Sanjay Kalra ( Department of Endocrinology,Bharti Hospital, Karnal )
Karthik Balachandran ( Department of Endocrinology, Billroth Hospitals, Chennai )
Ambady Ramachandran ( Dr. A. Ramachandran\'s Diabetes Hospitals, Chennai, India )
Chronic kidney disease (CKD) is a major cause of morbidity across the globe. The prevalence of CKD is rising rapidly, especially in low income and middle income countries.1 To manage this epidemic, timely screening and diagnosis is required. To do so, one needs simple and economical tools, which must also be accurate and reliable. The diagnosis of CKD can be based upon the estimation of eGFR (estimated-glomerular filtration rate) and proteinuria.2 The accepted staging of CKD, however, relies upon eGFR determination.3 Various methods of eGFR calculation are available, including the Cockcroft-Gault equation, MDRD (Modification of Diet in Renal Disease) Study equation, and the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation.4 The CKD- EPI equation4 is considered reliable, especially at GFR levels >60ml/min/1.73m2. The 2009 CKD-EPI creatinine equation is more accurate in estimating GFR and prognosis than the 2006 MDRD (Modification of Diet in Renal Disease) Study equation, and provides lower estimates of prevalence of decreased eGFR. It is a useful screening test, and should supersede the MDRD Study equation in practice. The 2012 CKD-EPI cystatin C equation is as accurate as the 2009 CKD-EPI creatinine equation in estimating GFR, does not require specification of race, and may be more accurate in patients with decreased muscle mass. The 2012 CKD-EPI creatinine-cystatin C equation is the most accurate, and serves to confirm decreased eGFR as determined by serum creatinine-based eGFR. There are certain limitations to the use of CKD-EPI, including the impact of ethnicity on GFR estimation. Various proposals, including one to use a two-level ethnicity equation,5 have been proposed. The limitation regarding ethnicity has not prevented South Asian researchers from using CKD-EPI in their studies, however large trials from India6 and Bangladesh7 have measured GFR by CKD-EPI to determine the prevalence of CKD in their countries. Colleagues from Karachi, Pakistan (Jessani et al) have gone one step ahead in this regard.8 In a cross-sectional population-based setting, 581 participants 40 years or older were enrolled from 10 randomly selected communities and renal clinics in Karachi. The aim was to assess the performance of existing GFR estimating equations in South Asians, and modify the existing equations or develop a new equation for use in this population. Bias (the median difference between measured GFR [mGFR] and eGFR), precision (the IQR of the difference), accuracy (P30; percentage of participants with eGFR within 30% of mGFR), and the root mean squared error were reported as cross-validated estimates along with bootstrapped 95% CIs based on 1,000 replications. The CKD-EPI creatinine equation performed better than the MDRD Study equation in the Karachi cohort. It showed higher accuracy at P30 (76.1% [95% CI, 72.7%-79.5%] vs 68.0% [95% CI, 64.3%-71.7%]; P < 0.001) and greater precision (IQR, 22.6 [95% CI, 19.9-25.3] vs 28.6 [95% CI, 25.8-31.5] mL/min/1.73 m2; P < 0.001). However, both equations overestimated mGFR. Applying modification factors for slope and intercept to the CKD-EPI equation to create a CKD-EPI Pakistan equation (such that eGFR [CKD-EPI (PK)] = 0.686 × eGFR [CKD-EPI] to the power 1.059) eliminated bias and improved accuracy (P30, 81.6% [95% CI, 78.4%-84.8%]; P < 0.001). The authors concluded that while the CKD-EPI creatinine equation is more accurate and precise than the MDRD Study equation in estimating GFR in South Asians, the CKD-EPI Pakistan equation further improves the performance of the CKD-EPI equation in this population, and may be used to calculate eGFR.
The same team9 followed this publication with a much larger cross-sectional study on 2873 participants aged >40 years in 12 representative communities in Karachi, Pakistan. Using the CKD EPI Pakistan equation, they found an overall prevalence (95% CI) of CKD of 12.5% (11.4 - 13.8%). The factors independently associated with CKD were older age, hypertension, and diabetes, elevated systolic blood pressure, and raised fasting plasma glucose, raised triglycerides, and history of stroke (p <0.05 for each). These findings are similar to those seen across other South Asian countries. While the publications of Jessani et al have found respect and recognition globally, they seem to have been ignored at home. This is probably because of a lack of awareness of CKD epidemic, even in allied specialties such as endocrinology and cardiology. It must be noted, though, that a few recent articles from India and China refer to the CKD-EPI Pakistan equation.10,11 Eminent researchers in India (A Ramachandran) have been popularizing the Pakistani equation in their talks. This trend is welcome, as the utility of Jessani et al\\\'s seminal work extends far beyond the boundaries of Karachi and Pakistan. The simple equation they have derived holds the ability to provide more accurate GFR determination, CKD screening and diagnosis, and thus CKD management and prevention. Its values adhere to the concept of quaternary prevention12 which enjoins us to avoid over diagnosis and overlabelling of medical conditions. To fulfil its potential, though, the Pakistani equation needs to be studied and validated in neighbouring countries of South Asia, and South Asian migrant populations abroad. If this is done, the pioneering work from Karachi will truly prove to be a milestone in South Asian health.
1. Stanifer JW, Muiru A, Jafar TH, Patel UD. Chronic kidney disease in low-and middle-income countries. Nephrol Dial Transplant. 2016; 31: 868-74.
2. Stevens LA, Levey AS. Current status and future perspectives for CKD testing. Am J Kid Dis. 2009; 53: S17-26.
3. Levey AS, Inker LA, Coresh J. GFR estimation: from physiology to public health. Am J Kid Dis. 2014; 63: 820-34.
4. CKD-EPI Adults (Conventional Units). Available from URL: https://www.niddk.nih.gov/health-information/communication-programs/nkdep/laboratory-evaluation/glomerular-filtration-rate-calculators/ckd-epi-adults-conventional-units. Last accessed on 8 October 2017
5. Stevens LA, Claybon MA, Schmid CH, Chen J, Horio M, Imai E, et.al. Evaluation of the Chronic Kidney Disease Epidemiology Collaboration equation for estimating the glomerular filtration rate in multiple ethnicities. Kid internat. 2011; 79: 555-62.
6. Singh AK, Farag YM, Mittal BV, Subramanian KK, Reddy SR, Acharya VN, Almeida AF, Channakeshavamurthy A, Ballal HS, Gaccione P, Issacs R. Epidemiology and risk factors of chronic kidney disease in India-results from the SEEK (Screening and Early Evaluation of Kidney Disease) study. BMC nephrology. 2013; 14: 114.
7. Saiedullah M, Begum S, Rahman MR, Khan MA, Hayat S, Kamaluddin SM, Shaheen MA. Evaluation of CKD-EPI and MDRD prediction equations for estimation of GFR in lean and obese Bangladeshi subjects. J Sci Res. 2012; 5: 207-13.
8. Jessani S, Levey AS, Bux R, Inker LA, Islam M, Chaturvedi N, Mariat C, Schmid CH, Jafar TH. Estimation of GFR in South Asians: a study from the general population in Pakistan. Am J Kid Dis. 2014; 63: 49-58.
9. Jessani S, Bux R, Jafar TH. Prevalence, determinants, and management of chronic kidney disease in Karachi, Pakistan-a community based cross-sectional study. BMC Nephrol. 2014; 15: 90.
10. Mulay AV, Gokhale SM. Comparison of serum creatinine-based estimating equations with gates protocol for predicting glomerular filtration rate in Indian population. Ind J Nephrol. 2017; 27: 124.
11. Wang J, Xie P, Huang JM, Qu Y, Zhang F, Wei LG, Fu P, Huang XJ. The new Asian modified CKD-EPI equation leads to more accurate GFR estimation in Chinese patients with CKD. Internat Urol Nephrol. 2016; 48: 2077-81.
12. Kalra S, Sreedevi A, Unnikrishnan AG. Quaternary prevention and diabetes. J Pak Med Assoc. 2014; 64: 1324-6.