Abstract
Background: Air trapping and lung hyperinflation are major determinants of prognosis and response to therapy in chronic obstructive pulmonary disease (COPD). They are often determined by body plethysmography, which has limited availability, and so the question arises as to what extent they can be estimated via spirometry. Methods: We used data from visits 1-5 of the COPD cohort COSYCONET. Predictive parameters were derived from visit 1 data, while visit 2-5 data was used to assess reproducibility. Pooled data then yielded prediction models including sex, age, height, and body mass index as covariates. Hyperinflation was defined as ratio of residual volume (RV) to total lung capacity (TLC) above the upper limit of normal. (ClinicalTrials.gov identifier: NCT01245933). Results: Visit 1 data from 1988 patients (Global Initiative for Chronic Obstructive Lung Disease grades 1-4, n=187, 847, 766, 188, respectively) were available for analysis (n=1231 males, 757 females;mean +/- SD age 65.1 +/- 8.4 years;forced expiratory volume in 1 s (FEV1) 53.1 +/- 18.4 % predicted (% pred);forced vital capacity (FVC) 78.8 +/- 18.8 % pred;RV/TLC 0.547 +/- 0.107). In total, 7157 datasets were analysed. Among measures of hyperinflation, RV/TLC showed the closest relationship to FEV1 % pred and FVC % pred, which were sufficient for prediction. Their relationship to RV/TLC could be depicted in nomograms. Even when neglecting covariates, hyperinflation was predicted by FEV1 % pred, FVC % pred or their combination with an area under the curve of 0.870, 0.864 and 0.889, respectively. Conclusions: The degree of air trapping/hyperinflation in terms of RV/TLC can be estimated in a simple manner from forced spirometry, with an accuracy sufficient for inferring the presence of hyperinflation. This may be useful for clinical settings, where body plethysmography is not available.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin > Institut und Poliklinik für Arbeits-, Sozial- und Umweltmedizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
Sprache: | Englisch |
Dokumenten ID: | 87018 |
Datum der Veröffentlichung auf Open Access LMU: | 25. Jan. 2022, 09:22 |
Letzte Änderungen: | 22. Jul. 2024, 05:32 |