Journal of Vascular Surgery
Volume 50, Issue 6 , Pages 1391-1398, December 2009

Impact of peripheral arterial disease on health status: A comparison with chronic heart failure

Center of Research on Psychology in Somatic Diseases, Department of Medical Psychology, Tilburg University, Tilburg, The Netherlands

Received 23 May 2009; accepted 27 July 2009.

Article Outline

Objective

To further document the experienced burden in patients with peripheral arterial disease (PAD), we compared the health status of patients with PAD and chronic heart failure (CHF). As a secondary aim, we studied clinical and socio-demographic correlates of health status in both conditions.

Methods

We conducted a cross-sectional observational study in four outpatient clinics in the Southern part of The Netherlands, with subjects consisting of ambulatory (346 PAD and 188 CHF) patients. All patients completed the Short-Form 12 to assess their physical and mental health status. Information about socio-demographic, clinical risk factors, and disease severity indices was obtained from patients' medical records. Propensity methodology was applied to enhance comparability between both medical conditions.

Results

Type of medical condition explained differences in health status (F = 33.1, P < .0001, Effect Size = 0.27). Impaired physical health status was more often reported in PAD patients (48.4%) compared with CHF patients (17.4%, Odds Ratio [OR] = 4.4, 95% Confidence Interval [CI] 2.3-8.8, P < .0001); impaired mental health status was more noted in CHF patients (43.5% vs. 22.0%, OR = 1.7, 95% CI 1.2-2.6, P = .002). In PAD, younger age (P = .002), low education (P = .02), cardiac history (P = .02), diabetes mellitus (P = .03), and a lower ankle brachial index (P = .003) were associated with worse physical health status; younger age (P = .01) and living without partner (P = .01) were associated with lower mental health status scores. In CHF, patients with comorbid diabetes mellitus (P < .001) and females (P = .001) reported worse physical health, whereas no clinical or socio-demographics were associated with mental health status.

Conclusions

By contrasting PAD patients' health status with another chronic disabling condition, the impact of PAD on patients' physical health status became evident; whereas mental health status was more affected in CHF, patients with PAD reported a greater physical burden as compared with CHF patients. PAD patients who were younger, lower-educated, without a partner or had a cardiac history especially reported a higher disease burden. Clinicians need to be aware of these differences in order to develop tailor-made disease management programs for different groups of cardiovascular patients.

 

The main challenges in peripheral arterial disease (PAD) refer to the prevention of cardiovascular events and the decrease of patients' disease burden.1 PAD is often a precursor of more advanced cardiovascular disease such as coronary and cerebrovascular disease.1 Recent findings indicate that PAD patients have worse long-term outcomes compared with coronary artery disease patients.2, 3 Despite these findings, deficiencies in awareness regarding PAD risk management and undertreatment of atherosclerotic risk factors still exist and may contribute to high rates of cardiovascular morbidity and mortality.2, 4

In addition to their increased cardiovascular risk, PAD patients are known to experience impaired health status due to lower-limb symptoms, sometimes even after receiving a technically successful endovascular revascularization.5, 6 In an era where patient-centered outcomes are becoming an important standard in evaluating treatment options,7, 8 information about subjective health status and its determinants in PAD is relatively under documented as compared with the body of research on health status that is available in other cardiovascular disease groups. This information will be necessary when designing tailor-made disease management programs for PAD patients, as programs developed in cardiac patients are not readily implementable in PAD patients.9

To estimate the burden associated with PAD, the first goal of this multi-center study was to compare the health status of patients with PAD and chronic heart failure (CHF).10 CHF has deleterious effects on prognosis and health status,11 and improving health status in CHF has been emphasized as an important treatment goal on its own.8 The second goal was to identify clinical risk factors associated with impaired health status in both patient groups.

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Methods 

Patients 

Patients with newly diagnosed symptomatic PAD were consecutively included at the vascular outpatient clinics of the St. Elisabeth Hospital and Twee Steden Hospital in Tilburg, The Netherlands (March 1, 2006 to May 31, 2008). CHF patients visiting the cardiology outpatient clinic of the St. Elisabeth Hospital, Tilburg, the Amphia Hospital, Breda, or the Zorgsaam Hospital, Terneuzen, The Netherlands (June 1, 2006 to May 31, 2008) were consecutively included for this study. All hospitals were public teaching hospitals in the Southern part of The Netherlands.

PAD inclusion criteria were defined as having symptomatic PAD and an abnormal resting Ankle-Brachial Index (ABI) (≤0.90) or an abnormal post-exercise ABI (ABI decrease of 15% after exercise).1 Stable CHF patients were included if they met the following criteria: systolic heart failure; Left Ventricle Ejection Fraction (LVEF) ≤40%; stable on oral medication during the past month; no medical admissions during the past month; New York Heart Association-functional class (NYHA) I-III. Exclusion criteria were cognitive impairment; chronic severe psychiatric condition (eg, psychosis) or invalidating or life-threatening conditions that prevented participation (eg, cancer); insufficient knowledge of the Dutch language or illiteracy. In addition, CHF patients aged ≤80 years were excluded (in order to avoid too much response burden in this older age group), as well as non-stable CHF patients that experienced an acute myocardial infarction one month prior to inclusion (in order to avoid unwanted confounding effects of the acute event). PAD patients were excluded if they had ischemic rest pain, tissue loss, ulcers, or gangrene. Patients with normal ABIs or patients with non-compressible ankle pressures were also ineligible for inclusion. Other reasons for exclusion included emigration or participation in another study.

PAD patients were asked to participate in the study by their treating vascular surgeon during their visit at the outpatient clinic, following a diagnostic work-up that confirmed the presence of PAD. CHF patients were approached for participation by their treating cardiologist or heart failure nurse during their outpatient visit to the cardiology department. All patients received a set of self-administered questionnaires which they could complete at home and return by mail.

The studies were approved by the local ethics committees of the participating hospitals and conducted conform to the Helsinki Declaration. All participants provided written informed consent.

Measures 

Health status 

The Dutch Short Form 12 (SF-12) was administered to assess health status.12, 13 This generic instrument measures overall physical and mental health status indicated by the Physical Component Summary and the Mental Component Summary scores.14 According to standard scoring procedures, all scales were standardized to the general Dutch population norms (range between 0-100, mean score = 50, SD = 10), with higher scores indicating better functioning.15 The SF-12 has been demonstrated to be a valid and reliable instrument.12

Disease severity 

In PAD patients, a handheld Doppler ultrasonic instrument with an 8-MHz vascular probe (Imexlab 9000; Imex Medical Systems Inc., Golden, Colorado, USA) was used by trained technicians to obtain systolic blood pressure readings in the right and left brachial arteries, right and left dorsalis pedis arteries, and right and left posterior tibial arteries. The ABI at rest and after walking on a treadmill was registered according to the latest Transatlantic Inter-Society Consensus (TASC) guidelines.1 Of the ABI values obtained in each leg, the lower resting ABI was used in all analyses. Duplex ultrasound scanning was employed to determine the localization of the lesions in the PAD patients. In CHF patients, information on NYHA class was obtained from the medical file; LVEF was collected by means of echocardiography and was used as an index of disease severity.

Socio-demographics and clinical variables 

Information on socio-demographics was self-reported by the participants and included gender, age, educational level (low education indicated patients who did not complete high school), and partner status. Clinical variables for both PAD and CHF patients were obtained from the patients' medical records and included cardiac history prior to the referral event (previous myocardial infarction, coronary artery bypass surgery, percutaneous coronary intervention), history of stroke or transient ischemic attack, current smoking, comorbidities (ie, diabetes mellitus, hypercholesterolemia, hypertension, renal failure, and chronic obstructive pulmonary disease, history of PAD and CHF) and prescribed cardioprotective medications (ie, aspirin, angiotensin-converting enzyme inhibitors, β-blockers, calcium channel blockers, diuretics, nitrates, statins, and anticoagulants).

Statistical analyses 

There were two main objectives in this study. We first compared the health status of patients with PAD and patients with CHF. For this purpose, patients were matched according to their clinical risk profile, in order to enhance comparability of PAD and CHF patients. Next, we evaluated a series of clinical and socio-demographic correlates of health status in both medical conditions. To optimize power, we used the whole cohort for the second purpose.

Matching PAD and CHF patients by clinical risk profile 

Baseline variables were examined for the total cohort and stratified by medical condition. Discrete variables were compared using χ2 tests and continuous variables with the Student t test for independent variables as appropriate. To enhance comparability between both medical conditions, propensity score methodology was applied using multivariable logistic regression analysis containing all baseline variables.16 A propensity score was then calculated for each patient, providing an estimate of the propensity toward belonging to either the PAD or the CHF group. Subsequently, PAD patients were matched with CHF patients based on their closest propensity score using a precision of three decimal points. After matching, baseline variables were examined again stratified by medical condition, to ensure that both groups had comparable clinical risk profiles.

Distribution of health status scores and clinical and prevalence of impaired health status 

To examine differences in levels of health status in PAD and CHF patients, multiple analyses of variance (MANOVA and ANOVA) were performed in the matched cohort (between-subjects design). Partial Eta Squared was calculated as an index of effect size.17 To facilitate clinical interpretability, the physical and mental health scores were dichotomized, including the lowest scoring 33%18 in the impaired health status group. Chi-square tests were used to compare prevalence of impaired physical and mental health in PAD vs CHF.

Clinical and socio-demographic correlates of health status 

For each patient subgroup separately, multivariable linear regression analyses were conducted to determine the correlates of health status. When determining the association between important correlates and health status, the following covariates were included: age, gender, current smoking, hypercholesterolemia, hypertension, and diabetes mellitus as these correlates are identified as major risk factors in cardiovascular disease.19, 20 In addition, all multivariable analyses were adjusted for cardiac history, disease severity (ie, in PAD we controlled for ABI, and in CHF for LVEF), history of PAD or CHF, and socio-demographic variables (having no partner, low education). Analyses were replicated excluding those patients with overlapping diagnoses (n = 9 with a history of PAD and n = 4 with a history of CHF) as sensitivity analyses. Results of both sets of analyses were similar, and therefore, the former described analyses – including the extra patients – will be reported here.

All statistical tests were two-tailed, and P < .05 was used to indicate statistical significance. Analyses were performed using SPSS 17.0 for Windows (SPSS Inc., Chicago, Ill).

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Results 

Matching PAD and CHF patients by clinical risk profile 

The total sample consisted of 534 patients, of which 346 had PAD diagnosis and 188 patients had CHF diagnosis (Fig 1). The mean age of the total sample was 66 years and 29% were female. Table I provides information about baseline characteristics before and after matching. Because the clinical risk profile differed for many aspects in both medical conditions (Table I, left), patients were matched based on their closest propensity score. We were able to match 104 PAD patients with 104 CHF patients, leaving 208 patients for further statistical analysis. These 208 patients were used in the health status comparison analyses. We used the full cohort when evaluating clinical and socio-demographic correlates of health status in each medical condition (n = 346 for PAD and n = 188 for CHF), in order to optimize power.

Table I. Baseline characteristics for the total sample and stratified by medical condition⁎
CharacteristicBefore matchingAfter matching†
Total sample (n = 534)PAD (n = 346)CHF (n = 188)P valueTotal sample (n = 208)PAD (n = 104)CHF (n = 104)P value
Socio-demographics
Age, mean ± SD (years)65.7±9.465.1±9.766.9±8.9.0467.2±9.267.3±9.567.1±8.9.79
Female gender29.2(156)33.2(115)21.8(41).0123.6(49)26.0(22)21.2(27).41
No partner23.4(125)24.3(84)21.8(41).5225.0(52)25.0(26)25.0(26)1.00
Low education30.6(162)28.4(98)34.8(64).1332.7(68)32.7(30)32.7(30)1.00
Medical history
Previous myocardial infarction33.1(176)17.3(60)62.4(116)<.000143.8(91)42.3(44)45.2(47).68
Previous coronary artery bypass surgery16.9(90)11.0(38)28.0(52)<.000118.8(39)17.3(18)20.2(21).59
Previous PCI13.7(73)8.2(28)24.2(45)<.000117.8(37)16.3(17)19.2(20).59
History of stroke or transient ischemic attack15.1(80)15.4(53)14.5(27).7913.9(29)14.4(15)13.5(14).84
Diabetes mellitus24.8(132)22.5(78)29.0(54).1030.3(63)32.7(34)27.9(29).45
Hypercholesterolemia67.0(355)68.6(236)64.0(119).2865.4(136)63.5(66)67.3(70).56
Hypertension54.0(268)59.9(206)43.0(80)<.000155.8(116)57.7(60)53.8(56).58
Current smoking42.0(224)52.3(181)23.0(43)<.000130.8(64)34.6(36)26.9(28).23
Renal failure7.3(39)9.6(33)3.2(6).015.8(12)7.7(8)3.8(4).23
Chronic obstructive pulmonary disease15.8(84)13.3(46)20.4(38).0322.1(46)21.2(22)23.1(24).74
BMI, mean ± SD27.1±4.626.6±4.727.9±4.4.0127.9±5.127.9±5.827.9±4.3.14
Medication
Aspirin59.8(319)74.6(258)32.6(61.0)<.000147.6(99)49.0(51)46.2(48).68
Angiotensin-converting enzyme inhibitors47.5(253)40.8(141)59.9(112)<.000154.8(114)52.9(55)56.7(59).58
β-blockers49.2(262)39.6(137)66.8(125)<.000158.2(121)57.7(60)58.7(61).89
Calcium channel blockers20.3(108)22.5(78)16.0(30).0822.1(46)23.1(24)21.2(22).74
Diuretics38.9(206)24.8(85)64.7(121)<.000154.8(114)48.1(50)61.5(64).06
Nitrates17.9(95)7.6(26)36.9(69)<.000124.0(50)21.2(22)26.9(28).33
Statins75.8(404)79.8(276)68.4(128).0165.9(137)64.4(67)67.3(70).66
Anticoagulants34.9(186)19.9(69)62.6(117)<.000178.0(37.5)32.7(34)42.3(44).15

BMI, Body mass index; PCI, percutaneous coronary intervention; PAD, peripheral arterial disease; CHF, chronic heart failure.

Significant results are presented in bold face.

⁎Results are presented as % (n), unless otherwise stated.

†Matched on age, gender, previous MI, previous CABG, previous PCI, hypertension, current smoking, renal failure, COPD, BMI, use of aspirin, ACE-inhibitors, β-Blockers, diuretics, nitrates, statins and anticoagulants.

After matching, there were no differences on baseline variables between PAD and CHF patients (Table I, right). CHF patients that could not be matched were more likely to on a beta blocker (81.0% vs. 58.7%) and to be older (70.2 vs. 67.1 years) as compared with matched CHF patients. Non-matched PAD patients were lower educated (63.6% vs. 32.7%), were less likely to have a history of myocardial infarction, to take ACE inhibitors (31.0% vs. 52.9%), diuretics (23.9% vs. 48.1%), but were more likely to be on aspirin (71.8% vs. 49.0%) and were more likely to be a smoker (62.0% vs. 34.6%) as compared with matched PAD patients.

In the matched cohort, the mean ABI for PAD patients was 0.65 (SD, 0.21), and four (3.8%) patients had a history of CHF. A total of 55.8% (58) presented with iliac disease, 71.2% (74) with femoral disease, 69.2% (72) with popliteal disease, 43.3% (45) presented with other below knee lesions, and 33.7% (35) patients presented with bilateral disease. A history of previous peripheral revascularization was present in 17.3% (18) of PAD patients. Mean LVEF for CHF patients was 33.7% (SD, 7.3), history of PAD was present in nine (8.7%) CHF patients. The majority of CHF patients had early stage disease; a total of 49 (47.1%) had NYHA class I, 44 (42.3%) was classified as NYHA class II, and three (10.6%) had NYHA class III.

Distribution of health status scores and clinical and prevalence of impaired health status 

The distribution of physical and mental health scores (mean, median, 25th to 75th percentiles, and range), stratified by medical condition are presented in Fig 2. PAD patients had lower physical health scores as compared with CHF patients and patients with CHF had lower mental health scores as compared with PAD patients. Statistical significance of differences in health status scores were analyzed using univariable analyses of variance (MANOVA and ANOVA). Type of medical condition explained differences in health status (physical and mental health) (F = 33.1, P < .0001, Effect Size = 0.27). On the subdomain level, the type of medical condition was also significantly associated with differences in mean health status scores (38.4 ± 10.2 for PAD vs 43.9 ± 7.1 for CHF, Fphysical health = 17.7, P < .0001, Effect Size = 0.09 and 47.0 ± 11.1 for PAD vs. 42.2 ± 6.8 for CHF, Fmental health = 12.4, P = .001, Effect Size = 0.06). According to generally accepted criteria,17 these Effect Sizes can be interpreted as small to moderate Effect Sizes.

  • View full-size image.
  • Fig 2. 

    Distribution of health status scores in PAD and CHF. Mean (closed circle), median (horizontal line), 25th to 75th percentile (box), and range (whiskers) of summary component scale scores by medical condition. CHF, Chronic heart failure; PAD, Peripheral arterial disease.

Fig 3 presents the prevalence of impaired physical and mental health status by medical condition. PAD patients had an increased risk of impaired physical health status as compared with CHF patients (48.4% vs 17.4%; OR = 4.4, P < .0001); conversely, impaired mental health status was more prevalent in CHF patients (43.5% vs 22.0%; OR = 1.7, P = .002). Importantly, results were replicated in the total cohort of matched and unmatched patients (results available from the authors).

  • View full-size image.
  • Fig 3. 

    Prevalence (%) of impaired health status (lowest tertile) stratified by medical condition. CHF, chronic heart failure; PAD, Peripheral arterial disease. *PAD coded as 1, and CHF coded as 0. †CHF coded as 1, and PAD coded as 0.

Clinical and socio-demographic correlates of health status 

Multivariable linear regression analyses were performed to identify relevant clinical and socio-demographic correlates of physical (Table II) and mental health status (Table III) in each medical condition. When including only one medical condition at a time, results indicated that PAD patients who did not complete high school education (P = .02), PAD patients with a history of cardiac disease (P = .02), or with comorbid diabetes mellitus (P = .03) reported lower physical health status scores whereas older age (P = .002) and higher ABI values (P = .003) were associated with higher physical health status scores. In CHF, female gender (P = .001) and comorbid diabetes mellitus (P < .001) were significantly associated with reporting worse physical health status (Table II). Older age (P = .01) was associated with higher mental health status scores in PAD patients, whereas PAD patients without a partner (P = .01) indicated to have worse mental health status scores as compared with those living with a partner. No clinical or sociodemographic correlates could be identified for mental health status in CHF patients (Table III).

Table II. Independent correlates of physical health status
CorrelatesPADCHF
β[95% CI]P valueβ[95% CI]P value
Age0.22[0.08; 0.35].002−0.09[−0.25; 0.06].24
Female gender−0.08[−0.19; −0.04].20−0.28[−0.44; −0.12].001
No partner−0.11[−0.23; 0.01].070.14[−0.03; 0.31].10
Low education−0.14[−0.26; −0.02].02−0.07[−0.23; 0.09].41
Cardiac history−0.15[−0.27; −0.03].02−0.04[−0.20; 0.13].67
ABI0.17[0.06; 0.29].003———
LVEF———−0.04[−0.19; 0.11].61
Comorbid PAD———0.01[−0.17; 0.16].96
Comorbid CHF−0.07[−0.18; 0.04].21———
Diabetes mellitus−0.13[−0.24; 0.01].03−0.31[−0.46; −0.15]<.001
Hypercholesterolemia−0.05[−0.16; 0.07].400.09[−0.08; 0.25].31
Hypertension−0.01[−0.11; 0.13].870.08[−0.07; 0.25].28
Current smoking−0.05[−0.07; 0.18].41−0.08[−0.24; 0.07].30

ABI, Ankle-brachial index; CHF, chronic heart failure; CI, confidence interval; LVEF, left ventricular ejection fraction; PAD, peripheral arterial disease.

Significant results are presented in bold face.

Table III. Independent correlates of mental health status
CorrelatesPADCHF
β[95% CI]P valueβ[95% CI]P value
Age0.24[0.07; 0.35].01−0.09[−0.30; 0.07].27
Female gender−0.06[−0.22; 0.16].75−0.06[−0.53; 0.12].51
No partner−0.20[−0.52; −0.06].010.06[−0.03; 0.24].55
Low education−0.05[−0.12; 0.10].85−0.13[−0.27; 0.04].13
Cardiac history0.10[−0.11; 0.13].880.05[−0.23; 0.22].60
ABI−0.04[−0.08; 0.15].52———
LVEF———0.03[−0.23; 0.19].72
Comorbid PAD———0.06[−0.20; 0.23].48
Comorbid CHF−0.06[−0.18; 0.05].32———
Diabetes mellitus−0.09[−0.21; 0.03].15−0.17[−0.55; 0.01].06
Hypercholesterolemia−0.09[−0.21; 0.03].120.06[−0.09; 0.24].49
Hypertension0.03[−0.09; 0.15].650.01[−0.09; 0.17].99
Current smoking0.02[−0.11; 0.15].73−0.01[−0.28; 0.15].89

ABI, Ankle-brachial index; CHF, chronic heart failure; CI, confidence interval; LVEF, left ventricular ejection fraction; PAD, peripheral arterial disease.

Significant results are presented in boldface.

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Discussion 

By comparing PAD patients' health status with another chronic disabling condition, the impact of PAD on patients' physical health status became evident; patients with PAD reported a greater physical burden as compared with CHF patients, whereas mental health status was more affected in CHF patients. These results were both found using the continuous and dichotomous health status scores. Different clinical and socio-demographic correlates of disease burden were identified in patients with PAD and CHF.

The most important finding of this study was the discrepancy in health status scores between both medical conditions. Intuitively, one would expect that patients with a more advanced manifestation of cardiovascular disease (ie, CHF patients) experience equal, if not greater symptom burden, and that this is accordingly reflected in their physical health status scores.21, 22 Our results underscore the importance of the issue of impaired physical health status in PAD patients and urge clinicians to focus on the invalidating character of PAD from the patient's point of view.

Mental health status was found to be worse in CHF patients as compared with PAD patients. However, this does not imply that mental health status is not affected by PAD. In fact, recent findings indicate that depressive mood is a substantial problem in PAD.23, 24 The reason why there was a discrepancy in mental health status levels between both groups may be that CHF patients have to deal with end of life issues due to the advanced character of their disease.25 The observed disparity that was found regarding physical health status in both medical conditions may be explained by the occurrence of response shift in patients with more advanced cardiovascular disease.26 CHF patients may have acquiesced in the fact that their condition and its associated burden are irreversible, while patients with PAD may perceive their illness as more transient and expect to improve physical functioning. In contrast with CHF, there are diverse treatment options available for PAD patients that are aimed to relieve symptom burden.1

Important clinical and socio-demographic correlates of worse health status scores in PAD included younger age, lower educational level, cardiac history, diabetes mellitus, lower ABI scores, and living without a partner. Clinical factors that were associated with lower health status scores in CHF patients were female gender and comorbid diabetes mellitus. All these characteristics are easy to detect in daily clinical practice and should increase clinicians' awareness, as these clinical and socio-demographic correlates have been previously shown to explain disparities in cardiovascular outcomes.27, 28

Our results illustrate that it may be worthwhile studying risk factors in terms of poor health status outcomes per individual cardiovascular condition; especially in PAD, a firm research tradition on documenting patient-centered outcomes is still lacking and needs further development. Input from these studies will be needed to develop disease-specific management programs. In cardiac disease, health professionals are familiar with a tradition of multidisciplinary disease management programs, offering patient education, smoking cessation, and diet and exercise counseling, which have proven to be effective in improving clinical outcomes and health status.29, 30 Such specific multidisciplinary treatment programs are not widespread in patients with PAD, although PAD patients have a poor cardiovascular prognosis and share the same risk factors with coronary heart disease patients.3, 31 The results of this study indicate that there is a need to develop specific management programs for PAD patients as different aspects of health status may be impacted by their condition and will require a tailor-made approach to optimize health status outcomes.

This study has some limitations: first, the current study did not evaluate the role of behavioral or intrapsychic factors, such as personality and distress, factors that may be equally important or even more important when documenting patients' health status.32, 33 Future research studying PAD patients' health status needs to incorporate traditional disease indicators and clinical information, as well as socio-demographic, behavioral, and psychological variables. Second, due to the cross-sectional nature of this study, no causality can be inferred from our findings. Third, since we analyzed the results of an observational study, we need to take into account the possibility of residual confounding. Finally, due to the lack of protocol-driven echo screening in PAD patients and ABI screening in CHF patients, we only could rely on their primary clinical diagnosis to define our clinical populations.

In conclusion, this study showed that physical health status was worse in PAD patients, as compared with CHF patients, whereas mental health status was more affected in CHF patients. Previous research already indicated that the secondary prevention of PAD patients is suboptimal when comparing with other cardiac patient groups.2 By contrasting the health status of PAD patients with the health status of CHF patients, this study identified a new need that requires action. We believe that our findings may initiate further research documenting risk populations of patients with PAD in terms of their health status. Health status measures are becoming increasingly important in the sense that they provide an answer to the need of having more sensitive outcome measures to evaluate treatment outcomes in PAD, as opposed to traditional clinical outcomes, such as death and patency rates. Focusing on patient-centered outcomes is also relevant because they provide important input for the development of disease management programs, and because of the potential prognostic information contained in these measures.34

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Author contributions 


Conception and design: KS, JD, AP

Analysis and interpretation: KS, AP, NK, FM

Data collection: KS, AP

Writing the article: KS, AP

Critical revision of the article: FM, NK, JD

Final approval of the article: KS, AP, NK, FM, JD

Statistical analysis: KS, AP

Obtained funding: JD

Overall responsibility: KS, JD

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The study was supported by The Netherlands Organization for Scientific Research, The Hague, The Netherlands with a VICI grant (453-04-004) to Dr. Johan Denollet. We would like to thank all participating patients and Drs Vriens, Van Berge Henegouwen, Burger, Heyligers, Kranendonk, de Feyter, Gerritsen, Brenninkmeijer, Szabó, Alings, Janssens, Mrs. Nooren, Mr. Van Hees, Mrs. Vingerhoets, and Mrs. de Wit for their help with the data collection.

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 Competition of interest: none.

 The editors and reviewers of this article have no relevant financial relationships to disclose per the JVS policy that requires reviewers to decline review of any manuscript for which they may have a competition of interest.

PII: S0741-5214(09)01581-X

doi:10.1016/j.jvs.2009.07.109

Journal of Vascular Surgery
Volume 50, Issue 6 , Pages 1391-1398, December 2009

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