Spirometry is the most frequently performed investigation to evaluate pulmonary function. It provides clinically useful information on the mechanical properties of the lung and the thoracic cage and aids in taking management-related decisions in a wide spectrum of diseases and disorders. Few measurements in medicine are so dependent on factors related to equipment, operator and the patient. Good spirometry requires quality assured measurements and a systematic approach to interpretation. Standard guidelines on the technical aspects of equipment and their calibration as well as the test procedure have been developed and revised from time-to-time. Strict compliance with standardisation guidelines ensures quality control. Interpretation of spirometry data is based only on two basic measurements--the forced vital capacity (FVC) and the forced expiratory volume in 1 second (FEV1) and their ratio, FEV1/FVC. A meaningful and clinically useful interpretation of the measured data requires a systematic approach and consideration of several important issues. Central to interpretation is the understanding of the development and application of prediction equations. Selection of prediction equations that are appropriate for the ethnic origin of the patient is vital to avoid erroneous interpretation. Defining abnormal values is a debatable but critical aspect of spirometry. A statistically valid definition of the lower limits of normal has been advocated as the better method over the more commonly used approach of defining abnormality as a fixed percentage of the predicted value. Spirometry rarely provides a specific diagnosis. Examination of the flow-volume curve and the measured data provides information to define patterns of ventilatory impairment. Spirometry must be interpreted in conjunction with clinical information including results of other investigations.
CITATION STYLE
Chhabra, S. K. (2015, April 1). Interpretation of Spirometry: Selection of Predicted Values and Defining Abnormality. The Indian Journal of Chest Diseases & Allied Sciences. https://doi.org/10.5005/ijcdas-57-2-91
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