SESSION TITLE: Pulmonary Physiology Posters
SESSION TYPE: Original Investigation Poster
PRESENTED ON: Wednesday, October 28, 2015 at 01:30 PM - 02:30 PM
PURPOSE: Normal values for pulmonary function testing (PFT) can vary widely, depending on age, gender, race, and size. Differentiating between low-normal lung function and mild pulmonary disease can be challenging. Therefore, the use of equations that will accurately predict normal PFT values is critical. Many equations have been created to predict normal PFT reference values for a wide range of populations. The applicability of existing equations to a population of military aviators is unknown. The purpose of our study was to create a set of equations that could be used to predict normal PFT values in United States Air Force (USAF) aviators.
METHODS: The USAF School of Aerospace Medicine has traditionally required PFTs, as part of a comprehensive aircrew medical evaluation. As a result, many aviators with no history of lung disease have had PFTs. We reviewed PFT data in U.S. Air Force aviators from 1968 - 2012. Those with lung disease, pulmonary symptoms, or a history of tobacco use were excluded. Regression analyses were used to create predictive equations for normal PFT values. Separate equations were developed for males and females for each of the following ethnic groups: African American, Asian/Pacific Islander, Caucasian, and Hispanic. Lung volumes were measured using helium dilution.
RESULTS: 15,838 PFTs were collected on individuals ranging from 17-74 years of age. 9,356 of these PFTs contained lung volume measurements. 10,144 contained diffusion capacity (DLCO) determinations. 3,469 lung volume and 3,936 DLCO measurements were used in the final analysis. The majority of our subjects were Caucasian males. Females and minorities were represented, though in some subsets, the number of subjects was too small to calculate predictive equations.
CONCLUSIONS: We present equations that can be used to calculate normal lung volumes and DLCO in healthy military aviators. The predictive power of our equations varies, depending on the size of each subgroup, but was greatest for Caucasian males.
CLINICAL IMPLICATIONS: Normal PFT values can vary widely, depending on the population. Equations to predict normal values should be derived from populations that closely match the patient. How our equations compare with existing normative equations and the applicability of our equations to other, similar populations are areas for future investigation. Inclusion of larger numbers of female and minority subjects in future studies may help to improve the power of predictive equations in these populations.
DISCLOSURE: The following authors have nothing to disclose: Joshua Sill, Lidia Ilcus, Jared Haynes, Rosa Alvarado, Lee Baggott
The equations presented in this study have not yet been validated or published for public use. They should be considered preliminary and are meant for research/investigative purposes only.