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      Performance and Determinants of Serum Creatinine and Cystatin C–Based GFR Estimating Equations in South Asians

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          Abstract

          Introduction

          The creatinine-based Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) estimated glomerular filtration rate (eGFR) equation was calibrated for the general Pakistan population (eGFRcr-PK) to eliminate bias and improve accuracy. Cystatin C–based CKD-EPI equations (eGFRcys and eGFRcr-cys) have not been assessed in this population, and non-GFR determinants of cystatin C are unknown.

          Methods

          We assessed eGFRcys, eGFRcr-cys, and non-GFR determinants of cystatin C in a cross-sectional study of 557 participants (≥40 years of age) from Pakistan. We compared bias (median difference in measured GFR [mGFR] and eGFR), precision (interquartile range [IQR] of differences), accuracy (percentage of eGFR within 30% of mGFR), root mean square error (RMSE), and classification of mGFR <60 ml/min/1.73 m 2 (area under the receiver operating characteristic curve [AUC] and net reclassification index [NRI]) among eGFR equations.

          Results

          We found that eGFRcys underestimated mGFR (bias, 12.7 ml/min/1.73 m 2 [95% confidence interval {CI} 10.7–15.2]). eGFRcr-cys did not improve performance over eGFRcr-PK in precision ( P = 0.52), accuracy ( P = 0.58), or RMSE ( P = 0.49). Results were consistent among subgroups by age, sex, smoking, body mass index (BMI), and eGFR. NRI was 7.31% (95% CI 1.52%–13.1%; P < 0.001) for eGFRcr-cys versus eGFRcr-PK, but AUC was not improved (0.92 [95% CI 0.87–0.96] vs. 0.90 [95% CI 0.86–0.95]; P = 0.056). Non-GFR determinants of higher cystatin C included male sex, smoking, higher BMI and total body fat, and lower lean body mass.

          Conclusion

          eGFRcys underestimated mGFR in South Asians and eGFRcr-cys did not offer substantial advantage compared with eGFRcr-PK. Future studies are warranted to better understand the large bias in eGFRcys and non-GFR determinants of cystatin C in South Asians.

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          Most cited references65

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          Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015

          Summary Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4–61·9) in 1980 to 71·8 years (71·5–72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7–17·4), to 62·6 years (56·5–70·2). Total deaths increased by 4·1% (2·6–5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8–18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6–16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9–14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1–44·6), malaria (43·1%, 34·7–51·8), neonatal preterm birth complications (29·8%, 24·8–34·9), and maternal disorders (29·1%, 19·3–37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000–183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000–532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation.
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            A concordance correlation coefficient to evaluate reproducibility.

            L Lin (1989)
            A new reproducibility index is developed and studied. This index is the correlation between the two readings that fall on the 45 degree line through the origin. It is simple to use and possesses desirable properties. The statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation. A Monte Carlo experiment with 5,000 runs was performed to confirm the estimate's validity. An application using actual data is given.
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              Estimating glomerular filtration rate from serum creatinine and cystatin C.

              Estimates of glomerular filtration rate (GFR) that are based on serum creatinine are routinely used; however, they are imprecise, potentially leading to the overdiagnosis of chronic kidney disease. Cystatin C is an alternative filtration marker for estimating GFR. Using cross-sectional analyses, we developed estimating equations based on cystatin C alone and in combination with creatinine in diverse populations totaling 5352 participants from 13 studies. These equations were then validated in 1119 participants from 5 different studies in which GFR had been measured. Cystatin and creatinine assays were traceable to primary reference materials. Mean measured GFRs were 68 and 70 ml per minute per 1.73 m(2) of body-surface area in the development and validation data sets, respectively. In the validation data set, the creatinine-cystatin C equation performed better than equations that used creatinine or cystatin C alone. Bias was similar among the three equations, with a median difference between measured and estimated GFR of 3.9 ml per minute per 1.73 m(2) with the combined equation, as compared with 3.7 and 3.4 ml per minute per 1.73 m(2) with the creatinine equation and the cystatin C equation (P=0.07 and P=0.05), respectively. Precision was improved with the combined equation (interquartile range of the difference, 13.4 vs. 15.4 and 16.4 ml per minute per 1.73 m(2), respectively [P=0.001 and P 30% of measured GFR, 8.5 vs. 12.8 and 14.1, respectively [P<0.001 for both comparisons]). In participants whose estimated GFR based on creatinine was 45 to 74 ml per minute per 1.73 m(2), the combined equation improved the classification of measured GFR as either less than 60 ml per minute per 1.73 m(2) or greater than or equal to 60 ml per minute per 1.73 m(2) (net reclassification index, 19.4% [P<0.001]) and correctly reclassified 16.9% of those with an estimated GFR of 45 to 59 ml per minute per 1.73 m(2) as having a GFR of 60 ml or higher per minute per 1.73 m(2). The combined creatinine-cystatin C equation performed better than equations based on either of these markers alone and may be useful as a confirmatory test for chronic kidney disease. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases.).
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                Author and article information

                Contributors
                Journal
                Kidney Int Rep
                Kidney Int Rep
                Kidney International Reports
                Elsevier
                2468-0249
                16 January 2021
                April 2021
                16 January 2021
                : 6
                : 4
                : 962-975
                Affiliations
                [1 ]Program in Health Services and Systems Research, Duke–NUS Medical School, Singapore
                [2 ]Division of Nephrology, Department of Medicine, Tufts Medical Center, Boston, Massachusetts, USA
                [3 ]Department of Community Health Sciences, Aga Khan University, Karachi, Pakistan
                [4 ]Department of Pediatrics (Division of Women and Child Health), Aga Khan University, Karachi, Pakistan
                [5 ]Department of Medicine, Aga Khan University, Karachi, Pakistan
                [6 ]Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, Minnesota, USA
                [7 ]Center for Quantitative Medicine, Office of Clinical Sciences, Duke–NUS Medical School, Singapore
                [8 ]Department of Renal Medicine, Singapore General Hospital, Singapore
                [9 ]Duke Global Health Institute, Duke University, Durham, North Carolina, USA
                Author notes
                [] Correspondence: Tazeen H. Jafar, Program in Health Services and Systems Research, Duke–NUS Medical School, 8 College Rd, 169857, Singapore. tazeen.jafar@ 123456duke-nus.edu.sg
                Article
                S2468-0249(21)00005-X
                10.1016/j.ekir.2021.01.005
                8071622
                33912746
                1b2dce2c-9381-4ccf-a31c-44b90962802a
                © 2021 International Society of Nephrology. Published by Elsevier Inc.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 31 December 2020
                : 4 January 2021
                Categories
                Clinical Research

                chronic kidney disease epidemiology collaboration (ckd-epi),cystatin c,estimating equations,glomerular filtration rate (gfr),kidney function,south asian

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