Assessment of respiratory function: influence of spirometry reference values and normality criteria selection

Abstract

The purpose of this study was to determine the impact upon classification of patients of the choice of reference equation and the criterion defining the lower limit of the normal range in clinical practice. One thousand consecutive spirometries were checked to calculate the predicted values [forced vital capacity (FVC) and forced expiratory volume in sec (FEV1)] in accordance with the equations by Morris, Cherniack, Crapo, Knudson and the Economic Community for Coal and Steel (ECCS). We quantified the difference between the predicted values obtained for each individual and each equation, determined the percentage of individuals whose classification might have changed from normal to abnormal when using a different equation and defined the lower limit of the normal range in accordance with the determination of 1. the 90% confidence interval or 2. 80% of predicted, comparing their differences. The greatest differences found were between the values given by Morris and Crapo's equations for male FEV1, between Morris and Cherniak for female FEV1 and male FVC and between Morris and Knudson for female FVC. Using 80% of predicted value for female FEV1, up to 35% of tests changed their classification from 'normal' to 'abnormal' upon changing the equation used. A high percentage of tests showed a lower limit of normal defined by the confidence interval under 80% and 70% of predicted value. This study emphasizes the importance of choosing the appropriate reference equation. We do not consider it acceptable to use a fixed percentage of the predicted value as the lower limit of normal because of the great number of patients found to be inappropriately classified.

Predictive Equations for Lung Function Based on a Large Occupational Population in North China

“…From the statistical analysis, the F values for the Adjusted Regression Equations (chest circumferences excluded in stepwise regression analysis) became larger than those for the Unadjusted Regression Equations (chest circumferences introduced in stepwise regression analysis). The R, R 2 , adjusted R 2 and Beta values showed little change.…”

“…It is generally agreed that a gross difference in interpretation of lung function would occur if different predictive equations are employed 2,8) . Glindmeyer 9) estimated that the variability introduced by choice of different predictive equations could be as much as 20% for FVC, FEV 1 and FEF 25-75% .…”

“…Due to differences in study populations, techniques or procedures, equations used to predict normal lung function vary [1][2][3] . It is imperative to establish appropriate predictive equations as reference for a given population.…”

Valores de referencia para parámetros de espirometría en la población adulta residente en Bogotá, D. C., Colombia

“…El cálculo del tamaño de la muestra se realizó teniendo en cuenta la estratificación por sexo y edad, con el fin de controlar por la influencia que tienen estas variables sobre la función pulmonar (23,(40)(41)(42).…”

The value of spirometry for primary care: Asthma and COPD

“…Choice of reference equations appropriate for the local population is important, since different reference values may lead to dissimilar conclusions in terms of normal and abnormal values and therefore diagnosis. 9 When spirometry was introduced in one general practice, Spann demonstrated a significant reduction of the underdiagnosis of COPD in high-risk populations, as well as improved differentiation between reversible and irreversible airway obstruction. 10 After bronchodilator treatment had been adjusted on the basis of spirometry results, 25% of patients reported a significant improvement in respiratory symptoms.…”