1 King Faisal Specialist Hospital & Research Center, Jeddah, Saudi Arabia
2 Henry Ford Hospital, Detroit, MI, 48202, USA
3 Henry Ford Wyandotte Hospital, MI, 48192, USA
4 Oakwood Hospital and Medical Center, Dearborn, MI, 48124, USA
5 Wayne State University School of Medicine, Detroit, MI, 48201, USA
Different formulas have been proposed to exclude restriction based on spirometry, however none of them have specifically tested the patients whose spirometry show both obstruction and a low forced vital capacity (FVC).
The study was designed to create an algorithm that would better predict the absence of restriction in such patients.
Retrospective analysis of prospectively collected data.
A cohort of consecutive adults that underwent complete pulmonary function testing from 2002-2004 was analyzed. The data was randomly split into two groups to allow for derivation and then validation of a predictive formula. Patients were randomly assigned into either a “derivation” or “validation” group. In the derivation group, stepwise logistic regression was used to determine a formula and optimal cut-off value for the variable with the best discriminative capacity. The formula was applied subsequently to the validation group to test the results and compared to previously published formula.
The study group contained 766 patients. We determined that the variable with the highest association with TLC was [(FEV1/FVC) % predicted/FVC % predicted]. A value of ≥1.11 was found to be the maximal cutoff to predict the absence of restriction.
The formula was applied to a validation group (n=397) and performed better than prior published algorithm with a sensitivity, specificity, positive predictive value and negative predictive value of 95%, 44%, 22%, and 98%, respectively.
Our formula performs superior to the previously published algorithms in patients with concomitant low FVC and obstruction to exclude restriction.
Keywords: Algorithm, restriction, spirometry, total lung capacity..
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