Quality Of Life In Patients With Pre-Dialysis Chronic Kidney Disease .

https://doi.org/10.33698/NRF0220- Lasara Kharbteng ,Monaloza, Sukhpal Kaur, Sandhya Ghai

Abstract : Introduction :Quality of life (QOL) is an important, yet neglected aspect of Chronic Kidney Disease (CKD) care. They may have suboptimal quality of life. Objective : To assess the quality of life in patients with pre-dialysis Chronic Kidney Disease. Methodology : A descriptive design was used. Consequently, sixty subjects were recruited from Nephrology outpatient department, PGIMER, Chandigarh. The quality of life was assessed by interviewing them using Kidney Disease and Quality of Life questionnaire (KDQOLTM-36). Resutls: Results showed that majority of the subjects had low scores on most of domains of quality of life, mainly burden of kidney disease, physical and mental health composite with mean scores of 51.14, 40.72 and 40.93 respectively. Higher scores were observed in the subscale- symptom/problem list and effects of kidney disease with mean scores of 81.59 and 87.29 respectively. The present study revealed that CKD patients have impaired QOL. Mostly affected domains are burden of kidney disease, physical and mental health composite.

Keywords

Quality of life, Chronic Kidney Disease

Correspondence at

Monaliza

Lecturer

National Institute of Nursing Education (NINE), PGIMER, Chandigarh

Introduction

Chronic Kidney Disease (CKD) is a rapidly growing health problem with high rate of morbidity and mortality. The prognosis is generally poor with worsening of physical functioning leading to psychological distress.1 The estimated prevalence of CKD (Stage 1-4) globally is 7.2% in individuals over 30 years of age.2 It is a major cause of poor health outcome of non– communicable diseases and affects 5% to 8% of world’s population.3 The approximate prevalence of CKD is 800 per million population.4 CKD is the 12th cause of death and 17th cause of disability in the world.5 Hypertension, diabetes mellitus, interstitial nephritis, glomerulopathies, polycystic kidney disease, hereditary renal disease, obstruction, repeated episodes of pyelonephritis, developmental or congenital disorder are all contributory factors leading to CKD.6 In CKD, there is destruction and deterioration of nephrons with declining renal functions. Serum creatinine and urea nitrogen levels increase as the total Glomerular Filtration Rate (GFR) and clearance is reduced. As a result, uremia develops affecting every system in the body which in turn affects quality of life to a great extent.7,8

Health related quality of life (HRQOL) is an important and unique dimension of chronic disease care and can be measured by a reliable, valid tool. The Kidney Disease Quality of Life -36TM is a kidney disease specific measure of HRQOL which focuses on particular health- related concerns of individual with kidney disease.9 The assessment of quality of life in CKD patients are helpful in knowing the impact it has on their life. Quality of life is affected to a great extent. There is minimal literature on QOL in CKD patients from low and middle-income countries, including India. A few issues unique to the developing world which could potentially affect the QOL include age, economic status, literacy level, loss of employment, and gender bias.10 The current study intends to assess the QOL in pre- dialysis CKD patients.

Materials and Methods

A descriptive study was carried out in patients with Chronic Kidney Disease (Pre- dialysis) attending Nephrology outpatient department, PGIMER, Chandigarh. CKD patients between the age group of 18-65yrs and who have clinically stable course for last 1 month were included in the study. Patients on dialysis, pregnant or lactating females were excluded from the study. 60 patients were enrolled consequently. Quality of life was assessed by using KDQOLTM-36 which is a standardized tool. It is a public document available without charge. It is a kidney disease-specific measure of health related quality of life (HRQOL). This instrument consists of 36 items or questions, divided in two components: one general component, including 12 quality of life questions based on the SF-12 (short version of the SF-36), and a specific 24- question component about the kidney disease. At the same time, each item or question is regrouped in five subscales or domains, where the general component groups the SF-12 subscale Physical health composite (questions 1-12) and SF-12 subscale Mental health composite (questions 1-12); while the specific component groups the subscales Burden of Kidney Disease (questions 13- 16), Symptoms and Problems (questions 17-28) and Effects of Kidney Disease on Daily Life (questions 29-36).

Scores of the different subscales were calculated according to Kidney Disease Quality Of Life (KDQOLTM-36) scoring program. Raw pre-coded numeric values for each item were transformed linearly toa0 to 100 range, with higher scores reflecting better quality of life. Item scores range from 0 to 100, with 0 indicating the worst and 100 the best quality of life. Each item was put ona0 to 100 range so that the lowest and highest possible scores are set at 0 and 100, respectively. Scores represent the percentage of total possible score achieved. It includes averaging items in each scale together.

Data was collected from Nephrology OPD, PGIMER, Chandigarh. Subjects who met the inclusion criteria were enrolled in the study from July – October, 2016 by total enumeration technique. Ethical clearance for the study was obtained from the Institution Ethical Committee. Written informed consent was taken from the study subjects. The subjects were assured of the confidentiality of the information. Subjects were interviewed using proforma containing socio demographic variables and clinical profile. Quality of life was assessed by using KDQOLTM-36. Analysis was done for the 60 subjects who were enrolled in the study. The data collected was entered in Statistical Package for Social Sciences (SPSS) version 20 for descriptive and inferential analysis. In descriptive statistics, percentage, mean, standard deviation and range were used to describe the data. In inferential statistics, t- test and ANOVA were used. secondary level and 18.3% were graduate. Out of total subjects, 35% were housewives, 20% were professional, 20% were unskilled worker, 11.7% were retired and 6.7% were skilled workers. Majority of study subjects were residing in urban areas (78.3%). Most of the subjects were CKD stage 3 (76.7%). Hypertension was present in 45.4% followed by diabetes (21.6%). The mean age± SD of the subjects was 51.9±8.7 years. The mean per capita income ±SD of the subjects was Rs 3920.95±3775.9. The mean duration of illness (years) ± SD of the subjects was 3.48±2.76 years. The mean eGFR, Hb and creatinine values were 35.07 ml/min/1.73m2, 12.18 gm/dL and 2.04 mg/dL respectively.

Quality of life of the subjects as per KDQOLTM -36 (Table 1)

Table 1 depicts the quality of life of the subjects as per KDQOLTM -36 score. Majority of the subjects had low scores on most domains of quality of life, mainly burden of kidney disease, physical and mental health composite with mean scores of 51.14, 40.72 and 40.93 respectively. Higher scores were obser ved in the subscale- symptom/problem list and effects of kidney disease with mean scores of 81.59 and 87.29 respectively. A high percentage of subjects scoring below the reference value,

Results

i.e., ≤ 50 was found in three of the five In socio-demographic profile of the subjects (N=60), 60% of the subjects were males and 40% were females. More than 50% of the subjects belongs to Hindu religion. 98.3% were married. 13.3% were illiterate, 13.3% were educated up to primary level, 55% were educated up to KDQOLTM-36 subscales i.e., burden of kidney disease, SF-Physical health composite and SF-Mental health composite. High percentage of subjects scoring above 50 was found in the subscales- symptom/problem list and effects of kidney disease.

Table 2 : Quality of life of the subjects as per KDQOL -36TM

(N=60)

Scale( Items in scale)	Mean± SD (Range)	% people score ≤ 50	% people score >50
Symptom/problem list : Soreness Chest pain Cramps Itchy skin Dry skin Shortness of breath Faintness or dizziness Lack of appetite Washed out or drained Numbness in hands or feet Nausea or upset stomach	81.59 ±16.47 (25-100)	8.3%	91.7%
Effects of kidney disease Fluid limitation Dietary restriction Ability to work at home Ability to travel Dependence on medical staff Stress or worries Sex life Personal appearance	87.29 ±13.50 (43.75-100)	3.3%	96.7%
Burden of kidney disease Interference with life Time spent dealing with disease Frustration Burden on family	51.14 ± 31.03 (0-100)	50%	50%
SF-12 Physical Health Composite General health rating Moderate activities Climbing several stairs Accomplished less (physical cause) Limited in kind of work Pain	40.72 ± 7.94 (19.04-57.66)	91.7%	8.3%
SF-12 Mental Health Composite Accomplished less (emotional cause) Works carefully Calm and peaceful Energy Downhearted and blue Social activities	40.93 ± 8.49 (19.97-58.73)	85%	15%

Correlation between sociodemographic, clinical profile, laboratory parameters and KDQOLTM -36 (Table 2)

Table 2 depicts correlation between sociodemographic, clinical profile, laboratory parameters and KDQOLTM -36. A significant correlation was found between per capita income and quality of life in the subscale SF-12 physical health composite (p value=0.03). Haemoglobin was also significantly associated with quality of life in the subscale SF-12 physical health composite (p value=0.05). This explained that with higher per capita income, there is an increased or improvement in physical health composite and also with higher level of haemoglobin, there is an increased or improvement in physical health composite.

Table 2: Correlation between sociodemographic, clinical profile, laboratory parameters and KDQOLTM -36    (N=60)

Variables	KDQOL TM -36
	Symptoms and problems	Effects of the kidney disease	Burden of the kidney disease	SF-12 Physical health composite	SF-12 Mental health composite
	r (P value)	r (P value)	r (P value)	r (P value)	r (P value)
Socio demographic
Age	0.05(0.66)	-0.16(0.37)	0.01(0.89)	0.14(0.26)	0.001(0.99)
Per capita income	0.12(0.36)	0.04(0.74)	0.08(0.49)	0.27(0.03)	0.01(0.89)
Clinical profile and
laboratory parameter
Creatinine	0.07(0.56)	0.03(0.82)	-0.06(0.61)	-0.03(0.79)	0.03(0.79)
Urea	-0.02(0.89)	0.14(0.33)	0.06(0.69)	-0.15(0.31)	-0.18(0.21)
Haemoglobin	0.02(0.83)	0.01(0.92)	-0.01(0.93)	0.25(0.05)	0.08(0.53)
eGFR level	0.05(0.67)	0.06(0.60)	0.09(0.49)	0.18(0.16)	0.01(0.88)

(r) Pearson’s correlation significant at 0.05

Association between mean values of socio demographic, clinical profile and laboratory parameter and KDQOLTM-36 subscales (Table 3)

Only few quality of life subscales were related with sociodemographic variables, i.e., gender, religion, habitat and educational level with significant differences in mean values. Gender was associated with the subscale symptoms/ problems where mean score in males and females were 86.36 and 74.43 respectively (p=0.005). Gender was also associated with the subscale SF-12 physical health composite where mean score in males and females were 42.65 and 37.83 respectively (p=0.02). Quality of life in males was better than females. Association was also found  between religion and subscale SF-12 mental health composite where mean score in Hindu and other religion was 42.60 and 37.82 respectively (p=0.03). Habitat was also associated with subscale effects of the kidney disease where mean score in rural and urban was 79.56 and 89.43 respectively (p=0.01). People residing in urban have better quality of life than those residing in rural. There was significant association between educational level with subscale SF-12 mental health composite where mean scores in the educational level- illiterate, primary, secondary and graduate or above were 34.35, 40.09, 41.30 and 45.23 respectively (p=0.04). This showed that people with higher educational level have better quality of life than those with lower educational level.

Table 4: Association between mean values of sociodemographic, clinical profile and laboratory parameter and KDQOLTM36 subscales

(N=60)

Mean score of KDQOLTM36
Socio demographic variables	N	Symptoms and problems (t test/ ANOVA, p value)	Effects of the kidney disease (t test/ ANOVA, p value)	Burden of kidney disease (t test/ ANOVA, p value)	SF-12 Physical health composite (t test/ANOVA, p value)	SF-12 Mental health composite (t test/ ANOVA, p value)
Gender*
Male	36	86.36	88.45	55.03	42.65	41.74
Female	24	74.43	85.54	45.31	37.83	39.72
		(2.91, 0.005)	(0.81, 0.41)	(1.19, 0.23)	(2.39, 0.02)	(0.90, 0.37)
Religion*
Hindu	39	81.06	87.10	47.43	41.01	42.60
Others (Muslim,	21	82.57	87.65	58.03	40.19	37.82
Buddhism)		(-0.33, 0.73)	(-0.14, 0.88)	(-1.26, 0.21)	(0.37, 0.70)	(2.14, 0.03)
Marital status*
Ever married	57	81.14	87.06	50.10	40.49	41.06
Never married	3	90.15	91.66	70.83	45.04	38.46
		(-0.33, 0.73)	(-0.57, 0.56)	(-1.13, 0.26)	(-0.96, 0.33)	(0.51, 0.69)
Habitat*
Rural	13	80.24	79.56	43.26	40.14	42.29
Urban	47	81.96	89.43	53.32	40.88	40.55
		(-0.33, 0.74)	(2.42, 0.01)	(-1.03, 0.30)	(-0.29, 0.77)	(0.65, 0.51)
Educational status#
Illiterate	8	78.97	90.62	49.21	36.30	34.35
Primary	8	75.28	80.08	46.87	40.98	40.09
Secondary	33	81.47	86.83	48.10	40.82	41.30
Graduate or above	11	88.43	91.47	64.77	43.46	45.23
		(1.09, 0.35)	(1.30, 0.28)	(0.86, 0.46)	(1.28, 0.28)	(2.82, 0.04)
Occupation #
Professional	12	81.06	90.36	56.77	43.99	40.09
Skilled worker	7	85.79	95.31	62.50	42.44	42.26
Unskilled worker	12	84.84	86.20	46.35	39.15	38.76
Housewife	21	75.75	83.78	45.53	37.37	41.37
Retired	7	83.11	82.59	48.21	44.05	42.51
0thers (unemployed,	4	97.15	100.00	71.87	45.69	43.53
student)		(1.45, 0.22)	(1.67, 0.15)	(0.73, 0.60)	(1.99, 0.09)	(0.31, 0.90)
CKD stage*
Stage 3	46	81.37	86.61	49.59	40.69	40.70
Stage 4	14	82.30	89.51	56.25	40.84	41.69
		(-0.18, 0.85)	(-0.69, 0.48)	(-0.77, 0.48)	(-0.06, 0.95)	(-0.37, 0.70)
Any comorbidities*
Yes	43	80.92	86.55	50.58	40.94	41.36
No	17	83.28	89.15	52.57	40.18	39.85
		(-0.49, 0.62)	(-0.66, 0.50)	(-0.22, 0.82)	(0.33, 0.74)	(0.61, 0.54)

*- Student’s t-test #- ANOVA

Discussion

Quality of life is affected to a great extent in CKD patients. The assessment of quality of life in CKD patients are helpful in knowing the impact it has on their life. The Kidney Disease Quality of Life -36TM is a kidney disease specific measure of HRQOL which focuses on particular health- related concerns of individual with kidney disease and is therefore used in this study as the study population consists of CKD patients.

Concerning QOL, a high percentage of subjects scoring below the reference value, i.e., ≤ 50 was found in three of the five KDQOLTM-36 subscales i.e., burden of kidney disease, SF-Physical health composite and SF-Mental health composite which was similar to a study reported by Guerrero VG et al in which the burden of kidney disease, SF-Physical health composite and SF-Mental health composite subscales were the most affected domains. 11 The mean quality of life scores of the different subscales are as follows : Symptom/problem list was 81.59, effects of kidney disease was 87.29, burden of kidney disease was 51.14, SF-12 Physical Health Composite was 40.93 and SF-12 Mental Health Composite was 40.72.

In present study, association was found between various variables and quality of life. Men showed better quality of life than women with significant differences in the symptom/problem list and physical health composite . These findings were supported by a study conducted by Fukushima on quality of life and associated factors in patients with CKD on hemodialysis showed that men presented better quality of life than women with significant differences in the symptoms/problems, sexual functioning, pain, general health, emotional function, energy and fatigue and mental component. People belonging to Hindu religion presented a better quality of life in mental health composite. Regarding per capita income, respondents with a higher income showed a better quality of life in the subscales burden of kidney disease, sleep, energy and fatigue. Another study conducted on quality of life with chronic hemodialysis showed that men scored better than women on the symptoms, effects and mental functioning subscales. A study by Morgado supports the present study findings which showed that age, gender and haemoglobin were the variables related with quality of life.12,13

People living in urban area scored better on the effects of kidney disease subscale than those living in rural area. This is supported by a study conducted on quality of life with chronic hemodialysis showed that people living in rural areas scored lower on the disease burden subscale than people living in urban areas. This may probably be due to the distances that people need to travel from their place of residence. The need for a companion and transportation times can act as negative factors in the perceived quality of life.14

A positive correlation was found between per capita income and physical health composite. The higher the income, better is physical health composite. Higher income may allow better social support. Moreover, ability to perform work is limited by CKD. And the increase costs related to the disease also explains the worst QOL in patients with a lower income. Patients with low income depend on public transportation for travelling to health care units which is not always reliable, and this causes fatigue and stress. In addition, the consequent of development of comorbidities impact quality of life. A study by Cruz supports the finding.10

A positive correlation was found between educational status and mental health composite. Better mental health composite was presented in individuals with higher educational status which was in contrast to a study by Cruz which showed that individuals with higher educational status presented higher physical component summary values.10 Regarding haemoglobin, a positive correlation was found with physical health composite. Higher levels was associated with better quality of life. Haemoglobin is the primary transporter of oxygen from lungs to the body tissues. Low haemoglobin can lead to fatigue and this decreases the performance of physical activity. People with low haemoglobin cannot perform normal functions in an optimal way. A study by Morgado supports the present study findings.13

The present study revealed that CKD patients have impaired QOL. Mostly affected domains are burden of kidney disease, physical and mental health composite. Limitation of the study is that generalization cannot be made from the findings out of the small study sample. Recommendation: Comparative studies to evaluate the quality of life between pre-dialysis and dialysis patients can be studied. The knowledge, attitude and practice of nurses in improving quality of life in CKD patients can be studied.

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