Demographic profile, spectrum, awareness, and cost of renal replacement therapy of chronic kidney disease patients in a public tertiary care center in Rajasthan, India

INTRODUCTION

Chronic kidney disease (CKD) is extremely common and has emerged as one of the leading non-communicable causes of death worldwide. It is projected to affect an increasing number of individuals over time and to further rise in importance among the various global causes of death.^[1] CKD contributes toward cardiovascular disease and increases mortality with a disproportionately large fraction of available healthcare resources burden.^[2,3] In India, several factors contribute to the high prevalence of CKD, such as consanguinity, increased congenital anomalies, deficiency or hypovitaminosis A, or malnutrition with poverty exposed to known and unknown nephrotoxin during pregnancy leading to small kidney volume at birth. Added to these exposures is the growing burden of hypertension and diabetes mellitus. By 2030, India is expected to have the world’s largest population of patients with diabetes.^[4-8]

Baseline characteristics of CKD patients in developing countries are lacking, especially in India which is a very heterogeneous country from social, cultural, economic, genetic, and climate and geography perspectives. More detailed, in-depth analysis will better understand factors such as age, ethnicity, level of development, and poverty in different regions on CKD causes and burden. This study was conducted to know how underlying demography, cost, and choice of renal replacement therapy (RRT) options for CKD prevalent in patients attending public tertiary care center in Rajasthan, India.

MATERIALS AND METHODS

It was an observational study that included a total of 252 CKD patients. These included patients who were on conservative treatment, on dialysis, and those who received renal transplantation. Patients who were attending the nephrology outpatient department from January 2020 to December 2020 were included in the study. During this period, CKD based on the kidney disease improving global outcome (KDIGO) was included in the study.^[9] All the patients were evaluated based on history taking, clinical examination, and laboratory investigations. Staging of CKD was done based on the KDIGO staging system. Glomerular filtration rate was estimated using CKD-EPI (creatinine) formula.^[9]

RESULTS

Demographic profile, CKD-cause, stage, and awareness of RRT

A total of 252 patients were included in the study. The mean age of the patients was 47.20 ± 15.53 years, and 70.23% were male. The body mass index (BMI) of the study population was 21.70 ± 4.67 kg/m². Jaipur was the predominant draining district, followed by Alwar. Around 30% of the population neither read nor write, 17% studied up to the eighth standard, 14.68% were graduates or had an equivalent degree, and 7.14% were studied above it. Agriculturists and laborers comprise around one-third of the patients, followed by self-employed people or those running their businesses; most females were housewives (64%).

The predominant cause was hypertension, followed by CGN and diabetes, consisting of 29.37%, 21.43%, and 15.87%, respectively. Nephrolithiasis and its complications were the predominant cause of CTIN. Around 14.68% were CKD of unknown origin, and 7.14% were genetic/adult polycystic kidney disease (ADPKD) patients. Diabetes was more common in the elderly, and CGN was more frequent in the young [Figure 1]. Diabetes was more frequent in patients with high income than CKD (u), seen in the low-income group. The majority of our patients were in the advanced stage of CKD. More than 50% were in stage V, 33.73% were on dialysis, 7.14% were on PD. CKD Stages I, II, and III were unaware of the RRT or its option. In Stage IV, only 4.4% were aware, and in Stage V, 17% of the patients were aware of the RRT and its option.

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Figure 1:

Bar diagram showing cause of CKD in different Age groups. Age groups between 18 and 40 years were the predominant population in our study (40.08%). DM is the most common cause of CKD in >60 years and CGN is most frequent in young ages (18–40 years). CKD: Chronic kidney disease, HTN: Hypertension, DM: Diabetes mellitus, CGN: Chronic glomerulonephritis, CTIN: Chronic tubule-interstitial Nephritis, CKD (u): CKD of unknown etiology.

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DISCUSSION

Rajasthan is the largest state in the Indian Union; however, the representation of CKD data is lacking. Two studies, Seek-India and Indian CKD (ICKD), published basic demographic details of CKD, its prevalence, and pattern in India except in Rajasthan.^[8,13] This is the only study from the state highlighting basic CKD details. Our study population was younger and more undernourished compared to the ICKD study population (47.20 ± 15.53 years. vs. 50.3 ± 11.8 years) and 21.70 ± 4.67 kg/m² vs. 24.4kg/m².^[8] Our state, which has a rural-dominated population (75.1%), had equal representation of the rural and urban populations in our study. This might be a referral bias as data collection was from the urban public tertiary care center, and most patients were in advanced CKD.^[14] Moreover, around half of the CKD patients in our study were from the capital city and countryside, likely due to our center’s free dialysis facilities. Among the CKD population, 47.62% had attended less than high school compared to the SEEK-India study; only 37.6% had less than high school. Younger population, more under-nutrition, poor education status, and more advanced CKD in our study population compared to the ICKD study population.

One interesting and surprising finding was the cause of CKD in our study population. In the ICKD study, which included a pan-India CKD population, diabetes was the most common cause of CKD, followed by CTIN and CKD of unknown origin. However, in our study, hypertension was the most common cause of CKD, followed by CGN and diabetes. One fundamental difference in our study was that it is a single-center study and contains a younger, advanced CKD population from a more compromised socioeconomic status. In our study, the highest age distribution was between 18 and 40 years, and it is well highlighted that as age increases, diabetes, a cause of CKD, increases [Figure 1]. Even the prevalence of diabetes has a strong correlation with per capita income and BMI and our population had low BMI compared to ICKD population. Moreover, our study population was younger and belonged to the lower socioeconomic status, and all these factors are associated with a decreased prevalence of diabetes.^[8,15] On the flip side, younger population in our study explains the high prevalence of CGN as a cause of CKD [Figure 1]. Hence, rather than unifying the causes of CKD, different age groups, socioeconomic status, and geographic distribution are likely to have an impact on CKD causation.

The cost of treatment increases as the stage of CKD increases. In our study, CKD Stage II direct monthly cost was Rs. 2435.71 (Rs. 29,228.52 annually), which increased to Rs. 4815.96 (Rs. 57,791.52 annually) at stage V. Similar trend was seen in a study by Ahlawat et al.^[16] However, there is a sharp jump in the cost of treatment in CAPD compared to HD. This is due to free HD to all ESRD patients in the state. Interestingly, this difference is lost when we compare the cost of CAPD and HD with those of Insurance. Similar results were seen in another Indian study by Jeloka et al., where the cost of treatment between CAPD and HD in self-paying patients was not different.^[17] Due to free access to HD, most of the patients in Stage V and on HD were of BSSY or who had no financial support [Table 2]. A similar trend was also reflected in renal transplants. However, CAPD was only opted by those who had insurance.

In addition, our study showed a significant difference in rural and urban CKD populations. The rural CKD patients had poor education and were predominantly agriculturists and laborers. CKD (u) is more seen in rural populations than in urban. They were more financially weak and had low family income. The financial support was in the form of BPL or BSSY cards. On the other hand, urban CKD patients were better educated, self-employed, and had higher family incomes. Diabetes and hypertension were more frequent in the urban population. Urban patients were financially more self-dependent and had more insurance cover compare to rural patients. Financial support, either in the form of a BSSY card, free dialysis, or Insurance, impacts decision to select the mode of RRT in our study [Table 2].

Our study is the first such attempt to highlight the basic information on CKD in the state. However, there are many limitations that need to be highlighted. First, this was a single-center-based study which might not reflect an accurate picture of CKD at the community level. Second, our study population reflects more advanced CKD, which is reflected in a high proportion of Stage V and HD patients due to the availability of free dialysis at our center. Third, as most patients were from weaker sections of society, this spectrum might not be reflected in patients attending corporate hospitals or center-based screening of CKD. Fourth, though this study hints toward variation in causes of CKD depending on social, economic, nutritional, and geographical location, generalization of information from this study on community-based CKD or non-public sector health care will not be justifiable. Fifth, the cost of medicines and RRT under various government schemes cannot be generalized to all patients. In addition to population differences, variability in practice patterns and access to healthcare services may be responsible for other additional differences.

CONCLUSION

Our study highlighted that different factors such as age, socioeconomic status, and geographic distribution have an impact on the causes of CKD. Age and financial support, either in the form of insurance or government policies, have an important impact on RRT selection.