Level of daily physical activity in individuals with COPD compared with healthy controls

<p>Abstract</p> <p>Background</p> <p>Persons with Chronic Obstructive Pulmonary Disease (COPD), performing some level of regular physical activity, have a lower risk of both COPD-related hospital admissions and mortality. COPD patients of all stages seem to benefit from exercise training programs, thereby improving with respect to both exercise tolerance and symptoms of dyspnea and fatigue. Physical inactivity, which becomes more severe with increasing age, is a point of concern in healthy older adults. COPD might worsen this scenario, but it is unclear to what degree. This literature review aims to present the extent of the impact of COPD on objectively-measured daily physical activity (DPA). The focus is on the extent of the impact that COPD has on duration, intensity, and counts of DPA, as well as whether the severity of the disease has an additional influence on DPA.</p> <p>Results</p> <p>A literature review was performed in the databases PubMed [MEDLINE], Picarta, PEDRO, ISI Web of Knowledge and Google scholar. After screening, 11 studies were identified as being relevant for comparison between COPD patients and healthy controls with respect to duration, intensity, and counts of DPA. Four more studies were found to be relevant to address the subject of the influence the severity of the disease may have on DPA. The average percentage of DPA of COPD patients vs. healthy control subjects for duration was 57%, for intensity 75%, and for activity counts 56%. Correlations of DPA and severity of the disease were low and/or not significant.</p> <p>Conclusions</p> <p>From the results of this review, it appears that patients with COPD have a significantly reduced duration, intensity, and counts of DPA when compared to healthy control subjects. The intensity of DPA seems to be less affected by COPD than duration and counts. Judging from the results, it seems that severity of COPD is not strongly correlated with level of DPA. Future research should focus in more detail on the relation between COPD and duration, intensity, and counts of DPA, as well as the effect of disease severity on DPA, so that these relations become more understandable.</p

The validity of using ICD-9 codes and pharmacy records to identify patients with chronic obstructive pulmonary disease

Background: Administrative data is often used to identify patients with chronic obstructive pulmonary disease (COPD), yet the validity of this approach is unclear. We sought to develop a predictive model utilizing administrative data to accurately identify patients with COPD. Methods: Sequential logistic regression models were constructed using 9573 patients with postbronchodilator spirometry at two Veterans Affairs medical centers (2003-2007). COPD was defined as: 1) FEV1/FVC <0.70, and 2) FEV1/FVC < lower limits of normal. Model inputs included age, outpatient or inpatient COPD-related ICD-9 codes, and the number of metered does inhalers (MDI) prescribed over the one year prior to and one year post spirometry. Model performance was assessed using standard criteria. Results: 4564 of 9573 patients (47.7%) had an FEV1/FVC < 0.70. The presence of ≥1 outpatient COPD visit had a sensitivity of 76% and specificity of 67%; the AUC was 0.75 (95% CI 0.74-0.76). Adding the use of albuterol MDI increased the AUC of this model to 0.76 (95% CI 0.75-0.77) while the addition of ipratropium bromide MDI increased the AUC to 0.77 (95% CI 0.76-0.78). The best performing model included: ≥6 albuterol MDI, ≥3 ipratropium MDI, ≥1 outpatient ICD-9 code, ≥1 inpatient ICD-9 code, and age, achieving an AUC of 0.79 (95% CI 0.78-0.80). Conclusion: Commonly used definitions of COPD in observational studies misclassify the majority of patients as having COPD. Using multiple diagnostic codes in combination with pharmacy data improves the ability to accurately identify patients with COPD.Department of Veterans Affairs, Health Services Research and Development (DHA), American Lung Association (CI- 51755-N) awarded to DHA, the American Thoracic Society Fellow Career Development AwardPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/84155/1/Cooke - ICD9 validity in COPD.pd

A re-randomisation design for clinical trials

Background: Recruitment to clinical trials is often problematic, with many trials failing to recruit to their target sample size. As a result, patient care may be based on suboptimal evidence from underpowered trials or non-randomised studies. Methods: For many conditions patients will require treatment on several occasions, for example, to treat symptoms of an underlying chronic condition (such as migraines, where treatment is required each time a new episode occurs), or until they achieve treatment success (such as fertility, where patients undergo treatment on multiple occasions until they become pregnant). We describe a re-randomisation design for these scenarios, which allows each patient to be independently randomised on multiple occasions. We discuss the circumstances in which this design can be used. Results: The re-randomisation design will give asymptotically unbiased estimates of treatment effect and correct type I error rates under the following conditions: (a) patients are only re-randomised after the follow-up period from their previous randomisation is complete; (b) randomisations for the same patient are performed independently; and (c) the treatment effect is constant across all randomisations. Provided the analysis accounts for correlation between observations from the same patient, this design will typically have higher power than a parallel group trial with an equivalent number of observations. Conclusions: If used appropriately, the re-randomisation design can increase the recruitment rate for clinical trials while still providing an unbiased estimate of treatment effect and correct type I error rates. In many situations, it can increase the power compared to a parallel group design with an equivalent number of observations

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Biologic Phenotyping of the Human Small Airway Epithelial Response to Cigarette Smoking

BACKGROUND: The first changes associated with smoking are in the small airway epithelium (SAE). Given that smoking alters SAE gene expression, but only a fraction of smokers develop chronic obstructive pulmonary disease (COPD), we hypothesized that assessment of SAE genome-wide gene expression would permit biologic phenotyping of the smoking response, and that a subset of healthy smokers would have a "COPD-like" SAE transcriptome. METHODOLOGY/PRINCIPAL FINDINGS: SAE (10th-12th generation) was obtained via bronchoscopy of healthy nonsmokers, healthy smokers and COPD smokers and microarray analysis was used to identify differentially expressed genes. Individual responsiveness to smoking was quantified with an index representing the % of smoking-responsive genes abnormally expressed (I(SAE)), with healthy smokers grouped into "high" and "low" responders based on the proportion of smoking-responsive genes up- or down-regulated in each smoker. Smokers demonstrated significant variability in SAE transcriptome with I(SAE) ranging from 2.9 to 51.5%. While the SAE transcriptome of "low" responder healthy smokers differed from both "high" responders and smokers with COPD, the transcriptome of the "high" responder healthy smokers was indistinguishable from COPD smokers. CONCLUSION/SIGNIFICANCE: The SAE transcriptome can be used to classify clinically healthy smokers into subgroups with lesser and greater responses to cigarette smoking, even though these subgroups are indistinguishable by clinical criteria. This identifies a group of smokers with a "COPD-like" SAE transcriptome

Barriers and facilitators of effective self-management in asthma: systematic review and thematic synthesis of patient and healthcare professional views

Self-management is an established, effective approach to controlling asthma, recommended in guidelines. However, promotion, uptake and use among patients and health-care professionals remain low. Many barriers and facilitators to effective self-management have 25 been reported, and views and beliefs of patients and health care professionals have been explored in qualitative studies. We conducted a systematic review and thematic synthesis of qualitative research into self-management in patients, carers and health care professionals regarding self-management of asthma, to identify perceived barriers and facilitators associated with reduced effectiveness of asthma self-management interventions. Electronic databases and guidelines were searched systematically for qualitative literature that explored factors relevant to facilitators and barriers to uptake, adherence, or outcomes of self-management in patients with asthma. Thematic synthesis of the 56 included studies identified 11 themes: 1) partnership between patient and health care professional; 2) issues around medication; 3) education about asthma and its management; 4) health beliefs; 5) self-management interventions; 6) co-morbidities 7) mood disorders and anxiety; 8) social support; 9) non-pharmacological methods; 10) access to healthcare; 11) professional factors. From this, perceived barriers and facilitators were identified at the level of individuals with asthma (and carers), and health-care professionals. Future work addressing the concerns and beliefs of adults, adolescents and children (and carers) with asthma, effective communication and partnership, tailored support and education (including for ethnic minorities and at risk groups), and telehealthcare may improve how self-management is recommended by professionals and used by patients. Ultimately, this may achieve better outcomes for people with asthma

Interleukin-6 Contributes to Inflammation and Remodeling in a Model of Adenosine Mediated Lung Injury

Chronic lung diseases are the third leading cause of death in the United States due in part to an incomplete understanding of pathways that govern the progressive tissue remodeling that occurs in these disorders. Adenosine is elevated in the lungs of animal models and humans with chronic lung disease where it promotes air-space destruction and fibrosis. Adenosine signaling increases the production of the pro-fibrotic cytokine interleukin-6 (IL-6). Based on these observations, we hypothesized that IL-6 signaling contributes to tissue destruction and remodeling in a model of chronic lung disease where adenosine levels are elevated.We tested this hypothesis by neutralizing or genetically removing IL-6 in adenosine deaminase (ADA)-deficient mice that develop adenosine dependent pulmonary inflammation and remodeling. Results demonstrated that both pharmacologic blockade and genetic removal of IL-6 attenuated pulmonary inflammation, remodeling and fibrosis in this model. The pursuit of mechanisms involved revealed adenosine and IL-6 dependent activation of STAT-3 in airway epithelial cells.These findings demonstrate that adenosine enhances IL-6 signaling pathways to promote aspects of chronic lung disease. This suggests that blocking IL-6 signaling during chronic stages of disease may provide benefit in halting remodeling processes such as fibrosis and air-space destruction

Down-Regulation of the Canonical Wnt β-Catenin Pathway in the Airway Epithelium of Healthy Smokers and Smokers with COPD

Background: The Wnt pathway mediates differentiation of epithelial tissues; depending on the tissue types, Wnt can either drive or inhibit the differentiation process. We hypothesized that key genes in the Wnt pathway are suppressed in the human airway epithelium under the stress of cigarette smoking, a stress associated with dysregulation of the epithelial differentiated state. Methodology/Principal Findings: Microarrays were used to assess the expression of Wnt-related genes in the small airway epithelium (SAE) obtained via bronchoscopy and brushing of healthy nonsmokers, healthy smokers, and smokers with COPD. Thirty-three of 56 known Wnt-related genes were expressed in the SAE. Wnt pathway downstream mediators b-catenin and the transcription factor 7-like 1 were down-regulated in healthy smokers and smokers with COPD, as were many Wnt target genes. Among the extracellular regulators that suppress the Wnt pathway, secreted frizzled-related protein 2 (SFRP2), was up-regulated 4.3-fold in healthy smokers and 4.9-fold in COPD smokers, an observation confirmed by TaqMan Real-time PCR, Western analysis and immunohistochemistry. Finally, cigarette smoke extract mediated up-regulation of SFRP2 and down-regulation of Wnt target genes in airway epithelial cells in vitro. Conclusions/Significance: Smoking down-regulates the Wnt pathway in the human airway epithelium. In the context that Wnt pathway plays an important role in differentiation of epithelial tissues, the down-regulation of Wnt pathway ma

Rare Variant Analysis of Human and Rodent Obesity Genes in Individuals with Severe Childhood Obesity

Obesity is a genetically heterogeneous disorder. Using targeted and whole-exome sequencing, we studied 32 human and 87 rodent obesity genes in 2,548 severely obese children and 1,117 controls. We identified 52 variants contributing to obesity in 2% of cases including multiple novel variants in GNAS, which were sometimes found with accelerated growth rather than short stature as described previously. Nominally significant associations were found for rare functional variants in BBS1, BBS9, GNAS, MKKS, CLOCK and ANGPTL6. The p.S284X variant in ANGPTL6 drives the association signal (rs201622589, MAF∼0.1%, odds ratio = 10.13, p-value = 0.042) and results in complete loss of secretion in cells. Further analysis including additional case-control studies and population controls (N = 260,642) did not support association of this variant with obesity (odds ratio = 2.34, p-value = 2.59 × 10 -3 ), highlighting the challenges of testing rare variant associations and the need for very large sample sizes. Further validation in cohorts with severe obesity and engineering the variants in model organisms will be needed to explore whether human variants in ANGPTL6 and other genes that lead to obesity when deleted in mice, do contribute to obesity. Such studies may yield druggable targets for weight loss therapies