44 research outputs found
Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals
Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of “modifiable risk factors”, measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details
Pilot study evaluating a brief mindfulness intervention for those with chronic pain: study protocol for a randomized controlled trial.
BACKGROUND: The burden of chronic pain is a major challenge, impacting the quality of life of patients. Intensive programmes of mindfulness-based therapy can help patients to cope with chronic pain but can be time consuming and require a trained specialist to implement. The self-management model of care is now integral to the care of patients with chronic pain; home-based interventions can be very acceptable, making a compelling argument for investigating brief, self-management interventions. The aim of this study is two-fold: to assess the immediate effects of a brief self-help mindfulness intervention for coping with chronic pain and to assess the feasibility of conducting a definitive randomized controlled trial to determine the effectiveness of such an intervention. METHODS/DESIGN: A randomized controlled pilot study will be conducted to evaluate a brief mindfulness intervention for those with chronic pain. Ninety chronic pain patients who attend hospital outpatient clinics will be recruited and allocated randomly to either the control or treatment group on a 1:1 basis using the computer-generated list of random numbers. The treatment group receives mindfulness audios and the control group receives audios of readings from a non-fiction book, all of which are 15 minutes in length. Immediate effects of the intervention are assessed with brief psychological measures immediately before and after audio use. Mindfulness, mood, health-related quality of life, pain catastrophizing and experience of the intervention are assessed with standardized measures, brief ratings and brief telephone follow-ups, at baseline and after one week and one month. Feasibility is assessed by estimation of effect sizes for outcomes, patient adherence and experience, and appraisal of resource allocation in provision of the intervention. DISCUSSION: This trial will assess whether a brief mindfulness-based intervention is effective for immediately reducing perceived distress and pain with the side effect of increasing relaxation in chronic pain patients and will determine the feasibility of conducting a definitive randomized controlled trial. Patient recruitment began in January 2015 and is due to be completed in June 2016. TRIAL REGISTRATION: ISRCTN61538090 Registered 20 April 2015
Opsonic phagocytosis in chronic obstructive pulmonary disease is enhanced by Nrf2 agonists
Rationale: Previous studies have identified defects in bacterial phagocytosis by alveolar macrophages (AM) in patients with chronic obstructive pulmonary disease (COPD) but the mechanisms and clinical consequences remain incompletely defined.
Objectives: To examine the effect of COPD on AM phagocytic responses and identify the mechanisms, clinical consequences and potential for therapeutic manipulation of these defects.
Methods: We isolated alveolar macrophages (AM) and monocyte-derived macrophages (MDM) from a cohort of COPD patients and controls within the MRC COPD-MAP consortium and measured phagocytosis of bacteria in relation to opsonic conditions and clinical features.
Measurements and Main Results: COPD AM and MDM have impaired phagocytosis of S. pneumoniae. COPD AM have a selective defect in uptake of opsonized bacteria, despite the presence of anti-pneumococcal antibodies in bronchoalveolar lavage, not observed in MDM or healthy donor’s AM. AM defects in phagocytosis in COPD are significantly associated with exacerbation frequency, isolation of pathogenic bacteria and health related quality of life scores. Bacterial binding and initial intracellular killing of opsonized bacteria in COPD AM was not reduced. COPD AM have reduced transcriptional responses to opsonized bacteria, including cellular stress responses that include transcriptional modules involving antioxidant defenses and Nrf2-regualted genes. Agonists of the cytoprotective transcription factor Nrf2 (sulforaphane and Compound) reverse defects in phagocytosis of S. pneumoniae and non-type able Haemophilus influenzae by COPD.
Conclusions: Patients with COPD have clinically relevant defects in opsonic phagocytosis by AM, associated with impaired transcriptional responses to cellular stress, which are reversed by therapeutic targeting with Nrf2 agonists
Prostanoid receptor EP1 and Cox-2 in injured human nerves and a rat model of nerve injury: a time-course study
BACKGROUND: Recent studies show that inflammatory processes may contribute to neuropathic pain. Cyclooxygenase-2 (Cox-2) is an inducible enzyme responsible for production of prostanoids, which may sensitise sensory neurones via the EP1 receptor. We have recently reported that while macrophages infiltrate injured nerves within days of injury, they express increased Cox-2-immunoreactivity (Cox-2-IR) from 2 to 3 weeks after injury. We have now investigated the time course of EP1 and Cox-2 changes in injured human nerves and dorsal root ganglia (DRG), and the chronic constriction nerve injury (CCI) model in the rat. METHODS: Tissue sections were immunostained with specific antibodies to EP1, Cox-2, CD68 (human macrophage marker) or OX42 (rat microglial marker), and neurofilaments (NF), prior to image analysis, from the following: human brachial plexus nerves (21 to 196 days post-injury), painful neuromas (9 days to 12 years post-injury), avulsion injured DRG, control nerves and DRG, and rat CCI model tissues. EP1 and NF-immunoreactive nerve fibres were quantified by image analysis. RESULTS: EP1:NF ratio was significantly increased in human brachial plexus nerve fibres, both proximal and distal to injury, in comparison with uninjured nerves. Sensory neurones in injured human DRG showed a significant acute increase of EP1-IR intensity. While there was a rapid increase in EP1-fibres and CD-68 positive macrophages, Cox-2 increase was apparent later, but was persistent in human painful neuromas for years. A similar time-course of changes was found in the rat CCI model with the above markers, both in the injured nerves and ipsilateral dorsal spinal cord. CONCLUSION: Different stages of infiltration and activation of macrophages may be observed in the peripheral and central nervous system following peripheral nerve injury. EP1 receptor level increase in sensory neurones, and macrophage infiltration, appears to precede increased Cox-2 expression by macrophages. However, other methods for detecting Cox-2 levels and activity are required. EP1 antagonists may show therapeutic effects in acute and chronic neuropathic pain, in addition to inflammatory pain
Effects of sleep disturbance on dyspnoea and impaired lung function following hospital admission due to COVID-19 in the UK:a prospective multicentre cohort study
BACKGROUND: Sleep disturbance is common following hospital admission both for COVID-19 and other causes. The clinical associations of this for recovery after hospital admission are poorly understood despite sleep disturbance contributing to morbidity in other scenarios. We aimed to investigate the prevalence and nature of sleep disturbance after discharge following hospital admission for COVID-19 and to assess whether this was associated with dyspnoea. METHODS: CircCOVID was a prospective multicentre cohort substudy designed to investigate the effects of circadian disruption and sleep disturbance on recovery after COVID-19 in a cohort of participants aged 18 years or older, admitted to hospital for COVID-19 in the UK, and discharged between March, 2020, and October, 2021. Participants were recruited from the Post-hospitalisation COVID-19 study (PHOSP-COVID). Follow-up data were collected at two timepoints: an early time point 2-7 months after hospital discharge and a later time point 10-14 months after hospital discharge. Sleep quality was assessed subjectively using the Pittsburgh Sleep Quality Index questionnaire and a numerical rating scale. Sleep quality was also assessed with an accelerometer worn on the wrist (actigraphy) for 14 days. Participants were also clinically phenotyped, including assessment of symptoms (ie, anxiety [Generalised Anxiety Disorder 7-item scale questionnaire], muscle function [SARC-F questionnaire], dyspnoea [Dyspnoea-12 questionnaire] and measurement of lung function), at the early timepoint after discharge. Actigraphy results were also compared to a matched UK Biobank cohort (non-hospitalised individuals and recently hospitalised individuals). Multivariable linear regression was used to define associations of sleep disturbance with the primary outcome of breathlessness and the other clinical symptoms. PHOSP-COVID is registered on the ISRCTN Registry (ISRCTN10980107). FINDINGS: 2320 of 2468 participants in the PHOSP-COVID study attended an early timepoint research visit a median of 5 months (IQR 4-6) following discharge from 83 hospitals in the UK. Data for sleep quality were assessed by subjective measures (the Pittsburgh Sleep Quality Index questionnaire and the numerical rating scale) for 638 participants at the early time point. Sleep quality was also assessed using device-based measures (actigraphy) a median of 7 months (IQR 5-8 months) after discharge from hospital for 729 participants. After discharge from hospital, the majority (396 [62%] of 638) of participants who had been admitted to hospital for COVID-19 reported poor sleep quality in response to the Pittsburgh Sleep Quality Index questionnaire. A comparable proportion (338 [53%] of 638) of participants felt their sleep quality had deteriorated following discharge after COVID-19 admission, as assessed by the numerical rating scale. Device-based measurements were compared to an age-matched, sex-matched, BMI-matched, and time from discharge-matched UK Biobank cohort who had recently been admitted to hospital. Compared to the recently hospitalised matched UK Biobank cohort, participants in our study slept on average 65 min (95% CI 59 to 71) longer, had a lower sleep regularity index (-19%; 95% CI -20 to -16), and a lower sleep efficiency (3·83 percentage points; 95% CI 3·40 to 4·26). Similar results were obtained when comparisons were made with the non-hospitalised UK Biobank cohort. Overall sleep quality (unadjusted effect estimate 3·94; 95% CI 2·78 to 5·10), deterioration in sleep quality following hospital admission (3·00; 1·82 to 4·28), and sleep regularity (4·38; 2·10 to 6·65) were associated with higher dyspnoea scores. Poor sleep quality, deterioration in sleep quality, and sleep regularity were also associated with impaired lung function, as assessed by forced vital capacity. Depending on the sleep metric, anxiety mediated 18-39% of the effect of sleep disturbance on dyspnoea, while muscle weakness mediated 27-41% of this effect. INTERPRETATION: Sleep disturbance following hospital admission for COVID-19 is associated with dyspnoea, anxiety, and muscle weakness. Due to the association with multiple symptoms, targeting sleep disturbance might be beneficial in treating the post-COVID-19 condition. FUNDING: UK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council
Effects of sleep disturbance on dyspnoea and impaired lung function following hospital admission due to COVID-19 in the UK: a prospective multicentre cohort study
BACKGROUND: Sleep disturbance is common following hospital admission both for COVID-19 and other causes. The clinical associations of this for recovery after hospital admission are poorly understood despite sleep disturbance contributing to morbidity in other scenarios. We aimed to investigate the prevalence and nature of sleep disturbance after discharge following hospital admission for COVID-19 and to assess whether this was associated with dyspnoea. METHODS: CircCOVID was a prospective multicentre cohort substudy designed to investigate the effects of circadian disruption and sleep disturbance on recovery after COVID-19 in a cohort of participants aged 18 years or older, admitted to hospital for COVID-19 in the UK, and discharged between March, 2020, and October, 2021. Participants were recruited from the Post-hospitalisation COVID-19 study (PHOSP-COVID). Follow-up data were collected at two timepoints: an early time point 2-7 months after hospital discharge and a later time point 10-14 months after hospital discharge. Sleep quality was assessed subjectively using the Pittsburgh Sleep Quality Index questionnaire and a numerical rating scale. Sleep quality was also assessed with an accelerometer worn on the wrist (actigraphy) for 14 days. Participants were also clinically phenotyped, including assessment of symptoms (ie, anxiety [Generalised Anxiety Disorder 7-item scale questionnaire], muscle function [SARC-F questionnaire], dyspnoea [Dyspnoea-12 questionnaire] and measurement of lung function), at the early timepoint after discharge. Actigraphy results were also compared to a matched UK Biobank cohort (non-hospitalised individuals and recently hospitalised individuals). Multivariable linear regression was used to define associations of sleep disturbance with the primary outcome of breathlessness and the other clinical symptoms. PHOSP-COVID is registered on the ISRCTN Registry (ISRCTN10980107). FINDINGS: 2320 of 2468 participants in the PHOSP-COVID study attended an early timepoint research visit a median of 5 months (IQR 4-6) following discharge from 83 hospitals in the UK. Data for sleep quality were assessed by subjective measures (the Pittsburgh Sleep Quality Index questionnaire and the numerical rating scale) for 638 participants at the early time point. Sleep quality was also assessed using device-based measures (actigraphy) a median of 7 months (IQR 5-8 months) after discharge from hospital for 729 participants. After discharge from hospital, the majority (396 [62%] of 638) of participants who had been admitted to hospital for COVID-19 reported poor sleep quality in response to the Pittsburgh Sleep Quality Index questionnaire. A comparable proportion (338 [53%] of 638) of participants felt their sleep quality had deteriorated following discharge after COVID-19 admission, as assessed by the numerical rating scale. Device-based measurements were compared to an age-matched, sex-matched, BMI-matched, and time from discharge-matched UK Biobank cohort who had recently been admitted to hospital. Compared to the recently hospitalised matched UK Biobank cohort, participants in our study slept on average 65 min (95% CI 59 to 71) longer, had a lower sleep regularity index (-19%; 95% CI -20 to -16), and a lower sleep efficiency (3·83 percentage points; 95% CI 3·40 to 4·26). Similar results were obtained when comparisons were made with the non-hospitalised UK Biobank cohort. Overall sleep quality (unadjusted effect estimate 3·94; 95% CI 2·78 to 5·10), deterioration in sleep quality following hospital admission (3·00; 1·82 to 4·28), and sleep regularity (4·38; 2·10 to 6·65) were associated with higher dyspnoea scores. Poor sleep quality, deterioration in sleep quality, and sleep regularity were also associated with impaired lung function, as assessed by forced vital capacity. Depending on the sleep metric, anxiety mediated 18-39% of the effect of sleep disturbance on dyspnoea, while muscle weakness mediated 27-41% of this effect. INTERPRETATION: Sleep disturbance following hospital admission for COVID-19 is associated with dyspnoea, anxiety, and muscle weakness. Due to the association with multiple symptoms, targeting sleep disturbance might be beneficial in treating the post-COVID-19 condition. FUNDING: UK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council
Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis
Cellular decision-making is mediated by a complex interplay of external stimuli with the intracellular environment, in particular transcription factor regulatory networks. Here we have determined the expression of a network of 18 key haematopoietic transcription factors in 597 single primary blood stem and progenitor cells isolated from mouse bone marrow. We demonstrate that different stem/progenitor populations are characterized by distinctive transcription factor expression states, and through comprehensive bioinformatic analysis reveal positively and negatively correlated transcription factor pairings, including previously unrecognized relationships between Gata2, Gfi1 and Gfi1b. Validation using transcriptional and transgenic assays confirmed direct regulatory interactions consistent with a regulatory triad in immature blood stem cells, where Gata2 may function to modulate cross-inhibition between Gfi1 and Gfi1b. Single-cell expression profiling therefore identifies network states and allows reconstruction of network hierarchies involved in controlling stem cell fate choices, and provides a blueprint for studying both normal development and human disease
Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus
A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk
AI is a viable alternative to high throughput screening: a 318-target study
: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery