24 research outputs found

    COPD_BERGEN_Fastq175

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    Resulting Illumina fastq files from 175 sputum samples collected as part of the Bergen COPD Cohort Study (BCCS) and its adjunct Bergen COPD Exacerbation Study (BCES)

    Mosaic plots of the FEV<sub>1</sub>% dynamic classes.

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    <p>Mosaic plots were used to assess positive or negative associations between clinical phenotypes and FEV<sub>1</sub> dynamic classes with other categorical variables. Since width and length of the boxes are proportional to the observed frequencies in the datasets, the area of the boxes represent the proportion of subjects that share the attributes. To the extent that the observed proportions of subjects differs from expected proportions, the boxes are shaded to different levels of Pearson residuals. The associations between FEV<sub>1</sub>% Dynamic Class with MDCPs and gender in the CF cohort are shown (A). The associations between FEV<sub>1</sub>% Dynamic Class, COPD GOLD grades and either MMRC dyspnea scores or pulmonary exacerbations are depicted (B,C).</p

    FEV<sub>1</sub>% dynamic variables in CF and COPD clinical phenotypes.

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    <p>Notched boxplots of the FEV<sub>1</sub>% dynamic variables for CF (A) and COPD (B) subjects are shown for each CF MDCP class and COPD GOLD grade.</p

    Spaghetti plots of the BCCS COPD cohort.

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    <p>This figure was similarly labeled as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190061#pone.0190061.g004" target="_blank">Fig 4</a>.</p

    Spaghetti plots of the regional CF cohort.

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    <p>The individual estimated median regression splines and their predicted first and second derivatives are depicted in the three CF FEV<sub>1</sub>% Dynamic Classes. A thousand equally spaced values of the estimated median regression spline and their predicted first and second derivatives were plotted for each subject in each FEV<sub>1</sub>% dynamic class (thin grey lines). The mean value at each interval point is plotted as the black solid line.</p

    Distribution of physiologic variables of CF and COPD subjects in the FEV<sub>1</sub>% dynamic classes.

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    <p>Notched boxplots of age, AF product, BMI and slope of the least-squares trend line are shown for CF (6A-D) and COPD (6E-H) subjects in the FEV<sub>1</sub>% Dynamic Classes. Also shown is the distribution of the median difference between best FEV<sub>1</sub>% (CF subjects) and the MMRC dyspnea score (COPD subjects).</p

    Median regression spline modeling of longitudinal FEV<sub>1</sub> measurements in cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) patients

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    <div><p>Rationale</p><p>Clinical phenotyping, therapeutic investigations as well as genomic, airway secretion metabolomic and metagenomic investigations can benefit from robust, nonlinear modeling of FEV<sub>1</sub> in <i>individual</i> subjects. We demonstrate the utility of measuring FEV<sub>1</sub> dynamics in representative cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) populations.</p><p>Methods</p><p>Individual FEV<sub>1</sub> data from CF and COPD subjects were modeled by estimating median regression splines and their predicted first and second derivatives. Classes were created from variables that capture the dynamics of these curves in both cohorts.</p><p>Results</p><p>Nine FEV<sub>1</sub> dynamic variables were identified from the splines and their predicted derivatives in individuals with CF (n = 177) and COPD (n = 374). Three FEV<sub>1</sub> dynamic classes (i.e. stable, intermediate and hypervariable) were generated and described using these variables from both cohorts. In the CF cohort, the FEV<sub>1</sub> hypervariable class (HV) was associated with a clinically unstable, female-dominated phenotypes while stable FEV<sub>1</sub> class (S) individuals were highly associated with the male-dominated milder clinical phenotype. In the COPD cohort, associations were found between the FEV<sub>1</sub> dynamic classes, the COPD GOLD grades, with exacerbation frequency and symptoms.</p><p>Conclusion</p><p>Nonlinear modeling of FEV<sub>1</sub> with splines provides new insights and is useful in characterizing CF and COPD clinical phenotypes.</p></div

    Clinical phenotype characterization.

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    <p>Notched boxplots of basic clinical and physiological characteristics of the CF (Fig 1A) and COPD (Fig 1B) cohorts. Each subject was mapped to either a MDCP class [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190061#pone.0190061.ref013" target="_blank">13</a>] or COPD GOLD grade. The AF product of an individual is the age at the most recent FEV<sub>1</sub> multiplied by the best FEV<sub>1</sub>% during the study period. The linear slope is the slope of the least squares trendline fitted to the FEV<sub>1</sub> data during the study period.</p

    CF and COPD FEV<sub>1</sub>% dynamic classes classifying variables.

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    <p>Notched boxplots demonstrate the distribution of FEV<sub>1</sub>% dynamic classifying variables for CF and COPD subjects in each of the FEV<sub>1</sub>% Dynamic Classes, i.e. stable (S), intermediate (I) and hypervariable (HV).</p
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