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Predictors of walking capacity in peripheral arterial disease patients

Abstract

OBJECTIVE:

To estimate walking capacity in intermittent claudication patients through a prediction model based on clinical characteristics and the walking impairment questionnaire.

METHODS:

The sample included 133 intermittent claudication patients of both genders aged between 30 and 80 years. Data regarding clinical characteristics, the walking impairment questionnaire and treadmill walking test performance were obtained. Multiple regression modeling was conducted to predict claudication onset distance and total walking distance using clinical characteristics (age, height, mass, body mass index, ankle brachial index lower, gender, history of smoking and co-morbid conditions) and walking impairment questionnaire responses. Comparisons of claudication onset distance and total walking distance measured during treadmill tests and estimated by a regression equation were performed using paired t-tests.

RESULTS:

Co-morbid conditions (diabetes and coronary artery disease) and questions related to difficulty in walking short distances (walking indoors - such as around your house and walking 5 blocks) and at low speed (walking 1 block at average speed - usual pace) resulted in the development of new prediction models high significant for claudication onset distance and total walking distance (p<0.001). In addition, non-significant differences from the results obtained by the treadmill test and estimated by the current model (p>0.05) were observed.

CONCLUSION:

The current study demonstrated that walking capacity can be adequately estimated based on co-morbid conditions and responses to the walking impairment questionnaire.

Intermittent Claudication; Peripheral Arterial Disease; Walking Prediction; Comorbidities


INTRODUCTION

Peripheral artery disease affects lower extremity arteries and reduces oxygen supply to peripheral tissues (11. Hirsch AT, Haskal ZJ, Hertzer NR, Bakal CW, Creager MA, Halperin JL, et al. ACC/AHA 2005 Practice Guidelines for the management of patients with peripheral arterial disease (lower extremity, renal, mesenteric, and abdominal aortic): a collaborative report from the American Association for Vascular Surgery/Society for Vascular Surgery, Society for Cardiovascular Angiography and Interventions, Society for Vascular Medicine and Biology, Society of Interventional Radiology, and the ACC/AHA Task Force on Practice Guidelines (Writing Committee to Develop Guidelines for the Management of Patients With Peripheral Arterial Disease): endorsed by the American Association of Cardiovascular and Pulmonary Rehabilitation; National Heart, Lung, and Blood Institute; Society for Vascular Nursing; TransAtlantic Inter-Society Consensus; and Vascular Disease Foundation. Circulation. 2006;113:e463-654, http://dx.doi.org/10.1161/CIRCULATIONAHA.106.174526.
http://dx.doi.org/10.1161/CIRCULATIONAHA...
). Intermittent claudication, the most prevalent symptom of peripheral artery disease, leads to reduced walking capacity, which has been associated with all-cause and cardiovascular mortality (22. McDermott MM, Tian L, Liu K, Guralnik JM, Ferrucci L, Tan J, et al. Prognostic value of functional performance for mortality in patients with peripheral artery disease. J Am Coll Cardiol. 2008;51(15):1482-9, http://dx.doi.org/10.1016/j.jacc.2007.12.034.
http://dx.doi.org/10.1016/j.jacc.2007.12...
,33. Leeper NJ, Myers J, Zhou M, Nead KT, Syed A, Kojima Y, et al. Exercise capacity is the strongest predictor of mortality in patients with peripheral arterial disease. J Vasc Surg. 2012;57(3):728-33.), mobility loss (44. McDermott MM, Guralnik JM, Tian L, Ferrucci L, Liu K, Liao Y, et al. Baseline functional performance predicts the rate of mobility loss in persons with peripheral arterial disease. J Am Coll Cardiol. 2007;50(10):974-82, http://dx.doi.org/10.1016/j.jacc.2007.05.030.
http://dx.doi.org/10.1016/j.jacc.2007.05...
) and lower extremity strength (55. Ayzin Rosoky RM, Wolosker N, Muraco-Netto B, Puech-Leao P. Ground reaction force pattern in limbs with intermittent claudication. Eur J Vasc Endovasc Surg. 2000;20(3):254-9, http://dx.doi.org/10.1053/ejvs.2000.1146.
http://dx.doi.org/10.1053/ejvs.2000.1146...
).

Walking capacity in intermittent claudication patients has been assessed in research settings with the standardized treadmill test, which provides the claudication onset distance and total walking distance (66. Gardner AW, Skinner JS, Cantwell BW, Smith LK. Progressive vs single-stage treadmill tests for evaluation of claudication. Med Sci Sports Exerc. 1991;23(4):402-8.). On the other hand, in clinical settings, the treadmill test is not feasible (77. Wolosker N, Ritti-Dias RM, Camara LC, Garcia YM, Jacob-Filho W, Puech-Leao P. Treadmill test is limited in elderly patients with peripheral arterial disease. Vasa. 2010;39(3):237-41, http://dx.doi.org/10.1024/0301-1526/a000035.
http://dx.doi.org/10.1024/0301-1526/a000...
), and other tools to predict walking capacity have been used. Previous studies have proposed specific equations to predict walking capacity in intermittent claudication patients. Gardner et al. (88. Gardner AW, Ricci MA, Case TD, Pilcher DB. Practical equations to predict claudication pain distances from a graded treadmill test. Vasc Med. 1996;1(2):91-6.), validated an equation to predict walking capacity based on ankle-brachial index, body mass index and current smoking status. Recently, Leitch et al. (99. Leicht AS, Crowther RG, Muller R, Golledge J. The effects of including quality of life responses in models to predict walking performance of patients with intermittent claudication. Eur J Vasc Endovasc Surg. 2011;41(4):511-7, http://dx.doi.org/10.1016/j.ejvs.2010.12.018.
http://dx.doi.org/10.1016/j.ejvs.2010.12...
), predicted walking capacity with better accuracy using general questions regarding quality of life in the equation.

The walking impairment questionnaire is a specific questionnaire for patients with intermittent claudication which has been used as an alternative tool to assess walking capacity (1010. Regensteiner JG, Steiner JF, Panzer J, WR H. Evaluation of walking impairment by questionnaire in patients with peripheral arterial disease. J Vasc Med Biol. 1990;2:142-52.,1111. Ritti-Dias RM, Gobbo LA, Cucato GG, Wolosker N, Jacob Filho W, Santarem JM, et al. Translation and validation of the walking impairment questionnaire in Brazilian subjects with intermittent claudication. Arq Bras Cardiol. 2009;92(2):136-49.). Previous studies have shown that the walking impairment questionnaire is more strongly correlated with walking capacity than the quality of life questionnaire (1212. Izquierdo-Porrera AM, Gardner AW, Bradham DD, Montgomery PS, Sorkin JD, Powell CC, et al. Relationship between objective measures of peripheral arterial disease severity to self-reported quality of life in older adults with intermittent claudication. J Vasc Surg. 2005;41(4):625-30, http://dx.doi.org/10.1016/j.jvs.2005.01.012.
http://dx.doi.org/10.1016/j.jvs.2005.01....
,1313. Myers SA, Johanning JM, Stergiou N, Lynch TG, Longo GM, Pipinos II. Claudication distances and the Walking Impairment Questionnaire best describe the ambulatory limitations in patients with symptomatic peripheral arterial disease. J Vasc Surg. 2008;47(3):550-5, http://dx.doi.org/10.1016/j.jvs.2007.10.052.
http://dx.doi.org/10.1016/j.jvs.2007.10....
). However, whether the walking impairment questionnaire accurately predicts claudication onset distance and total walking distance has not been not previously described.

Our hypothesis is that clinical status and walking impairment questionnaire responses are significant predictors of walking capacity. Therefore, the aim of this study was to estimate the walking capacity in intermittent claudication patients through a prediction model based on clinical characteristics and the walking impairment questionnaire.

MATERIAL AND METHODS

Patients

Four hundred forty consecutive patients were recruited at a tertiary care center that specializes in vascular disease. Patients with peripheral artery disease and claudication symptoms were included in this study if they had an ankle-brachial index ≤0.90 at rest, no pain at rest, and no evidence of mental disability identified by the Mini-Mental State Examination Questionnaire (1414. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59 Suppl 20:22-33;quiz 34-57.) and were willing to volunteer to participate in the study. A total of 133 intermittent claudication patients were deemed eligible for the study.

Assessments

Demographic information, height, weight, smoking history and comorbid conditions (hypertension, dyslipidemia, diabetes and coronary artery disease) were obtained through medical history and physical examination. Ankle and arm blood pressures were assessed, and the ankle-brachial index was calculated by the quotient of ankle systolic blood pressure over brachial systolic blood pressure (1515. Wolosker N, Rosoky RA, Nakano L, Basyches M, Puech-Leao P. Predictive value of the ankle-brachial index in the evaluation of intermittent claudication. Rev Hosp Clin Fac Med Sao Paulo. 2000;55(2):61-4.).

Walking capacity on treadmill

The patients performed a graded maximal treadmill test (model 2200.1 Trimline; Hebb Industries Inc., Whitehouse, Texas) using a specific protocol for patients with IC as previously described (66. Gardner AW, Skinner JS, Cantwell BW, Smith LK. Progressive vs single-stage treadmill tests for evaluation of claudication. Med Sci Sports Exerc. 1991;23(4):402-8.). Briefly, the treadmill speed was maintained at 2.0 mph, and the treadmill grade was increased 2% every 2 minutes until the patients could no longer continue because of claudication symptoms. The claudication onset distance and the total walking distance were defined, respectively, as the distance walked when the patient first reported pain in the leg and the distance at which the patient was unable to continue to exercise due to leg pain.

Walking Impairment Questionnaire

The walking impairment questionnaire is composed of 14 items distributed in 4 domains, one including general information and three regarding walking capacity (distance, speed and using stairs). Each item is ranked from 0 to 4 on a Likert scale, in which 0 represents unable to perform and 4 represents no difficulty. These data were obtained through personal interviews. The Brazilian Portuguese version of the walking impairment questionnaire has previously been validated (1111. Ritti-Dias RM, Gobbo LA, Cucato GG, Wolosker N, Jacob Filho W, Santarem JM, et al. Translation and validation of the walking impairment questionnaire in Brazilian subjects with intermittent claudication. Arq Bras Cardiol. 2009;92(2):136-49.).

The distances that are assessed by the walking impairment questionnaire range from walking indoors around the home to walking 5 blocks outside. The speeds are assessed as the difficulty of walking 1 block at each of the following speeds: slowly, average speed, quickly and jogging or running. Stair use ability is assessed by the difficulty of climbing up one, two or three flights of stair. We analyzed the reliability of each question after seven days in a subsample of 25 patients, and the interclass correlation coefficient ranged from 0.76 to 0.98.

Statistical Analysis

Data were analyzed using the Statistical Package for the Social Sciences (SPSS version 10, SPSS Inc., Chicago, Illinois, USA). Normality was verified by the Kolgomorov-Sminorv test. Multiple regression modeling was conducted to predict claudication onset distance and total walking distance from the independent variables: age, height, mass, body mass index, the ankle-brachial index of the lower extremities, gender (male = 1, female = 0), smoking history (yes = 1, no = 0), co-morbid conditions (hypertension, diabetes, dyslipidemia and coronary artery disease; yes = 1, no = 0) and walking impairment questionnaire responses (0 to 4).

The claudication onset distance and total walking distance measured during the treadmill test were compared to the estimated values of claudication onset distance and total walking distance obtained by the regression model using paired t-tests. The accuracy of the regression model was further examined by the absolute error [(absolute difference between predicted and actual value)/actual value x 100] and the proportion of predicted values within 10%, 10-25% and >25% of the treadmill result (1616. Leicht AS, Crowther RG. Pedometer accuracy during walking over different surfaces. Med Sci Sports Exerc. 2007;39(10):1847-50.). The significance level was set at p<0.05 for all analyses.

Ethics

The procedures used in this study were approved by the Institutional Review Board of the University of Pernambuco and by the Institutional Review Board of the Hospital of Clinics of University of São Paulo. Written informed consent was obtained from each patient prior to investigation.

RESULTS

The characteristics of the sample are shown in Table 1. Most of the patients were male (64.7%) and non-obese. The prevalence of co-morbid conditions ranged from 38.6% (diabetes) to 76.7% (hypertension).

Table 1

General characteristics of intermittent claudication patients (n = 133).


Table 2 displays the responses for each question of the walking impairment questionnaire: 27.9% of patients reported being unable to walk 5 blocks, 85.7% reported that they are not able to jog or run, and 20.3% reported that they are not able to climb three flights of stairs.

Table 2

Frequency of responses on the Walking Impairment Questionnaire in intermittent claudication patients.


Table 3

Prediction model for claudication distance and total walking distance in intermittent claudication patients.


Regression analyses indicated that Q1 (walking indoors - such as around your house), Q4 (walking 1 block) and Q9 (walking 1 block at average speed - usual pace) of the walking impairment questionnaire, as well as diabetes and coronary artery disease, were independent predictors of claudication onset distance and total walking distance (Table 3). Prediction models resulted in moderate correlation coefficients (claudication onset distance: r = 0.52; total walking distance: r = 0.58) and non-significant differences from the results obtained in treadmill test (Estimated by current model: claudication onset distance − 175±81 m and total walking distance − 408±173 m; Measured by the treadmill test: claudication onset distance − 175±155 m and total walking distance − 408±295 m; p>0.05). In addition, absolute errors less than 25% were found for claudication onset distance (21%) and total walking distance (32%) (Figure 1).

Figure 1

Distribution of absolute error of the current prediction model for estimating claudication distance (Panel A) and total walking distance (Panel B).


DISCUSSION

The current study demonstrated that walking capacity may be adequately estimated based on co-morbid conditions and walking impairment questionnaire questions. Inclusion of co-morbid conditions, such as diabetes and coronary artery disease, as well as questions related to difficulty in walking short distances and at low speeds resulted in the development of new prediction models for walking capacity that are more accurate than previously published models for patients with intermittent claudication (88. Gardner AW, Ricci MA, Case TD, Pilcher DB. Practical equations to predict claudication pain distances from a graded treadmill test. Vasc Med. 1996;1(2):91-6.,99. Leicht AS, Crowther RG, Muller R, Golledge J. The effects of including quality of life responses in models to predict walking performance of patients with intermittent claudication. Eur J Vasc Endovasc Surg. 2011;41(4):511-7, http://dx.doi.org/10.1016/j.ejvs.2010.12.018.
http://dx.doi.org/10.1016/j.ejvs.2010.12...
).

In the present study, diabetes and coronary artery disease were independent predictors of walking capacity. Previous studies have shown that diabetes and coronary artery disease are related to walking impairment in intermittent claudication patients (1717. Anderson JD, Epstein FH, Meyer CH, Hagspiel KD, Wang H, Berr SS, et al. Multifactorial determinants of functional capacity in peripheral arterial disease: uncoupling of calf muscle perfusion and metabolism. J Am Coll Cardiol. 2009;54:628-35, http://dx.doi.org/10.1016/j.jacc.2009.01.080.
http://dx.doi.org/10.1016/j.jacc.2009.01...

18. Brevetti G, Giugliano G, Brevetti L, Hiatt WR. Inflammation in peripheral artery disease. Circulation. 2010;122:1862-75, http://dx.doi.org/10.1161/CIRCULATIONAHA.109.918417.
http://dx.doi.org/10.1161/CIRCULATIONAHA...

19. Brevetti G, Schiano V, Chiariello M. Endothelial dysfunction: a key to the pathophysiology and natural history of peripheral arterial disease? Atherosclerosis. 2008;197:1-11, http://dx.doi.org/10.1016/j.atherosclerosis.2007.11.002.
http://dx.doi.org/10.1016/j.atherosclero...
-2020. Nasser M, Wolosker N, Uint L, Rosoky RA, Lobato M, Wajngarten M, et al. Relationship between soluble thrombomodulin in patients with intermittent claudication and critical ischemia. Thromb Res. 2006;117:271-7, http://dx.doi.org/10.1016/j.thromres.2005.03.010.
http://dx.doi.org/10.1016/j.thromres.200...
), which has previously been attributed to respiratory, metabolic and vascular dysfunction (2121. Brevetti G, Piscione F, Cirillo P, Galasso G, Schiano V, Barbato E, et al. In concomitant coronary and peripheral arterial disease, inflammation of the affected limbs predicts coronary artery endothelial dysfunction. Atherosclerosis. 2008;201:440-6, http://dx.doi.org/10.1016/j.atherosclerosis.2008.01.014.
http://dx.doi.org/10.1016/j.atherosclero...
,2222. Bruno RM, Penno G, Daniele G, Pucci L, Lucchesi D, Stea F, et al. Type 2 diabetes mellitus worsens arterial stiffness in hypertensive patients through endothelial dysfunction. Diabetologia. 2012;55:1847-55, http://dx.doi.org/10.1007/s00125-012-2517-1.
http://dx.doi.org/10.1007/s00125-012-251...
). In addition, diabetes has been associated with endothelial dysfunction and increased oxidative stress, pro-inflammatory status and mitochondrial dysfunction (2323. Tabit CE, Chung WB, Hamburg NM, Vita JA. Endothelial dysfunction in diabetes mellitus: molecular mechanisms and clinical implications. Rev Endocr Metab Disord. 2010;11:61-74, http://dx.doi.org/10.1007/s11154-010-9134-4.
http://dx.doi.org/10.1007/s11154-010-913...
). Coronary artery disease patients also have endothelial dysfunction and experience reduced cardiorespiratory fitness compared to non-coronary artery disease patients (2121. Brevetti G, Piscione F, Cirillo P, Galasso G, Schiano V, Barbato E, et al. In concomitant coronary and peripheral arterial disease, inflammation of the affected limbs predicts coronary artery endothelial dysfunction. Atherosclerosis. 2008;201:440-6, http://dx.doi.org/10.1016/j.atherosclerosis.2008.01.014.
http://dx.doi.org/10.1016/j.atherosclero...
).

Although the walking impairment questionnaire has been widely used to assess walking impairment in intermittent claudication patients (1313. Myers SA, Johanning JM, Stergiou N, Lynch TG, Longo GM, Pipinos II. Claudication distances and the Walking Impairment Questionnaire best describe the ambulatory limitations in patients with symptomatic peripheral arterial disease. J Vasc Surg. 2008;47(3):550-5, http://dx.doi.org/10.1016/j.jvs.2007.10.052.
http://dx.doi.org/10.1016/j.jvs.2007.10....
,2424. Jain A, Liu K, Ferrucci L, Criqui MH, Tian L, Guralnik JM, et al. The Walking Impairment Questionnaire stair-climbing score predicts mortality in men and women with peripheral arterial disease. J Vasc Surg. 2012;55:1662-73 e2, http://dx.doi.org/10.1016/j.jvs.2011.12.010.
http://dx.doi.org/10.1016/j.jvs.2011.12....
,2525. Gardner AW, Parker DE, Montgomery PS, Khurana A, Ritti-Dias RM, Blevins SM. Gender differences in daily ambulatory activity patterns in patients with intermittent claudication. J Vasc Surg. 2010;52:1204-10, http://dx.doi.org/10.1016/j.jvs.2010.05.115.
http://dx.doi.org/10.1016/j.jvs.2010.05....
), whether this questionnaire is able to predict walking capacity has not been previously analyzed. The results of the present study indicate that the walking impairment questionnaire predicts walking capacity in intermittent claudication patients. Questions related to difficulty in walking short distances and walking at low speeds were significantly correlated to claudication onset distance and total walking distance. Thus, it seems that the best questions to predict walking capacity are those indicative of major limitations of the patient.

Interestingly, in the present study, walking impairment questionnaire questions regarding climbing stairs were not predictors of walking capacity in peripheral artery disease patients. Previous studies have observed that the climbing stairs domain of the walking impairment questionnaire was correlated with walking capacity (11-11. Ritti-Dias RM, Gobbo LA, Cucato GG, Wolosker N, Jacob Filho W, Santarem JM, et al. Translation and validation of the walking impairment questionnaire in Brazilian subjects with intermittent claudication. Arq Bras Cardiol. 2009;92(2):136-49.

12. Izquierdo-Porrera AM, Gardner AW, Bradham DD, Montgomery PS, Sorkin JD, Powell CC, et al. Relationship between objective measures of peripheral arterial disease severity to self-reported quality of life in older adults with intermittent claudication. J Vasc Surg. 2005;41(4):625-30, http://dx.doi.org/10.1016/j.jvs.2005.01.012.
http://dx.doi.org/10.1016/j.jvs.2005.01....
-1313. Myers SA, Johanning JM, Stergiou N, Lynch TG, Longo GM, Pipinos II. Claudication distances and the Walking Impairment Questionnaire best describe the ambulatory limitations in patients with symptomatic peripheral arterial disease. J Vasc Surg. 2008;47(3):550-5, http://dx.doi.org/10.1016/j.jvs.2007.10.052.
http://dx.doi.org/10.1016/j.jvs.2007.10....
). However, these studies were performed using bivariate analysis, which does not control for the relationships between the climbing stairs domain and walking capacity to potential confounders, such as clinical characteristics or other walking impairment questionnaire domains.

Poor walking capacity has been associated with increased risk for all-cause and cardiovascular mortality (22. McDermott MM, Tian L, Liu K, Guralnik JM, Ferrucci L, Tan J, et al. Prognostic value of functional performance for mortality in patients with peripheral artery disease. J Am Coll Cardiol. 2008;51(15):1482-9, http://dx.doi.org/10.1016/j.jacc.2007.12.034.
http://dx.doi.org/10.1016/j.jacc.2007.12...
,33. Leeper NJ, Myers J, Zhou M, Nead KT, Syed A, Kojima Y, et al. Exercise capacity is the strongest predictor of mortality in patients with peripheral arterial disease. J Vasc Surg. 2012;57(3):728-33.), mobility loss (44. McDermott MM, Guralnik JM, Tian L, Ferrucci L, Liu K, Liao Y, et al. Baseline functional performance predicts the rate of mobility loss in persons with peripheral arterial disease. J Am Coll Cardiol. 2007;50(10):974-82, http://dx.doi.org/10.1016/j.jacc.2007.05.030.
http://dx.doi.org/10.1016/j.jacc.2007.05...
) and reduced strength in the lower extremities (55. Ayzin Rosoky RM, Wolosker N, Muraco-Netto B, Puech-Leao P. Ground reaction force pattern in limbs with intermittent claudication. Eur J Vasc Endovasc Surg. 2000;20(3):254-9, http://dx.doi.org/10.1053/ejvs.2000.1146.
http://dx.doi.org/10.1053/ejvs.2000.1146...
). Thus, the assessment of walking capacity is clinically relevant. The results of this study showed that walking capacity is adequately estimated based on clinical characteristics and walking impairment questionnaire questions; this is useful for clinicians to quantify the walking capacity of intermittent claudication patients easily.

The present study has some limitations. Walking capacity was assessed in the graded treadmill test. Therefore, other ways of assessing walking capacity (e.g., the 6-minute test) cannot be predicted using the regression models proposed in this study. The equations for predicting the claudication onset distance and total walking distance were not cross-validated in an independent group of similar peripheral arterial disease patients. This study included only peripheral artery disease patients with claudication symptoms, and the predictive models cannot be extrapolated for patients with peripheral arterial disease in other stages.

In conclusion, the model based on walking impairment questionnaire and co-morbid conditions adequately predicted the walking capacity in intermittent claudication patients. This information is useful for clinicians to easily quantify the walking capacity of intermittent claudication patients.

This study was founded by grants of “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)” and research scholarship (RMR and CLF) from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).

REFERENCES

  • 1
    Hirsch AT, Haskal ZJ, Hertzer NR, Bakal CW, Creager MA, Halperin JL, et al. ACC/AHA 2005 Practice Guidelines for the management of patients with peripheral arterial disease (lower extremity, renal, mesenteric, and abdominal aortic): a collaborative report from the American Association for Vascular Surgery/Society for Vascular Surgery, Society for Cardiovascular Angiography and Interventions, Society for Vascular Medicine and Biology, Society of Interventional Radiology, and the ACC/AHA Task Force on Practice Guidelines (Writing Committee to Develop Guidelines for the Management of Patients With Peripheral Arterial Disease): endorsed by the American Association of Cardiovascular and Pulmonary Rehabilitation; National Heart, Lung, and Blood Institute; Society for Vascular Nursing; TransAtlantic Inter-Society Consensus; and Vascular Disease Foundation. Circulation. 2006;113:e463-654, http://dx.doi.org/10.1161/CIRCULATIONAHA.106.174526.
    » http://dx.doi.org/10.1161/CIRCULATIONAHA.106.174526
  • 2
    McDermott MM, Tian L, Liu K, Guralnik JM, Ferrucci L, Tan J, et al. Prognostic value of functional performance for mortality in patients with peripheral artery disease. J Am Coll Cardiol. 2008;51(15):1482-9, http://dx.doi.org/10.1016/j.jacc.2007.12.034.
    » http://dx.doi.org/10.1016/j.jacc.2007.12.034
  • 3
    Leeper NJ, Myers J, Zhou M, Nead KT, Syed A, Kojima Y, et al. Exercise capacity is the strongest predictor of mortality in patients with peripheral arterial disease. J Vasc Surg. 2012;57(3):728-33.
  • 4
    McDermott MM, Guralnik JM, Tian L, Ferrucci L, Liu K, Liao Y, et al. Baseline functional performance predicts the rate of mobility loss in persons with peripheral arterial disease. J Am Coll Cardiol. 2007;50(10):974-82, http://dx.doi.org/10.1016/j.jacc.2007.05.030.
    » http://dx.doi.org/10.1016/j.jacc.2007.05.030
  • 5
    Ayzin Rosoky RM, Wolosker N, Muraco-Netto B, Puech-Leao P. Ground reaction force pattern in limbs with intermittent claudication. Eur J Vasc Endovasc Surg. 2000;20(3):254-9, http://dx.doi.org/10.1053/ejvs.2000.1146.
    » http://dx.doi.org/10.1053/ejvs.2000.1146
  • 6
    Gardner AW, Skinner JS, Cantwell BW, Smith LK. Progressive vs single-stage treadmill tests for evaluation of claudication. Med Sci Sports Exerc. 1991;23(4):402-8.
  • 7
    Wolosker N, Ritti-Dias RM, Camara LC, Garcia YM, Jacob-Filho W, Puech-Leao P. Treadmill test is limited in elderly patients with peripheral arterial disease. Vasa. 2010;39(3):237-41, http://dx.doi.org/10.1024/0301-1526/a000035.
    » http://dx.doi.org/10.1024/0301-1526/a000035
  • 8
    Gardner AW, Ricci MA, Case TD, Pilcher DB. Practical equations to predict claudication pain distances from a graded treadmill test. Vasc Med. 1996;1(2):91-6.
  • 9
    Leicht AS, Crowther RG, Muller R, Golledge J. The effects of including quality of life responses in models to predict walking performance of patients with intermittent claudication. Eur J Vasc Endovasc Surg. 2011;41(4):511-7, http://dx.doi.org/10.1016/j.ejvs.2010.12.018.
    » http://dx.doi.org/10.1016/j.ejvs.2010.12.018
  • 10
    Regensteiner JG, Steiner JF, Panzer J, WR H. Evaluation of walking impairment by questionnaire in patients with peripheral arterial disease. J Vasc Med Biol. 1990;2:142-52.
  • 11
    Ritti-Dias RM, Gobbo LA, Cucato GG, Wolosker N, Jacob Filho W, Santarem JM, et al. Translation and validation of the walking impairment questionnaire in Brazilian subjects with intermittent claudication. Arq Bras Cardiol. 2009;92(2):136-49.
  • 12
    Izquierdo-Porrera AM, Gardner AW, Bradham DD, Montgomery PS, Sorkin JD, Powell CC, et al. Relationship between objective measures of peripheral arterial disease severity to self-reported quality of life in older adults with intermittent claudication. J Vasc Surg. 2005;41(4):625-30, http://dx.doi.org/10.1016/j.jvs.2005.01.012.
    » http://dx.doi.org/10.1016/j.jvs.2005.01.012
  • 13
    Myers SA, Johanning JM, Stergiou N, Lynch TG, Longo GM, Pipinos II. Claudication distances and the Walking Impairment Questionnaire best describe the ambulatory limitations in patients with symptomatic peripheral arterial disease. J Vasc Surg. 2008;47(3):550-5, http://dx.doi.org/10.1016/j.jvs.2007.10.052.
    » http://dx.doi.org/10.1016/j.jvs.2007.10.052
  • 14
    Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59 Suppl 20:22-33;quiz 34-57.
  • 15
    Wolosker N, Rosoky RA, Nakano L, Basyches M, Puech-Leao P. Predictive value of the ankle-brachial index in the evaluation of intermittent claudication. Rev Hosp Clin Fac Med Sao Paulo. 2000;55(2):61-4.
  • 16
    Leicht AS, Crowther RG. Pedometer accuracy during walking over different surfaces. Med Sci Sports Exerc. 2007;39(10):1847-50.
  • 17
    Anderson JD, Epstein FH, Meyer CH, Hagspiel KD, Wang H, Berr SS, et al. Multifactorial determinants of functional capacity in peripheral arterial disease: uncoupling of calf muscle perfusion and metabolism. J Am Coll Cardiol. 2009;54:628-35, http://dx.doi.org/10.1016/j.jacc.2009.01.080.
    » http://dx.doi.org/10.1016/j.jacc.2009.01.080
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  • No potential conflict of interest was reported.

Publication Dates

  • Publication in this collection
    Apr 2013

History

  • Received
    7 Dec 2012
  • Reviewed
    20 Dec 2012
  • Accepted
    28 Dec 2012
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