Background
Patients at end stage renal disease (ESRD) are known to be particularly frail [
1]. Compared to the general population, they show a reduced physical performance [
2,
3], a higher fall rate [
4‐
8], and higher cognitive impairment [
9].
Often the lower health status of ESRD has been explained with factors related to the renal replacement therapy (RRT) – mostly haemodialysis (HD) – in particular, a reduced physical activity level [
10‐
12], and cerebrovascular disorders [
13,
14]. Although this explanation sounds reasonable, recently the transitional phase from a severe kidney failure to chronic haemodialysis was analysed in order to better understand the impact RRT has on the frailty process of CKD patients [
15‐
17]. These reports share the observation that a frail population in the pre-dialysis phase or in the first months of HD seems to exhibit no further deterioration once the patients started their RRT.
Currently there is not much detailed knowledge about the highly prevalent gait impairments seen in CKD and ESRD patients, and how these impairments affect gait quality [
18]. When gait assessment is applied to CKD patient populations it is rather limited to the dialytic population, and pre-dialytic groups are rather neglected in this regard, notwithstanding the suggestions that gait abnormalities that lead to heightened risk of falls already exist in early stages of CKD [
4‐
8]. CKD patients show a significantly slower gait speed that is associated with physical [
19‐
22], cognitive [
23], sensory [
24] and metabolic [
25,
26] capacities, factors that are all influenced by CKD severity. However, cognitive factors may also impact gait in people with CKD [
26,
27], and may be mediated by small vessel disease often seen in these patients [
18]. A recent study found an association between gait abnormality and CKD severity [
28], which suggests that gait is already affected in early stages of CKD and not only at stage 5. It is necessary to clarify whether changes in spatio-temporal gait variables become apparent, and whether these in turn relate to changes in cognition and fall events.
A cross-sectional study design will allow assessment of the relationship between CKD exposure and gait outcomes, and consequently help determine whether a longitudinal study would be warranted [
29]. The aim of this study, therefore, is to analyse gait parameters in patients categorised into different CKD stages and specifically the presence of a worsening in these parameters as CKD progress. Because of the degenerative nature of CKD that includes the loss of muscle mass and the development of cognitive disorders with already mild reduction of the renal function, we hypothesise to find a linear decrease of gait quality in dependence of the CKD severity.
Results
51 patients were asked by the nephrologist to participate. 1 person (CKD 5 not on HD) died before the principal investigator could fix the date for the visit. 5 patients change their mind once contacted by the principal investigator and denied to participate (1 was CKD 3, 2 were CKD 4 and 2 were CKD 5 not on dialysis). No participant was excluded by the principal investigator during the visit. 45 patients accepted to participate in the study which led to an almost equal distribution of the participants in 5 CKD severity groups: stage 1–2 (
n = 8); stage 3 (
n = 9); stage 4 (
n = 9); stage 5 not on dialysis (
n = 10); 5 on HD (
n = 9). The combined CKD group 1 & 2 was on average younger than the other three groups (60 vs. 74 years). Table
1 describes the clinical aspects of the participants, and shows a general tendency to worse clinical status, in particular a reduction of physical performance, with decreasing eGFR. Table
2 reports descriptive values for single gait characteristics by CKD status. Table
3 reports the correlation and regression analyses on the single characteristics. A decrease in gait speed, stride length and step length, among the spatio-temporal parameters, was statistically associated with a worsening kidney function, both at a univariable and at a multivariable analysis. Among parameters evaluating variability only CV of step length was correlated in univariable and age and sex corrected models. CV of stride time was significantly correlated only in non-parametric analysis and gait regularity was correlated only at univariable analyses.
Table 1
Main demographic, clinical and functional data: mean ± SD [range]
General characteristics |
Gender (M / W) | 6 / 2 | 6 / 3 | 8 / 1 | 4 / 6 | 4 / 5 | |
Age (years) | 60.4 ± 13.7 [40–83] | 74.7 ± 9.1 [63–92] | 77.1 ± 10.5 [53–85] | 72.1 ± 4.4 [65–79] | 75.9 ± 7.2 [62–86] | |
BMI (kg/m2) | 25.3 ± 2.4 [22–28.7] | 27.4 ± 4.0 [22.2–33.7] | 28.4 ± 3.7 [23.5–36.4] | 28.9 ± 5.5 [16.7–34.3] | 29.2 ± 3.3 [22.6–35.1] | 18.5 – 24.9 |
Schooling (years) | 11.5 ± 3.0 [8–16] | 9.6 ± 2.6 [5–14] | 10.1 ± 4.0 [5–17] | 6.9 ± 2.8 [3–13] | 8.7 ± 3.3 [5–17] | |
CKD specific parameters |
eGFR (ml/min/1.73 m2) | 68.8 ± 16.2 [56–108] | 35.1 ± 5.9 [26–44] | 22.1 ± 4.9 [16–29] | 10.3 ± 1.7 [7–13] | 9.4 ± 4.0 [4–17] | |
Time on HD (weeks) | - | - | - | - | 81 ± 43 [13–131] | |
Health status |
Physical health | 52.1 ± 7.7 [36.5–60.9] | 45.5 ± 10.1 [25.0–55.3] | 49.7 ± 8.6 [34.2–62.4] | 40.3 ± 7.8 [25.0–52.5] | 37.6 ± 10.2 [19.9–50.6] | > 40 |
Mental health | 53.8 ± 7.0 [40.0–60.7] | 52.7 ± 7.9 [38.1–62.0] | 49.5 ± 12.9 [23.3–60.6] | 54.4 ± 7.9 [37.9–65.1] | 48.7 ± 8.0 [39.3–59.7] | > 40 |
Autonomy | 100 ± 0.0 [100–100] | 99.4 ± 1.7 [95–100] | 100 ± 0.0 [100–100] | 98.5 ± 3.4 [90–100] | 91.7 ± 8.3 [80–100] | ≥ 75 |
Independence | 21.0 ± 1.5 [18–22] | 20.4 ± 1.4 [17–22] | 18.4 ± 1.6 [16–21] | 17.1 ± 3.2 [10–22] | 12.8 ± 3.9 [7–19] | ≥ 17 |
General fatigue | 6.0 ± 1.9 [4–9] | 10.4 ± 4.2 [4–16] | 9.6 ± 3.8 [5–17] | 11.5 ± 3.1 [7–15] | 11.1 ± 4.4 [4–17] | < 10 |
Pain | 17.5 ± 27.1 [0–80] | 17.8 ± 18.4 [0–50] | 13.9 ± 18.2 [0–50] | 51.0 ± 33.8 [0–100] | 29.4 ± 24.8 [0–60] | < 40 |
GDS-10 | 0.9 ± 0.6 [0–2] | 1.1 ± 1.2 [0–4] | 2.6 ± 2.9 [0–7] | 2.6 ± 3.4 [0–10] | 3.7 ± 1.7 [1–6] | ≤ 5 |
Comorbidity severity Index | 2.0 ± 0.1 [1.8–2.0] | 2.5 ± 0.3 [2.3–3.0] | 2.2 ± 0.3 [1.7–2.5] | 2.0 ± 0.2 [1.6–2.2] | 2.0 ± 0.3 [1.5–2.5] | ≤ 2 |
Comorbidity index | 0.0 ± 0.0 [0–0] | 1.3 ± 0.5 [1, 2] | 1.7 ± 1.1 [1–4] | 1.6 ± 1.1 [1–4] | 1.6 ± 0.5 [1, 2] | ≤ 2 |
Physical Performance |
SPPB | 11.1 ± 1.1 [9–12] | 11.6 ± 0.7 [10–12] | 10.3 ± 1.3 [8–12] | 9.4 ± 2.5 [4–12] | 6.3 ± 2.4 [3–10] | > 6 |
ETGUG (seconds) | 18.7 ± 1.8 [16.3–21.4] | 20.7 ± 3.7 [14.8–26.7] | 22.6 ± 3.3 [16.9–26.3] | 27.5 ± 9.6 [16.4–43.8] | 36.7 ± 13.5 [20.5–55.6] | < 34 |
POMA | 27.0 ± 0.9 [26–28] | 26.0 ± 2.3 [21–28] | 25.6 ± 1.9 [23–28] | 24.7 ± 2.8 [21–28] | 21.7 ± 4.4 [16–28] | > 19 |
Steps/daya | 10,876 ± 3,419 [5,843–16,881]1 | 9,979 ± 5,432 [3,664–22,027] | 6,251 ± 2,779 [3,576–11,463]1 | 7,144 ± 3,639 [2,839–15,862] | 3,406 ± 3,257 [402–11,145] | > 5,000 |
Handgrip (kg)b -Male -Female | 47.7 ± 9.0 [38–58] 36.0 ± 4.2 [33–39] | 41.7 ± 13.1 [21–58] 28.0 ± 0.0 [28–28] | 29.0 ± 7.6 [20–44] 24.0 ± 0.0 [24–24] | 28.3 ± 9.6 [19–40] 10.4 ± 3.3 [8–16] | 21.3 ± 4.3 [15–25] 12.4 ± 3.9 [8–18] | ≥ 27 ≥ 16 |
Hip flexion (kg)c -Male -Female | 23.0 ± 6.9 [14.0–31.3] 16.1 ± 0.9 [15.4–16.7] | 23.2 ± 7.6 [18.8–36.7] 11.9 ± 1.5 [10.1–12.9] | 19.6 ± 3.1 [14.6–23.2] 12.0 ± 0.0 [12.0–12.0] | 18.9 ± 13.5 [9.3–42.4] 14.3 ± 2.1 [11.4–17.4] | 12 ± 3.6 [8.2–15.3] 11.4 ± 3.4 [7–15.3] | > 11 > 10 |
Cognitive Status |
MMSE | 28.9 ± 1.1 [27–30] | 28.3 ± 0.7 [27–29] | 26.7 ± 2.3 [23–29] | 26.2 ± 4.1 [16–29] | 25.9 ± 1.6 [24–28] | > 24 |
FABd | 3.3 ± 0.7 [2–4] | 2.9 ± 1.1 [1–4] | 0.7 ± 1.1 [0–3] | 1.9 ± 1.5 [0–4] | 1.3 ± 1.5 [0–4] | ≥ 1 |
TMT_Ad | 3.8 ± 0.7 [2–4] | 3.3 ± 1.1 [1–4] | 2.2 ± 1.8 [0–4] | 2.2 ± 1.9 [0–4] | 2.7 ± 1.6 [0–4]1 | ≥ 1 |
TMT_Bd | 3.6 ± 0.7 [2–4] | 2.7 ± 1.7 [0–4] | 2.8 ± 1.9 [0–4] | 2.3 ± 2.1 [0–4]1 | 1.7 ± 2.0 [0–4]1 | ≥ 1 |
Haematology parameters |
Calcium (mmol/L) | 2.4 ± 0.1 [2.3–2.5]2 | 2.3 ± 0.1 [2.2–2.4]1 | 2.3 ± 0.2 [2.0–2.5]1 | 2.3 ± 0.2 [2.0–2.5] | 2.2 ± 0.1 [2.0–2.4] | 2.15 – 2.55 |
Phosphates (mmol/L) | 1.0 ± 0.2 [0.8–1.2]2 | 1.1 ± 0.1 [0.9–1.3]1 | 1.2 ± 0.2 [0.9–1.4]1 | 1.6 ± 0.2 [1.3–1.8] | 1.7 ± 0.5 [1.0–2.9] | 0.81 – 1.45 |
Haemoglobin (g/L) | 142.3 ± 9.5 [124–154]1 | 133.8 ± 13.6 [115–156] | 130.0 ± 20.1 [99–171]1 | 101.5 ± 10.5 [84–119] | 103.8 ± 11.2 [87–122] | 140 – 180 |
Haematocrit (L/L) | 0.44 ± 0.03 [0.38–0.48]1 | 0.41 ± 0.05 [0.36–0.50] | 0.40 ± 0.07 [0.29–0.53]1 | 0.31 ± 0.04 [0.26–0.38] | 0.31 ± 0.04 [0.26–0.39] | 0.45 – 0.55 |
Table 2
Gait characteristics: mean ± SD [range]
Spatio-temporal parameters |
Gait speed (m/s) | 1.31 ± 0.14 [1.09–1.55] | 1.22 ± 0.20 [0.86–1.53] | 1.12 ± 0.15 [0.93–1.36] | 1.03 ± 0.36 [0.56–1.54] | 0.86 ± 0.25 [0.53–1.23] |
Cadence (steps/min) | 107.4 ± 9.0 [95–120] | 113.7 ± 10.5 [103–136] | 110.0 ± 6.0 [98–118] | 110.8 ± 14.6 [84–130] | 101.6 ± 13.7 [79–126] |
Stride time (s) | 1.14 ± 0.09 [1.03–1.27] | 1.08 ± 0.08 [0.95–1.18] | 1.10 ± 0.06 [1.02–1.22] | 1.12 ± 0.16 [0.95–1.46] | 1.21 ± 0.17 [0.96–1.55] |
Stride length (m) | 1.37 ± 0.26 [1.11–1.78] | 1.18 ± 0.16 [0.96–1.42] | 1.18 ± 0.25 [0.67–1.56] | 1.08 ± 0.32 [0.74–1.59] | 1.05 ± 0.22 [0.81–1.44] |
Step time (s) | 0.57 ± 0.04 [0.52–0.63] | 0.54 ± 0.04 [0.48–0.59] | 0.55 ± 0.03 [0.51–0.61] | 0.56 ± 0.08 [0.47–0.73] | 0.61 ± 0.08 [0.48–0.77] |
Step length (m) | 0.69 ± 0.13 [0.56–0.89] | 0.59 ± 0.08 [0.48–0.71] | 0.59 ± 0.13 [0.33–0.78] | 0.54 ± 0.16 [0.37–0.79] | 0.52 ± 0.11 [0.4–0.72] |
Variability |
CV Stride time | 3.0 ± 1.5 [1.2–5.5] | 4.1 ± 3.4 [1.3–10.7] | 2.8 ± 1.6 [0.7–6.1] | 4.9 ± 2.8 [1.4–10.7] | 4.4 ± 1.5 [1.8–6.9] |
CV Stride length | 3.4 ± 1.0 [1.4–5.2] | 5.4 ± 3.4 [2.6–13.1] | 4.9 ± 2.8 [2.3–10.4] | 7.5 ± 4.1 [3.0–15.4] | 4.5 ± 2.0 [1.6–8.2] |
CV Step time | 9.0 ± 7.4 [2.3–18.7] | 7.6 ± 4.8 [2.1–16.9] | 7.4 ± 3.7 [2.2–12.7] | 10.2 ± 4.3 [3.3–16.8] | 7.9 ± 2.8 [2.6–12.0] |
CV Step length | 6.5 ± 3.1 [4.0–13.1] | 7.3 ± 4.0 [4.5–16.2] | 8.3 ± 3.4 [4.8–15.7] | 11.1 ± 5.3 [3.9–19.9] | 11.3 ± 8.0 [2.7–30.4] |
Gait regularity | 0.96 ± 0.03 [0.91–0.99] | 0.95 ± 0.04 [0.87–1.00] | 0.90 ± 0.16 [0.47–0.98] | 0.92 ± 0.07 [0.78–0.99] | 0.83 ± 0.13 [0.53–0.95] |
Dual-task cost of gait |
Gait speed (%) | 11.8 ± 14.2 [2–45] | 11.6 ± 10.3 [-4–28] | 14.6 ± 9.2 [2–29] | 15.8 ± 10.2 [-1–35] | 19.3 ± 10.7 [8–37] |
Cadence (%) | 7.9 ± 11.6 [-1–35] | 6.8 ± 7.4 [-1–21] | 6.4 ± 5.7 [-2–16] | 7.8 ± 4.8 [-1–14] | 10.0 ± 8.4 [-1–25] |
Stride time (%) | 11.8 ± 22.6 [-1–67] | 7.4 ± 7.9 [-2–21] | 8.0 ± 6.8 [-2–19] | 8.9 ± 5.6 [-1–17] | 12.3 ± 11.3 [0–34] |
Stride length (%) | -1.8 ± 4.5 [-7–6] | 2.4 ± 6.6 [-5–15] | 3.1 ± 8.8 [-11–17] | -1.2 ± 9.9 [-14–18] | 4.7 ± 8.2 [-6–23] |
Table 3
Correlation coefficient, p value and confidence interval between gait parameters and CKD severity (n = 45)
Spatio-temporal parameters |
Gait speed (m/s) | -0.55 (p < 0.01) [-0.73;-0.30] | -0.53 (p < 0.01) [-0.72;-0.28] | -0.07 (p < 0.01) [-0.12;-0.02] |
Cadence (steps/min) | -0.18 (p = 0.23) [-0.45;0.12] | -0.14 (p = 0.34) [-0.44;0.16] | -0.51 (p = 0.70) [-3.2;2.2] |
Stride time (s) | 0.22 (p = 0.15) [-0.08;0.48] | 0.15 (p = 0.33) [-0.20;0.43] | 0.01 (p = 0.52) [-0.02;0.04] |
Stride length (m) | -0.40 (p < 0.01) [-0.62;-0.12] | -0.39 (p < 0.01) [-0.62;-0.13] | -0.06 (p = 0.05) [-0.11;-0.001] |
Step time (s) | 0.21 (p = 0.16) [-0.09;0.47] | 0.14 (0.37) [-0.17;0.44] | 0.004 (p = 0.55) [-0.01;0.02] |
Step length (m) | -0.41 (p < 0.01) [-0.63;-0.13] | -0.39 (p < 0.01) [-0.62;-0.10] | -0.03 (p = 0.04) [-0.06;-0.001] |
Variability |
CV Stride time | 0.22 (p = 0.18) [-0.08;0.48] | 0.29 (p = 0.05) [0.02;0.52] | 0.29 (p = 0.31) [-0.28;0.86] |
CV Stride length | 0.19 (p = 0.20) [-0.11;0.46] | 0.22 (p = 0.14) [-0.05;0.45] | 0.34 (p = 0.37) [-0.41;1.10] |
CV Step time | 0.02 (p = 0.90) [-0.28;0.31] | 0.13 (p = 0.39) [-0.22;0.42] | 0.36 (p = 0.52) [-0.76;1.48] |
CV Step length | 0.36 (p = 0.01) [0.08;0.59] | 0.37 (p = 0.01) [0.06;0.64] | 1.42 (p = 0.02) [0.21;2.62] |
Gait regularity | -0.38 (p < 0.01) [-0.61;-0.10] | -0.48 (p < 0.01) [-0.69;-0.23] | -0.02 (p = 0.06) [-0.05;0.001] |
Dual-task cost of gaita |
Gait speed (%) | 0.40 (p < 0.01) [0.13;0.62] | 0.34 (p = 0.02) [0.03;0.59] | 2.52 (p = 0.03) [0.32;4.72] |
Cadence (%) | 0.28 (p = 0.07) [-0.02;0.53] | 0.20 (p = 0.19) [-0.09;0.50] | 1.10 (p = 0.13) [-0.35;2.55] |
Stride time (%) | 0.32 (p = 0.03) [0.03;0.57] | 0.26 (p = 0.09) [-0.04;0.54] | 1.71 (p = 0.06) [-0.05;3.47] |
Stride length (%) | 0.12 (p = 0.43) [-0.18;0.40] | 0.15 (p = 0.34) [-0.13;0.40] | 0.85 (p = 0.36) [-0.99;2.70] |
Among parameters on dual-task cost of gait, gait speed was correlated in all three models, while stride time was correlated only in parametric univariable analysis. In Additional file
2, the data are presented graphically with Boxplots.
Discussion
The aim of this study was to analyse gait parameters in patients categorised into different CKD disease stages and to determine whether these measures got worse in relation to the disease progression. To the best of our knowledge, this is the first study that focused on the correlation between several gait variability parameters and CKD severity. The results indicate that three variability parameters out of five (CV of stride time, CV of step length and gait regularity) deteriorate in a linear way with the reduction of eGRF and suggests that already in early stages of CKD (namely stage 3) changes in the brain structure may influence gait quality. The other variability measures show no decline over the disease progression, however, the values observed for step time and stride length variability show values that are consistently high and are, when compared to benchmarks, to be considered in ranges attributable to pathologic walking behaviour [
45]. It can, therefore, be speculated that ceiling effects may explain why further worsening in these parameters cannot be detected.
It is widely known that CKD severity affects the health status both for physical and cognitive performance [
1‐
3,
9] and the clinical parameters collected in this study confirms this. The relation between muscle strength and gait performance is well known [
20,
26,
46] and decreased muscle strength may explain why people show decreased walking velocity [
47]. Therefore, it is not surprising to find in our results the same tendency towards a worsening result with increasing CKD severity for clinical muscle related parameters (handgrip strength, fatigue, physical health, time for ETGUG) as well as for gait speed and stride length. Less studied in this population, however, is the relation between cognitive aspects and gait variability parameters.
Gait disorders may be caused by muscular peripheral impairment, may have a neurologic central origin, or may be due to a combination of factors [
48]. Where lower extremity strength would be indicative for how fast people can walk [
49], measures of gait variability are indicative of brain functioning [
50]. The proxy assessments related to skeletal muscle mass that we applied (ETGUG, handgrip, fatigue) showed a deterioration already in early stages of the illness, and confirm that muscle wastage is a driving factor for decreased walking speed in CKD, and should, therefore, be monitored throughout all stages [
51,
52]. In fact, it is known that CKD-sarcopenia is a secondary sarcopenia, which, compared to the age-related primary sarcopenia, occurs earlier and in a more intense way and with a greater magnitude [
52]. This seems to be confirmed in our sample, where the difference in muscle strength related factors (i.e. handgrip) between age-matched patients at different CKD stages is meaningful. This rapid loss of muscle strength is explained by mitochondrial damage and protein degradation [
52‐
54] typical for CKD patients. However, changes in grip strength are largely reflective of decreased integrity of the nervous system [
55] and sarcopenia is also linked to changes in the central nervous system [
56,
57]. This would hint to the possibility of gait disorders in CKD caused by peripheral and central factors.
Although these results apparently also explain the slowdown of gait speed and shortening of stride length [
58,
59], some other factors, e.g. cognitive factors, should be considered as well. These factors may help in explaining the relation between gait performance, brain health and kidney failure [
60]. In particular, cerebrovascular diseases are related to a reduced gait performance [
61‐
64]. These findings led to a definition of the motoric cognitive risk syndrome [
65,
66] as characterized by a slow gait and mild cognitive impairment. The CKD population is more affected by cerebrovascular disease, and the rate of vascular dementia is higher than the rate of degenerative dementia, in contrast to the general population [
67], which should be reflected in gait variability values. The individuals selected for our study show in general values for gait variability in all five disease stages that are indicative of pathological walking [
45]. The reduction of both gait performance (lower gait speed and shorter stride length) and executive function (FAB, TMT) in CKD stages ≥ 3 observed in our study is therefore coherent with brain changes due to kidney failure [
68‐
70]. The higher dual-task cost of gait speed is an additional hint towards this link [
71‐
74]. This finding confirms the association between gait disorders and gray matter atrophy in CKD patients both with and without cognitive disorders [
75]. Based on these observations a more comprehensive analysis of gait changes in clinical CKD populations seems warranted.
In our study we also calculated gait variability, that is known to be related to neurocognitive factors [
76‐
80]. As gait variability and gait speed are controlled by different brain regions [
78,
79], and gait speed is also affected by muscle strength (see above), it is not unexpected that they are influenced differently by CKD severity, and that they are not related [
81,
82]. Finally, in addition to metabolic disorders that lead to muscle mass loss and changes in the brain that lead to gait impairment, it is worth mentioning that recent research showed a disturbed corticospinal control of gait in sarcopenic patients [
83]. Functional decline of gait in CKD patients seems a complex process that should be treated through a multidisciplinary approach.
The aim of this study was to describe gait characteristics of CKD patients at different stages. We found statistically relevant correlations between a decline in gait speed, stride length and spatial and temporal variability. This can be explained on the one hand by muscle wastage, and on the other hand by cognitive decline, especially executive function, due to cerebrovascular disorders. As these changes start already in patients with a moderately reduced kidney function, interventions to prevent cognitive and physical decline should be offered early in form of training that stimulates both physical and cognitive domains.
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