOC signature yielded good diagnostic accuracy for sputum eosinophilia ≥ 3% in headspace (AUROC (95% CI) 0.90(0.80-0.99), p<0.0001), correlated inversely with sputum eosinophil % (rs= -0.71, p<0.0001) and outperformed FeNO (AUROC (95% CI) 0.61(0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89(0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90(0.75-1.0) in U-BIOPRED - again outperforming FeNO in U-BIOPRED 0.62 (0.33-0.90). CONCLUSIONS: We have discovered and provided early-stage clinical validation of a volatile biomarker signature associated with eosinophilic airway inflammation. Further work is needed to translate our discovery using point of care clinical sensors.

Plasma steroid concentrations reflect acute disease severity and normalise during recovery in people hospitalised with COVID-19.

OBJECTIVE: Endocrine systems are disrupted in acute illness, and symptoms reported following coronavirus disease 2019 (COVID-19) are similar to those found with clinical hormone deficiencies. We hypothesised that people with severe acute COVID-19 and with post-COVID symptoms have glucocorticoid and sex hormone deficiencies. DESIGN/PATIENTS: Samples were obtained for analysis from two UK multicentre cohorts during hospitalisation with COVID-19 (International Severe Acute Respiratory Infection Consortium/World Health Organisation [WHO] Clinical Characterization Protocol for Severe Emerging Infections in the UK study), and at follow-up 5 months after hospitalisation (Post-hospitalisation COVID-19 study). MEASUREMENTS: Plasma steroids were quantified by liquid chromatography-mass spectrometry. Steroid concentrations were compared against disease severity (WHO ordinal scale) and validated symptom scores. Data are presented as geometric mean (SD). RESULTS: In the acute cohort (n = 239, 66.5% male), plasma cortisol concentration increased with disease severity (cortisol 753.3 [1.6] vs. 429.2 [1.7] nmol/L in fatal vs. least severe, p < .001). In males, testosterone concentrations decreased with severity (testosterone 1.2 [2.2] vs. 6.9 [1.9] nmol/L in fatal vs. least severe, p < .001). In the follow-up cohort (n = 198, 62.1% male, 68.9% ongoing symptoms, 165 [121-192] days postdischarge), plasma cortisol concentrations (275.6 [1.5] nmol/L) did not differ with in-hospital severity, perception of recovery, or patient-reported symptoms. Male testosterone concentrations (12.6 [1.5] nmol/L) were not related to in-hospital severity, perception of recovery or symptom scores. CONCLUSIONS: Circulating glucocorticoids in patients hospitalised with COVID-19 reflect acute illness, with a marked rise in cortisol and fall in male testosterone. These findings are not observed 5 months from discharge. The lack of association between hormone concentrations and common post-COVID symptoms suggests steroid insufficiency does not play a causal role in this condition.

Accelarated immune ageing is associated with COVID-19 disease severity.

BACKGROUND: The striking increase in COVID-19 severity in older adults provides a clear example of immunesenescence, the age-related remodelling of the immune system. To better characterise the association between convalescent immunesenescence and acute disease severity, we determined the immune phenotype of COVID-19 survivors and non-infected controls. RESULTS: We performed detailed immune phenotyping of peripheral blood mononuclear cells isolated from 103 COVID-19 survivors 3-5 months post recovery who were classified as having had severe (n = 56; age 53.12 ± 11.30 years), moderate (n = 32; age 52.28 ± 11.43 years) or mild (n = 15; age 49.67 ± 7.30 years) disease and compared with age and sex-matched healthy adults (n = 59; age 50.49 ± 10.68 years). We assessed a broad range of immune cell phenotypes to generate a composite score, IMM-AGE, to determine the degree of immune senescence. We found increased immunesenescence features in severe COVID-19 survivors compared to controls including: a reduced frequency and number of naïve CD4 and CD8 T cells (p < 0.0001); increased frequency of EMRA CD4 (p < 0.003) and CD8 T cells (p < 0.001); a higher frequency (p < 0.0001) and absolute numbers (p < 0.001) of CD28-ve CD57+ve senescent CD4 and CD8 T cells; higher frequency (p < 0.003) and absolute numbers (p < 0.02) of PD-1 expressing exhausted CD8 T cells; a two-fold increase in Th17 polarisation (p < 0.0001); higher frequency of memory B cells (p < 0.001) and increased frequency (p < 0.0001) and numbers (p < 0.001) of CD57+ve senescent NK cells. As a result, the IMM-AGE score was significantly higher in severe COVID-19 survivors than in controls (p < 0.001). Few differences were seen for those with moderate disease and none for mild disease. Regression analysis revealed the only pre-existing variable influencing the IMM-AGE score was South Asian ethnicity ([Formula: see text] = 0.174, p = 0.043), with a major influence being disease severity ([Formula: see text] = 0.188, p = 0.01). CONCLUSIONS: Our analyses reveal a state of enhanced immune ageing in survivors of severe COVID-19 and suggest this could be related to SARS-Cov-2 infection. Our data support the rationale for trials of anti-immune ageing interventions for improving clinical outcomes in these patients with severe disease.

Residual Lung Abnormalities after COVID-19 Hospitalization: Interim Analysis of the UKILD Post-COVID-19 Study.

Rationale: Shared symptoms and genetic architecture between coronavirus disease (COVID-19) and lung fibrosis suggest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may lead to progressive lung damage. Objectives: The UK Interstitial Lung Disease Consortium (UKILD) post-COVID-19 study interim analysis was planned to estimate the prevalence of residual lung abnormalities in people hospitalized with COVID-19 on the basis of risk strata. Methods: The PHOSP-COVID-19 (Post-Hospitalization COVID-19) study was used to capture routine and research follow-up within 240 days from discharge. Thoracic computed tomography linked by PHOSP-COVID-19 identifiers was scored for the percentage of residual lung abnormalities (ground-glass opacities and reticulations). Risk factors in linked computed tomography were estimated with Bayesian binomial regression, and risk strata were generated. Numbers within strata were used to estimate posthospitalization prevalence using Bayesian binomial distributions. Sensitivity analysis was restricted to participants with protocol-driven research follow-up. Measurements and Main Results: The interim cohort comprised 3,700 people. Of 209 subjects with linked computed tomography (median, 119 d; interquartile range, 83-155), 166 people (79.4%) had more than 10% involvement of residual lung abnormalities. Risk factors included abnormal chest X-ray (risk ratio [RR], 1.21; 95% credible interval [CrI], 1.05-1.40), percent predicted DlCO less than 80% (RR, 1.25; 95% CrI, 1.00-1.56), and severe admission requiring ventilation support (RR, 1.27; 95% CrI, 1.07-1.55). In the remaining 3,491 people, moderate to very high risk of residual lung abnormalities was classified at 7.8%, and posthospitalization prevalence was estimated at 8.5% (95% CrI, 7.6-9.5), rising to 11.7% (95% CrI, 10.3-13.1) in the sensitivity analysis. Conclusions: Residual lung abnormalities were estimated in up to 11% of people discharged after COVID-19-related hospitalization. Health services should monitor at-risk individuals to elucidate long-term functional implications.

Lung volume reduction surgery versus endobronchial valves: a randomised controlled trial.

BACKGROUND: Lung volume reduction surgery (LVRS) and bronchoscopic lung volume reduction (BLVR) with endobronchial valves can improve outcomes in appropriately selected patients with emphysema. However, no direct comparison data exist to inform clinical decision making in people who appear suitable for both procedures. Our aim was to investigate whether LVRS produces superior health outcomes when compared with BLVR at 12 months. METHODS: This multicentre, single-blind, parallel-group trial randomised patients from five UK hospitals, who were suitable for a targeted lung volume reduction procedure, to either LVRS or BLVR and compared outcomes at 1 year using the i-BODE score. This composite disease severity measure includes body mass index, airflow obstruction, dyspnoea and exercise capacity (incremental shuttle walk test). The researchers responsible for collecting outcomes were masked to treatment allocation. All outcomes were assessed in the intention-to-treat population. RESULTS: 88 participants (48% female, mean±sd age 64.6±7.7 years, forced expiratory volume in 1 s percent predicted 31.0±7.9%) were recruited at five specialist centres across the UK and randomised to either LVRS (n=41) or BLVR (n=47). At 12 months follow-up, the complete i-BODE was available in 49 participants (21 LVRS/28 BLVR). Neither improvement in the i-BODE score (LVRS -1.10±1.44 versus BLVR -0.82±1.61; p=0.54) nor in its individual components differed between groups. Both treatments produced similar improvements in gas trapping (residual volume percent predicted: LVRS -36.1% (95% CI -54.6- -10%) versus BLVR -30.1% (95% CI -53.7- -9%); p=0.81). There was one death in each treatment arm. CONCLUSION: Our findings do not support the hypothesis that LVRS is a substantially superior treatment to BLVR in individuals who are suitable for both treatments.

Collaboration between explainable artificial intelligence and pulmonologists improves the accuracy of pulmonary function test interpretation.

BACKGROUND: Few studies have investigated the collaborative potential between artificial intelligence (AI) and pulmonologists for diagnosing pulmonary disease. We hypothesised that the collaboration between a pulmonologist and AI with explanations (explainable AI (XAI)) is superior in diagnostic interpretation of pulmonary function tests (PFTs) than the pulmonologist without support. METHODS: The study was conducted in two phases, a monocentre study (phase 1) and a multicentre intervention study (phase 2). Each phase utilised two different sets of 24 PFT reports of patients with a clinically validated gold standard diagnosis. Each PFT was interpreted without (control) and with XAI's suggestions (intervention). Pulmonologists provided a differential diagnosis consisting of a preferential diagnosis and optionally up to three additional diagnoses. The primary end-point compared accuracy of preferential and additional diagnoses between control and intervention. Secondary end-points were the number of diagnoses in differential diagnosis, diagnostic confidence and inter-rater agreement. We also analysed how XAI influenced pulmonologists' decisions. RESULTS: In phase 1 (n=16 pulmonologists), mean preferential and differential diagnostic accuracy significantly increased by 10.4% and 9.4%, respectively, between control and intervention (p<0.001). Improvements were somewhat lower but highly significant (p<0.0001) in phase 2 (5.4% and 8.7%, respectively; n=62 pulmonologists). In both phases, the number of diagnoses in the differential diagnosis did not reduce, but diagnostic confidence and inter-rater agreement significantly increased during intervention. Pulmonologists updated their decisions with XAI's feedback and consistently improved their baseline performance if AI provided correct predictions. CONCLUSION: A collaboration between a pulmonologist and XAI is better at interpreting PFTs than individual pulmonologists reading without XAI support or XAI alone.

Randomised controlled trial to investigate the use of high-frequency airway oscillations as training to improve dyspnoea (TIDe) in COPD.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is characterised by symptomatic dyspnoea and reduced exercise tolerance, in part as a result muscle weakness, for which inspiratory muscle training (IMT) may be useful. Excess mucus hypersecretion commonly coexists in COPD and may lead to reduce ventilation, further impacting on breathlessness. Devices for sputum clearance may be employed to aid mucus expectoration. This trial aimed to explore the effectiveness of a combined IMT and high-frequency airway oscillating (HFAO) device in the management of dyspnoea. METHODS: This was a double-blinded, randomised sham-controlled trial which recruited symptomatic patients with COPD. Patients were randomised to either a HFAO device (Aerosure) or sham device for 8 weeks, three times a day. The primary outcome was the Chronic Respiratory Questionnaire dyspnoea (CRQ-D) domain. Pre-specified subgroup analyses were performed including those with respiratory muscle weakness, excessive sputum and frequent exacerbators. RESULTS: 104 participants (68% men, mean (SD) age 69.75 years (7.41), forced expiratory volume in 1 s per cent predicted 48.22% (18.75)) were recruited to this study with 96 participants completing. No difference in CRQ-D was seen between groups (0·28, 95% CI -0.19 to 0.75, p=0.24), though meaningful improvements were seen over time in both groups (mean (SD) HFAO 0.45 (0.78), p<0.01; sham 0.73 (1.09), p<0.01). Maximal inspiratory pressure significantly improved in the HFAO group over sham (5.26, 95% CI 0.34 to 10.19, p=0.05). Similar patterns were seen in the subgroup analysis. CONCLUSION: There were no statistical differences between the HFAO and the sham group in improving dyspnoea measured by the CRQ-D. TRIAL REGISTRATION NUMBER: ISRCTN45695543.

A proof of concept for continuous, non-invasive, free-living vital signs monitoring to predict readmission following an acute exacerbation of COPD: a prospective cohort study.

BACKGROUND: The use of vital signs monitoring in the early recognition of an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) post-hospital discharge is limited. This study investigated whether continuous vital signs monitoring could predict an AECOPD and readmission. METHODS: 35 people were recruited at discharge following hospitalisation for an AECOPD. Participants were asked to wear an Equivital LifeMonitor during waking hours for 6 weeks and to complete the Exacerbations of Chronic Pulmonary Disease Tool (EXACT), a 14-item symptom diary, daily. The Equivital LifeMonitor recorded respiratory rate (RR), heart rate (HR), skin temperature (ST) and physical activity (PA) every 15-s. An AECOPD was classified as mild (by EXACT score), moderate (prescribed oral steroids/antibiotics) or severe (hospitalisation). RESULTS: Over the 6-week period, 31 participants provided vital signs and symptom data and 14 participants experienced an exacerbation, of which, 11 had sufficient data to predict an AECOPD. HR and PA were associated with EXACT score (p < 0.001). Three days prior to an exacerbation, RR increased by mean ± SD 2.0 ± 0.2 breaths/min for seven out of 11 exacerbations and HR increased by 8.1 ± 0.7 bpm for nine of these 11 exacerbations. CONCLUSIONS: Increased heart rate and reduced physical activity were associated with worsening symptoms. Even with high-resolution data, the variation in vital signs data remains a challenge for predicting AECOPDs. Respiratory rate and heart rate should be further explored as potential predictors of an impending AECOPD. TRIAL REGISTRATION: ISRCTN registry; ISRCTN12855961. Registered 07 November 2018-Retrospectively registered, https://www.isrctn.com/ISRCTN12855961.

Device-assessed sleep and physical activity in individuals recovering from a hospital admission for COVID-19: a multicentre study.

BACKGROUND: The number of individuals recovering from severe COVID-19 is increasing rapidly. However, little is known about physical behaviours that make up the 24-h cycle within these individuals. This study aimed to describe physical behaviours following hospital admission for COVID-19 at eight months post-discharge including associations with acute illness severity and ongoing symptoms. METHODS: One thousand seventy-seven patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and individuals with type 2 diabetes were comparators. RESULTS: Valid accelerometer data from 253 women and 462 men were included. Women engaged in a mean ± SD of 14.9 ± 14.7 min/day of moderate-to-vigorous physical activity (MVPA), with 12.1 ± 1.7 h/day spent inactive and 7.2 ± 1.1 h/day asleep. The values for men were 21.0 ± 22.3 and 12.6 ± 1.7 h /day and 6.9 ± 1.1 h/day, respectively. Over 60% of women and men did not have any days containing a 30-min bout of MVPA. Variability in sleep timing was approximately 2 h in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer total sleep time, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes. CONCLUSIONS: Those recovering from a hospital admission for COVID-19 have low levels of physical activity and disrupted patterns of sleep several months after discharge. Our comparative cohorts indicate that the long-term impact of COVID-19 on physical behaviours is significant.

Longitudinal changes to quadriceps thickness demonstrate acute sarcopenia following admission to hospital for an exacerbation of chronic respiratory disease.

Acute admission to hospital for an exacerbation of chronic respiratory disease (CRD) may impair skeletal muscle mass and function. We measured quadriceps thickness (Qthick), as a surrogate marker of muscle mass, at hospital admission, discharge, 6 weeks and 3 months in 55 patients with CRD. Qthick fell by 8.3% during the period of hospitalisation, which was sustained at 6 weeks, and only partially recovered at 3 months. Sustained loss was most marked in patients readmitted during the follow-up period. Acute reduction in quadriceps muscle mass occurs during hospitalisation, with prolonged and variable recovery, which is prevented with subsequent hospital readmission.

Breathomics for the clinician: the use of volatile organic compounds in respiratory diseases.

Exhaled breath analysis has the potential to provide valuable insight on the status of various metabolic pathways taking place in the lungs locally and other vital organs, via systemic circulation. For years, volatile organic compounds (VOCs) have been proposed as feasible alternative diagnostic and prognostic biomarkers for different respiratory pathologies.We reviewed the currently published literature on the discovery of exhaled breath VOCs and their utilisation in various respiratory diseasesKey barriers in the development of clinical breath tests include the lack of unified consensus for breath collection and analysis and the complexity of understanding the relationship between the exhaled VOCs and the underlying metabolic pathways. We present a comprehensive overview, in light of published literature and our experience from coordinating a national breathomics centre, of the progress made to date and some of the key challenges in the field and ways to overcome them. We particularly focus on the relevance of breathomics to clinicians and the valuable insights it adds to diagnostics and disease monitoring.Breathomics holds great promise and our findings merit further large-scale multicentre diagnostic studies using standardised protocols to help position this novel technology at the centre of respiratory disease diagnostics.

LabPipe: an extensible bioinformatics toolkit to manage experimental data and metadata.

BACKGROUND: Data handling in clinical bioinformatics is often inadequate. No freely available tools provide straightforward approaches for consistent, flexible metadata collection and linkage of related experimental data generated locally by vendor software. RESULTS: To address this problem, we created LabPipe, a flexible toolkit which is driven through a local client that runs alongside vendor software and connects to a light-weight server. The toolkit allows re-usable configurations to be defined for experiment metadata and local data collection, and handles metadata entry and linkage of data. LabPipe was piloted in a multi-site clinical breathomics study. CONCLUSIONS: LabPipe provided a consistent, controlled approach for handling metadata and experimental data collection, collation and linkage in the exemplar study and was flexible enough to deal effectively with different data handling challenges.

Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software.

Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful analytical tool for both nontargeted and targeted analyses. However, there is a need for more integrated workflows for processing and managing the resultant high-complexity datasets. End-to-end workflows for processing GC×GC data are challenging and often require multiple tools or software to process a single dataset. We describe a new approach, which uses an existing underutilized interface within commercial software to integrate free and open-source/external scripts and tools, tailoring the workflow to the needs of the individual researcher within a single software environment. To demonstrate the concept, the interface was successfully used to complete a first-pass alignment on a large-scale GC×GC metabolomics dataset. The analysis was performed by interfacing bespoke and published external algorithms within a commercial software environment to automatically correct the variation in retention times captured by a routine reference standard. Variation in 1tR and 2tR was reduced on average from 8 and 16% CV prealignment to less than 1 and 2% post alignment, respectively. The interface enables automation and creation of new functions and increases the interconnectivity between chemometric tools, providing a window for integrating data-processing software with larger informatics-based data management platforms.

Airway inflammation in COPD: progress to precision medicine.

Chronic obstructive pulmonary disease (COPD) is a significant cause of morbidity and mortality worldwide, and its prevalence is increasing. Airway inflammation is a consistent feature of COPD and is implicated in the pathogenesis and progression of COPD, but anti-inflammatory therapy is not first-line treatment. The inflammation has many guises and phenotyping this heterogeneity has revealed different patterns. Neutrophil-associated COPD with activation of the inflammasome, T1 and T17 immunity is the most common phenotype with eosinophil-associated T2-mediated immunity in a minority and autoimmunity observed in more severe disease. Biomarkers have enabled targeted anti-inflammatory strategies and revealed that corticosteroids are most effective in those with evidence of eosinophilic inflammation, whereas, in contrast to severe asthma, response to anti-interleukin-5 biologicals in COPD has been disappointing, with smaller benefits for the same intensity of eosinophilic inflammation questioning its role in COPD. Biological therapies beyond T2-mediated inflammation have not demonstrated benefit and in some cases increased risk of infection, suggesting that neutrophilic inflammation and inflammasome activation might be largely driven by bacterial colonisation and dysbiosis. Herein we describe current and future biomarker approaches to assess inflammation in COPD and how this might reveal tractable approaches to precision medicine and unmask important host-environment interactions leading to airway inflammation.

Rehabilitation in chronic respiratory diseases: In-hospital and post-exacerbation pulmonary rehabilitation.

Exacerbations of chronic obstructive pulmonary disease (COPD) that require hospitalization are important events for patients. Functional impairment and skeletal muscle dysfunction can increase the risk of hospitalization and readmission, independent of lung function. In addition, once a patient is admitted, multiple factors can lead to worsening outcome including immobility, systemic inflammation and nutritional depletion. These non-pulmonary factors are potentially amenable to exercise therapy, as part of pulmonary rehabilitation (PR). Peri-exacerbation PR has an important role in the management of exacerbations of COPD. In this review, we explore how functional limitation and skeletal muscle dysfunction affect patients having a severe exacerbation of COPD, the systemic impact of hospitalization on patients including potential aetiologies and the role of PR around the time of an exacerbation. This includes rehabilitation during the inpatient phase, post-exacerbation rehabilitation and rehabilitation bridging hospital discharge. We also describe potential future developments in peri-exacerbation PR.

Changes in physical activity during hospital admission for chronic respiratory disease.

BACKGROUND AND OBJECTIVE: Establishing the amount of inpatient physical activity (PA) undertaken by individuals hospitalized for chronic respiratory disease is needed to inform interventions. This observational study investigated whether PA changes when a person is an inpatient, how long is required to obtain representative PA measures and whether PA varies within a day and between patients of differing lengths of stay. METHODS: A total of 389 participants were recruited as early as possible into their hospitalization. Patients wore a PA monitor from recruitment until discharge. Step count was extracted for a range of wear time criteria. Single-day intraclass correlation coefficients (ICC) were calculated, with an ICC ≥ 0.80 deemed acceptable. RESULTS: PA data were available for 259 participants. No changes in daily step count were observed during the inpatient stay (586 (95% CI: 427-744) vs 652 (95% CI: 493-812) steps/day for day 2 and 7, respectively). ICC across all wear time criteria were > 0.80. The most stringent wear time criterion, retaining 80% of the sample, was ≥11 h on ≥1 day. More steps were taken during the morning and afternoon than overnight and evening. After controlling for the Medical Research Council (MRC) grade or oxygen use, there was no difference in step count between patients admitted for 2-3 days (short stay) and those admitted for 7-14 days (long stay). CONCLUSION: Patients move little during their hospitalization, and inpatient PA did not increase during their stay. A wear time criterion of 11 waking hours on any single day was representative of the entire admission whilst retaining an acceptable proportion of the initial sample size. Patients may need encouragement to move more during their hospital stay.

Prospective risk of osteoporotic fractures in patients with advanced chronic obstructive pulmonary disease.

Despite the high prevalence of osteoporosis in chronic obstructive pulmonary disease (COPD) patients, the fracture risk prediction tools are not routinely undertaken in the management of COPD. We quantified fracture risk using a validated risk prediction tool (Fracture Risk Assessment (FRAX®)) and determined potential bone-protection treatment needs in patients with advanced COPD. The 10-year probability of major osteoporotic or hip fracture was calculated using the FRAX tool in a cohort of patients attending a hospital complex COPD service. Patients were identified to be at low, intermediate and high risk based on their FRAX scores, in accordance with the National Osteoporosis Guideline Group recommendations, to assess the number of patients requiring bone mineral density (BMD) testing or bone protection therapy. Two hundred forty-seven patients [mean (standard deviation (SD)) age 66 (9.1) years, 26% current smokers, 40% women and median (interquartile range (IQR)) Medical Research Council (MRC) breathlessness scale 4 (0)] had a 10-year probability of 9.5% (6.1) and 3.8% (4.6) for major osteoporotic and hip fractures, respectively. Thirty-six percentage of patients were identified to be at intermediate risk of developing fragility fracture, requiring BMD assessment, while 9% were at high risk, requiring treatment. Thirty-two percentage of high-risk patients were on bisphosphonates. The FRAX score can be used to assess the fracture risk within the COPD cohort and assist with decision-making about BMD measurement and provision of bone protection therapy.

Influence of muscle mass in the assessment of lower limb strength in COPD: validation of the prediction equation.

Absence of established reference values limits application of quadriceps maximal voluntary contraction (QMVC) measurement. The impact of muscle mass inclusion in predictions is unclear. Prediction equations encompassing gender, age and size with (FFM+) and without (FFM-), derived in healthy adults (n=175), are presented and compared in two COPD cohorts recruited from primary care (COPD-PC, n=112) and a complex care COPD clinic (COPD-CC, n=189). Explained variance was comparable between the prediction models (R2: FFM+: 0.59, FFM-: 0.60) as were per cent predictions in COPD-PC (88.8%, 88.3%). However, fat-free mass inclusion reduced the prevalence of weakness in COPD, particularly in COPD-CC where 11.9% fewer were deemed weak.