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 Table of Contents  
ORIGINAL ARTICLES
Year : 2020  |  Volume : 11  |  Issue : 3  |  Page : 158-162

Correlation between cortical renal thickness and estimated glomerular filtration rate in diabetic nephropathy patients


Maharaja Agrasen Hospital, Punjabi Bagh, New Delhi, India

Date of Submission28-Jun-2020
Date of Decision10-Jul-2020
Date of Acceptance20-Jul-2020
Date of Web Publication1-Sep-2020

Correspondence Address:
Dr. Rajeev Chawla
Maharaja Agrasen Hospital, Punjabi Bagh, New Delhi.
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/JOD.JOD_54_20

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  Abstract 

Background and Objectives: Conventionally urine creatinine test and renal ultrasound are used in clinical practice for staging and progression of diabetic nephropathy. The objectives of this study were (1) to determine the correlation between cortical renal thickness and eGFR (estimated glomerular filtration rate) in diabetic nephropathy, and (2) to further assess if the cortical renal thickness is a better predictor of eGFR than the linear bipolar length in diabetic nephropathy. Materials and Methods: A total of 163 patients were recruited between April 2017 and March 2018 (86 men and 77 women) who had diabetic nephropathy with eGFR <90mL/min/1.73 m2 according to Cockcroft–Gault formulation. Results: The mean age (mean ± standard deviation [SD]) of the patients was 59.5 ± 7.2 years with range 39 –78 years and the median age was 59 years. The mean level of creatinine (mean ± SD) of the patients was 1.4 ± 0.4 mg/dL with range 0.6–3.2 mg/dL and the median was 1.4 mg/dL. Mean eGFR (in mL/min/1.73 m2) being 49.8 ± 13.4 (range 41.2–62.5). Cortical renal thickness right upper part, right middle part, left upper part, and left middle part (in mm) were found to be 5.5 ± 1.04, 5.6 ± 1.05, 5.5 ± 1, and 5.6 ± 1.02, respectively. Mean values of renal length of right- and left-sided kidney were 9.2 ± 0.4 and 9.5 ± 0.4, respectively. Pearson’s coefficient of correlation showed a moderately significant correlation between eGFR and cortical renal thickness in diabetic nephropathy patients. Correlation coefficient of the cortical renal thicknesses correlated better with eGFR than cortical renal length. Summary and Conclusion: This cross-sectional study in diabetic nephropathy patients showed a positive correlation between eGFR and cortical renal thickness. Cortical renal thickness was found to be a better predictor of renal function than bipolar renal length.

Keywords: Cortical renal length (CRL), cortical renal thickness (CRT), estimated glomerular filtration rate (eGFR), diabetic nephropathy


How to cite this article:
Chawla R, Zala S, Punyani H, Dhingra J. Correlation between cortical renal thickness and estimated glomerular filtration rate in diabetic nephropathy patients. J Diabetol 2020;11:158-62

How to cite this URL:
Chawla R, Zala S, Punyani H, Dhingra J. Correlation between cortical renal thickness and estimated glomerular filtration rate in diabetic nephropathy patients. J Diabetol [serial online] 2020 [cited 2020 Sep 25];11:158-62. Available from: http://www.journalofdiabetology.org/text.asp?2020/11/3/158/294050




  Introduction Top


As per the Global Burden of Disease, chronic kidney disease (CKD) is the 12th leading cause of death worldwide.[1] Diabetes is the leading cause of CKD accounting for almost 1.1 million patients worldwide.

CKD may not have any symptoms in early stage and symptoms mostly occur after stage 3 CKD. Normally urine creatinine test and ultrasonography are used in clinical practice regularly to look for any reversible cause and kidney biopsy is done for prognosis purposes.[2] Patients with CKD mostly show increased cortical echogenicity, decreased renal size, and decreased differentiation between cortex and medulla on ultrasonography.[3],[4],[5],[6]

Renal failure could manifest as progressive reduction in the cortical thickness.[3] One study has shown a linear correlation between estimated glomerular filtration rate (eGFR) and cortical thickness.[7] Limitations of this study were small sample size; and the measurements were obtained by technologists on ultrasound scan not in real-time during the study but by consensus on imaging files.

We planned this unicentre, noninterventional, prospective study to evaluate the relationship between degree of renal injury in patients with CKD and renal cortex thickness obtained in real-time by ultrasound and determining the reproducibility of such measurements as a novel approach to early diagnosis of diabetic nephropaty as not many studies have evaluated the same previously.

Aims and Objectives

  1. To determine the correlation between renal cortical thickness and eGFR in diabetic nephropathy.


  2. To further assess if cortical thickness is a better predictor of eGFR than the linear bipolar length in diabetic nephropathy.



  Materials and Methods Top


A total of 163 patients with age >18 years of either sex with established diagnosis of diabetic nephropathy and eGFR <90mL/min/1.73 m2 according to Cockcroft–Gault (CG) formulation were enrolled. Prevalence of overt nephropathy and microalbuminuria was found to be 2.2% and 26.9%, respectively, in urban Asian patients with diabetes in “CurES 45”.[8] Considering the increasing incidence of type 2 diabetes mellitus with nephropathy, and prevalence of 12%, a sample size of 163 was obtained using Cochrane’s formula with at least 95% confidence limit.

This study was approved by the Ethical Committee of the hospital and written consent from all the study participants was obtained.

Patients with end-stage renal disease, obstructive nephropathy, hypertensive nephropathy, adult polycystic renal disease, chronic progressive glomerulonephritis, and orthostatic albuminuria were excluded.

3.5-MHz curvilinear transducer was used for performing ultrasound examination using standard gray-scale B-mode imaging. The bipolar length was measured in the sagittal plane from the upper to the lower pole. The cortical renal thickness (CRT) was measured in the upper and middle thirds of the kidney in the sagittal plane, above the medullary pyramid, perpendicularly to the capsule [Figure 1]. The lowest value of serum creatinine measured in the last 3 months was used for eGFR calculations to minimize the influence of superimposed acute on chronic renal insufficiency as it represented the best recorded renal function during the study period.
Figure 1: Ultrasound image of right kidney showing CRL and CRT

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The CG equations was used for eGFR calculation as follows: eGFR = (140 – age) × (weight in kg) × (0.85 if female) / (72× Cr), where Cr is creatinine.

Statistical analysis

Epi Info (TM) 7.2.2.2. was used for Statistical Analysis, namely inferences and associations and basic cross-tabulation. t test was used to compare the means. Chi-square test (

[INLINE 1]

) was used to test the association of different study variables. Z-test (standard normal deviate) was used to test the significant difference between two proportions. Pearson correlation coefficient was calculated to find the correlation between two variables. One-way analysis of variance (ANOVA) followed by post hoc Tukey’s test was performed with the help of critical difference (CD) or least significant difference (LSD) at 5% and 1% level of significance to compare the different correlation values. A value of P < 0.05 was considered to be statistically significant.


  Results Top


This cross-sectional study comprised 163 diabetic nephropathy patients. Correlation between eGFR and CRT in diabetic nephropathy patients was evaluated.

The overall statistics of study subjects are given in [Table 1].
Table 1: Overall statistics

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There were 52.8% males, and male:female ratio was 1.1:1.0. The mean serum creatinine (mean ± standard deviation [SD]) was 1.4 ± 0.4 mg/dL (range 0.6–3.2 mg/dL) and the median was 1.4 mg/dL. Approximately 86.51% of patients had creatinine level significantly higher than the normal limit.

Mean values of various biochemical parameters measured in study subjects were as follows: mean eGFR (in mL/min/1.73 m2) was 49.8 ± 13.4 with range of 41.2–625. Mean CRT of right upper part, right middle part, left upper part, and left middle part (in mm) recorded was 5.5 ± 1.04, 5.6 ± 1.05, 5.5 ± 1, and 5.6 ± 1.02, respectively. Mean values of renal length of right- and left-sided kidney were 9.2 ± 0.4 and 9.5 ± 0.4, respectively [Table 2]. Mean values of all the parameters were below the normal limit.
Table 2: Mean cortical renal thickness (in mm) at different parts of kidney

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All the correlations were positive and significant. Thus, the CRT and renal length decreased with the decreasing values of all the eGFR. As per correlation coefficient, a better correlation was seen between CRTs with eGFR than cortical renal length [Table 4] [Figure 2]. Thus, in diabetic nephropathy a reduction in cortical thickness was a better predictor of falling eGFR than the linear bipolar length
Figure 2: Correlation between eGFR, cortical renal thickness, and cortical renal length

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Significant difference in correlation between CRT and eGFR and CRL and eGFR (F = 77.24; P < 0.0001) was observed as per one-way ANOVA [Table 3]. Mean correlation between CRT and eGFR was significantly higher than that of mean correlation between CRL and eGFR (P < 0.001) as per Tukey’s CD [Table 4] (refer to Scatter Graphs 1–6). Thus, in diabetic nephropathy CRT was a better predictor of eGFR than linear bipolar length (CRL) (P < 0.001).
Table 3: Correlation between eGFR, cortical renal thickness, and cortical renal length

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Table 4: Correlation between eGFR, cortical renal thickness (CRT), and cortical renal length (CRL) of both parts taken altogether

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Scatter Graphs 1–6 showing a correlation between CRT and level of eGFR.


  Discussion Top


In this study, the ratio of male and female (male:female) was 1.1:1.0. Test of proportion showed that the proportion of males (52.8%) was higher than that of females, which closely resembles epidemiology of diabetic nephropathy in India.

Majority of the study participants were in the age group between 50 and 64 years (66.5%). Very few participants were in the extremes of age groups, that is, less than 40 years.

This study showed a statistically significant relationship between cortical thickness measured at ultrasound and renal function in patients with diabetic nephropathy. All the correlations were positive. With decreasing values of the eGFR, the CRT and renal length were decreasing.

However, as per the correlation coefficient values of the CRT more correlated better with eGFR than cortical renal length. Thus, cortical thickness was a better predictor of eGFR than the linear bipolar length in diabetic nephropathy.

Similar results have been shown by Beland et al.[9] and they have suggested that cortical thickness would be a good indicator for renal function impairment as they could show a statistically significant linear relationship and a strong correlation (r2 = 0.66) between cortical thickness and renal function.[4] They also showed that cortical thickness measured at ultrasound may be related more closely to eGFR than renal length in patients with chronic renal failure.

However, their study had limitations of small sample size (n = 25) and the retrospective consensual analysis of previously acquired imaging files.

Yamashita et al.[10] showed that the renal function status can be indirectly estimated by means of renal cortex measurements in the upper and middle third of the left kidney. Also, the bipolar length of the left kidney could serve as an indirect estimate of renal function impairment, but with less significant results. On the contrary, estimated renal function and parenchymal thickness have proved to be only weakly and nonsignificantly correlated; thus, parenchymal thickness cannot not be used as an indicator of renal function impairment. It is known that glomeruli are found in the renal cortex and columns of Bertin, and renal tubules, in the medullary pyramids. The progressive renal function impairment affects the glomeruli which frequently results in tapering of the renal cortex and of columns of Bertin, so that the kidney presents with tapered, lobulated contours in association with increased presence of fat in the renal sinus, indicating chronic nephropathy. Even with these changes, however, the bipolar length and parenchymal thickness may still be within the curve of normality. Thus, many times kidneys may not present any significant anatomical abnormality so the natural progression of nephropathy is likely to be missed. Hence, there is important relevance of a parameter such as cortical thickness as a possible predictor of CKD and its progression.

Sanusi et al.[11] suggested that in case of diabetic kidney disease, nephromegaly, characterized by hypertrophy affects all components and, in some cases, measurements, including cortical thickness, remain normal until the final stage of CKD is present. However, in our study all the parameters including CRT and renal length were decreased as our mean eGFR was 49.84 ± 13.49 which is grade 3 chronic renal disease.

This study had certain limitations. It had a sample size of 163 which may limit the generalization of the study findings. The study was limited to one tertiary care hospital and further evaluation of nephropathy for etiology was not done.

In conclusion, CRT was found to be a better predictor of renal function than bipolar renal length (cortical renal length). By measuring CRT diabetic nephropathy can be diagnosed in early stages although serum creatinine may still be in the normal range providing a window of opportunity to intervene early to reduce the morbidity and mortality related to diabetic nephropathy.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Wang H, Naghavi M, Allen C, Barber RM, Bhutta ZA, Carter A . GBD 2015 Mortality and Causes of Death Collaborators. 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. Lancet 2016;388:1459-544.   Back to cited text no. 1
    
2.
Kariyanna SS, Light RP, Agarwal R A longitudinal study of kidney structure and function in adults. Nephrol Dial Transplant 2010;25:1120-6.  Back to cited text no. 2
    
3.
Emamian SA, Nielsen MB, Pedersen JF, Ytte L Kidney dimensions at sonography: Correlation with age, sex, and habitus in 665 adult volunteers. AJR Am J Roentgenol 1993;160:83-6.  Back to cited text no. 3
    
4.
Raj DS, Hoisala R, Somiah S, Sheeba SD, Yeung M Quantitation of change in the medullary compartment in renal allograft by ultrasound. J Clin Ultrasound 1997;25:265-9.  Back to cited text no. 4
    
5.
Tarzamni MK, Nezami N, Rashid RJ, Argani H, Hajealioghli P, Ghorashi S Anatomical differences in the right and left renal arterial patterns. Folia Morphol (Warsz) 2008;67:104-10.  Back to cited text no. 5
    
6.
Cockcroft DW, Gault MH Prediction of creatinine clearance from serum creatinine. Nephron 1976;16:31-41.  Back to cited text no. 6
    
7.
Ingelfinger JR Is microanatomy destiny? N Engl J Med 2003;348:99-100.  Back to cited text no. 7
    
8.
Unnikrishnan RI, Rema M, Pradeepa R, Deepa M, Shanthirani CS, Deepa R, et al. Prevalence and risk factors of diabetic nephropathy in an urban south Indian population: The Chennai urban rural epidemiology study (CURES 45). Diabetes Care 2007;30:2019-24.  Back to cited text no. 8
    
9.
Beland MD, Walle NL, Machan JT, Cronan JJ Renal cortical thickness measured at ultrasound: Is it better than renal length as an indicator of renal function in chronic kidney disease? AJR Am J Roentgenol 2010;195:W146-9.  Back to cited text no. 9
    
10.
Yamashita SR, Atzingen AC, Iared W, Bezerra ASA, Ammirati AL, Canziani MEF,et al. Value of renal cortical thickness as a predictor of renal function impairment in chronic renal disease patient. Radiol Bras 2015;48:12-6.  Back to cited text no. 10
    
11.
Sanusi AA, Akinsola A, Ajayi AA Creatinine clearance estimation from serum creatinine values: Evaluation and comparison of five prediction formulae in Nigerian patients. Afr J Med Med Sci 2000;29:7-11.  Back to cited text no. 11
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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