Frailty in Older Patients with End-Stage Renal Disease and Undergoing Chronic Haemodialysis in Vietnam
1
Department of Geriatrics & Gerontology, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam
2
Department of Interventional Cardiology, Thong Nhat Hospital, Ho Chi Minh City 700000, Vietnam
3
Westmead Applied Research Centre, Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
*
Authors to whom correspondence should be addressed.
Diabetology 2023, 4(3), 312-322; https://doi.org/10.3390/diabetology4030027
Submission received: 21 May 2023
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Revised: 21 July 2023
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Accepted: 27 July 2023
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Published: 1 August 2023
(This article belongs to the Special Issue Exclusive Papers Collection of Editorial Board Members in Diabetology)
Abstract
:Background: There is limited evidence on the association between chronic kidney disease (CKD) and frailty in older people in Vietnam. This study aimed to investigate the prevalence of frailty and its impact on mortality in older patients with end-stage renal disease. Method: This is a prospective, observational study performed at two large Dialysis Centres in Vietnam from November 2020 to June 2021. Consecutive older patients diagnosed with end-stage renal disease and on haemodialysis were recruited. Participants’ frailty status was defined by the Clinical Frailty Scale (CFS). The study outcome was all-cause mortality at the sixth month. Results: A total of 175 participants were recruited (mean age 72.4 years, 58.9% female). Using the cut point of CFS ≥ 4, 87.4% of the participants were frail. Mortality at the sixth month was 14.9%, 31.9% in participants with CFS ≥ 7, 12.8% in participants with CFS = 6, 7.5% in participants with CFS from 4 to 5, and 4.5% in participants with CFS ≤ 3 (p = 0.001). Cox regression analysis showed that, compared with the non-frail participants, the probability of death over 6 months was nearly two-fold higher in the mildly frail, three-fold higher in the moderately frail, and nine-fold higher in the severely frail participants. Conclusions: This study demonstrated a very high prevalence of frailty in older patients with end-stage renal disease and dialysis and the significant impact of frailty severity on mortality. Healthcare providers should consider incorporating frailty screening into routine care for older patients with end-stage renal disease and dialysis.
Keywords:
chronic kidney disease; end-stage renal disease; dialysis; diabetes; frailty; elderly; Vietnam1. Introduction
Chronic kidney disease is a health condition associated with a high degree of morbidity and mortality [1,2]. Chronic kidney disease is characterised by an irreversible progressive reduction in kidney function commonly caused by diabetes or hypertension [1,2]. Current international guidelines define chronic kidney disease as decreased kidney function with a glomerular filtration rate of less than 60 mL/min or laboratory measurements that indicate kidney damage that is present for at least 3 months [1,2]. In its early stages, chronic kidney disease is normally asymptomatic. However, as the disease progresses, symptoms will develop, eventually resulting in end-stage kidney disease. At this point, the glomerular filtration rate will be less than 15 mL/min and the kidneys will be unable to perform necessary functions. resulting in uraemia, anaemia, electrolyte imbalances, fluid overload and acidaemia, and eventually death [1,2]. At this point, renal replacement therapy is required. The options are kidney transplantation or dialysis, the latter being the more common approach [3]. Even with dialysis, there is a significant reduction in the quality and quantity of life, especially in the first year of commencement [4]. Chronic kidney disease is a very common condition in older people, and it can have a significant impact on adverse health outcomes including, functional decline, reduced energy intake, and sarcopenia, all of which can lead to frailty [5,6]. Chronic inflammation, fluid overload, malnutrition, protein wasting, decreased muscle mass, and insulin resistance are all common in chronic kidney disease and make an individual more likely to progress to frailty [7].
Frailty is the loss of physiological reserve as we age, which predisposes those affected to increased morbidity and mortality when subjected to stressors. Frailty is common in people with chronic kidney disease, with more than 60% of dialysis-dependent chronic kidney disease patients having this condition [6]. The highest prevalence of frailty is seen in end-stage kidney disease requiring dialysis, up to 81%, compared with earlier-stage disease not receiving dialysis, which ranges from 2.8 to 16% [8].
The association between frailty and chronic kidney disease is not completely understood. Both frailty and chronic kidney disease share common risk factors, including ageing, comorbidities, malnutrition, and inflammation [9,10]. Chronic kidney disease has systemic effects that contribute to the development and progression of frailty. The accumulation of uremic toxins, fluid imbalances, and nutrient deficiencies associated with chronic kidney disease can lead to muscle wasting, weight loss, fatigue, and physical impairment, all of which are hallmarks of frailty [9,10]. Uremic toxins and their associations with cellular degeneration are potential causes of frailty [11]. Studies have shown that, in people with chronic kidney disease (and particularly end-stage renal disease), sarcopenia and cachexia are common and can contribute to the development of frailty [12]. Chronic inflammation also plays an important role. Raised levels of pro-inflammatory cytokines in people with chronic kidney disease may contribute to age-related muscle atrophy and sarcopenia, which are key features of frailty [9,13]. Protein-energy wasting, a state of nutritional and metabolic derangement characterized by simultaneous loss of systemic body protein and energy stores, is common in patients with chronic kidney disease and end-stage renal disease [12,14]. Protein-energy wasting is associated with the hypercatabolic state induced by uraemia, anorexia, and systemic inflammation and can contribute to the development or worsening of frailty [12,14]. Anaemia and mineral and bone disorders related to chronic kidney disease may further contribute to frailty by impairing mobility and functional capacity [9]. In addition, the burden of comorbidities associated with chronic kidney disease, such as hypertension, diabetes, and heart failure, can also exacerbate frailty syndrome in older patients [9,10].
On the other hand, frailty can be a risk factor for the progression of chronic kidney disease through various mechanisms [9,10]. Frail people with chronic kidney disease (and particularly those on chronic dialysis) may have difficulty in adhering to treatment regimens, making it challenging to manage their condition effectively. Reduced physical activity and muscle wasting associated with frailty can lead to decreased kidney function and impaired renal blood flow. Frailty-related factors, such as inflammation and oxidative stress, may exacerbate renal damage, accelerating the decline in kidney function [15]. Frailty has been independently associated with increased all-cause mortality, all-cause hospitalisation, and falls in patients with chronic kidney disease [6].
In 2016, the European Renal Best Practice Working Group on Clinical Practice Guideline, regarding the management of older patients with chronic kidney disease stage 3b or higher, recommended frailty assessment in older patients with advanced chronic kidney disease [16]. Older patients with stage 5 chronic kidney disease should receive multidisciplinary assessment, including frailty, cognitive function, comorbidities, nutritional status, functional status, and psychosocial factors. The guideline also recommended the integration of frailty in predicting mortality for patients with chronic kidney disease stage 3–5; for example, they suggested using the Bansal score to predict the individual 5-year risk of death before end-stage kidney disease in non-frail older patients and in patients at low risk in the Bansal score, and a score including the assessment of frailty should be calculated [16]. Frailty scores can provide additional information during patient assessment and shared decision-making regarding the treatment of patients with chronic kidney disease.
In Vietnam, the burden of chronic kidney disease remains high, with over 10,000 cases per 100,000 and 20.6 deaths per 100,000 [17]. The incidence of chronic kidney disease was estimated to be approximately 120 per million people in Vietnam [18]. Owing to the alarmingly fast rate of diabetes development in this country (with approximately 5.8 million people with diabetes currently living in Vietnam) [19,20], it is likely that the burden of chronic kidney disease and the costs associated will continue to rise exponentially [18]. The number of people with end-stage renal disease has been consistently increasing, with an annual tally of approximately 90,000 patients with end-stage renal disease [21]. However, there is limited evidence on the relationship between frailty and chronic kidney disease in older people in Vietnam. Therefore, this study aimed to examine the prevalence of frailty and the impact of frailty on mortality in older patients with end-stage renal disease receiving dialysis.
2. Materials and Methods
2.1. Study Design and Population
This is a prospective, observational, multi-centre study conducted at the Dialysis Centres of Trung Vuong Hospital and Thong Nhat Hospital in Ho Chi Minh City, Vietnam, from November 2020 to June 2021. The inclusion criteria included: (1) age ≥ 60 years and (2) diagnosis with end-stage renal disease and currently on haemodialysis. The exclusion criteria included: (1) dementia, (2) having mental illness or visual impairment that could affect their ability to answer the study questionnaires, (3) having acute illnesses that required admission, and (4) did not provide consent.
The study was approved by the Ethics Committees of the University of Medicine and Pharmacy at Ho Chi Minh City (Reference Number 788/2020/HDDD-DHYD, 2 November 2020). Informed consent was obtained from all participants.
2.2. Data Collection
Data were collected from patient medical records and patient interviews. The information obtained included demographic characteristics, height, weight, medical history, blood test results, and comorbidities. Frailty assessment was conducted by two investigators (TVN and TTXP) and any disputes were discussed and reconciled among them. All participants were followed up for 6 months after being included in the study.
2.3. Outcome Variables
All-cause mortality: Mortality data were obtained through medical records (for death during hospitalization) and by making phone calls to the contact numbers provided by the participants or their caregivers after 6 months. The date and causes of death were documented.
2.4. Predictive Variables
Frailty: The predictive variable of interest was frailty. Frailty was defined by the Clinical Frailty Scale (CFS) [22,23]. The CFS score ranges from 1–9, and a score of 4 or greater indicates a frailty status: [22,24].
CFS 1 (very fit): Robust, active, energetic, and motivated people. They are among the fittest for their age and tend to exercise regularly.
CFS 2 (fit): People who are less fit than category 1. They have no active disease symptoms. Often, they exercise or are very active occasionally.
CFS 3 (managing well): People whose medical problems are well controlled, even if occasionally symptomatic. However, they are not regularly active beyond routine walking.
CFS 4 (very mild frailty): Previously classified as “vulnerable”, this category marks the early transition from complete independence. While people in this category do not depend on others for daily help, often, symptoms limit their activities. A common complaint is being “slowed up” and/or being tired during the day.
CFS 5 (mild frailty): These people often have more evident slowing. They need help with high-order instrumental activities of daily living, such as transportation, heavy housework, and finances. Typically, mild frailty progressively impairs their ability to manage shopping and walking outside alone, meal preparation, and medications, and begins to restrict light housework.
CFS 6 (moderate frailty): People who need help with all outside activities and with keeping their house. They usually have problems with stairs and need help with bathing, and might need minimal assistance with dressing.
CFS 7 (severe frailty): People who are completely dependent in terms of personal care, from whatever cause (physical or cognitive). They seem stable and not at high risk of dying within 6 months.
CFS 8 (very severe frailty): Completely dependent for personal care and approaching end of life. Typically, they cannot recover, even from a minor illness.
CFS 9 (terminally ill): Approaching the end of life. This category applies to people with a life expectancy of less than 6 months, who are not otherwise living with severe frailty.
2.5. Covariates
Demographics and lifestyle factors. Age and sex were defined as recorded in medical records. The body mass index (BMI, kg/m2) was calculated based on the measured weight (kg) and height (m). Participants were classified into 4 groups: underweight (BMI < 18.5 kg/m2), normal (BMI 18.5–22.9 kg/m2), overweight (BMI 23.0–24.9 kg/m2), and obese (BMI ≥ 25.0 kg/m2). Educational status was obtained through interviews and included the following categories: illiterate, primary school, secondary school, high school, and higher education (college/university). Smoking status was defined based on self-report as non-smoking or smoking (including current smokers or ex-smokers who stopped smoking less than 1 year ago).
2.6. Comorbidities
Comorbidities were recorded based on a pre-defined list that included diabetes, dyslipidaemia, ischemic heart disease, heart failure, stroke, peripheral artery disease, anaemia, stomach problems, chronic pulmonary disease, chronic liver disease, and cancer. Anaemia was defined based on haemoglobin (Hb) levels of <12.0 g/dL in women and <13.0 g/dL in men, while other conditions were defined based on the medical records.
2.7. Statistical Analysis
Categorical variables are presented as percentages and frequencies. Continuous variables are presented as means and standard deviations. Participants were categorised into 4 groups according to their CFS score: Group 1—CFS ≤ 3 (non-frail), Group 2—CFS 4–5 (very mildly to mild frail), Group 3—CFS 6 (moderately frail), and Group 4—CFS ≥ 7 (severely to very severely frail). Comparisons among frailty groups were assessed using Chi-square tests (or Fisher’s exact tests) for categorical variables and Student’s t-tests for continuous variables. Two-tailed p-values of <0.05 were considered statistically significant.
To compare the time to death among the frailty groups, the Kaplan–Meier estimator was applied to generate survival curves in the 6-month follow-up period and differences between frailty groups were assessed using the log-rank tests. Cox proportional hazards regression was applied to examine whether frailty severity predicted mortality. The results are presented as the hazard ratio (HR) and 95% confidence interval (CI). The models were adjusted for other potential confounders that had a significant association with mortality through univariate analysis (with p < 0.05). All variables were checked for multicollinearity and interactions. Data analysis was conducted using SPSS for Windows 27.0 (IBM Corp., Armonk, NY, USA).
Sample size justification: Based on a systematic review and meta-analysis on the impact of frailty on mortality in patients with chronic kidney disease [8] and mortality rate in frail older patients in Vietnam [25], we estimated that at least 150 participants were needed to detect a significant difference in mortality between frail and non-frail patients (assuming a mortality rate of 5% in non-frail patients and a 4-fold increase in mortality in patients with frailty, at 80% power, 5% significance level, and 1-sided test).
3. Results
3.1. General Characteristics
During the study period, a total of 308 patients with chronic haemodialysis were admitted to the study centres and 210 of them met the inclusion criteria. Among these, 20 patients met the exclusion criteria and 15 refused to participate in the study. A total of 175 participants were included in this study. They had a mean age of 72.4 ± 8.5 years and 58.9% were female.
The participant characteristics are presented in Table 1. The most common comorbidities were anaemia (82.8%), followed by diabetes (62.9%), heart failure (60.0%), dyslipidaemia (58.9%), ischemic heart disease (49.7%), stroke (25.7%), stomach problems (24.0%), chronic liver disease (14.3%), chronic pulmonary disease (8.0%), cancer (4.0%), and peripheral artery disease (4.0%). Around a quarter of the participants were underweight, 48.0% had a normal body mass index, 10.3% were overweight, and 18.9% were obese. The mean duration of dialysis was 3.6 years.
Figure 1 presents the distribution of the CFS score among the study participants. The median CFS score was 5 (range from 3 to 8). Using the cut point of CFS ≥ 4, 87.4% of the participants were frail (38.3% were very mildly/mildly frail, 22.3% were moderately frail, and 26.9% were severely/very severely frail).
Compared with the non-frail participants (CFS ≤ 3), frailer participants were older (mean age 67.6 years in participants with CFS ≤ 3 versus 69.1 years in participants with CFS 4–5, 75.8 years in participants with CFS 6, and 76.5 years in participants with CFS ≥ 7, p-value < 0.001). The prevalence of underweightness increased across the frailty spectrum: 9.1% in participants with CFS ≤ 3, 13.4% in those with CFS 4–5, 25.6% in those with CFS 6, and 40.4% in those with CFS ≥ 7. Frailer participants had a higher burden of chronic diseases, particularly diabetes (80.9% in participants with CFS ≥ 7, 59.0% in participants with CFS 6, 55.2% in participants with CFS 4–5, and 54.5% in participants with CFS ≤ 3), heart failure (72.3% in participants with CFS ≥ 7, 66.7% in participants with CFS 6, 58.2% in participants with CFS 4–5, and 27.3% in participants with CFS ≤ 3), stroke (42.6% in participants with CFS ≥ 7, 20.5% in participants with CFS 6, 20.9% in participants with CFS 4–5, and 13.6% in participants with CFS ≤ 3), peripheral artery disease (10.6% in participants with CFS ≥ 7, 5.1% in participants with CFS 6, and 0% in those with CFS < 6), and cancer (10.6% in participants with CFS ≥ 7, 5.1% in participants with CFS 6, and 0% in those with CFS < 6) (Table 1).
3.2. Mortality Rate at the Sixth Month
After 6 months, 14.9% (26/175) of the participants died. The leading known cause of death was infection (53.8%), followed by acute myocardial infarction (7.7%) and strokes (7.7%).
Compared with the non-frail patients, participants in the frailer groups had higher mortality rates: 31.9% in participants with CFS score ≥ 7, 12.8% in participants with CFS = 6, 7.5% in participants with CFS score from 4 to 5, and 4.5% in participants with CFS score ≤ 3 (p = 0.001)
3.3. The Impact of Frailty on Mortality
Figure 2 presents the survival curves for all-cause mortality across the four frailty groups. The Kaplan–Meier survival function for mortality indicated that frailer participants had a higher probability of dying than the non-frail patients during the six-month follow-up (log rank Chi-square 18.07, 3df, p < 0.001, and Breslow Chi-square 19.16, 3df, p < 0.001). The p-value for comparisons between participants with CFS 4–5 versus those for participants with CFS ≤ 3 was 0.643, that for participants with CFS 6 versus participants with CFS ≤ 3 was 0.312, and that for participants with CFS ≥ 7 versus participants with CFS ≤ 3 was 0.036.
Univariate Cox regression analysis showed that, compared with the non-frail participants, the probability of mortality over 6 months was nearly two-fold higher in the mildly frail, three-fold higher in the moderately frail, and nine-fold higher in the severely frail participants. The association between frailty and mortality remained significant after adjusting for potential confounders (Table 2).
4. Discussion
In this study, in 175 older patients with end-stage renal disease and on chronic haemodialysis, the prevalence of frailty was very high (87.4%). We found that frailty independently predicted mortality in the 6 months after discharge in this population.
The participants’ characteristics in our study were similar to the characteristics of patients with chronic kidney disease reported in previous studies in Vietnam. In a cross-sectional study of 1175 patients (mean age 65) with chronic kidney disease in Ho Chi Minh City in 2019, approximately half of the participants with chronic kidney disease had diabetes or cardiovascular disease [26]. In a study published in 2022 on quality of life in Vietnamese patients on chronic dialysis (178 participants, median age 66), approximately 40% of the participants had diabetes and cardiovascular disease (including heart failure and ischemic heart disease) [21]. In that study, 98.3% of the participants had anaemia and 25.8% were underweight [21].
The prevalence of frailty in our study aligned with findings from international studies in older patients with chronic dialysis. A recent systematic review of 32 studies (n = 36,076, age range: 50–83 years) showed that the prevalence of frailty ranged from 7% in people with chronic kidney disease stages 1–4 to 73% in people on haemodialysis [10]. Other studies showed that frailty was present in 43% of patients with severe chronic kidney disease, 54% of pre-dialysis patients, and ranged from 30% to 82% among dialysis patients, depending on the study settings and frailty assessment tools [27]. In another meta-analysis by Mei and colleagues of 18 cohort studies with 22,788 participants, the median reported prevalence of frailty in people with chronic kidney disease was 41.8% (range 2.8–81.5%) and frailty increased mortality risk (pooled HR 1.48, 95% CI 1.21–1.81, p < 0.001). [8]
Several tools are available to screen for frailty in older adults. While the frailty phenotype and the frailty index were applied in most of the studies, the CFS has recently been increasingly used in patients with chronic kidney disease [10,27,28]. In a study conducted by Clark and colleagues in 564 patients with chronic dialysis, frailty was assessed by the CFS. The authors found that, compared with participants with CFS ≤ 3, those with CFS 4–5 had a 60% increased risk of readmission (HR 1.60, 95% CI 1.09–2.35), and those with CFS 6–7 had a 93% increased risk of readmission (HR 1.93, 95% CI 1.16–3.22) [29]. Yoshida and colleagues used the CFS to evaluate frailty in 310 patients aged 75 plus with chronic kidney disease who initiated dialysis, and found that frailty was present in 33.2% of the cohort, with the HR for mortality in frail participants versus non-frail participants being 1.59 (95% CI 1.10–2.58, p < 0.001) [30]. In fact, the CFS has been recommended for frailty screening programs within nephrology services, particularly in patients with advanced chronic kidney disease due to its accuracy in frailty screening [28].
Strengths and Limitations
To our best understanding, this is the first study in Vietnam to investigate frailty in older patients with end-stage renal disease and haemodialysis. The study was conducted at two large dialysis centres in Vietnam. However, our follow-up duration was only 6 months, and information on readmission and other important adverse events, such as falls, was not well documented. Further studies with larger sample sizes and longer follow-up periods are needed to understand the impact of frailty on adverse outcomes and quality of life in older patients with end-stage renal disease and dialysis. This study was designed and powered to detect a difference in mortality between frail versus non-frail patients. However, when conducting the analysis, frailty was categorized into four groups according to the CFS scores. Although the association between the CFS categories and mortality was found to be significant, the results should be taken with caution due to limitations in power. Another limitation is that information on the nutrition and physical activities of the participants was not collected, and the small sample size did not allow exploratory analysis to examine the predictive factors for frailty in this population. Further studies are needed to identify the risk factors for developing frailty in patients with chronic kidney disease in Vietnam. Understanding these risk factors is important in clinical practice, as it can help clinicians identify those patients at a higher risk of developing frailty, thus enabling early intervention to prevent or delay its onset.
In conclusion, this study demonstrated a very high prevalence of frailty in older patients with end-stage renal disease and dialysis and the significant impact of frailty severity on mortality. Our study highlights the need to screen for frailty in older patients with end-stage renal disease and dialysis. Screening for frailty in older patients with end-stage renal disease and dialysis has several implications for clinical practice. First, it can help to identify older patients who are at high risk of adverse outcomes, such as mortality, falls, and readmission. These high-risk patients can then be targeted for interventions aiming at improving their health outcomes, such as exercise programs, nutritional support, social support, and medication review. Second, frailty screening may help healthcare providers and patients to make shared decisions about treatment goals and preferences. More research is needed to determine the most effective interventions for frailty in this population.
Author Contributions
Conceptualization, T.V.N. and T.N.N.; Data curation, T.V.N. and T.T.X.P.; Formal analysis, T.V.N., T.T.X.P., M.J.B. and T.N.N.; Investigation, T.V.N., T.T.X.P. and T.N.N.; Methodology, T.V.N., T.T.X.P., M.J.B. and T.N.N.; Project administration, T.V.N. and T.T.X.P.; Resources, T.V.N. and T.T.X.P.; Software, T.V.N., T.T.X.P., M.J.B. and T.N.N.; Supervision, T.V.N.; Validation, T.V.N. and T.N.N.; Visualization, T.V.N., T.T.X.P., M.J.B. and T.N.N.; Writing—original draft, T.V.N., M.J.B. and T.N.N.; Writing—review and editing, T.V.N., T.T.X.P., M.J.B. and T.N.N. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of the University of Medicine and Pharmacy at Ho Chi Minh City (Reference Number 788/2020/HDDD-DHYD, date of approval 2 November 2020).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data presented in this study are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy and ethics concerns.
Conflicts of Interest
The authors have no competing interest to declare that are relevant to the content of this article.
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Figure 1.
Distribution of the clinical frailty scale in the study participants.
Figure 2.
The survival curves for all-cause mortality by frailty severity.
Table 1.
Participants’ general characteristics.
| Characteristics | All (n = 175) | CFS ≤ 3 (n = 22) | CFS 4–5 (n = 67) | CFS 6 (n = 39) | CFS ≥ 7 (n = 47) | p-Value |
|---|---|---|---|---|---|---|
| Age, years | 72.4 ± 8.5 | 67.6 ± 4.4 | 69.1 ± 7.7 | 75.8 ± 7.3 | 76.5 ± 9.0 | <0.001 |
| Female | 103 (58.9%) | 9 (40.9%) | 39 (58.2%) | 27 (69.2%) | 28 (59.6%) | 0.197 |
| Education | ||||||
| Illiterate | 6 (3.4%) | 1 (4.5%) | 2 (3.0%) | 3 (7.7%) | 0 | 0.328 |
| Primary school | 48 (27.4%) | 4 (18.2%) | 20 (29.9%) | 9 (23.1%) | 15 (31.9%) | |
| Secondary school | 43 (24.6%) | 2 (9.1%) | 16 (23.9%) | 9 (23.1%) | 16 (34.0%) | |
| High school | 41 (23.4%) | 7 (31.8%) | 15 (22.4%) | 10 (25.6%) | 9 (19.1%) | |
| Higher education | 37 (21.1%) | 8 (36.4%) | 14 (20.9%) | 8 (20.5%) | 7 (14.9%) | |
| Smoking | 50 (28.6%) | 9 (40.9%) | 19 (28.4%) | 7 (17.9%) | 15 (31.9%) | 0.255 |
| Body mass index | ||||||
| Underweight (<18.5) | 40 (22.9%) | 2 (9.1%) | 9 (13.4%) | 10 (25.6%) | 19 (40.4%) | 0.016 |
| Normal (18.5–22.9) | 84 (48%) | 14 (63.6%) | 36 (53.7%) | 16 (41.0%) | 18 (38.3%) | |
| Overweight (23.0–24.9) | 18 (10.3%) | 4 (18.2%) | 5 (7.5%) | 6 (15.4%) | 3 (6.4%) | |
| Obese (≥25.0) | 33 (18.9%) | 2 (9.1%) | 17 (25.4%) | 7 (17.9%) | 7 (14.9%) | |
| Duration of dialysis (years) | 3.6 ± 3.5 | 2.9 ± 3.5 | 4.2 ± 3.9 | 3.4 ± 2.6 | 3.4 ± 3.6 | 0.432 |
| Comorbidities | ||||||
| Anaemia | 144 (82.8%) | 16 (72.7%) | 55 (82.1%) | 32 (82.1%) | 41 (89.1%) | 0.408 |
| Diabetes | 110 (62.9%) | 12 (54.5%) | 37 (55.2%) | 23 (59.0%) | 38 (80.9%) | 0.028 |
| Heart failure | 105 (60.0%) | 6 (27.3%) | 39 (58.2%) | 26 (66.7%) | 34 (72.3%) | 0.003 |
| Dyslipidaemia | 103 (58.9%) | 14 (63.6%) | 33 (49.3%) | 26 (66.7%) | 30 (63.8%) | 0.238 |
| Ischemic heart disease | 87 (49.7%) | 8 (36.4%) | 30 (44.8%) | 18 (46.2%) | 31 (66.0%) | 0.061 |
| Stroke | 45 (25.7%) | 3 (13.6%) | 14 (20.9%) | 8 (20.5%) | 20 (42.6%) | 0.018 |
| Stomach problems | 42 (24.0%) | 7 (31.8%) | 14 (20.9%) | 8 (20.5%) | 13 (27.7%) | 0.638 |
| Chronic liver disease | 25 (14.3%) | 2 (9.1%) | 12 (17.9%) | 4 (10.3%) | 7 (14.9%) | 0.654 |
| Chronic pulmonary disease | 14 (8.0%) | 0 | 4 (6.0%) | 3 (7.7%) | 7 (14.9%) | 0.143 |
| Cancer | 7 (4.0%) | 0 | 0 | 2 (5.1%) | 5 (10.6%) | 0.020 |
| Peripheral artery disease | 7 (4.0%) | 0 | 0 | 2 (5.1%) | 5 (10.6%) | 0.020 |
Continuous data are presented as means ± standard deviations. Categorical data are shown as n (%).
Table 2.
Hazard ratios of frailty and other predictive variables for all-cause mortality.
| Variables | Unadjusted HRs for All-Cause Mortality (95% CI) | p-Values | Adjusted HRs for All-Cause Mortality (95% CI) | p-Values |
|---|---|---|---|---|
| Frailty severity | ||||
| CFS ≤ 3 (reference) | 1 | 1 | ||
| CFS 4–5 | 1.66 (0.19–14.23) | 1.72 (0.20–14.93) | ||
| CFS 6 | 3.03 (0.35–25.91) | 0.002 | 2.81 (0.30–26.29) | 0.029 |
| CFS ≥ 7 | 8.70 (1.15–65.90) | 6.99 (0.84–58.44) | ||
| Age (years) | 1.08 (1.03–1.13) | 0.002 | 1.03 (0.98–1.08) | 0.300 |
| Male (versus Female) | 2.35 (1.07–5.19) | 0.034 | 2.10 (0.90–4.91) | 0.087 |
| Body mass index | 0.073 | - | ||
| Underweight (reference) | 1 | |||
| Normal | 0.44 (0.19–1.01) | |||
| Overweight | 0.36 (0.08–1.64) | |||
| Obese | 1.94 (0.04–0.88) | |||
| Duration of dialysis (years) | 0.95 (0.83–1.07) | 0.375 | - | |
| Comorbidities | ||||
| Anaemia | 2.50 (0.59–10.62) | 0.213 | - | |
| Diabetes | 1.35 (0.59–3.11) | 0.478 | - | |
| Heart failure | 2.39 (0.96–5.96) | 0.061 | - | |
| Dyslipidaemia | 1.15 (0.52–2.53) | 0.733 | - | |
| Ischemic heart disease | 2.44 (1.06–5.61) | 0.036 | 1.37 (0.56–3.40) | 0.492 |
| Stroke | 1.06 (0.45–2.52) | 0.894 | - | |
| Stomach problems | 1.76 (0.79–3.96) | 0.168 | - | |
| Chronic liver disease | 0.47 (0.11–2.01) | 0.311 | - | |
| Chronic pulmonary disease | 1.56 (0.47–5.19) | 0.470 | - | |
| Cancer | 2.18 (0.51–9.21) | 0.291 | - | |
| Peripheral artery disease | 2.18 (0.51–9.21) | 0.291 | - |
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MDPI and ACS Style
Nguyen, T.V.; Pham, T.T.X.; Burns, M.J.; Nguyen, T.N. Frailty in Older Patients with End-Stage Renal Disease and Undergoing Chronic Haemodialysis in Vietnam. Diabetology 2023, 4, 312-322. https://doi.org/10.3390/diabetology4030027
AMA Style
Nguyen TV, Pham TTX, Burns MJ, Nguyen TN. Frailty in Older Patients with End-Stage Renal Disease and Undergoing Chronic Haemodialysis in Vietnam. Diabetology. 2023; 4(3):312-322. https://doi.org/10.3390/diabetology4030027
Chicago/Turabian StyleNguyen, Tan Van, Thu Thi Xuan Pham, Mason Jenner Burns, and Tu Ngoc Nguyen. 2023. "Frailty in Older Patients with End-Stage Renal Disease and Undergoing Chronic Haemodialysis in Vietnam" Diabetology 4, no. 3: 312-322. https://doi.org/10.3390/diabetology4030027
