Abstract
Aims: The progression of atherosclerosis and decline in physical function are poor prognostic factors in patients with cardiovascular disease (CVD). The ankle–brachial index (ABI) is a widely used indicator of the degree of progression of atherosclerosis, which may be used to identify patients with CVD who are at risk of poor physical function. This study examined the association between ABI and poor physical function in patients with CVD.
Methods: We reviewed the data of patients with CVD who completed the ABI assessment and physical function tests (6-min walking distance, gait speed, quadriceps isometric strength, and short physical performance battery). Patients were divided into five categories according to the level of ABI, and the association between ABI and poor physical function was examined using multiple logistic regression analysis. Additionally, restricted cubic splines were used to examine the nonlinear association between ABI and physical function.
Results: A total of 2982 patients (median [interquartile range] age: 71[62–78] years, 65.8% males) were included in this study. Using an ABI range of 1.11–1.20 as a reference, logistic regression analysis showed that ABI ≤ 1.10 was associated with poor physical function. The restricted cubic spline analysis showed that all physical functions increased with an increase in ABI level. The increase in physical function plateaued at an ABI level of approximately 1.1.
Conclusions: ABI may be used to identify patients with poor physical function. ABI levels below 1.1 are potentially associated with poor physical function in patients with CVD.
See editorial vol. 31: 353-354
Abbreviation: 6MWD: 6-minute walking distance, ABI: ankle–brachial index, ACE: angiotensin-converting enzyme , ACS: acute coronary syndrome , ARB: angiotensin II receptor blocker, BM: body mass, BMI: body mass index, CI: confidence interval, CRP: C-reactive protein , CVD: cardiovascular disease, DBP: diastolic blood pressure;, eGFR: estimated glomerular filtration rate, HDL-C: high-density lipoprotein cholesterol, HF: heart failure, IQR: interquartile range, LDL-C: low-density lipoprotein cholesterol, LVEF: left ventricular ejection fraction, MI: myocardial infarction, OR: odds ratio, PAD: peripheral arterial disease, QIS: quadriceps isometric strength, SBP: systolic blood pressure, SPPB: short physical performance battery, TC: total cholesterol, TG: triglyceride
Introduction
In community-dwelling older adults with cardiovascular disease (CVD), the progression of atherosclerosis and decline in physical function lead to poor prognosis1, 2). Atherosclerosis and poor physical function share the same risk factors, which includes aging3), insulin resistance4, 5), malnutrition6, 7), and low physical activity8, 9). Previous studies have suggested that the progression of atherosclerosis is associated with poor physical function in patients with CVD10, 11).
Ankle–brachial index (ABI), the ratio of systolic blood pressure (SBP) at the ankle joint level to the SBP in the brachial artery, is often used as an indicator to assess the progression of atherosclerosis and peripheral arterial disease (PAD)12). Guidelines and meta-analyses use an ABI level of ＜0.90 to identify patients with PAD, and an ABI level of ＜1.00 to identify patients with an increased risk of coronary events and mortality13-15) due to atherosclerosis. Multiple studies have shown that a decline in physical function is an important poor prognostic factor in patients with CVD that precedes coronary events and mortality16), suggesting that poor physical function may be identified before patients reach the ABI cutoff for the increased risk of coronary events and mortality (i.e., 1.00).
Aim
This study examined the association between ABI and poor physical function in patients with CVD and determined the ABI cutoff to identify patients at risk of poor physical function.
Methods
Study Design and Population
This was a single-center retrospective observational study that reviewed a cohort of consecutive patients with CVD who were admitted to Kitasato University Hospital and underwent cardiac rehabilitation during hospitalization between December 2006 and December 2021.
From a cohort of 9744 consecutive patients with CVD who are ≥ 18 years old, we excluded 3179 patients whose ABI was not evaluated and 3497 patients who did not perform physical function tests (6-min walking distance [6MWD], gait speed, quadriceps isometric strength [QIS], and/or short physical performance battery [SPPB]). In addition, patients who presented with incompressible arteries, as indicated by an ABI of ＞1.4 17), and a history of lower extremity revascularization and treatment were excluded. Finally, 2982 patients were included in the study (Fig.1). The study protocol conformed to the tenets of the Declaration of Helsinki and was approved by the Ethics Committee of Kitasato University Medical Ethics Organization (no. KMEO B22-143). Since this was an observational study that did not involve invasive procedures or interventions, written informed consent was not required according to the “Ethical Guidelines for Medical and Health Research for Subjects” by the Japanese Ministry of Health, Labor, and Welfare.
Age, sex, physical characteristics (body mass [%BM], height, and body mass index [BMI]), vital signs (blood pressure and heart rate), diagnosis (acute coronary syndrome, heart failure [HF], post-cardiac surgery, and aortic disease), comorbidities (hypertension, dyslipidemia, diabetes mellitus, prior HF, and prior myocardial infarction [MI]), presence of intermittent claudication, smoking habit (current or not), medication use, and biochemical data before discharge from the hospital were collected from electronic medical records. The formula used for the estimated glomerular filtration rate (eGFR) was the one recommended by the Japanese Society of Nephrology: for male: 194×(serum creatinine)1.094×(age)0.287; for female: 194×(serum creatinine)1.094×(age)0.287×0.739 18). Simpson’s method was used to estimate left ventricular ejection fraction (LVEF) on two-dimensional echocardiograms. Physical activity status prior to admission was assessed using a three-item self-administered questionnaire previously developed and validated by Smith et al.19). Patients reported the number of bouts of vigorous-intensity physical activity lasting 20 min and walking or moderate-intensity activity lasting 30 min in a usual week. According to the responses in the questionnaire, each subject’s physical activity level was classified as high, adequate, low, or minimal.
ABI Measurements
ABI was measured during the period of hospitalization using a blood pressure pulse–wave inspection device (BP-203RPEII form; Omron Colin Co., Ltd., Komaki, Japan), which uses the oscillometric technique and was previously validated as a screening device for assessing subclinical vascular pathology20, 21). After a 5-min rest in the supine position, patients’ SBPs were simultaneously measured twice with cuffs placed over the brachial arteries of both arms and posterior tibial arteries of both legs. The first measurement was discarded, and the second measurement was stored in the database. The resting ABI was determined for each leg by dividing the ankle SBP by the brachial pressure; the The lower of the left and right ABIs were used in the data analysis22).
Physical Function Measurements
We measured 6MWD, gait speed, QIS, and SPPB of the patients before they were discharged from the hospital. 6MWD was determined according to the guidelines of the American Thoracic Society under the supervision of technicians23). The use of a walking aid during the test was permitted if required. Patients received standardized instructions to walk as much distance as possible in a set amount of time down a straight, flat corridor marked at 1-meter intervals, and the distance (m) was recorded after 6 min.
The time required for patients to walk between the 10- and 16-m marks was measured. The gait speed was calculated by dividing the distance (m) by time (s).
SPPB, which consists of three components (4-m usual gait speed, repeated chair stands, and standing balance), was measured according to the established methods24). Each component score ranged from 0 to 4 points. Thus, the SPPB score ranged from 0 to 12 (0=worst to 12=best).
QIS was measured with a handheld dynamometer (µ-Tas; ANIMA, Tokyo, Japan) fixed to a rigid bar. With the patient sitting on a bench, 5-s maximal isometric voluntary contractions of the quadriceps were collected two times successively for both legs, with the knee joints fixed at a 90°-flexion and the hip joints at an approximately 90°-flexion. The lower end of the pressure sensor was placed on the two lateral fingers from the lateral malleolus, and it was installed on the front of the lower thigh. The strength of the right and left quadriceps were tested consecutively. The greatest strength values on the right and left sides were averaged and expressed as an absolute value (kg) and relative to %BM.
Statistical Analysis
Continuous variables are presented as mean±standard deviation, and non-normally distributed variables are presented as medians (interquartile ranges [IQRs]). Categorical variables are expressed as frequency and percentages. For the missing data on confounders, we performed multiple imputations using the chained equation method, assuming that analyzed data were missing at random. Results from 20 imputed datasets were combined for analysis using Rubin’s formula.
Patients were divided into five categories according to the level of ABI: ABI ≤ 0.90, ABI 0.91–1.00, ABI 1.01–1.10, ABI 1.11–1.20, and ABI 1.20–1.40. Baseline characteristics were compared between ABI categories using the Kruskal–Wallis test for continuous variables, and the χ2 test was used for categorical variables. To examine the association between physical function and the ABI levels, we performed a Jonckheere–Terpstra test for continuous variables and a Cochran–Armitage trend test for categorical variables.
We constructed adjusted models to investigate the association between ABI and poor physical function (6MWD ＜300 m25) and ＜400 m26), gait speed ＜0.8 m/s27) and ＜1.0 m/s28), SPPB ＜9 points29) for both sexes, and QIS ＜45.0 %BM and ＜35.0 %BM in males and females, respectively30)). We used a multiple logistic regression model adjusted for age, sex, BMI, SBP, comorbidities (hypertension, dyslipidemia, and diabetes), smoking, prior MI, and prior HF; use of angiotensin-converting enzyme inhibitor, angiotensin II receptor blocker, beta-blocker, diuretic agents, and statins; levels of total cholesterol, low-density lipoprotein, and high-density lipoprotein cholesterol; physical activity; and intermittent claudication. Odds ratio (OR) and 95% confidence interval (CI) were calculated for the other ABI categories in comparison with the reference range of 1.11–1.20 2). Furthermore, we modeled nonlinear associations between ABI and physical function using restricted cubic splines with three knots. The model was adjusted for age and sex. Statistical analyses were performed using Stata/SE version 16.1 (StataCorp LP, College Station, TX, USA). In all analyses, a two-tailed p＜0.05 indicated statistical significance.
Results
Study Population
Table 1 shows the baseline characteristics for all patients and for patients classified according to the level of ABI. The median (IQR) age of the study population was 71 (62–78) years, 65.8% of the patients were male, 4.0% had intermittent claudication, 43.5% had HF, 20.9% had acute coronary syndrome, 32.4% had post-cardiac surgery, and 9.9% had aortic disease. Among the 2982 patients, 356 (11.9%) had an ABI of ≤ 0.90, 401 (13.5%) had an ABI of 0.91–1.00, 950 (31.9%) had an ABI of 1.01–1.10, 890 (29.9%) had an ABI of 1.11–1.20, and 385 (12.9%) had an ABI of 1.21–1.40. Lower ABI levels were associated with a higher percentage of the presence of intermittent claudication (p trend ＜ 0.001).
Table 1.Baseline characteristics for all patients and for patients classified by ABI categories.
| Factor |
Missing data
n (%)
|
Overall
n = 2982
|
ABI |
|
≤ 0.90
n = 356 (11.9%)
|
0.91 – 1.00
n = 401 (13.5%)
|
1.01 – 1.10
n = 950 (31.9%)
|
1.11 – 1.20
n = 890 (29.9%)
|
1.21 – 1.40
n = 385 (12.9%)
|
p-value
|
| Age, years |
0 (0.0) |
71 [62 – 78] |
74 [67 – 80] |
72 [59 – 79] |
70 [59 – 78] |
72 [63 – 78] |
71 [63 – 77] |
＜0.001 |
| Male |
0 (0.0) |
1963 (65.8) |
239 (67.1) |
242 (60.4) |
582 (61.3) |
610 (68.5) |
290 (75.3) |
＜0.001 |
| ABI |
0 (0.0) |
1.08 [1.00 – 1.16] |
0.77 [0.66 – 0.86] |
0.97 [0.94 – 0.99] |
1.06 [1.04 – 1.08] |
1.15 [1.13 – 1.17] |
1.26 [1.22 – 1.30] |
＜0.001 |
| Body mass, kg |
7 (0.2) |
57.5 [49.5 – 66.2] |
56.6 [48.8 – 64.1] |
54.6 [47.0 – 63.7] |
57.8 [49.8 – 66.9] |
58.1 [50.1 – 66.8] |
58.6 [52.2 – 66.1] |
＜0.001 |
| Height, cm |
0 (0.0) |
162.0 [155.0 – 168.0] |
161.5 [153.4 – 167.0] |
160.0 [151.9 – 167.8] |
161.1 [154.0 – 168.0] |
163.0 [156.0 – 169.0] |
163.7 [158.2 – 168.5] |
＜0.001 |
| BMI, kg/m2
|
7 (0.2) |
22.0 [19.8 – 24.6] |
21.8 [19.8 – 24.2] |
21.3 [19.5 – 24.2] |
22.5 [19.9 – 25.1] |
22.1 [19.9 – 24.3] |
21.8 [19.6 – 24.5] |
＜0.001 |
| SBP, mmHg |
19 (0.6) |
115 [103 – 127] |
117 [102 – 134] |
110 [99 – 124] |
114 [101 – 126] |
115 [104 – 128] |
116 [106 – 128] |
＜0.001 |
| DBP, mmHg |
20 (0.7) |
66 [58 – 75] |
64 [56 – 74] |
65 [58 – 74] |
66 [58 – 75] |
67 [59 – 76] |
66 [58 – 74] |
0.001 |
| Heart rate, bpm |
178 (6.0) |
74 [65 – 85] |
76 [65 – 89] |
79 [67 – 91] |
73 [66 – 85] |
72 [63 – 82] |
72 [62 – 83] |
＜0.001 |
| LVEF, % |
157 (5.3) |
57.0 [43.7 – 65.8] |
52.0 [39.2 – 65.1] |
52.0 [35.0 – 63.7] |
57.4 [42.9 – 65.6] |
59.0 [49.0 – 66.9] |
57.3 [46.0 – 66.0] |
＜0.001 |
| Diagnostic category |
|
|
|
|
|
|
|
|
| HF |
0 (0.0) |
1296 (43.5) |
186 (52.3) |
218 (54.4) |
375 (39.5) |
339 (38.1) |
178 (46.2) |
＜0.001 |
| ACS |
0 (0.0) |
624 (20.9) |
57 (16.0) |
66 (16.5) |
221 (23.3) |
213 (23.9) |
67 (17.4) |
＜0.001 |
| Post-cardiac surgery |
0 (0.0) |
967 (32.4) |
102 (28.7) |
131 (32.7) |
311 (32.7) |
279 (31.4) |
144 (37.4) |
0.126 |
| Aortic disease |
0 (0.0) |
294 (9.9) |
35 (9.8) |
31 (7.7) |
106 (11.2) |
93 (10.5) |
29 (7.5) |
0.162 |
| Comorbid conditions |
|
|
|
|
|
|
|
|
| Hypertension |
0 (0.0) |
2046 (68.6) |
279 (78.4) |
267 (66.8) |
614 (64.6) |
618 (69.4) |
267 (69.4) |
＜0.001 |
| Dyslipidemia |
0 (0.0) |
1349 (45.2) |
191 (53.7) |
189 (47.1) |
433 (45.6) |
395 (44.4) |
141 (36.6) |
＜0.001 |
| Diabetes |
0 (0.0) |
1118 (37.5) |
188 (52.8) |
139 (34.7) |
330 (34.7) |
328 (36.9) |
133 (34.6) |
＜0.001 |
| Intermittent claudication |
0 (0.0) |
120 (4.0) |
85 (23.4) |
16 (4.0) |
10 (1.1) |
7 (0.8) |
2 (0.5) |
＜0.001 |
| Smoking |
30 (1.0) |
576 (19.5) |
72 (20.3) |
79 (20.0) |
201 (21.4) |
159 (18.0) |
65 (17.2) |
0.287 |
| Prior MI |
0 (0.0) |
436 (14.6) |
70 (19.7) |
63 (15.7) |
137 (14.4) |
116 (13.0) |
50 (13.0) |
0.036 |
| Prior HF |
0 (0.0) |
809 (27.1) |
118 (33.2) |
138 (34.4) |
251 (26.4) |
201 (22.6) |
101 (26.2) |
＜0.001 |
| Medications |
|
|
|
|
|
|
|
|
| ACE inhibitor or ARB |
0 (0.0) |
2045 (68.6) |
255 (71.6) |
275 (68.6) |
670 (70.5) |
588 (66.1) |
257 (66.8) |
0.171 |
| Beta-blocker |
0 (0.0) |
2069 (69.4) |
261 (73.3) |
302 (75.3) |
663 (69.8) |
600 (32.6) |
243 (63.1) |
0.001 |
| Diuretic agents |
0 (0.0) |
1711 (57.4) |
226 (63.5) |
257 (64.1) |
553 (58.2) |
468 (52.6) |
207 (53.8) |
＜0.001 |
| Statin |
0 (0.0) |
1600 (53.7) |
231 (64.9) |
213 (53.1) |
514 (54.1) |
459 (51.6) |
183 (47.5) |
＜0.001 |
| Laboratory data |
|
|
|
|
|
|
|
|
| Albumin, g/dL |
50 (1.7) |
3.6 [3.2 – 3.9] |
3.4 [3.1 – 3.7] |
3.6 [3.1 – 3.9] |
3.6 [3.3 – 4.0] |
3.6 [3.2 – 4.0] |
3.6 [3.2 – 3.9] |
＜0.001 |
| Hemoglobin, g/dL |
14 (0.5) |
11.7 [10.3 – 13.4] |
11.3 [10.0 – 12.8] |
11.8 [10.5 – 13.5] |
11.7 [10.4 – 13.4] |
11.9 [10.4 – 13.6] |
11.3 [9.9 – 12.8] |
＜0.001 |
| CRP, mg/dL |
19 (0.6) |
0.66 [0.20 – 1.94] |
0.67 [0.21 – 2.02] |
0.64 [0.20 – 1.92] |
0.62 [0.21 – 1.88] |
0.70 [0.21 – 2.13] |
0.63 [0.17 – 1.70] |
0.540 |
| TG, mg/dL |
1411 (47.3) |
102 [74 – 145] |
112 [81 – 159] |
102 [76 – 138] |
101 [75 – 144] |
102 [73 – 149] |
96 [71 – 133] |
0.070 |
| TC, mg/dL |
1382 (46.3) |
168 [139 – 201] |
161 [130 – 191] |
162 [140 – 196] |
173 [142 – 206] |
172 [141 – 204] |
163 [135 – 193] |
0.001 |
| LDL-C, mg/dL |
1376 (46.1) |
83 [60 – 113] |
76 [54 – 103] |
83 [60 – 105] |
87 [61 – 117] |
84 [60 – 119] |
85 [61 – 110] |
0.014 |
| HDL-C, mg/dL |
1156 (38.8) |
48 [39 – 59] |
43 [34 – 56] |
46 [39 – 56] |
47 [39 – 60] |
50 [41 – 60] |
50 [38 – 61] |
＜0.001 |
| BNP, pg/mL |
1178 (39.5) |
233.1 [86.1 – 575.7] |
354.8 [153.2 – 765.3] |
315.1 [120.9 – 761.7] |
231.0 [87.0 – 539.3] |
175.9 [66.7 – 497.8] |
186.6 [67.4 – 523.4] |
＜0.001 |
| eGFR, mL/min/1.73 m2
|
15 (0.5) |
55.0 [39.6 – 68.0] |
46.0 [28.0 - 61.0] |
56.0 [37.0 – 70.0] |
56.0 [42.0 – 69.6] |
56.0 [43.0 – 68.2] |
55.0 [37.0 - 68.0] |
＜0.001 |
| Physical activity |
580 (19.5) |
|
|
|
|
|
|
0.002 |
| Minimal |
|
1354 (56.4) |
186 (66.0) |
211 (63.4) |
440 (55.8) |
361 (51.8) |
156 (51.7) |
|
| Low |
|
281 (11.7) |
30 (10.6) |
33 (9.9) |
96 (12.2) |
81 (11.6) |
41 (13.6) |
|
| Adequate |
|
708 (29.5) |
61 (21.6) |
85 (25.5) |
234 (29.7) |
233 (33.4) |
95 (31.5) |
|
| High |
|
59 (2.5) |
5 (1.8) |
4 (1.2) |
18 (2.3) |
22 (3.2) |
10 (3.3) |
|
Note: Values are n (%), mean±standard deviation, or median [interquartile range].
ABI, ankle–brachial index; ACE, angiotensin-converting enzyme; ACS, acute coronary syndrome; ARB, angiotensin II receptor blocker; BMI, body mass index; BNP, B-type natriuretic peptide; CRP, C-reactive protein; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; HF, heart failure; LDL-C, low-density lipoprotein cholesterol; LVEF, left ventricular ejection fraction; MI, myocardial infarction; SBP, systolic blood pressure; TC, total cholesterol; TG, triglyceride.
Table 2 shows the physical function of all included patients according to the ABI levels. The median [IQR] 6MWD, gait speed, SPPB, and QIS of the study population were 389 [292–472] m, 1.09 [0.88–1.26] m/s, 12 [10–12] points, and 41.2 [31.3–51.7] %BM, respectively. Lower ABI levels were associated with short 6MWD, slow gait speed, low SPPB, and low QIS (all p trend ＜0.001).
Table 2.Association of ABI with poor physical function
| Physical function |
Overall
n = 2982
|
ABI |
|
≤ 0.90
n = 356 (11.9%)
|
0.91 – 1.00
n = 401 (13.5%)
|
1.01 – 1.10
n = 950 (31.9%)
|
1.11 – 1.20
n = 890 (29.9%)
|
1.21 – 1.40
n = 385 (12.9%)
|
p trend
|
| 6MWD, m |
389 [292 – 472] |
306 [191 – 388] |
366 [260 – 453] |
400 [300 – 483] |
407 [323 – 480] |
410 [342 – 410] |
＜0.001 |
| ＜300 m |
777 (26.1) |
170 (47.8) |
126 (31.4) |
236 (24.8) |
180 (20.2) |
65 (16.9) |
＜0.001 |
| ＜400 m |
1574 (52.8) |
276 (77.5) |
243 (60.6) |
470 (49.5) |
411 (46.2) |
174 (45.2) |
＜0.001 |
| Gait speed, m/s |
1.09 [0.88 – 1.26] |
0.94 [0.73 - 1.13] |
1.07 [0.84 – 1.22] |
1.10 [0.88 – 1.28] |
1.12 [0.92 – 1.27] |
1.12 [0.95 – 1.28] |
＜0.001 |
| ＜0.8 m/s |
558 (18.7) |
113 (31.7) |
87 (21.7) |
179 (18.8) |
130 (14.6) |
49 (12.7) |
＜0.001 |
| ＜1.0 m/s |
1150 (38.6) |
210 (59.0) |
175 (43.6) |
352 (37.1) |
298 (33.5) |
115 (29.9) |
＜0.001 |
| SPPB, points |
12 [10 – 12] |
11 [9 – 12] |
12 [10 – 12] |
12 [11 – 12] |
12 [11 – 12] |
12 [12 – 12] |
＜0.001 |
| ＜9 points |
392 (13.2) |
89 (25.0) |
62 (15.5) |
126 (13.3) |
85 (9.6) |
30 (7.8) |
＜0.001 |
| QIS, %BM |
41.2 [31.3 – 51.7] |
34.6 [27.2 – 45.2] |
38.1 [30.6 – 49.1] |
41.6 [31.8 – 52.6] |
42.9 [32.6 – 54.8] |
43.0 [33.9 – 51.6] |
＜0.001 |
| Male ＜45 %BM, Female ＜35 %BM |
1510 (50.6) |
246 (69.1) |
227 (56.6) |
436 (45.9) |
409 (46.0) |
192 (49.9) |
＜0.001 |
Note: Values are n (%), mean±standard deviation, or median [interquartile range].
6MWD, 6-minute walking distance; ABI, ankle-brachial index; BM, body mass; QIS, quadriceps isometric strength; SPPB, short physical performance battery.
Table 3 and Fig.2 show the associations between the ABI levels and poor physical functions. For the ABI ≤ 1.1 category, the risk of poor physical function increased with decreasing ABI, even after adjusting for confounding factors. For the ABI 1.20–1.40 category, only small and nonsignificant differences in ORs were found.
Table 3.Univariate and Multivariate logistic regression analysis of the association between poor physical function and ABI
| Poor physical function |
ABI |
Unadjusted OR (95% CI) |
p-value
|
Adjusted OR＊ (95% CI)
|
p-value
|
| 6MWD ＜300 m |
≤ 0.90 |
3.605 (2.767 – 4.697) |
＜0.001 |
3.184 (2.257 – 4.494) |
＜0.001 |
|
0.91 – 1.00 |
1.807 (1.384 – 2.360) |
＜0.001 |
1.836 (1.323 – 2.548) |
＜0.001 |
|
1.01 – 1.10 |
1.304 (1.046 – 1.625) |
0.018 |
1.398 (1.077 – 1.816) |
0.012 |
|
1.11 – 1.20 |
1.000 (reference) |
- |
1.000 (reference) |
- |
|
1.21 – 1.40 |
0.801 (0.586 – 1.095) |
0.165 |
0.849 (0.593 – 1.215) |
0.372 |
| 6MWD ＜400 m |
≤ 0.90 |
4.021 (3.034 – 5.329) |
＜0.001 |
3.844 (2.679 – 5.515) |
＜0.001 |
|
0.91 – 1.00 |
1.792 (1.410 – 2.278) |
＜0.001 |
2.206 (1.626 – 2.993) |
＜0.001 |
|
1.01 – 1.10 |
1.141 (0.950 – 1.371) |
0.158 |
1.254 (1.002 – 1.570) |
0.048 |
|
1.11 – 1.20 |
1.000 (reference) |
- |
1.000 (reference) |
- |
|
1.21 – 1.40 |
0.961 (0.756 – 1.222) |
0.746 |
0.987 (0.743 – 1.310) |
0.926 |
| Gait speed ＜0.8 m/s |
≤ 0.90 |
2.719 (2.033 – 3.635) |
＜0.001 |
2.109 (1.469 – 3.026) |
＜0.001 |
|
0.91 – 1.00 |
1.620 (1.198 – 2.190) |
0.002 |
1.492 (1.050 – 2.121) |
0.026 |
|
1.01 – 1.10 |
1.357 (1.060 – 1.738) |
0.015 |
1.397 (1.055 – 1.850) |
0.020 |
|
1.11 – 1.20 |
1.000 (reference) |
- |
1.000 (reference) |
- |
|
1.21 – 1.40 |
0.853 (0.599 – 1.213) |
0.375 |
0.924 (0.625 – 1.365) |
0.690 |
| Gait speed ＜1.0 m/s |
≤ 0.90 |
2.857 (2.219 – 3.680) |
＜0.001 |
2.213 (1.617 – 3.030) |
＜0.001 |
|
0.91 – 1.00 |
1.538 (1.208 – 1.958) |
＜0.001 |
1.511 (1.134 – 2.014) |
0.005 |
|
1.01 – 1.10 |
1.169 (0.965 – 1.416) |
0.110 |
1.221 (0.978 – 1.525) |
0.078 |
|
1.11 – 1.20 |
1.000 (reference) |
- |
1.000 (reference) |
- |
|
1.21 – 1.40 |
0.846 (0.653 – 1.096) |
0.206 |
0.869 (0.649 – 1.163) |
0.344 |
| SPPB ＜9 points |
≤ 0.90 |
3.157 (2.274 – 4.382) |
＜0.001 |
2.468 (1.676 – 3.635) |
＜0.001 |
|
0.91 – 1.00 |
1.732 (1.219 – 2.461) |
0.002 |
1.612 (1.092 – 2.379) |
0.016 |
|
1.01 – 1.10 |
1.448 (1.082 – 1.939) |
0.013 |
1.497 (1.090 – 2.057) |
0.013 |
|
1.11 – 1.20 |
1.000 (reference) |
- |
1.000 (reference) |
- |
|
1.21 – 1.40 |
0.800 (0.518 – 1.236) |
0.315 |
0.830 (0.523 – 1.319) |
0.432 |
| QIS ＜45 %BM (Male) |
≤ 0.90 |
2.562 (1.984 – 3.310) |
＜0.001 |
1.962 (1.453 – 2.649) |
＜0.001 |
| ＜35 %BM (Female) |
0.91 – 1.00 |
1.560 (1.231 – 1.977) |
＜0.001 |
1.646 (1.266 – 2.140) |
＜0.001 |
|
1.01 – 1.10 |
1.077 (0.896 – 1.295) |
0.431 |
1.034 (0.848 – 1.262) |
0.739 |
|
1.11 – 1.20 |
1.000 (reference) |
- |
1.000 (reference) |
- |
|
1.21 – 1.40 |
0.920 (0.722 – 1.173) |
0.501 |
1.170 (0.906 – 1.512) |
0.229 |
Note: ＊After adjusting for age, sex, BMI, SBP, hypertension, dyslipidemia, diabetes, smoking, prior MI, prior HF, ACE inhibitor or ARB, beta- blocker, diuretic agents, statin, TC, LDL-C, HDL-C, physical activity, and intermittent claudication.
6MWD, 6-minute walking distance; ABI, ankle-brachial index; ACE, angiotensin-converting enzyme; ARB, angiotensin II receptor blocker; BM, body mass; BMI, body mass index; CI, confidence interval; HDL-C, high-density lipoprotein cholesterol; HF, heart failure; LDL-C, low-density lipoprotein cholesterol; MI, myocardial infarction; OR, odds rato; QIS, quadriceps isometric strength; SBP, systolic blood pressure; SPPB, short physical performance battery; TC, total cholesterol.
Fig.3 shows nonlinear associations between ABI and physical function using restricted cubic splines. All physical functions increased with increasing ABI. However, the increase in physical function plateaued when the ABI level reached approximately 1.1.
Discussion
In our study, a lower ABI level was associated with lower 6MWD, gait speed, QIS, and SPPB. Furthermore, compared with patients with an ABI level of 1.11–1.20, those with an ABI level of ≤ 1.10 were more likely to have poor physical function. The association between low ABI and low physical function remained significant after accounting for confounding factors. These results suggest that physical function may be impaired when the ABI level is higher than the cutoff, which is associated with a greater risk of PAD and mortality (i.e., ABI ＜1.0). This suggests that it is important to promote lifestyle modification, including exercise habits, to prevent atherosclerosis and to prevent the decline in physical function, even in patients with an ABI of 1.00–1.10, which have not been previously recognized as abnormal values.
Several studies have examined the association between ABI and physical functions11, 31). Matsushita et al.31) investigated the association between ABI and SPPB and handgrip strength in community-dwelling older adults. The result showed that those with borderline ABI (ABI=0.91–1.00) and low ABI (ABI ≤ 0.90) had poorer physical functions compared with those with an ABI of 1.11–1.20, while those with an ABI of 1.01–1.10 showed no significant difference. In addition, Tanaka et al.11) investigated the association between ABI and the measures of physical function (e.g., 6MWD, gait speed, handgrip strength, QIS, and standing balance) in patients with acute HF. In their study, patients were classified into three groups (low ABI, borderline ABI, and normal ABI), and their association with each physical function measure was examined. The result showed that the group with the low ABI (ABI ≤ 0.9) had a lower 6MWD compared with that of the group with a normal ABI (ABI 1.00–1.40), while there was no significant difference between the groups with the low (ABI ≤ 0.90) and borderline ABI (ABI 0.91–0.99). To our knowledge, the present study is the first to examine the associations of more detailed ABI levels (i.e., ABI ≤ 0.90, ABI 0.91–1.00, ABI 1.01–1.10, ABI 1.11–1.20, and ABI 1.20–1.40) with poor physical function in patients with CVD. The results of this study indicated that patients with CVD may develop poor physical function at a higher ABI level than the traditionally used cutoff values for PAD and a higher risk of cardiovascular events13-15).
Several mechanisms underlie the observed association between low ABI and poor physical function. Important factors may include skeletal muscle atrophy and skeletal muscle fiber type shift associated with reduced skeletal muscle blood flow32, 33). In particular, patients with PAD show skeletal muscle atrophy in the lower extremities due to continuous ischemia, which may affect physical functions specific to the lower extremities34, 35). It is also suggested that excessive vasoconstriction is associated with increased sympathetic nerve activity and activation of the renin–angiotensin system due to decreased cardiac function36), and decreased vasodilatory capacity due to decreased production of nitric oxide37) may induce decreased muscle blood flow38) and poor physical function. Furthermore, common risk factors for poor physical function and atherosclerosis not investigated in detail in this study, which includes aging3), malnutrition6, 7), insulin resistance5), physical inactivity8, 9), and chronic inflammation39), may explain the association between ABI and poor physical function.
ABI assessment is noninvasive, simple to measure, and has been reported to be useful not only in the assessment of PAD but also in the risk stratification for mortality and coronary events13-15). In addition, ABI assessment is useful to detect asymptomatic PAD. Typically, two-thirds of all patients with PAD are asymptomatic40). In patients with HF, about two-thirds of those with an ABI of ≤ 0.9 reported no intermittent claudication11). In the present study, only 23.4% of the subjects with an ABI of ≤ 0.9 had intermittent claudication, and only 4.0% and 1.1% of subjects with an ABI of 0.91–1.00 and 1.01–1.10, respectively, showed poor physical function (Table 1). Assessing ABI without symptoms such as intermittent claudication may identify patients at risk of poor physical function at an earlier time. These results suggest that ABI assessment can help in the risk stratification of patients with CVD and the implementation of interventions at an earlier stage.
Limitation
This study had several limitations. First, this was a single-center retrospective observational study. In addition, since only Asian populations were included, it is unclear whether the results can be generalized to patients of other ethnicities. Second, the patients included in this study participated in the cardiac rehabilitation program and completed physical function measures. Therefore, patients with more severe conditions and poor physical function were not included. Third, data on potential confounders such as physical function prior to hospitalization, nutritional status, inflammatory status, and socioeconomic status were not available for this study. Finally, although the clinical guidelines for PAD recommend Doppler measurement for measuring ABI17), ABI in this study was measured using an oscillometric method, which is inaccurate compared with the Doppler measurement in the evaluation of severe PAD17).
Conclusion
An ABI level of ≤ 1.1 is potentially associated with poor physical function in patients with CVD. These results suggest that maintaining ABI levels higher than previously proposed cutoffs for PAD and cardiovascular events may preserve physical function in patients with CVD. In addition, ABI may have additional value in screening for poor physical function in patients with CVD.
Funding
This study was partially supported by Japan Society the Promotion of Science (JSPS) KAKENHI (grant number: 21H03309) and JST RISTEX Japan (grant number: JPMJRX20IC).
Disclosures
Dr. Kamiya received funding outside of the submitted work from Eiken Chemical CO. Ltd. And SoftBnak Corporation. Although Dr. Yamashita has no conflict of interest related to this work, he holds company stock (less than 5% of the total) and receives a salary as one of the directors of an employer.
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