Limitations of U25 CKiD and CKD-EPI eGFR formulae in patients 2-20 years of age with measured GFR&gt;60 mL/min/1.73 m2 – A cross-sectional study

doi:10.21203/rs.3.rs-3132710/v1

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Research Article

Limitations of U25 CKiD and CKD-EPI eGFR formulae in patients 2-20 years of age with measured GFR>60 mL/min/1.73 m2 – A cross-sectional study

https://doi.org/10.21203/rs.3.rs-3132710/v1

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published 16 Oct, 2023

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Background: When applying Pierce U25 formula for estimating glomerular filtration rate (eGFR), we observed a higher proportion of eGFR<90 mL/min/1.73 m² (chronic kidney disease=CKD stage 2). We compared agreement and accuracy of the Pierce U25 (ages 2-25), Pottel (ages 2-100), and CKD-EPI (ages 18-100) formulae to GFR measurements.

Methods: Post-hoc analysis of the three eGFRs compared to 367 ⁹⁹m technetium-diethylene-triamine penta-acetic acid (⁹⁹Tc DTPA) GFR measurements (240 patients) using 3 sampling points and Brockner/Mørtensen correction (body surface area calculation based on ideal weight) on simultaneous serum creatinine and cystatin C measurements.

Results: Overall, the U25 formula performed well with a Spearman r of 0.8102 (95% confidence interval 0.7706 to 0.8435, p<0.0001) while diagnostic accuracy was low in patients with normal mGFR. The U25 formula reclassified 29.5% of patients with normal mGFR as CKD stage 2; whereas the average of the modified Schwartz formula based on serum creatinine and the Filler formula based on cystatin C, only over diagnosed CKD stage 2 in 8.5%, 24.5% within 10% and 62.7% within 30%. We therefore combined both. The average Schwartz/Filler eGFR had 36.5% of results within 10%, 84.7% within 30%, and normal mGFR accuracy was 26.8%, 63.9% for 10% and 30%, respectively, outperforming the CKD-EPI and Pottel formulae.

Interpretation: The Pierce U25 formula results correlated well with mGFR<75 mL/min/1.73m². Over the entire GFR range, accuracy was better for patients with a higher mGFR, when averaging the combined Schwartz/Filler formulae. More work is needed to prospectively confirm our findings in other centers.

Cystatin C

GFR

diagnostic accuracy

bias

precision

AUC

sensitivity

specificity

In children with chronic kidney disease (CKD), gold standard nuclear medicine or inulin clearance studies are impractical for kidney function estimates, therefore we use estimated glomerular filtration rate (eGFR) formulae based on serum creatinine and cystatin C.[1] The Schwartz eGFR formula is indexed to height in children,[2, 3] however, it has limitations, especially in patients with abnormal muscle mass.[4] The introduction of a second endogenous biomarker, cystatin C, greatly improved eGFR calculations, especially when combining serum creatinine and cystatin C.

The new Pierce CKiD U25 formula[5] (from here on referred to as U25) is recommended for 2–25-year-olds and it was derived mostly from patients with advanced CKD rather than patients with normal measured GFR (mGFR) or patients who hyper filtrate. Hyperfiltration affects the diagnostic performance of serum creatinine while cystatin C is much less affected.[6] An important concept is the fact that at 18 years, one cannot simply switch from the pediatric approach based on height, to the adult approach using age in the CKD-Epi formula,[7] since creatinine-based eGFR does not converge until age 25–30.[8] Hence, it is more appropriate to use the pediatric formula until at least age 25.[5, 8, 9] Low agreement between the pediatric and adult formulae has also been shown in patients with autosomal dominant polycystic kidney disease.[10] One of the reasons for the poor performance of the CKD-Epi formula in people younger than 30 years of age, is the fact that less than 30 of the 3,995 people from three areas of the world were in that age group. Sharma et al. demonstrated that the diagnostic performance of any eGFR formula is always best in the GFR range where most of the patients were included.[11] The original CKiD study included patients with CKD stage 2 and higher, but the U25 formula included a second cohort with milder CKD.¹ Pottel et al. introduced a formula for the full age spectrum.[12]

In our Canadian tertiary center, we used the old Filler formula based on cystatin C for eGFR calculation.[13] When we use the U25 formula, we diagnosed CKD stage 2 more frequently when compared to the modified Schwartz and Filler formula. The diagnostic performance of the U25 formula in children with CKD stage 1 has not been externally validated, so it is unknown which formula is best to use in these patients. Given this information, we sent some patients for ⁹⁹m technetium-diethylene-triamine penta-acetic acid (⁹⁹Tc DTPA) gold standard GFR measurements, using Brockner/Mørtensen correction and body surface area (BSA) calculation based on a body mass index (BMI) z-score of 0.0, and confirmed that the U25 formula over-diagnosed CKD. We wanted to understand why there were discrepancies using the U25 formula in the high GFR range among our CKD patients.

We performed a post-hoc analysis of a previously published prospective study.[14] The study was approved by the Institutional Review Board, and written consent was obtained from the parents or legal guardians of the patients. Data was prospectively collected on 367 ⁹⁹Tc DTPA GFR measurements with three-point sampling at 2-,3- and 4-hours post injection GFR, IDMS traceable creatinine and serum cystatin C levels from 240 patients, at a single tertiary care Canadian center with a predominantly Caucasian population. Eligible patients were 2 to 20 years of age with CKD stages I-V. Because of the impact of body mass on the accuracy of the mGFR, we calculated the BSA with the Mosteller formula[15] based on an age and sex-based BMI z-score of zero ideal weight rather than using the actual weight.[16] BMI was calculated by the ratio of weight [kg] and square of height [m]. BMI z-scores were calculated from the age and gender-specific standard deviations published by the US National Center for Health Statistics.[17] Creatinine was measured enzymatically and converted to IDMS traceability. The methods of measuring cystatin C were described elsewhere.[13] As this was an older method using Dade Behring reference materials, the cystatin C concentrations were corrected to international certified reference materials.[18]

Utilized formulae

Cystatin C eGFR was calculated using the Filler formula[13] and the U25 formula.[5] Creatinine eGFR was calculated using the original Schwartz formula,[2] the modified Schwartz formula,⁴ the Pottel full age spectrum formula (FAS),[12] and the U25 formula.[5] We also averaged the U25 creatinine and U25 cystatin C GFR estimates as well as the modified Schwartz and Filler formula GFR estimates.

Evaluation of eGFR

We calculated relative bias, precision and accuracy, as recommended by the National Kidney Foundation [19].

Relative bias = mean % difference = [100∗(⁹⁹mTc DTPA GFR - various eGFR)/ ⁹⁹mTc DTPA GFR].
Precision = standard deviation (SD) of the bias.
Relative precision = SD of the relative bias.
Accuracy
= Percentage of cystatin C eGFR values within 10% and 30% of the respective ⁹⁹mTc DTPA GFR measurements.

Statistical analysis

Continuous data were tested for normal distribution using the D’Agostini Pearson omnibus test. Normally distributed data were analyzed using parametric methods (mean, standard deviation, t-test, Pearson correlation), otherwise appropriate non-parametric tests were used. Even though most of the eGFR estimates were not normally distributed, we calculated both Pearson and Spearman rank correlation coefficients. We also performed a separate analysis by sex and tested whether the slopes and t-intercepts of the regression lines differed. The agreement between ⁹⁹mTc DTPA GFR and the various GFR estimates was analyzed by Bland and Altman analysis.[20] All analyses were performed using GraphPad Prism software, version 9 for Mac OS (GraphPad Inc., San Diego, CA, USA).

Patients and mGFR and eGFR results

The median age of the 240 patients was 11.7 years (range 2.0–17.9 years) and 133 (55%) were males. The number of mGFR assessments ranged from 1–3 per patient. The reasons for GFR measurement included congenital anomalies of the kidneys and urinary tract (19.5%), glomerulopathies (14.4%), obstructive uropathy (13.4%), reflux nephropathy (13.0%), proteinuria (9.9%), oncologic disease-associated nephropathy (6.8%), and others (23%). Patient and number of measurement characteristics as well as the main results of the mGFR and eGFRs are summarized in Table 1. There was no missing data.

Table 1

Patient characteristics
Patient characteristics
Total number of patients/measurements	240/367
Percentage males	55%
Measurements with mGFR < 75 mL/min/1.73 m²	88
	Mean	STDev	Min	Max
Age [years]	11.3	4.4	2.1	20
Creatinine [µmol/L]	68.5	45.4	14.1	530
Height [cm]	141.5	25.5	75	192.6
Weight [kg]	41.7	20	10	119.6
BSA [m2]	1.26	0.41	0.46	2.47
BMI [kg/m²]	19.52	4.46	12.03	37.18
BMI z-score	0.57	1.42	-2.72	8.34
ideal weight [kg]	38.28	16.3	9.19	77.22
ideal BSA based on BMI Z-score [m²]	1.21	0.37	0.44	2.02
GFR for ideal BSA [mL/min/1.73 m²]	102.97	38.63	7.02	250.27
GFR for actual weight BSA [mL/min/1.73 m²]	106.82	39.63	7	243
Traub GFR [21] [mL/min/1.73 m²]	101.85	38.51	6.73	248.28
Schwartz eGFR [2] [mL/min/1.73 m²]	92.03	31.93	11.62	233.56
mod. Schwartz eGFR [3] [mL/min/1.73 m²]	102.77	36.56	14.11	233.56
Filler CysC eGFR [13] [mL/min/1.73 m²]	102.2	39.48	8.45	294.77
U25 Cr eGFR [5] [mL/min/1.73 m²]	83.22	29.17	10.16	214.18
U25 CysC eGFR [5] [mL/min/1.73 m²]]	88.85	28.96	10.07	209.83
U25 comb eGFR [5] [mL/min/1.73 m²]	86.04	26.05	10.11	161.2
FAS age[12] eGFR [mL/min/1.73 m²]	91.95	31.38	11.96	236.44
average mod. Schwartz and Filler CysC eGFR	102.5	35.27	11.28	222.3
mGFR = measured glomerular filtration rate; STDev = standard deviation; Min = minimum; Max = maximum; BSA = body surface area; GFR = glomerular filtration rate; BMI = body mass index; FAS = Full age spectrum; mod.=modified

The mGFR calculations based on ideal weight resulted on a mean GFR measurement that was 4 mL/min/1.73 m² lower than the eGFR measurement based on the actual weight. This approach was not significantly different from the Traub GFR,[21] which is another way to normalize GFR measurements to an ideal body weight.

The averages of the original Schwartz formula, the U25 creatinine, the U25 cystatin C, the combined U25, and the FAS equations were all significantly lower than the average mGFR (p < 0.0001, one sample t-test for hypothetical value of 102.97, which was the average mGFR), whereas the modified Schwartz eGFR, the Filler eGFR and the average of those two formulae was not significantly different.

Over-identification of CKD with a cut-off of 90 mL/min/1.73 m²

We calculated the percentage of falsely classifying CKD at different cut-offs, starting with 90mL/min/1.73 m² BSA. The results are presented in Table 2. The combined U25 formula over-identified CKD stage 2 (eGFR < 90 mL/min/1.73 m²) in 29.5% of the cases.

Table 2

Percentage of falsely classifying eGFR lower than the cut-offs of 90, 75 and 60 mL/min/1.73 m² mGFR
	U25[5] combined eGFR	Filler[13] CysC eGFR	FAS[12] age eGFR	mod. Schwartz[3] eGFR	Schwartz[2] eGFR	Average mod. Schwartz and Filler CysC eGFR
Percent of falsely classified eGFR < 90 mL/min/1.73 m²	29.5%	10.3%	28.6%	24.1%	14.3%	8.5%
Percent of falsely classified eGFR < 75 mL/min/1.73 m²	11.8%	6.1%	10.4%	11.5%	6.8%	5.0%
Percent of falsely classified eGFR < 60 mL/min/1.73 m²	5.2%	4.0%	4.3%	4.3%	2.8%	3.1%
CysC = cystatin C; FAS = full age spectrum; eGFR = estimated glomerular filtration rate

Over-identification of CKD with a cut-off of 75 mL/min/1.73 m²

We tested a cut-off of 75 mL/min/1.73 m². The combined U25 formula over diagnosed an mGFR of > 75 mL/min/1.73 m² BSA in 11.8% of cases while the average modified Schwartz and Filler cystatin C formula only over diagnosed in 5% of cases.

Over-identification of CKD with a cut-off of 60 mL/min/1.73 m²

We tested a cut-off of 60 mL/min/1.73 m² (CKD stage 3). The combined U25 formula over diagnosed a mGFR of > 60 mL/min/1.73 m² in 5.2% of the cases while the average modified Schwartz and Filler cystatin C formulae only over diagnosed it in 3.1% of cases. Five percent is acceptable, as such U25 converged to the line of identity at a mGFR of > 60 mL/min/1.73 m² (see Table 2).

Correlation analysis

All eGFR formula correlated strongly with the mGFR, with the highest Spearman r values observed for the U25 cystatin C, U25 combined and the average modified Schwartz and Filler GFR estimates. The results are summarized in Table 3. In Fig. 1, we plotted the scatter plots for mGFR against the combined U25, the FAS and the average modified Schwartz and Filler GFR estimates. As can be seen, the closest fit is with the average modified Schwartz and Filler GFR estimates, although the U25 formula has a tighter fit around the line of identity for an mGFR below 60 mL/min/1.73 m².

Table 3

Bland and Altman agreement analysis and correlation analysis
	Average Filler CysC mod. Schwartz GFR	Schwartz[2] GFR	mod. Schwartz[3] GFR	Filler[13] CysC GFR	U25[5] creatinine eGFR	U25[5] CysC eGFR	U25[5] creatinine and CysC combined eGFR	Pottel Full Age Spectrum for age[12] eGFR
Bland and Altman analysis
Bias	-1.122	9.216	-1.347	0.4838	-19.15	-11.88	14.66	8.982
SD of Bias	21.22	24.02	24.84	23.16	25.62	22.56	20.4	26.4
95% Limits of Agreement
From	-42.71	-37.87	-50.04	-44.9	-69.36	-56.09	-25.32	-42.76
To	40.47	56.3	47.34	45.87	31.06	32.33	54.65	60.73
Correlation Analysis
Spearman r	0.824	0.7571	0.7582	0.8084	0.7006	0.8102	0.8149	0.6923
95% confidence interval	0.7870 to 0.8552	0.7082 to 0.7987	0.7095 to 0.7997	0.7685 to 0.8421	0.6426 to 0.7505	0.7706 to 0.8435	0.7761 to 0.8475	0.6331 to 0.7435
P-value
P (two-tailed)	< 0.0001	< 0.0001	< 0.0001	< 0.0001	< 0.0001	< 0.0001	< 0.0001	< 0.0001
P value summary	****	****	****	****	****	****	****	****
Number of XY pairs	367	367	367	367	367	367	367	367
CysC = cystatin C, mod.=modified

Bland and Altman analysis

The U25 creatinine formula had the largest bias while the average modified Schwartz and Filler eGFR had the lowest bias. All formulae had a similar standard deviation of the bias (See Table 3).

Diagnostic Accuracy for all and separated by a cut-off of 75 mL/min/1.73 m ².

The best accuracy for all measurements was found for the modified Schwartz and the average modified Schwartz or Filler eGFR formulae (Table 4). When analyzing the subgroups separately, for the lower GFR group, U25 combined and the average of the modified Schwartz and Filler eGFRs performed best, with the latter being within 10% in 41.4% of the cases and within 30% in 88.5% of the cases. For the higher GFR cut-off group, all formulae performed worse, however, the averaged modified Schwartz and Filler eGFRs were accurate within 10% in 26.8% of the cases and within 30% in 63.9% of the cases. The best performing formulae are highlighted in bold at the Table 4.

Table 4

Breakdown of Pearson r and accuracy of the various eGFR formulae across the entire GFR range, < 75 mL/min/1.73 m², and ≥ 75 mL/min/1.73 m²
Group	All			mGFR < 75 mL/min/1.73 m²			mGFR > 75 mL/min/1.73 m²
	Pearson r	Within 10%	Within 30%	Pearson r	Within 10%	Within 30%	Pearson r	Within 10%	Within 30%
original Schwartz[2] eGFR	0.7404 (0.6903 to 0.7834)	29.7%	72.5%	0.7618 (0.6572 to 0.8376)	42.5%	86.2%	0.5175 (0.4260 to 0.5986)	19.7%	52.2%
Modified Schwartz[3] eGFR	0.7434 (0.6938 to 0.7860)	35.7%	80.9%	0.6966 (0.5703 to 0.7907)	33.3%	74.7%	0.5403 (0.4515 to 0.6185)	27.9%	63.4%
Filler[13] CysC eGFR	0.7642 (0.7180 to 0.8037)	33.2%	80.1%	0.7294 (0.6138 to 0.8144)	28.7%	78.2%	0.5501 (0.4625 to 0.6270)	26.5%	61.7%
U25 Creat[5] eGFR	0.6895 (0.6317 to 0.7397)	22.1%	55.3%	0.7587 (0.6530 to 0.8354)	32.2%	78.2%	0.4406 (0.3408 to 0.5306)	14.5%	36.9%
U25 CysC[5] eGFR	0.7818 (0.7385 to 0.8186)	24.5%	64.3%	0.7537 (0.6463 to 0.8318)	34.5%	78.2%	0.5653 (0.4798 to 0.6403)	16.4%	45.9%
U25 comb[5] eGFR	0.8207 (0.7842 to 0.8515)	24.5%	62.7%	0.8122 (0.7263 to 0.8731)	44.8%	85.1%	0.6234 (0.5459 to 0.6903)	13.9%	42.6%
FAS age[12] eGFR	0.6839 (0.6253 to 0.7348)	25.3%	65.4%	0.7234 (0.6057 to 0.8101)	36.8%	79.3%	0.4446 (0.3452 to 0.5341)	16.7%	46.7%
average modified Schwartz and Filler CysC eGFR	0.813 (0.7752 to 0.8451)	36.5%	84.7%	0.813 (0.7752 to 0.8451)	41.40%	88.5%	0.6283 (0.5516 to 0.6945)	26.8	63.9
mGFR = measured GFR; eGFR = estimated glomerular filtration rate; CysC = cystatin C; FAS = full age spectrum

Analysis by sex

We then analyzed the goodness of fit and whether the slopes and intercepts of the regression lines for the Pottel FAS, U25 and the new average of the Filler and modified Schwartz formulae differed. For U25, the slopes for males and females were significantly different (p = 0.0015). The slopes of the regression lines for the average modified Schwartz and Filler eGFR were not different (p = 0.0697), however, the elevations between both regression lines were different (p < 0.0001). The slopes of the regression lines for the Pottel FAS eGFR were not different (p = 0.0753). Only for the Pottel FAS eGFR, the Y intercepts were not significantly different (p = 0.2489). The analysis by sex is provided in Fig. 2.

In this post-hoc analysis of 367 mGFR measurements conducted with a precise gold standard method, we confirmed our clinical observations that the U25 formula underestimates GFR for a measured GFR over 75 mL/min/1.73 m² BSA. This was applicable regardless of whether creatinine, cystatin C or combined estimates were used. The diagnostic performance of the relatively new Pottel FAS formula was not as good as the U25 formula. We also found that the diagnostic performance of the modified Schwartz and Filler formulae was better in the high GFR range and could even be improved if averaged. Our data suggest that averaging the modified Schwartz and Filler eGFR formulae may result in better diagnostic performance in the normal GFR range than the U25 formula.

It is not surprising that a combination of eGFR based on cystatin C and creatinine outperforms a formula that is based on only one biomarker. This has been demonstrated for the combination of cystatin C and creatinine, [5, 22, 23] for beta trace protein and beta 2 microglobulin, which are other promising endogenous GFR markers.[24, 25] However, similar to cystatin C and creatinine, separate formulae are needed for children, adolescents and young adults as compared to adults > 30 years of age.[25] The performance of the U25 formula in the higher GFR range leaves room for improvement. The main reason for this could be that the median mGFR in the training cohort was 49 mL/min/1.73 m2 BSA (interquartile range 34–66) and 47 mL/min/1.73 m2 BSA (interquartile range 32–66) in the validation cohort,[5] which means that < 25% of patients had a mGFR > 66 mL/min/1.73 m2 BSA.

Diagnostic performance is always best in the range of GFR the formula was generated.[11] This explains the excellent diagnostic performance of the U25 formula in the lower GFR range and the inferior performance in the high GFR range. Nyman et. al. showed a similar underperformance of the U25 in a large cohort of children and young adults against mGFR, especially the cystatin C U25.[26] However, Nyman et. al. did not offer a solution to the observation, even though they had mGFR in a large patient cohort with a mean GFR of 97 mL/min/1.73 m² BSA. The Filler formula remains the only formula that is validated for hyperfiltration and it had more patients with a normal GFR than CKD stages 2 and higher. Both, the modified Schwartz and Filler formula have been externally validated.[27] Our findings offer a solution, namely averaging the modified Schwartz and Filler formula, while we agree with the conclusions of Nyman et al.[26]

Our study has limitations. It is a single center study with only one gold standard mGFR method. The CKD-Epi formula in adults has its robustness since 3 different mGFR methods were pooled, however, less than 30 patients were < 30 years of age were included.[7] Combined data based on different methods, seems to improve identification of patients with CKD. The original Filler formula included ⁵¹Cr ethylene diamine tetra-acetic acid (EDTA) and ⁹⁹mTc DTPA clearance methods. We could not use the EDTA clearance data because of the non-IDMS certified creatinine measurements. Our patient number with low GFR was lower than in the U25 cohort. Nonetheless, our study confirms the findings of Nyman et al.[26] and offers a solution to the problem, namely averaging the modified Schwartz formula using IDMS traceable creatinine and the Filler formula using cystatin C measured against certified reference materials. In our center, we measure cystatin C on a Roche multi-analyzer platform using certified reference materials with a 90-minute turn-around-time.[28]

Based on our findings and using kidney scan measurements, the U25 works best for an mGFR < 75 mL/min/1.73m², but overall accuracy for patients with higher mGFR (including the hyperfiltration range), was significantly better when averaging the modified Schwartz and Filler formulae for patients ages > 18 months to 25 years. External validation as well as multinational collaboration with a variety of gold standard mGFR methods needs to take place.

Disclosures:

The authors have no conflict of interest with regards to the study.

Funding:

There was no funding associated with this analysis.

Filler G, Yasin A, Medeiros M (2014) Methods of assessing renal function. Pediatr Nephrol 29:183–192
Schwartz GJ, Haycock GB, Edelmann CM Jr, Spitzer A (1976) A simple estimate of glomerular filtration rate in children derived from body length and plasma creatinine. Pediatrics 58:259–263
Schwartz GJ, Munoz A, Schneider MF, Mak RH, Kaskel F, Warady BA, Furth SL (2009) New equations to estimate GFR in children with CKD. J Am Soc Nephrol 20:629–637
Filler G, Lee M (2018) Educational review: measurement of GFR in special populations. Pediatr Nephrol 33:2037–2046
Pierce CB, Munoz A, Ng DK, Warady BA, Furth SL, Schwartz GJ (2021) Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease. Kidney Int 99:948–956
Huang SH, Sharma AP, Yasin A, Lindsay RM, Clark WF, Filler G (2011) Hyperfiltration affects accuracy of creatinine eGFR measurement. Clin J Am Soc Nephrol 6:274–280
Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh J, Ckd EPI (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150:604–612
Webster-Clark M, Jaeger B, Zhong Y, Filler G, Alvarez-Elias A, Franceschini N, de Diaz-Gonzalez ME (2018) Low agreement between modified-Schwartz and CKD-EPI eGFR in young adults: a retrospective longitudinal cohort study. BMC Nephrol 19:194
Selistre L, Rabilloud M, Cochat P, de Souza V, Iwaz J, Lemoine S, Beyerle F, Poli-de-Figueiredo CE, Dubourg L (2016) Comparison of the Schwartz and CKD-EPI Equations for Estimating Glomerular Filtration Rate in Children, Adolescents, and Adults: A Retrospective Cross-Sectional Study. PLoS Med 13:e1001979
Schellekens P, Verjans M, Janssens P, Dachy A, De Rechter S, Breysem L, Allegaert K, Bammens B, Vennekens R, Vermeersch P, Pottel H, Mekahli D (2023) Low agreement between various eGFR formulae in pediatric and young adult ADPKD patients. Pediatr Nephrol
Sharma AP, Yasin A, Garg AX, Filler G (2011) Diagnostic accuracy of Cystatin C–based eGFR equations at different GFR levels in children. Clin J Am Soc Nephrol 6:1599–1608
Pottel H, Hoste L, Dubourg L, Ebert N, Schaeffner E, Eriksen BO, Melsom T, Lamb EJ, Rule AD, Turner ST, Glassock RJ, De Souza V, Selistre L, Mariat C, Martens F, Delanaye P (2016) An estimated glomerular filtration rate equation for the full age spectrum. Nephrol Dial Transplant 31:798–806
Filler G, Lepage N (2003) Should the Schwartz formula for estimation of GFR be replaced by cystatin C. formula? Pediatr Nephrol 18:981–985
Sharma AP, Yasin A, Garg AX, Filler G (2011) Diagnostic Accuracy of Cystatin C‚ÄìBased eGFR Equations at Different GFR Levels in Children. Clin J Am Soc Nephrol 6:1599–1608
Mosteller RD (1987) Simplified calculation of body-surface area. N Engl J Med 317:1098
Filler G, Ferris M, Gattineni J (2021) Assessment of Kidney Function in Children, Adolescents, and Young Adults. In: Emma F, Goldstein S, Bagga A, Bates CM, Shroff R (eds) Pediatric Nephrology Springer, Berlin, Heidelberg https://doi.org/10.1007/978-3-642-27843-3_87-1
http://www.cdc.gov/nchs/about/major/nhanes/growthcharts/zscore/zscore.htm
Grubb A, Horio M, Hansson LO, Bjork J, Nyman U, Flodin M, Larsson A, Bokenkamp A, Yasuda Y, Blufpand H, Lindstrom V, Zegers I, Althaus H, Blirup-Jensen S, Itoh Y, Sjostrom P, Nordin G, Christensson A, Klima H, Sunde K, Hjort-Christensen P, Armbruster D, Ferrero C (2014) Generation of a new cystatin C-based estimating equation for glomerular filtration rate by use of 7 assays standardized to the international calibrator. Clin Chem 60:974–986
K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 39:S1-266
Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310
Traub SL, Kichen L (1983) Estimating ideal body mass in children. Am J Hosp Pharm 40:107–110
Delgado C, Baweja M, Crews DC, Eneanya ND, Gadegbeku CA, Inker LA, Mendu ML, Miller WG, Moxey-Mims MM, Roberts GV, St Peter WL, Warfield C, Powe NR (2022) A Unifying Approach for GFR Estimation: Recommendations of the NKF-ASN Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease. Am J Kidney Dis 79:268–288e261
Schwartz GJ, Schneider MF, Maier PS, Moxey-Mims M, Dharnidharka VR, Warady BA, Furth SL, Munoz A (2012) Improved equations estimating GFR in children with chronic kidney disease using an immunonephelometric determination of cystatin C. Kidney Int 82:445–453
Inker LA, Tighiouart H, Coresh J, Foster MC, Anderson AH, Beck GJ, Contreras G, Greene T, Karger AB, Kusek JW, Lash J, Lewis J, Schelling JR, Navaneethan SD, Sondheimer J, Shafi T, Levey AS (2016) GFR Estimation Using beta-Trace Protein and beta2-Microglobulin in CKD. Am J Kidney Dis 67:40–48
Filler G, Alvarez-Elias AC, Westreich KD, Huang SS, Lindsay RM (2016) Can the new CKD-EPI BTP-B2M formula be applied in children? Pediatr Nephrol 31:2175–2177
Nyman U, Bjork J, Berg U, Bokenkamp A, Dubourg L, Goffin K, Grubb A, Hansson M, Larsson A, Littmann K, Asling-Monemi K, Pottel H, Delanaye P (2022) The Modified CKiD Study Estimated GFR Equations for Children and Young Adults Under 25 Years of Age: Performance in a European Multicenter Cohort. Am J Kidney Dis 80:807–810
Zheng K, Gong M, Qin Y, Song H, Shi X, Wu Y, Li F, Li X (2017) Validation of glomerular filtration rate-estimating equations in Chinese children. PLoS ONE 12:e0180565
Ismail OZ, Bhayana V, Kadour M, Lepage N, Gowrishankar M, Filler G (2017) Improving the translation of novel biomarkers to clinical practice: The story of cystatin C implementation in Canada: A professional practice column. Clin Biochem 50:380–384

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published 16 Oct, 2023

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Limitations of U25 CKiD and CKD-EPI eGFR formulae in patients 2-20 years of age with measured GFR>60 mL/min/1.73 m2 – A cross-sectional study

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Patients and Methods

Utilized formulae

Evaluation of eGFR

Statistical analysis

Results

Patients and mGFR and eGFR results

Over-identification of CKD with a cut-off of 90 mL/min/1.73 m²

Over-identification of CKD with a cut-off of 75 mL/min/1.73 m²

Over-identification of CKD with a cut-off of 60 mL/min/1.73 m²

Correlation analysis

Bland and Altman analysis

Analysis by sex

Discussion

Conclusion/Summary

Declarations

Disclosures:

Funding:

References

Status:

Journal Publication

Version 1

Limitations of U25 CKiD and CKD-EPI eGFR formulae in patients 2-20 years of age with measured GFR>60 mL/min/1.73 m2 – A cross-sectional study

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Patients and Methods

Utilized formulae

Evaluation of eGFR

Statistical analysis

Results

Patients and mGFR and eGFR results

Over-identification of CKD with a cut-off of 90 mL/min/1.73 m2

Over-identification of CKD with a cut-off of 75 mL/min/1.73 m2

Over-identification of CKD with a cut-off of 60 mL/min/1.73 m2

Correlation analysis

Bland and Altman analysis

Analysis by sex

Discussion

Conclusion/Summary

Declarations

Disclosures:

Funding:

References

Status:

Journal Publication

Version 1

Over-identification of CKD with a cut-off of 90 mL/min/1.73 m²

Over-identification of CKD with a cut-off of 75 mL/min/1.73 m²

Over-identification of CKD with a cut-off of 60 mL/min/1.73 m²