Assessment of the dynamics of concentration of biomarkers of acute kidney injury in remote shock wave lithotripsy in children

封面


如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅或者付费存取

详细

BACKGROUND: For several decades, remote shock wave lithotripsy has been considered a universally recognized gold standard for the treatment of upper urinary tract concrements. Despite its noninvasiveness, each lithotripsy session causes acute kidney injury which cannot be reliably assessed with traditional indicators used in nephrourology. Currently, new modern indicators found in the urine and serum are thought to be more informative biomarkers. In this paper, we investigated the effectiveness of some of them for possible potentials in the diagnostics of acute kidney injury in remote lithotripsy.

AIM: To evaluate changes in acute kidney injury biomarkers during remote shock wave lithotripsy in children.

MATERIALS AND METHODS: 54 children with urolithiasis, who had a session of remote shock wave lithotripsy, were enrolled in the study. In all patients, samples of urine and blood serum were taken three times for assessing biomarkers concentration: before lithotripsy session, after 45 min and after 24 h.

RESULTS: Statistically significant changes in the concentration of all urine biomarkers (NGAL, L-FABP, TIMP-2, calbindin-D, KIM-1) were registered at the basal level and 45 min after the procedure. A number of markers studied by us in the blood serum showed more significant changes 24 h after the procedure (IL-18, TNF-α). Although IGFBP-1 concentration increased slightly after 45 min, this change was not statistically significant (p <0.781). The level of cystatin C did not increase after lithotripsy.

CONCLUSION: The performed analysis of changes in biomarkers concentration has revealed a sufficiently high informative value of biomarkers in assessing the degree of acute kidney injury during remote lithotripsy in children. It also allows to suggest that the studied biomarkers may be promising indicators characterizing such an injury.

全文:

受限制的访问

作者简介

Sergey Zorkin

National Medical Research Center for Children’s Health

Email: zorkin@nczd.ru
ORCID iD: 0000-0002-2731-5008
SPIN 代码: 4762-8837

MD, Dr. Sci. (Medicine), Professor

俄罗斯联邦, Moscow

Oleg Nikulin

National Medical Research Center for Children’s Health

编辑信件的主要联系方式.
Email: dr.nikulin.oleg@yandex.ru
ORCID iD: 0000-0003-3640-9994
俄罗斯联邦, Moscow

Elena Semikina

National Medical Research Center for Children’s Health

Email: semikina@nczd.ru
ORCID iD: 0000-0001-8923-4652
SPIN 代码: 3647-4967

MD, Dr. Sci. (Medicine)

俄罗斯联邦, Moscow

Marina Snovskaya

National Medical Research Center for Children’s Health

Email: snows@inbox.ru
ORCID iD: 0000-0002-5263-6743
SPIN 代码: 9899-1095

MD, Cand. Sci. (Medicine)

俄罗斯联邦, Moscow

Dmitriy Shakhnovskiy

National Medical Research Center for Children’s Health

Email: shahnovskii_dmit@mail.ru
ORCID iD: 0000-0003-2883-2493
SPIN 代码: 4946-0848
俄罗斯联邦, Moscow

Rimir Bayazitov

National Medical Research Center for Children’s Health

Email: krasik17@yandex.ru
ORCID iD: 0000-0002-2809-1894
俄罗斯联邦, Moscow

参考

  1. Gadzhiev N, Prosyannikov M, Malkhasyan V, et al. Urolithiasis prevalence in the Russian Federation: Analysis of trends over a 15-year period. World J Urol. 2021;39(10):3939-3944. EDN: SUSDKJ doi: 10.1007/s00345-021-03729-y
  2. Talso M, Tefik T, Mantica G, et al. Extracorporeal shockwave lithotripsy: Current knowledge and future perspectives. Minerva Urol Nefrol. 2019;71(4):365-372. doi: 10.23736/S0393-2249.19.03415-5
  3. Zorkin SN, Nikulin OD, Shahnovskiy DS. Remote shock wave lithotripsy in the treatment of urolithiasis in children: Types and possibilities. Detskaya khirurgiya (Russian Journal of Pediatric Surgery). 2023;26(6):321-326. EDN: IYZCXD doi: 10.55308/1560-9510-2022-26-6-321-326
  4. Hughes SF, Jones N, Thomas-Wright SJ, et al. Shock wave lithotripsy, for the treatment of kidney stones, results in changes to routine blood tests and novel biomarkers: A prospective clinical pilot-study. Eur J Med Res. 2020;25(1):18. doi: 10.1186/s40001-020-00417-2
  5. Milišić E, Alić J, Zvizdić Z, et al. Urinary neutrophil gelatinase-associated lipocalin level as a biomarker of acute kidney injury following extracorporeal shock wave lithotripsy. Cent Eur J Urol. 2021;74(4):579-587. EDN: DPGUHH doi: 10.5173/ceju.2021.0174
  6. Nazarov TK, Komyakov BK, Rychkov IV, et al. Role of biomarkers of acute kidney damage during lithotripsy of high-density stones. Urologiia. 2019;(1):23-27. EDN: FKKLMH doi: 10.18565/urology.2019.1.23-27
  7. Clark DL, Connors BA, Evan AP, et al. Localization of renal oxidative stress and inflammatory response after lithotripsy. BJU Int. 2009;103(11):1562-1568. doi: 10.1111/j.1464-410X.2008.08260.x
  8. Krambeck AE, Gettman MT, Rohlinger AL, et al. Diabetes mellitus and hypertension associated with shock wave lithotripsy of renal and proximal ureteral stones at 19 years of followup. J Urol. 2006;175(5):1742-1747. doi: 10.1016/S0022-5347(05)00989-4
  9. Wu Q, Liang R, Huang Y, et al. Association between renal urolithiasis after extracorporeal shock wave lithotripsy therapy and new-onset hypertension: An updated meta-analysis. J Int Med Res. 2021;49(4):3000605211002003. doi: 10.1177/03000605211002003
  10. Dzięgała M, Krajewski W, Kołodziej A, et al. Evaluation and physiopathology of minor transient shock wave lithotripsy--induced renal injury based on urinary biomarkers levels. Cent Eur J Urol. 2018;71(2):214-220. doi: 10.5173/ceju.2018.1629
  11. Willis LR, Evan AP, Connors BA, et al. Relationship between kidney size, renal injury, and renal impairment induced by shock wave lithotripsy. J Am Soc Nephrol. 1999;10(8):1753-1762. doi: 10.1681/ASN.V1081753
  12. Dalton RN. Serum creatinine and glomerular filtration rate: perception and reality. Clin Chem. 2010;56(5):687-689. doi: 10.1373/clinchem.2010.144261
  13. Liu X, Guan Y, Xu S, et al. Early predictors of acute kidney injury: A narrative review. Kidney Blood Press Res. 2016;41(5):680-700. doi: 10.1159/000447937
  14. Oh DJ. A long journey for acute kidney injury biomarkers. Ren Fail. 2020;42(1):154-165. doi: 10.1080/0886022X.2020.1721300
  15. Wołyniec W, Ratkowski W, Renke J, Renke M. Changes in novel AKI biomarkers after exercise: A systematic review. Int J Mol Sci. 2020;21(16):5673 doi: 10.3390/ijms21165673
  16. Annamalai SK, Kapur NK. Contrast induced nephropathy after coronary or vascular intervention: More biomarkers than answers. Catheter Cardiovasc Interv. 2018;91(7):1192-1193. doi: 10.1002/ccd.27671
  17. Yuan SM. Acute kidney injury after cardiac surgery: Risk factors and novel biomarkers. Braz J Cardiovasc Surg. 2019;34(3):352-360. doi: 10.21470/1678-9741-2018-0212
  18. Zhang YL, Qiao SK, Wang RY, Guo XN. NGAL attenuates renal ischemia/reperfusion injury through autophagy activation and apoptosis inhibition in rats. Chem Biol Interact. 2018;(289):40-46. doi: 10.1016/j.cbi.2018.04.018
  19. Kachko A, Costafreda MI, Zubkova I, et al. Determinants in the Ig variable domain of human HAVCR1 (TIM-1) are required to enhance hepatitis C virus entry. J Virol. 2018;92(6):e01742-17. EDN: YFLEPB doi: 10.1128/JVI.01742-17
  20. Bank JR, van der Pol P, Vreeken D, et al. Kidney injury molecule-1 staining in renal allograft biopsies 10 days after transplantation is inversely correlated with functioning proximal tubular epithelial cells. Nephrol Dialysis Transplant. 2017;32(12):2132-2141. doi: 10.1093/ndt/gfx286
  21. Miroshkina IV, Grickevich AA, Baytman TP, et al. The role of markers of acute kidney damage in assessing kidney function with its ischemia. Exp Clin Urol. 2018;(4):114-121. EDN: VRTKPJ
  22. Lin X, Yuan J, Zhao Y, Zha Y. Urine interleukin-18 in prediction of acute kidney injury: A systemic review and meta-analysis. J Nephrol. 2015;28(1):7-16. EDN: YZOJLD doi: 10.1007/s40620-014-0113-9
  23. Wang S, Zhang Z, Wang J, Miao H. MiR-107 induces TNF-α secretion in endothelial cells causing tubular cell injury in patients with septic acute kidney injury. Biochem Biophys Res Commun. 2017;483(1):45-51. doi: 10.1016/j.bbrc.2017.01.013
  24. Yamamoto T, Noiri E, Ono Y, et al. Renal L-type fatty acid-binding protein in acute ischemic injury. J Am Soc Nephrol. 2007;18(11):2894-2902. doi: 10.1681/ASN.2007010097
  25. Schrezenmeier EV, Barasch J, Budde K, et al. Biomarkers in acute kidney injury--pathophysiological basis and clinical performance. Acta Physiologica. 2017;219(3):556-574. EDN: YVTLYF doi: 10.1111/apha.12764
  26. Fagerberg L, Hallström BM, Oksvold P, et al. Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics. Mol Cell Proteomics. 2014;13(2):397-406. EDN: MTOMUS doi: 10.1074/mcp.M113.035600
  27. Ortega LM, Heung M. The use of cell cycle arrest biomarkers in the early detection of acute kidney injury. Is this the new renal troponin? Nefrología (Engl Ed). 2018;38(4):361-367. doi: 10.1016/j.nefro.2017.11.013
  28. Emlet DR, Pastor-Soler N, Marciszyn A, et al. Insulin-like growth factor binding protein 7 and tissue inhibitor of metalloproteinases-2: Differential expression and secretion in human kidney tubule cells. Am J Physiol Renal Physiol. 2017;312(2):F284-296. EDN: YXCIST doi: 10.1152/ajprenal.00271.2016
  29. Johnson AC, Zager RA. Mechanisms underlying increased TIMP2 and IGFBP7 urinary excretion in experimental AKI. J Am Soc Nephrol. 2018;29(8):2157-2167. doi: 10.1681/ASN.2018030265
  30. Lane BR, Babitz SK, Vlasakova K, et al. Evaluation of urinary renal biomarkers for early prediction of acute kidney injury following partial nephrectomy: A feasibility study. Eur Urol Focus. 2020;6(6):1240-1247. doi: 10.1016/j.euf.2018.10.017
  31. George B, Szilagyi JT, Joy MS, Aleksunes LM. Regulation of renal calbindin expression during cisplatin-induced kidney injury. J Biochem Mol Toxicol. 2022;36(7):e23068. EDN: FQRRTU doi: 10.1002/jbt.23068
  32. Vittori M, Baroni S, Ferraro PM, et al. Neutrophil gelatinase-associated lipocalin (NGAL) value changes before and after shock wave lithotripsy. Urolithiasis. 2017;45(4):347-351. doi: 10.1007/s00240-016-0932-3
  33. Kardakos IS, Volanis DI, Kalikaki A, et al. Evaluation of neutrophil gelatinase-associated lipocalin, interleukin-18, and cystatin C as molecular markers before and after unilateral shock wave lithotripsy. Urology. 2014;84(4):783-788. doi: 10.1016/j.urology.2014.05.034
  34. Codorniu A, Lemasle L, Legrand M, et al. Methods used to assess the performance of biomarkers for the diagnosis of acute kidney injury: A systematic review and meta-analysis. Biomarkers. 2018;23(8):766-772. doi: 10.1080/1354750X.2018.1493616
  35. Okuda H, Obata Y, Kamijo-Ikemori A, Inoue S. Quantitative and qualitative analyses of urinary L-FABP for predicting acute kidney injury after emergency laparotomy. J Anesth. 2022;36(1):38-45. EDN: AMDCCM doi: 10.1007/s00540-021-03003-w
  36. Griffin BR, Faubel S, Edelstein CL. Biomarkers of drug-induced kidney toxicity. Ther Drug Monit. 2019;41(2):213-226. doi: 10.1097/FTD.0000000000000589
  37. Yang J, Lim SY, Kim MG, et al. Urinary tissue inhibitor of metalloproteinase and insulin-like growth factor-7 as early biomarkers of delayed graft function after kidney transplantation. Transplant Proc. 2017;49(9):2050-2054. doi: 10.1016/j.transproceed.2017.09.023
  38. Gunnerson KJ, Shaw AD, Chawla LS, et al. TIMP2/IGFBP7 biomarker panel accurately predicts acute kidney injury in high-risk surgical patients. J Trauma Acute Care Surg. 2016;80(2):243-249. doi: 10.1097/TA.0000000000000912
  39. George B, Joy MS, Aleksunes LM. Urinary protein biomarkers of kidney injury in patients receiving cisplatin chemotherapy. Exp Biol Med. 2018;243(3):272-282. doi: 10.1177/1535370217745302
  40. Fazel M, Sarveazad A, Mohamed Ali K, et al. Accuracy of urine kidney injury molecule-1 in predicting acute kidney injury in children; a systematic review and meta-analysis. Arch Acad Emerg Med. 2020;8(1):e44.
  41. Ng CF, Lo AK, Lee KW, et al. A prospective, randomized study of the clinical effects of shock wave delivery for unilateral kidney stones: 60 versus 120 shocks per minute. J Urol. 2012;188(3):837-842. doi: 10.1016/j.juro.2012.05.009
  42. Bantis A, Tsakaldimis G, Zissimopoulos A, et al. Can tumor necrosis factor a (TNF-a) and interleukin 6 (IL-6) be used as prognostic markers of infection following ureteroscopic lithrotripsy and extracorporeal shock wave lithotripsy for ureteral stones? Hell J Nucl Med. 2015;18(Suppl 1):160.
  43. Yuan SM. Acute kidney injury after cardiac surgery: Risk factors and novel biomarkers. Braz J Cardiovasc Surg. 2019;34(3):352-360. doi: 10.21470/1678-9741-2018-0212
  44. Gan J, Zhou X. Comparison of urine neutrophil gelatinase-associated lipocalin and interleukin-18 in prediction of acute kidney injury in adults. Medicine. 2018;97(39):e12570. doi: 10.1097/MD.0000000000012570
  45. Pan HC, Yang SY, Chiou TT, et al. Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: A systematic review and meta-analysis. Crit Care. 2022;26(1):349. EDN: HEITPL doi: 10.1186/s13054-022-04223-6
  46. Clark DL, Connors BA, Evan AP, et al. Effect of shock wave number on renal oxidative stress and inflammation. BJU Int. 2011;107(2):318-322. doi: 10.1111/j.1464-410X.2010.09311.x
  47. Goktas C, Coskun A, Bicik Z, et al. Evaluating ESWL-induced renal injury based on urinary TNF-α, IL-1α, and IL-6 levels. Urol Res. 2012;40(5):569-573. doi: 10.1007/s00240-012-0467-1
  48. Milišić E, Zvizdić Z, Jonuzi A, et al. Short-term changes in renal function in children and adolescents undergoing extracorporeal shock wave lithotripsy. Med Glas (Zenica). 2019;16(2):224-230. doi: 10.17392/1036-19

补充文件

附件文件
动作
1. JATS XML
下载
2. Fig. 1. Remote shock wave lithotripsy impact at NGAL concentration in the urine: 1st checkpoint — before the study; 2nd checkpoint — 45 min after the procedure; 3rd checkpoint — 24 hours after the procedure. The data are presented as a median, p <0.026, Friedman’s criterion.

下载 (62KB)
索引源数据
3. Fig. 2. Remote shock wave lithotripsy impact at L-FABP concentration in the urine: 1st checkpoint — before the study; 2nd checkpoint — 45 min after the procedure; 3rd checkpoint — 24 hours after the procedure. The data are presented as a median, p=0.003, Friedman’s criterion.

下载 (58KB)
索引源数据
4. Fig. 3. Remote shock wave lithotripsy impact at TIMP-2 concentration in the urine: 1st checkpoint — before the study; 2nd checkpoint — 45 min after the procedure; 3rd checkpoint — 24 hours after the procedure. The data are presented as a median, p <0.001, Friedman’s criterion.

下载 (64KB)
索引源数据
5. Fig. 4. Remote shock wave lithotripsy impact at calbindin-D concentration in the urine: 1st checkpoint — before the study; 2nd checkpoint — 45 min after the procedure; 3rd checkpoint — 24 hours after the procedure. The data are presented as a median, p <0.001, Friedman’s criterion.

下载 (56KB)
索引源数据
6. Fig. 5. Remote shock wave lithotripsy impact at KIM-1 concentration in the urine: 1st checkpoint — before the study; 2nd checkpoint — 45 min after the procedure; 3rd checkpoint — 24 hours after the procedure. The data are presented as a median, p <0.001, Friedman’s criterion.

下载 (58KB)
索引源数据
7. Fig. 6. Remote shock wave lithotripsy impact at IL-18 concentration in the urine: 1st checkpoint — before the study; 2nd checkpoint — 45 min after the procedure; 3rd checkpoint — 24 hours after the procedure. The data are presented as a median, p=0.037, Friedman’s criterion.

下载 (61KB)
索引源数据
8. Fig. 7. Remote shock wave lithotripsy impact at TNF-a concentration in the urine: 1st checkpoint — before the study; 2nd checkpoint — 45 min after the procedure; 3rd checkpoint — 24 hours after the procedure. The data are presented as a median, p <0.001, Friedman’s criterion.

下载 (56KB)
索引源数据
9. Fig. 8. Remote shock wave lithotripsy impact at IGFBP-7 concentration in the urine: 1st checkpoint — before the study; 2nd checkpoint — 45 min after the procedure; 3rd checkpoint — 24 hours after the procedure. The data are presented as a median, p=0.724, Friedman’s criterion.

下载 (57KB)
索引源数据
10. Fig. 9. Remote shock wave lithotripsy impact at cystatin-C concentration in the urine: 1st checkpoint — before the study; 2nd checkpoint — 45 min after the procedure; 3rd checkpoint — 24 hours after the procedure. The data are presented as a median, p <0.001, Friedman’s criterion.

下载 (60KB)
索引源数据

版权所有 © Zorkin S.N., Nikulin O.D., Semikina E.L., Snovskaya M.A., Shakhnovskiy D.S., Bayazitov R.R., 2023

##common.cookie##