11 research outputs found

    BODE-Index vs HADO-Score in Chronic Obstructive Pulmonary Disease: Which one to use in general practice?

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    <p>Abstract</p> <p>Background</p> <p>Forced expiratory volume in one second (FEV<sub>1</sub>) is used to diagnose and establish a prognosis in chronic obstructive pulmonary disease (COPD). Using multi-dimensional scores improves this predictive capacity.Two instruments, the BODE-index (<b>B</b>ody mass index, <b>O</b>bstruction, <b>D</b>yspnea, <b>E</b>xercise capacity) and the HADO-score (<b>H</b>ealth, <b>A</b>ctivity, <b>D</b>yspnea, <b>O</b>bstruction), were compared in the prediction of mortality among COPD patients.</p> <p>Methods</p> <p>This is a prospective longitudinal study. During one year (2003 to 2004), 543 consecutively COPD patients were recruited in five outpatient clinics and followed for three years. The endpoints were all-causes and respiratory mortality.</p> <p>Results</p> <p>In the multivariate analysis of patients with FEV<sub>1 </sub>< 50%, no significant differences were observed in all-cause or respiratory mortality across HADO categories, while significant differences were observed between patients with a lower BODE (less severe disease) and those with a higher BODE (greater severity). Among patients with FEV<sub>1 </sub>≥ 50%, statistically significant differences were observed across HADO categories for all-cause and respiratory mortality, while differences were observed across BODE categories only in all-cause mortality.</p> <p>Conclusions</p> <p>HADO-score and BODE-index were good predictors of all-cause and respiratory mortality in the entire cohort. In patients with severe COPD (FEV<sub>1 </sub>< 50%) the BODE index was a better predictor of mortality whereas in patients with mild or moderate COPD (FEV<sub>1 </sub>≥ 50%), the HADO-score was as good a predictor of respiratory mortality as the BODE-index. These differences suggest that the HADO-score and BODE-index could be used for different patient populations and at different healthcare levels, but can be used complementarily.</p

    Map of clusters and distribution of patients.

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    <p>Map created by the first and second components derived from the MCA is shown at the center. Four circles at the sides show how patients move between clusters after one year of follow-up. Relative positions of the subjects in the planes are represented by different colors, depending on the subtype provided by the cluster analysis. Definition of the axes is suggested based on information provided in appendix Table A1. The horizontal axis, first component, can be defined as an index of the respiratory conditions of the patient, milder (left side) vs. more severe (right side). The vertical axis, second component, can be defined as an index of the systemic status, worse (bottom) vs. better (top).</p

    Partial dendrogram obtained from the cluster analysis.

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    <p>The dendogram represents the results from the cluster analysis performed with the four components obtained from the multiple correspondence analysis. The graphical display includes an easy interpretation of the partition and a brief description of the resulting clusters.</p
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