Practical Equations to Predict Claudication Pain Distances from a Graded Treadmill Test

Abstract

Treadmill testing is used to estimate the severity of claudication, but routine use is not practical or cost-effective in all settings. Thus, the purposes of this study were: (1) to develop and cross-validate prediction equations for treadmill claudication pain distances in a heterogeneous cohort of peripheral arterial occlusive disease patients, and (2) to determine if the regression equations were more accurate in assessing claudication distances than self-reported distances of patients. Medical history, vital signs, resting ankle/brachial systolic pressure index (ABI), and claudication distances during a graded treadmill test were obtained on a validation group of 178 claudicants and on a cross-validation group of 94 c1audicants. The independent predictors of claudication pain distances of the validation group were ABI, body mass index, gender, and current smoking status, with multiple correlation coefficients of R=0.73 and R=0.82 for the distances to onset and to maximal pain, respectively. These equations were successfully cross-validated on an independent group of claudicants, as the predicted distances to onset of claudication pain (167.2±102.6 m) and to maximal pain (354.6±154.3 m) were similar (p=0.99) to measured distances (169.1±127.8 m and 356.6±181.0 m, respectively). However, the selfreported distances to onset (89.5±126.3) and to maximal claudication pain (189.2±284.3) were 1-2 blocks less than either the measured or predicted distances (p<O.Ol). It is concluded that claudication pain distances during an incremental treadmill test can be more accurately estimated from a composite of variables obtained during medical screening than by relying on the self-report of patients. Consequently, in clinical settings where treadmill testing is impractical, the functional severity of claudication can be assessed without exercise testing.

The effect of metabolic syndrome components on exercise performance in patients with intermittent claudication

“…32,33 Rather, the clustering of risk factors that comprise the metabolic syndrome, particularly abdominal obesity, negatively affects exercise performance of patients with PAD. These data support previous findings that metabolic syndrome impairs ICD and ACD in patients with intermittent claudication 16,17 and lowers cardiopulmonary fitness in adult men and women 34 and in patients with intermittent claudication.…”

Calf muscle hemoglobin oxygen saturation characteristics and exercise performance in patients with intermittent claudication

“…6 The ankle-brachial index (ABI) is a standard outcome measure to quantify vascular insufficiency in PAD patients. 1,7 However, ABI is not a measure of exercise-mediated muscular ischemia and is either modestly 4,8,9 or poorly 5,10,11 correlated with walking distances to onset and to maximal pain during standardized treadmill tests. The ankle systolic pressure measured after treadmill exercise is another standard outcome measure to assess vascular insufficiency, 12-14 but it also does not provide real-time information on muscular ischemia during exercise.…”

“…1 Intermittent claudication is ischemic muscular leg pain that occurs during ambulation when the peripheral circulation is inadequate to meet the metabolic requirement of the active leg musculature. Consequently, intermittent claudication leads to ambulatory dysfunction [2][3][4][5] and a decline in daily physical activities. 6 The ankle-brachial index (ABI) is a standard outcome measure to quantify vascular insufficiency in PAD patients.…”

Reliability of treadmill testing in peripheral arterial disease: A meta-regression analysis

“…[17][18][19][20] Twelve studies were excluded because of the lack of repetition of an initial C-or G-test. 3,18,[21][22][23][24][25][26][27][28][29][30] In four studies, the time between the treadmill tests exceeded our preset limit. 7,31-33 Finally, in nine studies, the ICC was not available and it was not possible to determine the ICC from the given data.…”