Introduction

Proper selection and use of well-calibrated instruments and an appropriate test protocol should produce one or more of the measured variables described in Chapter 4. These variables now require integration, one with another, and meaningful interpretation to complete the purpose of the exercise test.

Some tests, such as field tests, yield one specific measured variable. These variables are typically compared with reference values (so-called predicted normal values) or related to serial measurements for a given individual. They do not necessarily require integration with other results. The interpretation of individual variables has been thoroughly explained in Chapter 4. However, a brief consideration of the derivation and limitations of reference values will now be addressed.

Laboratory exercise tests, notably the maximal incremental work rate protocols, yield an impressive array of data. The results can be bewildering unless organized and interpreted in a systematic manner. This chapter describes how test data can be displayed, in graphical or tabular format, thus enabling the practitioner to evaluate these data systematically and arrive at conclusions that address the specific purpose of the test.

Based on logical data displays of multiple variables, a scheme for the recognition of specific response patterns can be developed. The scheme presented in this chapter acknowledges that clinical exercise testing is often limited in its ability to point to a specific diagnosis. However, for each abnormal response pattern, the implications are discussed and examples of clinical conditions giving rise to that pattern are given.