Peripheral artery disease is associated with frailty in chronic hemodialysis patients

Abstract

Objectives

The clinical condition of frailty is a common problem in the elderly population. However, the relationship between peripheral artery disease and frailty in hemodialysis patients remains unknown. The aim of this study was to identify the relationships between peripheral artery disease and frailty in Japanese chronic hemodialysis patients.

Methods

A total of 362 chronic hemodialysis patients who regularly visited six institutions were enrolled. To evaluate frailty, the modified Fried’s frailty phenotype adjusted for Japanese were used. Peripheral artery disease was defined as ankle-brachial index <0.9.

Results

Of 362 patients, 62 patients (17.1%) were categorized as peripheral artery disease group and 300 patients (82.9%) as Non-peripheral artery disease group. The prevalence of frailty in the peripheral artery disease group was significantly higher than in the Non-peripheral artery disease group (34% vs. 18%, P = 0.0103). Non-shunt side grip strength was significantly stronger in the Non-peripheral artery disease group (23.6 kg vs. 17.0 kg, P < 0.0001). Thigh circumferences were also significantly larger in the Non-peripheral artery disease group (41.7 cm vs. 39.7 cm, P = 0.0054). A multivariate logistic regression analysis demonstrated that the factors independently associated with peripheral artery disease were as follows: frailty (odds ratio = 2.06, 95% confidence interval 1.09–3.89) and myocardial infarction (odds ratio = 3.74, 95% confidence interval 2.05–6.83).

Conclusions

It is concluded that peripheral artery disease is closely associated with frailty in hemodialysis patients.

Keywords

Frailty hemodialysis peripheral artery disease

Introduction

Recently, the global population has acquired longevity. Lifespan of the global population has begun rapidly increasing.¹ However, the healthy life expectancy at birth was about ten-year shorter than the life expectancy.² Global population has never enjoyed the merit of longevity, and the functional health lost has become a major concern.

These days, clinical condition of frailty has become a particularly problematic issue in elderly population. Frailty is considered to be the end of healthy life as well as a preliminary step of persons needing long-term care.³ Frailty leads not only to social endpoints, but also to hard endpoints, such as mortality.⁴ The factors associated with presence of frailty were aging, female gender, race, socioeconomic state, smoking, obesity, shrinking, a history of cardiovascular disease, bone fracture, falling, chronic obstructive pulmonary disease, diabetes mellitus (DM), depression,⁵ undernutrition,⁶ dementia,⁷ malignancy,⁸ chronic kidney disease (CKD), and end-stage renal disease (ESRD).⁹ Fried and colleague’s described Cardiovascular Health Study (CHS) frailty phenotypes as a definition of frailty.¹⁰ Currently, this index is commonly known.

Based on Fried’s definition, frailty has been documented in 7% of the elderly population, 14% of CKD patients without dialysis and 42% of adult ESRD patients on hemodialysis (HD),⁹ whereas frailty was 21.4% of our participants.¹¹ Patients with HD are at high risk for cardiovascular morbidity simultaneously. Peripheral arterial disease (PAD) is common complication in HD patients and is associated with increased risk of cardiovascular mortality.^12,13 However, an association of PAD with frailty in HD patients remains unknown.

We previously reported the current status of frailty in Japanese HD patients.¹¹ We hypothesized that PAD patients in chronic HD cohort are prone to develop frailty. Therefore, in this study, we aimed to investigate the association between PAD and frailty in Japanese HD patients.

Materials and methods

Study design and participants

This study was a multicenter, cross-sectional, and observational investigation during October 2015 to February 2016. This study was conducted at six institutions with an HD unit, including five general hospitals and one private clinic: Innoshima General Hospital, Nippon Kokan Fukuyama Hospital, Sumitomo Besshi Hospital, Mihara Shiromachi Hospital, Akaiwa Medical Association Hospital, and Sugimoto Clinic. All of the data acquisition were done by the attending physicians and medical staff at each institution and sent to the Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences for the analysis.

The subjects were all chronic HD patients who regularly visited the institutions within the period of this study, and who agreed with the aim and protocol of the present study. The initial exclusion criteria were: (1) refusal to participate, (2) hospitalization due to accidents or sickness, and (3) patients who found it difficult to answer the questionnaire. After that, we excluded participants who did not completely fill in the frailty contents as we described previously.¹¹ Finally, we excluded patients who could not be determined Ankle Brachial Index (ABI) from those remaining after the initial exclusion. As a result, a total of 362 chronic HD patients were enrolled (Figure 1).

Figure 1.

Enrolled patients.

Figure 1 shows the included patients of this study. For the reasons indicated in the boxes on the right side, we eliminated 176 patients in total. In the end, we enrolled 362 patients.

Evaluation measurements and factors

By checking medical records, the following risk factors of each patient were evaluated: body mass index (BMI), hypertension (HTN), dyslipidemia (DLP), DM, smoking habit, ischemic heart disease (IHD), stroke (STK), PAD, frequency and quantity of dialysis, data of blood tests, ABI, brachial-ankle plus wave velocity (ba PWV). The definition of HTN, DLP, DM, IHD, STK, and PAD, and measurement of physical domain are described previously.¹¹ ABI was used for definition of PAD as we described in the section “Definition of PAD”. To evaluate the dialysis efficiency, we calculated single-pooled Kt/V.¹⁴ To evaluate the nutritional status, we calculated normalized protein catabolic rate (nPCR)¹⁵ and Geriatric Nutritional Risk Index (GNRI),¹⁶ and asked participants to fill out the Mini Nutritional Assessment-Short Form (MNA-SF)¹⁷ questionnaire. To evaluate the frailty status, we asked participants to check the appropriate boxes no the frailty phenotype questionnaire which we made according to the section “Definition of the frailty”.

Definition of the PAD

We defined PAD according to major prospected cohort study.¹⁸ In our study PAD was defined as ABI <0.9, and then we defined ABI ≥0.9 as Non-PAD.

Definition of the frailty

The operational definition of frailty phenotype in the present study was as we described previously.¹¹ Individuals who met at least three criteria were defined as frailty. All five criteria were modified from the original Fried CHS frailty phenotype.¹⁰

Ethics

This study complied with the Declaration of Helsinki (seventh revision, 2013) on medical protocol and ethics. This was a cross-sectional observational study. Since we collected the data from physicians’ charts and questionnaires filled out by the patients, the Institutional Review Boards at each hospital waived the requirement of written informed consent but requested patients be given the opportunity to refuse enrollment by leaflets or the hospital website. Finally, each ethics committee of the Institutional Review Board approved the protocol. The study protocol was registered as a clinical trial; UMIN ID: 000024783.

Statistical analysis

All data were expressed as the mean ± standard deviation or n (%). Differences among each phenotype were examined by a student t-test or chi-squared test. To evaluate the predictors of PAD, we performed univariate and multivariate logistic regression analyses which estimated the prevalence odds ratio (OR) for PAD relative to Non-PAD. A difference of P <0.05 was taken as statistically significant. All data were analyzed using Sigma Plot for Windows (version 13.0, Systat Software Inc., San Jose, California, USA).

Results

Backgrounds of the patients

Backgrounds of participants are shown in Table 1. Age was significantly higher in PAD group than in Non-PAD group. Regarding blood tests, plasma hemoglobin (Hb), albumin and Total cholesterol concentration were significantly lower in PAD group than in Non-PAD group. ba PWV was significantly higher in PAD group. Regarding the components related to dialysis, duration of dialysis was significantly longer in PAD group than in Non-PAD group. Kt/V sp was also higher in PAD group, although these in both groups were over 1.4. Among the risk factors, the prevalence of DM and MI were significantly higher in PAD group.

Table 1.

Profiles of the patients.

	PAD group	Non-PAD group	P-value
Age	71.1 ± 9.6	66.6 ± 12.1	0.0055^a
Sex (men)	59.7% (37/62)	61.3% (184/300)	0.9201^b
BMI (kg/m²)	22.1±4.1	21.8 ± 3.4	0.5514
Smoking history	48.6% (30/62)	43.7% (131/300)	0.5888^b
Number of oral medicine	11.3 ± 3.7	10.0 ± 3.7	0.0784
Using medicine for dementia	3.2% (2/62)	2.3% (7/300)	0.9704^b
Hb (g/dL)	10.8 ± 0.9	10.7 ± 1.0	0.7325
Alb (g/dL)	3.4 ± 0.3	3.7 ± 0.5	0.0024
T. Cho (mg/dL)	147.7 ± 33.0	163.3 ± 42.6	0.0069
BUN (mg/dL)	56.9 ± 13.3	66.3 ± 17.4	0.0004
Cre (mg/dL)	9.0 ± 2.3	9.6 ± 3.6	0.2320
ba PWV (cm/s)	2108 ± 151	1904 ± 26	0.0209
GNRI	93.2 ± 9.7	96.7 ± 10.5	0.0761
MNA-SF	11.7 ± 2.0	11.5 ± 2.1	0.6371
Dialysis sessions/week	3.0 ± 0.0	3.0 ± 0.2	0.8913^a
Dialysis time (hour)	4.1 ± 0.4	4.1 ± 0.3	0.8845
Dialysis history (years)	11.1 ± 9.0	8.1 ± 7.2	0.0044
Water removal/dry weight (%)	4.1 ± 1.5	4.4 ± 0.3	0.1102
Kt/V sp	1.55 ± 0.34	1.43 ± 0.41	0.0259
DM	61.0% (36/62)	37.3% (112/300)	0.0012^b
HTN	66.1% (41/62)	75.7% (227/300)	0.1615^b
DLP	24.2% (15/62)	22.0% (66/300)	0.8337^b
MI	45.2% (28/62)	15.7% (47/300)	<0.0001^b
CI	14.5% (9/62)	15.7% (47/300)	0.9719^b

BMI: body mass index; Hb: hemoglobin; Alb: albumin; T. Cho: total cholesterol; BUN: blood urea nitrogen; ba PWV: brachial-ankle pulse wave velocity; GNRI: Geriatric Nutritional Risk Index; MNR-SF: Mini Nutritional Assessment-Short Form; Kt/V sp: Kt/V single pool (K reflects clearance of BUN, t reflects dialysis time, and V reflects body fluid volume); DM: diabetes mellitus; HTN: hypertension; DLP: dyslipidemia; MI: myocardial infarction; CI: cerebral infarction; PAD: peripheral arterial disease.

P-values were obtained by T-test (with no mark).

^aMann–Whitney rank sum test.

^bChi-square test.

Prevalence of frailty

The prevalence of frailty in PAD group (34%) was significantly higher than that in Non-PAD group (18%) (Figure 2).

Figure 2.

Prevalence of frailty.

Figure 2 shows prevalence of frail in PAD group and Non-PAD group. In PAD group, 34% of patients were frail. On the other hand, 18% of Non-PAD group were frail. Proportion of Frail patients was significantly larger in PAD group. P-values were obtained by Chi-square test.

Muscle strength or muscle mass

Grip strength of Non-shunt side was significantly lower in PAD group than in Non-PAD group (Figure 3(a)). As for the arm circumference of Non-shunt side, no significant difference was detected between the two groups (Figure 3(b)). Thigh circumference was significantly shorter in PAD group (Figure 3(c)).

Figure 3.

Muscle strength or muscle mass.

These bar charts show the barometers of muscle strength or mass of upper limb and muscle mass of lower limb. A; Grip strength of non-shunt side. B; Arm circumference of non-shunt side. C; Thigh circumference (The mean of both sides). Upper and lower limb muscle strength was significantly lower in PAD groups. Upper muscle mass is also lower in PAD group. P-values were obtained by T-test.

Multiple logistic regressions

To evaluate the association between PAD and its risk factors, univariate and multivariate logistic regression were performed. Univariate regression revealed that frailty, age, number of oral medicine, MI, and DM had strong correlation with PAD (Table 2). Furthermore, multiple logistic regression analyses in several models showed that frailty still showed significant correlation with PAD. Since DM is closely associated with PAD and it is one of the well-known risk factors of PAD, DM was excluded from multiple logistic regression models.

Table 2.

Multiple logistic regressions.

	Univariate regression			Multiple logistic model 1			Multiple logistic model 2
	Odds ratio	95% CI	P-value	Odds ratio	95% CI	P-value	Odds ratio	95% CI	P-value
Frailty	2.22	1.22–4.04	0.009	2.06	1.09–3.89	0.025	2.08	1.07–4.03	0.030
Age ≥ 75	1.89	1.08–3.32	0.026	1.65	0.90–3.00	0.099	1.86	1.00–3.45	0.048
Sex (men)	0.96	0.55–1.68	0.896				0.82	0.38–1.78	0.610
BMI < 18.5, ≥ 25.0	1.56	0.89–2.72	0.115				1.69	0.92–3.11	0.091
Smoking	1.25	0.73–2.17	0.406				1.25	0.60–2.61	0.555
Oral medicine ≥ 6	4.71	1.11–20.0	<0.001	3.25	0.75–14.2	0.116	3.28	0.75–14.4	0.116
GNRI < 92	1.76	1.09–2.88	0.235
MI	4.08	2.27–7.32	<0.001	3.74	2.05–6.83	<0.001	3.59	1.93–6.65	<0.001
DM	2.23	1.28–3.86	0.004

BMI: body mass index; GNRI: Geriatric Nutritional Risk Index; MI: myocardial infarction; DM: diabetes mellitus.

From univariate regression, frailty, age, number of oral medicine, MI, and DM had strong correlation with Peripheral Artery Disease (PAD). After adjusting their interrelationships by using Multiple Logistic Regression analysis, Frailty was still remained as a significant risk factor of PAD (Model 1). Model 2 contains the classical risk factors. After adjusting interrelationships among classical risk factors, Frailty was still remained as a significant risk factor of PAD. BMI, GNRI, myocardial infarction (MI), DM. P-values were obtained by single or multiple logistic regression analysis.

Discussion

Our primary purpose of this study was to determine the association between PAD and frailty in Japanese HD patients. We found that the proportion of frailty in PAD group was two times higher than that in Non-PAD group. Grip strength and thigh circumference values were significantly associated with the existence of PAD. After adjusting classical risk factors, PAD has a significant correlation with frailty.

A previous study revealed that the existence of PAD aggravates doubled the risk of frailty in the Non-HD cohort.¹⁹ However, the relationship between PAD and frailty remained still unclear in HD patients. Former studies described that the score of ABI tended to be higher in HD patients than Non-HD cohort.^20,21 Therefore, there is a possibility that our Non-PAD groups in our study might include several PAD patients, if we conducted the image test to them in detail. However, it is important that our results are derived by non-invasive and simple examination, and the present association between PAD and frailty, such as the lower grip strength and smaller thigh circumference values in patients with PAD was not changed according to the definition of PAD as ABI <1.0. Former cohorts demonstrated that the HD patients with DM tend to have asymptomatic PAD.^22,23 The result of the multivariate logistic regression analysis suggested that the screening of PAD using ABI test could provide a preferable maker to detect not only PAD patients, but also patients with frailty. In the 5-year follow-up study concerning PAD, patients with low ABI was associated with higher incidence of mobility loss and becoming unable to walk compared to patients with normal ABI.²⁴ The loss of ability to walk leads to the low physical activity. Slow walking speed and low physical activity are main component of frailty criteria, and the frailty cycle which Fried proposed shows the low activity leads to the low strength.

This study also demonstrated that the low grip strength and the small thigh circumference values were significantly associated with the existence of PAD. It was a very interesting result, since the diseases of lower limbs weaken the muscles of upper limbs. Several studies demonstrated that lower ABI had interrelation between the strength of planter flexion or knee extension in Non-HD cohort.^25,26 However, these studies did not describe that there was significant relationship between low ABI score and grip strength. The significant relationship between the grip strength and low ABI score in our study might proceed from that we examined the chronic HD cohort. Generally, it is considered that chronic HD patients tend to have physical deconditioning because of the long-sustained bed ridden and the decreased activity caused by exhaustion after HD itself. Therefore, HD patients might suffer from the decrease in whole body muscle, resulting in the decrease in grip strength.

This study had several limitations. First, this was a cross-sectional study. Therefore, the risk for the hospitalization, having crucial limb ischemia, amputation or death in PAD population with frailty was not revealed in this analysis. Second, we did not examine detailed physical function, such as walking speed and chair standing up time. These points were closely related the symptoms of PAD and frailty itself. Third, we did not check the tolerability for exercise. Thus, we cannot assess the change of physical function plentifully, if we intervene against PAD and frailty in the future. Fourth, we did not examine physical body composition, such as muscle mass, body fat, and edema, with computed tomography scan, bioelectrical impedance analysis or Dual Energy X-Ray Absorptiometry; however, brachial or femoral circumferences were measured in this study, so these might be substitution for body consumption.

In conclusion, our study demonstrated the significant association between PAD and frailty in chronic HD cohort. Therefore, the screening by ABI might be worth to find not only PAD patients but also the patients with frailty. For chronic HD patients, early detection and therapeutic intervention for PAD would be important to prevent the adverse outcome and poor quality of life. Further prospective longitudinal assessment and interventional study are required to disclose the detail interaction between PAD and frailty in HD patients.

Footnotes

Acknowledgement

We would like to thank Dr. Taro Sugimoto of the Sugimoto Clinic and Dr. Hiroo Hashimoto from Innoshima General Hospital for their kind help in contacting the patients of their respective institutions, and the medical staff at each institution for their help in collecting the patients’ data. We also would like to thank Akiyo Nouchi for her help to manage data.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Jun Wada receives speaker honoraria from Astellas, Boehringer Ingelheim, Daiichi Novartis, Sankyo, and Tanabe Mitsubishi, and receives grant support from Astellas, Bayer, Baxter, Chugai, Daiichi Sankyo, Kissei, Kyowa Hakko Kirin, MSD, Novartis, Novo Nordisk, Ono, Otsuka, Pfizer, Teijin, Torii, and Takeda.

References

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016; 388: 1459–1544.

Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016; 388: 1603–1658.

Langmann

Perera

Ferchak

et al . Inflammatory markers and frailty in long-term care residents. J Am Geriatr Soc 2017.

Clegg

Young

Iliffe

et al . Frailty in elderly people. Lancet 2013; 381: 752–762.

Woods

LaCroix

Gray

et al . Frailty: emergence and consequences in women aged 65 and older in the Women's Health Initiative Observational Study. J Am Geriatr Soc 2005; 53: 1321–1330.

Bartali

Frongillo

Bandinelli

et al . Low nutrient intake is an essential component of frailty in older persons. J Gerontol Ser A Biol Sci Med Sci 2006; 61: 589–593.

Buchman

Boyle

Wilson

et al . Frailty is associated with incident Alzheimer's disease and cognitive decline in the elderly. Psychosom Med 2007; 69: 483–489.

Handforth

Clegg

Young

et al . The prevalence and outcomes of frailty in older cancer patients: a systematic review. Ann Oncol Off J Eur Soc Med Oncol 2015; 26: 1091–1101.

Musso

Jauregui

Macias

NJF.

Frailty phenotype and chronic kidney disease: a review of the literature. Int Urol Nephrol 2015; 47: 1801–1807.

10.

Fried

Tangen

Walston

et al . Frailty in older adults: evidence for a phenotype. J Gerontol Ser A Biol Sci Med Sci 2001; 56: M14656.

11.

Takeuchi

Uchida

Kakio

et al . The prevalence of frailty and its associated factors in japanese hemodialysis patients. Agin Dis. Early edition. DOI: 10.14336/AD.2017.0429.

12.

Rajagopalan

Dellegrottaglie

Furniss

et al . Peripheral arterial disease in patients with end-stage renal disease: observations from the Dialysis Outcomes and Practice Patterns Study (DOPPS). Circulation 2006; 114: 1914–1922.

13.

Hokimoto

Sakamoto

Akasaka

et al . High mortality rate in hemodialysis patients who undergo invasive cardiovascular procedures related to peripheral artery disease – community-based observational study in Kumamoto Prefecture. Circ J 2015; 79: 1269–1276. Society.

14.

Shinzato

Nakai

Fujita

et al . Determination of Kt/V and protein catabolic rate using pre- and postdialysis blood urea nitrogen concentrations. Nephron 1994; 67: 280–290.

15.

Depner

Daugirdas

JT.

Equations for normalized protein catabolic rate based on two-point modeling of hemodialysis urea kinetics. J Am Soc Nephrol JASN 1996; 7: 780–785.

16.

Kobayashi

Ishimura

Kato

et al . Geriatric Nutritional Risk Index, a simplified nutritional screening index, is a significant predictor of mortality in chronic dialysis patients. Nephrol Dial Transpl Off Publ Eur Dial Transpl Assoc Eur Ren Assoc 2010; 25: 3361–3365.

17.

Lilamand

Kelaiditi

Cesari

et al . Validation of the mini nutritional assessment-short form in a population of frail elders without disability. Analysis of the toulouse frailty platform population in 2013. J Nutr Health Aging 2015; 19: 570–574.

18.

Diehm

Allenberg

Pittrow

et al . Mortality and vascular morbidity in older adults with asymptomatic versus symptomatic peripheral artery disease. Circulation 2009; 120: 2053–2061.

19.

Singh

Bailey

Noheria

et al . Frailty across the spectrum of ankle-brachial index. Angiology 2012; 63: 229–236.

20.

Miura

Minamisawa

Ueki

et al . Impressive predictive value of ankle-brachial index for very long-term outcomes in patients with cardiovascular disease: IMPACT-ABI study. PloS One 2017; 12: e0177609

21.

Viazzi

Leoncini

Ratto

et al . Peripheral artery disease and blood pressure profile abnormalities in hemodialysis patients. J Nephrol 2017; 30: 427–433.

22.

Matsuzawa

Aoyama

Yoshida

Clinical characteristics of patients on hemodialysis with peripheral arterial disease. Angiology 2015; 66: 911–917.

23.

Shiraki

Iida

Takahara

et al . Predictors of delayed wound healing after endovascular therapy of isolated infrapopliteal lesions underlying critical limb ischemia in patients with high prevalence of diabetes mellitus and hemodialysis. Eur J Vasc Endovasc Surg Off J Eur Soc Vasc Surg 2015; 49: 565–573.

24.

McDermott

Guralnik

Tian

et al . Associations of borderline and low normal ankle-brachial index values with functional decline at 5-year follow-up: the WALCS (Walking and Leg Circulation Study). J Am Coll Cardiol 2009; 53: 1056–1062.

25.

McDermott

Tian

Ferrucci

et al . Associations between lower extremity ischemia, upper and lower extremity strength, and functional impairment with peripheral arterial disease. J Am Geriatr Soc 2008; 56: 724–729.

26.

Min

Cho

Lee

et al . Thigh circumference and low ankle brachial index in US adults: results from the National Health and Nutrition Examination Survey 1999–2004. Int J Cardiol 2013; 163: 40–45.