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Abstract

Objective

To determine the prevalence of cognitive impairment (CI) among middle-aged to older patients receiving maintenance haemodialysis (MHD) and to investigate the potential association between CI and physical performance.

Methods

This cross-sectional observational study enrolled participants aged 55–85 years who received MHD. Cognitive status was assessed using the Mini Mental State Examination (MMSE). Physical performance was measured by hand grip strength, the Timed Up and Go Test (TUGT) and the 4-m walking speed. Sociodemographic, clinical and laboratory parameters were recorded for each patient.

Results

The study included 592 patients (363 males); and of these, 126 (21.3%) were diagnosed with CI. Compared with patients with normal cognitive function, those with CI were significantly older and had significantly longer dialysis duration, lower educational level, higher Malnutrition Inflammation Score, higher depression and higher Charlson Comorbidity Index score. After adjustment for covariates, multiple regression analysis suggested that grip strength (odds ratio [OR] = 0.959, 95% confidence interval [CI] = 0.924, 0.996) and 4-m walking speed (OR = 0.161, 95% CI = 0.070, 0.368) were protective factors. TUGT (OR = 1.037, 95%CI = 1.003, 1.071) was a risk factor.

Conclusion

Physical performance was correlated with CI and might be a significant indicator for the early identification of CI in middle-aged to older MHD patients.

Keywords

Cognitive impairment haemodialysis grip strength Timed Up and Go Test 4-m walking speed

Introduction

End-stage renal disease (ESRD) is an important public health problem throughout the world.¹ Maintenance haemodialysis (MHD) is a primary renal replacement therapy modality undertaken for at least 3 months that improves prognosis and extends the survival of individuals with ESRD. According to the Chinese Renal Data System, 447 435 patients with ESRD were undergoing haemodialysis by the end of 2016.² A markedly elevated prevalence of CI and dementia has been reported among MHD patients compared with the general population, particularly among the elderly.³ Moreover, existing data indicate that MHD patients with CI necessitate increased attention from dialysis staff,⁴ experience prolonged hospitalizations, face higher mortality risks and are more likely to exhibit poorer adherence to treatment plans.^5,6 Therefore, CI warrants significant attention in the middle-aged to older MHD population.

Decreased physical performance has been identified as a contributing risk factor for CI.⁷ Poor physical performance is associated with worse clinical outcomes and poor quality of life.⁸ Current physical activity guidelines for Americans advocate for engaging in multicomponent physical activities, such as balance training, aerobic exercises and muscle strengthening, as these activities have been demonstrated to enhance cognition and reduce the risk of dementia.⁹ Despite this, the relationship between physical performance and CI remains unexplored among MHD patients. Therefore, the primary objective of this current study was to assess the prevalence of CI among middle-aged to older MHD patients and to investigate the potential association between CI and physical performance within this population.

Patients and methods

Study design and patient population

This cross-sectional study enrolled consecutive patients undergoing MHD from seven haemodialysis centres in Shanghai and Suzhou between July 2020 and April 2021. All patients were invited to participate in a comprehensive geriatric assessment along with cognitive function assessment. The inclusion criteria included the following: (i) aged 55–85 years with intact communication abilities; (ii) regular MHD for at least 3 months, conducted 2–3 times a week, each session lasting 4–5 h; (iii) willingness to participate in this study. The exclusion criteria were as follows: (i) severe cerebrovascular disease, and other serious mental disorders, or ongoing treatment with psychotropic drugs during the observation period; (ii) presence of other serious diseases; (iii) inability to perform physical performance tests; (iv) impediment in completing the assessment scale due to other reasons.

This study followed the STROBE statement Guidelines.¹⁰ The study was approved by The Ethics Committee of Shanghai University of Medicine and Health Sciences (no. 2019-A4-2621-19-201001-03-12010419771113601X). All of the study participants provided written informed consent. All patient details have been de-identified.

Sociodemographic and clinical characteristics

All patients underwent face-to-face interviews, where they completed a standardized questionnaire covering both sociodemographic and clinical characteristics. Sociodemographic factors included education level, residence, marital status, sleep duration, and smoking and drinking habits. Clinical characteristics encompassed age, sex, height, weight, dialysis duration, primary renal disease and concurrent ailments. Comorbidity was assessed using the Charlson Comorbidity Index (CCI), consolidating multiple conditions into a single score based on 19 comorbidity conditions. Physical activity levels were evaluated using the short form of the International Physical Activity Questionnaire, while nutritional status was determined by the Malnutrition Inflammation Score (MIS). Depression was screened using the Patient Health Questionnaire-9.

Assessment of cognitive impairment

The Mini Mental State Examination (MMSE) was used to assess cognitive function.¹¹ It is a highly reliable screening tool for dementia and easily accepted by elderly people. MMSE consists of 30 items with scores ranging from 0 to 30, with the higher scores indicating better cognitive performance. The MMSE includes a broad set of cognitive domains that measure the following: time orientation (5 points), place orientation (5 points), registration (3 points), attention and calculation (5 points), recall (3 points) and language (9 points).¹² The cut-off points used for CI were as follow: ≤17 for illiterate people; ≤20 for people with primary school education only; and ≤24 for people with middle school or higher levels of education.¹³ The cognitive assessments were performed by trained investigators (J.X. & X.Z.).

Assessment of physical performance

The assessment of physical performance included the following: muscle strength; balance function; and mobility using the handgrip strength, Timed Up and Go Test (TUGT) and gait speed. Handgrip strength was assessed on their non-fistula hand or dominant hand with an indwelling dialysis catheter, using a dynamometer (GRIP-D; Takei, Niigata, Japan). Participants were asked to exert maximum effort twice and the best of the two measurements was recorded.¹⁴ TUGT counts the number of seconds needed for an individual to stand up from a chair, then walk 3 m, turn around, walk back to the chair and sit down again with their back against the chair.¹⁵ To determine gait speed, the participants were asked to walk 4 m twice at their usual pace on a flat surface. Gait speed was calculated as the time taken (s) to complete the 4-m distance (m/s); and the mean speed from the two tests was used in the study.¹⁴ Walking aids were allowed during the test. These performance-based tests were performed before the haemodialysis session.

Laboratory measures

Routine biochemical laboratory indices were measured before haemodialysis, including haemoglobin, albumin, calcium, phosphorus, parathyroid hormone and C-reactive protein. Haemodialysis adequacy was defined as Kt/V. Laboratory indicators were collected on the day or within 1 week of the patient’s cognitive function assessment.

Statistical analyses

All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA). Data with a normal distribution are presented as mean ± SD, whereas data that are not normally distributed are presented as median (interquartile range). Categorical data are presented as n (%). Baseline sociodemographic and clinical characteristics were compared between patients with different cognitive function using Student’s t-test for normally distributed continuous variables, Mann–Whitney U-test for continuous variables that were not normally distributed, and χ²-test for categorical variables. A logistic regression model was used to investigate the relationship between physical performance and CI. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Linear regression models were used to examine the relationship between physical performance and various cognitive domains. Covariates were added sequentially to the linear model to evaluate the association at different levels of adjustment. Crude was the unadjusted model. Model 1 was adjusted for age, sex and body mass index. Model 2 was additionally adjusted for model 1 variables and years of education, CCI, dialysis duration, MIS and depression score. A two-sided P-value of <0.05 was considered to be statistically significant.

Results

This cross-sectional study identified 880 patients that underwent MHD at seven haemodialysis centres in Shanghai and Suzhou. Of these, 288 patients were excluded from the analysis: 236 were not in the age range; 20 were diagnosed with severe cerebrovascular disease; 8 had hemiplegia; and 24 were unable to complete the physical performance tests or scales (Figure 1). The final analysis included 592 patients (363 males; 61.3%) with a mean ± SD age of 66.89 ± 6.97 years. Of these patients, 126 patients (21.3%) were diagnosed with CI.

Figure 1.

Flowchart showing progress through enrolment, exclusion and analysis of patients (n = 592) that underwent maintenance haemodialysis (MHD) at seven haemodialysis centres and were enrolled in a study investigating the prevalence of cognitive impairment (CI) among middle-aged to older MHD patients and the potential association between CI and physical performance within this population.

The sociodemographic and clinical characteristics of the study population stratified according to CI are presented in Table 1. Compared with participants with normal cognitive function, those with CI were significantly older (P = 0.018), had a significantly longer dialysis duration (P = 0.027) and a significantly lower educational level (P = 0.016); and a significantly higher MIS score (P = 0.012), a significantly higher depression score (P < 0.001) and a significantly higher CCI score (P = 0.018). Participants with CI also had a significantly lower grip strength (P < 0.001), a significantly longer TUGT (P = 0.008) and a significantly slower walking speed (P < 0.001) compared with the participants with normal cognitive function.

Table 1.

Sociodemographic and clinical characteristics of middle-aged to older patients (n = 592) who underwent maintenance haemodialysis (MHD) stratified according to the presence of cognitive impairment.

Characteristic	Normal cognition groupn = 466	Cognitive impairment groupn = 126	Statistical analysis^a
Age, years	66.42 ± 6.84	68.08 ± 7.37	P = 0.018
Male	293 (62.9%)	70 (55.6%)	NS
BMI, kg/m²	23.34 ± 3.55	23.18 ± 3.39	NS
Dialysis duration, months	54.84 ± 44.10	67.37 ± 58.84	P = 0.027
Married	412 (88.4%)	101 (80.2%)	NS
Living alone	16 (3.4%)	5 (4.0%)	NS
Alcohol drinker	216 (46.4%)	51 (40.5%)	NS
Smoker	235 (50.4%)	60 (47.6%)	NS
Duration of education			P = 0.016
<6 years	67 (14.4%)	28 (22.2%)
6–12 years	340 (73.0%)	91 (72.2%)
>12 years	59 (12.7%)	7 (5.6%)
Primary disease			NS
Diabetic nephropathy	106 (22.7%)	39 (31.0%)
Hypertensive nephropathy	67 (14.4%)	27 (21.4%)
Primary glomerular disease	140 (30.0%)	34 (27.0%)
Polycystic kidney disease	32 (6.9%)	5 (4.0%)
Others	121 (26.0%)	21 (16.7%)
Laboratory metrics
Single-pool Kt/V	1.38 ± 0.35	1.41 ± 0.28	NS
Haemoglobin, g/l	111.43 ± 14.98	110.44 ± 16.13	NS
Albumin, g/l	39.30 ± 3.49	38.86 ± 3.98	NS
CRP, mg/l	2.70 (1.24–5.80)	2.98 (1.34–5.90)	NS
Calcium, mmol/l	2.27 ± 0.26	2.23 ± 0.27	NS
Phosphorus, mmol/l	1.91 ± 0.62	1.94 ± 0.68	NS
Parathyroid hormone, pg/ml	295.56 ± 270.23	293.21 ± 269.88	NS
IPAQ, met/wk	1386 (693–3066)	981 (198–2772)	NS
Depression score	4.84 ± 4.61	6.94 ± 6.26	P < 0.001
CCI	3.99 ± 1.67	4.40 ± 1.81	P = 0.018
MIS	4.38 ± 2.77	5.12 ± 3.46	P = 0.012
Sleep duration, h	8.31 ± 2.34	8.62 ± 2.06	NS
Physical performance
Grip strength, kg	23.29 ± 7.99	20.77 ± 7.00	P < 0.001
TUGT, s	9.92 ± 5.88	12.60 ± 8.20	P = 0.008
4-m walking test, m/s	0.98 ± 0.29	0.79 ± 0.31	P < 0.001

Data presented as mean ± SD, median (interquartile range) and n of patients (%).

Student’s t-test was used for normally distributed continuous variables; Mann–Whitney U-test was used for continuous variables that were not normally distributed; and χ²-test was used for categorical variables; NS, no significant between-group difference (P ≥ 0.05).

BMI, body mass index; Kt/V, an indicator for evaluating dialysis adequacy; CRP, C-reactive protein; IPAQ, international physical activity questionnaires; CCI, Charlson Comorbidity Index; MIS, Malnutrition Inflammation Score; TUGT, Timed Up and Go Test.

The relationship between physical performance and CI is presented in Table 2. After identification of significant independent variables and covariates through univariate analysis, the grip strength (OR = 0.959, 95% CI = 0.924, 0.996) and 4-m walking speed (OR = 0.161, 95% CI = 0.070, 0.368) correlated inversely with CI, indicating that an increased grip strength and faster walking speed were associated with a reduced risk of CI. Conversely, TUGT (OR = 1.037, 95% CI = 1.003, 1.071) showed a positive correlation with CI, suggesting that spending more time on TUGT was a risk factor for CI.

Table 2.

Logistic regression analysis of physical performance and cognitive impairment variables in middle-aged to older patients (n = 592) who underwent maintenance haemodialysis.

Variables	Unadjusted		Model 1		Model 2
Variables	OR (95% CI）	P-value	OR (95% CI）	P-value	OR (95% CI）	P-value
Grip strength	0.957 (0.932, 0.983)	P = 0.001	0.960 (0.927, 0.994)	P = 0.021	0.959 (0.924, 0.996)	P = 0.030
TUGT	1.055 (1.024, 1.087)	P < 0.001	1.048 (1.016, 1.081)	P = 0.003	1.037 (1.003, 1.071)	P = 0.031
4-m walking test	0.127 (0.064, 0.254)	P < 0.001	0.131 (0.062, 0.277)	P < 0.001	0.161 (0.070, 0.368)	P < 0.001

Model 1: adjusted for age, sex and body mass index; Model 2: adjusted for age, sex, body mass index, years of education, Charlson Comorbidity Index, dialysis duration, Malnutrition Inflammation Score, depression score.

OR, odds ratio; CI, confidence interval; TUGT, Timed Up and Go Test.

Furthermore, the relationship between physical performance and each cognitive domain was investigated. The grip strength correlated with the total score of MMSE as well as with the attention and calculation sub-score (Table 3). TUGT correlated with the total score of MMSE as well as with the time orientation, place orientation, and attention and calculation sub-scores (Table 4). The 4-m walking speed demonstrated correlations with the total score of MMSE and with the time orientation, place orientation, attention and calculation, recall and language sub-scores (Table 5). These results align with above findings (Table 2), suggesting that grip strength may influence cognitive function through attention and calculation; TUGT may impact cognitive function through time orientation, place orientation, attention and calculation; and the 4-m walking speed may affect cognitive function through time orientation, place orientation, attention and calculation, recall and language.

Table 3.

Multivariate linear regression analysis of the association between grip strength and cognitive impairment domains in middle-aged to older patients (n = 592) who underwent maintenance haemodialysis.

Variables	Unadjusted		Model 1		Model 2
Variables	β	P-value	β	P-value	β	P-value
MMSE score	0.120	P < 0.001	0.075	P = 0.004	0.067	P = 0.007
MMSE sub-scores
Orientation to time	0.023	P < 0.001	0.014	P = 0.039	0.012	P = 0.079
Orientation to place	0.011	P < 0.001	0.007	P = 0.087	0.007	P = 0.100
Registration	0.007	P = 0.011	0.005	P = 0.154	0.004	P = 0.217
Attention and calculation	0.036	P < 0.001	0.025	P = 0.018	0.025	P = 0.014
Recall	0.005	P = 0.001	0.004	P = 0.016	0.003	P = 0.068
Language	0.039	P < 0.001	0.021	P = 0.068	0.016	P = 0.148

MMSE, Mini Mental State Examination.

Table 4.

Multivariate linear regression analysis of the association between Timed Up and Go Test and cognitive impairment domains in middle-aged to older patients (n = 592) who underwent maintenance haemodialysis.

Variables	Unadjusted		Model 1		Model 2
Variables	β	P-value	β	P-value	β	P-value
MMSE score	−0.137	P < 0.001	−0.108	P < 0.001	−0.072	P = 0.003
MMSE sub-scores
Orientation to time	−0.027	P < 0.001	−0.022	P = 0.001	−0.014	P = 0.032
Orientation to place	−0.013	P < 0.001	−0.011	P < 0.001	−0.009	P = 0.026
Registration	−0.006	P = 0.046	−0.005	P = 0.146	−0.004	P = 0.377
Attention and calculation	−0.040	P < 0.001	−0.035	P < 0.001	−0.029	P = 0.006
Recall	−0.006	P < 0.001	−0.005	P = 0.01	−0.002	P = 0.272
Language	−0.046	P < 0.001	−0.032	P = 0.004	−0.016	P = 0.061

MMSE, Mini Mental State Examination.

Table 5.

Multivariate linear regression analysis of the association between 4-m walking speed and cognitive impairment domains in middle-aged to older patients (n = 592) who underwent maintenance haemodialysis.

Variables	Unadjusted		Model 1		Model 2
Variables	β	P-value	β	P-value	β	P-value
MMSE score	4.104	P < 0.001	3.521	P < 0.001	2.637	P < 0.001
MMSE sub-scores
Orientation to time	0.706	P < 0.001	0.583	P < 0.001	0.375	P = 0.012
Orientation to place	0.355	P < 0.001	0.291	P < 0.001	0.229	P = 0.011
Registration	0.192	P = 0.006	0.154	P = 0.038	0.114	P = 0.155
Attention and calculation	1.195	P < 0.001	1.140	P < 0.001	0.963	P < 0.001
Recall	0.206	P < 0.001	0.181	P < 0.001	0.128	P = 0.003
Language	1.532	P < 0.001	1.256	P < 0.001	0.918	P < 0.001

MMSE, Mini Mental State Examination.

Discussion

The objective of this multicentre cross-sectional study was to assess the prevalence of CI among middle-aged to older Chinese patients undergoing MHD across seven haemodialysis facilities in Shanghai and Suzhou. In addition, the study aimed to investigate the relationship between CI and physical performance in this population. The current findings demonstrated that among the 592 MHD patients studied, 21.3% were diagnosed with CI based on the MMSE score. Furthermore, the current analysis indicated that physical performance remained significantly associated with CI even after adjusting for potential confounders. Specifically, greater grip strength and faster walking speed were identified as protective factors against CI, whereas slower TUGT was identified as a risk factor. These results were not only similar to previous findings among older adults residing in suburban areas of China,¹⁶ but also aligned with observations among older adults with pre-dialysis chronic kidney disease in Japan.⁷

Multiple previous studies have investigated cognitive function among dialysis patients through cross-sectional analyses, revealing a substantial prevalence of CI, with 30% to 80% of patients exhibiting at least mild cognitive impairment.¹⁷ Notably, the prevalence of CI in this current study was 21.3%, lower than that reported in previous studies.¹⁷ This observed variation in CI prevalence can be attributed to several factors, including the varying sensitivities of screening tools, utilization of different cut-off scores for defining CI, divergent sample sizes, demographic characteristics such as age, sex and education level, as well as cultural disparities based on study location. Furthermore, discrepancies in inclusion and exclusion criteria, tailored to the specific objectives of each study, may also contribute to the variability in reported prevalence rates. The primary aim of this current study was to investigate the relationship between physical function and CI. However, the exclusion of patients with a history of stroke, who were unable to complete the physical performance assessment, may have led to a significant underestimation of CI prevalence. In addition, the timing of cognitive screening in the current study may have influenced cognitive performance, as the highest scores were typically achieved before haemodialysis.¹⁸ In this current study, all assessments were conducted prior to haemodialysis sessions. Conversely, in most studies, cognitive tests were administered during or after haemodialysis, potentially resulting in an overestimation of CI prevalence.^18,19 Hence, estimates of CI within the haemodialysis population may be subject to bias, and the development of cognitive testing protocols that address these limitations may prove beneficial in future research endeavours.

Various physical measures may have differential impacts on cognitive changes, including alterations in specific cognitive domains and global cognitive decline.²⁰ Grip strength, commonly utilized as an indicator of muscle strength,²¹ also serves as a proxy for muscle mass.²² It has been reported to correlate with CI in the general population and predict 10-year cognitive decline assessed using the MMSE among older individuals.^20,23 In addition, a previous study observed that grip strength may serve as an early marker of CI in the general population.²⁴ Consistent with these findings, the current study demonstrated a significant correlation between grip strength and CI among middle-aged to older patients undergoing MHD. Further examination of the relationship between grip strength and overall cognition, as well as various cognitive domains, revealed correlations with overall cognition, attention and calculation. These results mirror findings in the older general population, where grip strength was associated with overall cognition, time orientation, immediate recall and language.¹⁶ Some researchers posit that the association between low grip strength and cognitive decline may share a common aetiopathogenesis. Neuroimaging studies have indicated that skilled hand movements and handgrip strength are linked to various brain regions, including the primary motor area, supplementary motor area, premotor cortex and cerebellum, all of which play roles in higher cognitive functions.^20,25,26 Others suggest that the correlation between low grip strength and global cognitive decline may be attributed to reduced grey and white matter volumes in multiple brain regions, white matter hyperintensities, and greater activation in specific brain areas.^27,28 In addition, factors frequently observed in MHD patients, such as high oxidative stress, elevated inflammatory markers, insulin resistance and low sex steroid levels, contribute to both muscle loss and cognitive decline, potentially explaining the association between poor physical function and cognitive decline.^29,30 However, further investigation is warranted to explore the relationship between grip strength and other cognitive domains.

The TUGT serves as a straight forward and reliable method for evaluating patients’ functional mobility, with established reliability across various populations, including the elderly.³¹ It has been widely used in assessing various chronic conditions, including chronic kidney disease patients undergoing haemodialysis.³² Notably, older adults with CI tend to perform poorly on the TUGT and CI has been identified as an independent determinant of TUGT scores.³³ Consistent with these findings, the current study also found a significant correlation between TUGT and CI among middle-aged to older MHD patients. Further analysis revealed an inverse correlation between TUGT and global cognition, as well as specific cognitive domains such as time orientation, place orientation, attention and calculation. These current findings parallel earlier observations in community-dwelling older populations.¹⁶ While TUGT is regarded as a rapid and simple tool for assessing mobility, gait, balance and fall risk,³⁴ its execution necessitates integration of multiple systems and may be considered complex, particularly in older adults with CI. A previous study found that a slower TUGT was associated with cognitive language deficits, poor attention and computing skills.³⁵ Another study demonstrated that a longer TUGT duration correlated with lower hippocampal volume, with the relationship between the hippocampus and TUGT performance being notably pronounced compared with other brain regions.³⁶ Hence, there is a need for further longitudinal studies to elucidate the relationship between TUGT and CI in future research endeavours.

This current study found that slow gait speed was independently associated with CI. It also demonstrated that walking speed correlated with all cognitive areas except registration. Previous studies consistently showed associations between physical abilities like gait speed and handgrip strength, and cognitive function in older adults. For example, a previous study found that changes in gait speed were related to fluid cognition shifts, while handgrip strength was tied to changes in overall cognitive function.³⁷ Another study suggested that walking and gait might rely on both motor and cognitive functions, hinting at shared neural and pathological mechanisms.³⁸ The neural networks governing walking involve regions responsible for attention, executive function, visuospatial abilities and motor control. Prior research has implicated specific brain areas such as the cerebellum, basal ganglia, hippocampus, and parietal and frontal cortices in both gait and executive functions.^39,40 Despite these findings, the precise mechanisms connecting gait speed and cognition remain incompletely understood. Further investigation is needed to clarify these relationships.

This current study had several limitations. First, all study participants were considered relatively ‘healthy’ as those unable to complete the physical performance assessment were excluded, which possibly lead to a biased sample. Secondly, the use of the MMSE alone to assess CI, while convenient, may not adequately capture executive and visual-spatial functions. Thirdly, due to the study’s cross-sectional design, it was not possible to establish causal relationships between physical function and CI. Lastly, the frequency of intradialytic hypotension, a recognized mechanism of CI in HD patients, was not measured.⁴¹ Addressing these limitations in future research will provide a more comprehensive understanding of the relationship between physical function and CI in MHD patients.

In conclusion, these current findings indicated a relatively high occurrence of CI among middle-aged to older Chinese patients undergoing MHD. The study found significant correlations between CI and measures of physical performance, including grip strength, TUGT and 4-m walking speed. In addition, the current analysis demonstrated that grip strength was associated with overall cognition, attention and calculation; TUGT was correlated with overall cognition, time orientation, place orientation, attention and calculation; and the 4-m walking speed was associated with overall cognition and various cognitive domains, except registration. These physical performance measures of grip strength, TUGT and walking speed may serve as important indicators for the early detection of CI in middle-aged to older MHD patients.

Supplemental Material

sj-pdf-1-imr-10.1177_03000605241259439 - Supplemental material for Association of physical performance with cognitive impairment in middle-aged to older haemodialysis patients: a multicentre cross-sectional observational study

Supplemental material, sj-pdf-1-imr-10.1177_03000605241259439 for Association of physical performance with cognitive impairment in middle-aged to older haemodialysis patients: a multicentre cross-sectional observational study by Jia Xu, Xinhui Zhao, Qi Guo, Cheng Yu, Wei Ding, Jianying Niu, Junli Zhao, Liming Zhang, Suhua Zhang, Hualin Qi and Minhui Xi in Journal of International Medical Research

Footnotes

Acknowledgements

The sponsor and investigators thank the patients and their families for their participation and support for this clinical study. We thank the medical staff at the Department of Nephrology, Tongji Hospital, Department of Nephrology, Shanghai Ninth People’s Hospital, Department of Nephrology, The Fifth People’s Hospital, Department of Nephrology, Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Department of Nephrology, Zhabei Central Hospital of JingAn District, Department of Nephrology, Suzhou Kowloon Hospital, Department of Nephrology, the People’s Hospital of Pudong New District in Shanghai.

Author contributions

J.X. and X.Z. were responsible for protocol development, data analysis and manuscript writing. W.D., J.N., C.Y., J.Z., L.Z. and S.Z. were responsible for conducting the research. Q.G. and H.Q. were responsible for project development. H.Q. and M.X. were responsible for project development and manuscript review and editing. All authors reviewed the final version of the manuscript and approved it for submission.

Declaration of conflicting interest

The authors declare that there are no conflicts of interest.

Funding

This study was supported by the grants from the General Project (no. PW2020A-59) and Key Discipline Construction Project (no. PWZxk2022-19) of Pudong Health and Family Planning Commission of Shanghai.

ORCID iDs

Qi Guo

Liming Zhang

Hualin Qi

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