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LETTER TO THE EDITOR
Year : 2019  |  Volume : 8  |  Issue : 3  |  Page : 179-180

Donor's versus recipient's demographic data for estimating kidney function in kidney transplant recipients


Department of Clinical Pharmacy, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran

Date of Web Publication16-Oct-2019

Correspondence Address:
Prof. Simin Dashti-Khavidaki
Department of Clinical Pharmacy, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran
Iran
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jrpp.JRPP_19_23

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How to cite this article:
Nabiee M, Dashti-Khavidaki S. Donor's versus recipient's demographic data for estimating kidney function in kidney transplant recipients. J Res Pharm Pract 2019;8:179-80

How to cite this URL:
Nabiee M, Dashti-Khavidaki S. Donor's versus recipient's demographic data for estimating kidney function in kidney transplant recipients. J Res Pharm Pract [serial online] 2019 [cited 2019 Nov 20];8:179-80. Available from: http://www.jrpp.net/text.asp?2019/8/3/179/269282



Dear Editor,

Estimated glomerular filtration rate (eGFR) is clinically used to evaluate the level of kidney function and approximating maintenance doses of drugs that are renally eliminated.

Most commonly used equations for eGFR calculation are the chronic kidney disease epidemiology collaboration, modification of diet in renal diseases, and Cockcroft-Gault. These three formulas use serum creatinine concentration to estimate GFR.[1] All these equations, although with different accuracies, can be applied to estimate drug dosing.[1]

In kidney transplant recipients, allograft rejection and drug-induced nephrotoxicity are the two persistent threats that necessitate kidney function monitoring. Some investigators have assessed the accuracy of commonly used eGFR equations in kidney transplant recipients. One can conclude that they have used recipients' age, weight, and gender in these eGFR formulas since there is no mention of the donors' data in those studies.[2],[3] They noted that predictive performances of many eGFR equations are modest in kidney transplant recipients, while biases may significantly be associated with recipients' demographic characteristics including body mass index, age, and sex.[2],[3]

These discrepancies may in part be due to the using of recipients' biometric data without considering donor's demographic data for estimating GFR. Patients' demographic characteristics including age, sex, race, and weight are usually considered in eGFR equations since they represent interindividual variations in muscle mass and creatinine production.[2],[3] Age is a physiologic factor that affects GFR as well as creatinine production and tubular secretion.[4] In addition, pathologic conditions that are common in older patients (such as diabetes and atherosclerosis) as well as physiologic senescence may alter the accuracy of GFR estimates.[4]

Although not clearly mentioned in the method sections of most studies, one can conclude that all of those studies included demographic characteristics of the kidney transplant recipients in the eGFR equations. Considering the role of age on serum creatinine production may justify the use of recipient's age in equations; however, considering the age of the kidney, donor's age may also need to be taken into account. It seems that evaluating eGFR of paired kidneys from a single donor in two different recipients at different time points after transplantation would be worthy in future studies to assess the role of donors' demographic data on eGFR.

Multiple other factors influence the serum creatinine concentration in kidney transplant recipients. For example, trimethoprim that is administered as a component of cotrimoxazole® for prophylaxis of Pneumocystis jiroveci pneumonia inhibits tubular secretion of creatinine. Corticosteroids that are usually administered as induction and maintenance immunosuppressive regimen induce muscle wasting and affect creatinine generation.[5] Hence, higher doses of steroids within the 1st day after transplantation and lower doses later may alter serum creatinine concentrations. Therefore, developing new eGFR equations for use in kidney transplant recipients by including demographic data of the donor, drugs types, and steroid dose may be necessary to optimize the accuracy of eGFR in this population.

Acknowledgments

The authors would like to thank Professor Gary R. Matzke for giving valuable comments and editing this editorial letter.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Matzke GR, Aronoff GR, Atkinson AJ Jr., Bennett WM, Decker BS, Eckardt KU, et al. Drug dosing consideration in patients with acute and chronic kidney disease-a clinical update from kidney disease: Improving global outcomes (KDIGO). Kidney Int 2011;80:1122-37.  Back to cited text no. 1
    
2.
Bosma RJ, Doorenbos CR, Stegeman CA, van der Heide JJ, Navis G. Predictive performance of renal function equations in renal transplant recipients: An analysis of patient factors in bias. Am J Transplant 2005;5:2193-203.  Back to cited text no. 2
    
3.
Gaspari F, Ferrari S, Stucchi N, Centemeri E, Carrara F, Pellegrino M, et al. Performance of different prediction equations for estimating renal function in kidney transplantation. Am J Transplant 2004;4:1826-35.  Back to cited text no. 3
    
4.
Glassock RJ, Rule AD. The implications of anatomical and functional changes of the aging kidney: With an emphasis on the glomeruli. Kidney Int 2012;82:270-7.  Back to cited text no. 4
    
5.
Horber FF, Scheidegger J, Frey FJ. Overestimation of renal function in glucocorticosteroid treated patients. Eur J Clin Pharmacol 1985;28:537-41.  Back to cited text no. 5
    




 

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