The role of cardiopulmonary exercise testing in perioperative risk assessment.

Accurate assessment of a patient’s risk of major perioperative complications is a challenging task. To accomplish this, clinicians must account for the multiple factors that determine this risk. These include the operative conditions (elective or emergent), the anatomic site and duration of the procedure, and the degree of physiological stress that it presents. These surgical factors are balanced against patient-related risk factors that include age, the presence of comorbidities, the results of preoperative testing, and what is termed the patient’s “functional capacity,” a key element in the algorithmic approach to perioperative assessment. “Fitness” for surgery is a term often used to denote a quantitative measurement of functional capacity. It is a measure of whether a person’s cardiopulmonary system can withstand the physiological stress of surgery, and therefore, only has practical meaning in relation to the type of surgery being proposed. Traditionally, fitness is measured by querying what daily activity or task represents the patient’s highest level of exertion and estimating the level of O2 consumption required to perform it. This “metabolic equivalent of the task” (MET) is expressed as a multiple of the resting adult metabolic rate of 3.5 mL O2 consumption/kg/min, or 1 MET. Functional status is thus judged by the patient’s maximal task performance on a MET scale: poor (< 4 METs= climbing a flight of stairs), moderate (4 to 6 METs=doing housework, playing doubles tennis), good (7 to 10 METs=playing basketball, jogging), or excellent (>10 METs, fast swimming, fast jump-roping). Some of the activities used to quantify METs, such as the ability to climb flights of stairs, show an inverse correlation to the odds of surgical complications. In general, however, a patient’s METs estimate has not been found to reliably predict low functional capacity or fitness, likely due to its subjective nature. Other tools developed to measure functional capacity, such as the Duke Activity Status Index (DASI), achieve greater precision and reproducibility by querying the patient’s ability to perform a broad range of specific activities. In the perioperative arena, DASI has good accuracy for predicting disability-free survival after surgery, although its ability to predict moderate-to-severe postoperative complications (POCs) is less robust. DASI is essentially subjective as well, relying on the patient’s report of his/ her activity level, which is known to be affected by recall bias and framing of questions. A simple and more objective test of functional capacity is the 6-minute walk test (6MWT), in which a patient is asked to walk as far as possible along a specified track in 6 minutes. Although the 6MWT is reproducible and correlates with a patient’s maximal work rate (WR), the only large studies to date show that it correlates only weakly with key surgical outcomes; the 6MWT does not actually measure peak metabolic rate and is thus an approximate biomarker of fitness. Another preoperative assessment tool, the maximal cardiopulmonary exercise testing (CPET), asks the patient to demonstrate his/her highest achievable energy consumption on a treadmill or cycle ergometer, while expired gas is collected for analysis of the patient’s metabolic state. As such, CPET reveals the patient’s physiological reserve, that is, the degree to which (s)he can augment metabolic rate over the resting baseline and thus tolerate the added metabolic stress of surgery and the postoperative period. Evidence has accumulated over 25 years that CPET can quantify the risk of adverse surgical outcomes by virtue of its ability to quantify peak O2 consumption and other physiological parameters during exercise. Unlike cardiac stress testing, which is focused on coronary ischemia, CPET tests whether exercise capacity is limited by dysfunction of any element in the pathway of oxidative metabolism, including the airways, lung parenchyma, heart, vasculature, red cells,muscles, andmitochondria, and importantly, can distinguish between these causes. It thus has the potential to identify a variety of interventions that may ameliorate surgical risk. In this chapter, wewill examine the evidence behind this claim, and further discuss the utility of CPET for perioperative decision-making in general.