Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter September 28, 2020

Influence of patients’ clinical features at intensive care unit admission on performance of cell cycle arrest biomarkers in predicting acute kidney injury

  • Bo Yang EMAIL logo , Yun Xie , Francesco Garzotto , Ghada Ankawi , Alberto Passannante , Alessandra Brendolan , Raffaele Bonato , Mariarosa Carta , Davide Giavarina , Enrico Vidal , Dario Gregori ORCID logo and Claudio Ronco ORCID logo

Abstract

Objectives

Identification of acute kidney injury (AKI) can be challenging in patients with a variety of clinical features at intensive care unit (ICU) admission, and the capacity of biomarkers in this subpopulation has been poorly studied. In our study we examined the influence that patients’ clinical features at ICU admission have over the predicting ability of the combination of urinary tissue inhibitor of metalloproteinase-2 (TIMP2) and insulin-like growth factor binding protein 7 (IGFBP7).

Methods

Urinary [TIMP2]•[IGFBP7] were measured for all patients upon admission to ICU. We calculated the receiver operating characteristics (ROC) curves for AKI prediction in the overall cohort and for subgroups of patients according to etiology of ICU admission, which included: sepsis, trauma, neurological conditions, cardiovascular diseases, respiratory diseases, and non-classifiable causes.

Results

In the overall cohort of 719 patients, 239 (33.2%) developed AKI in the first seven days. [TIMP2]•[IGFBP7] at ICU admission were significantly higher in AKI patients than in non-AKI patients. This is true not only for the overall cohort but also in the other subgroups. The area under the ROC curve (AUC) for [TIMP2]•[IGFBP7] in predicting AKI in the first seven days was 0.633 (95% CI 0.588–0.678), for the overall cohort, with sensitivity and specificity of 66.1 and 51.9% respectively. When we considered patients with combined sepsis, trauma, and respiratory disease we found a higher AUC than patients without these conditions (0.711 vs. 0.575; p=0.002).

Conclusions

The accuracy of [TIMP2]•[IGFBP7] in predicting the risk of AKI in the first seven days after ICU admission has significant variability when the reason for ICU admission is considered.


Corresponding author: Bo Yang, Department of Nephrology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, PR China; and International Renal Research Institute of Vicenza, San Bortolo Hospital, Viale Rodolfi 37, 36100Vicenza, Italy, E-mail:

Acknowledgments

The authors are grateful to Gregorio Aramid Romero González, Alejandra Molano Trivino, Ana De Castro, and all the fellows of the International Renal Research Institute of Vicenza who helped in the study.

  1. Research funding: None declared.

  2. Author contributions: CR, BY, YX, FG and RB contributed to study design. BY, YX, GA and AP contributed to data collection. AB and FF contributed to patient enrollment. DG and MC contributed to laboratory work. FG, EV and GD contributed to statistical analysis. BY, GA, AP and CR contributed to manuscript writing and editing. All authors read and approved the final manuscript. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: CR is a consultant for Astute Medical, Ortho, and Biomerieux. All the other authors declared no competing interests.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: The study was approved by the Institutional Ethics Committee of San Bortolo Hospital, Vicenza, Italy (Comitato Etico provinciale aULSS 8 Vicenza) (Exp. number: 03/17). The clinical investigation was conducted according to the principles expressed in the Declaration of Helsinki.

References

1. Susantitaphong, P, Cruz, DN, Cerda, J, Abulfaraj, M, Alqahtani, F, Koulouridis, I, et al. World incidence of AKI: a meta-analysis. Clin J Am Soc Nephrol 2013;8:1482–93. https://doi.org/10.2215/cjn.00710113.Search in Google Scholar

2. Ronco, C, Ricci, Z. The concept of risk and the value of novel markers of acute kidney injury. Crit Care 2013;17:117. https://doi.org/10.1186/cc12488.Search in Google Scholar PubMed PubMed Central

3. Balasubramanian, G, Al-Aly, Z, Moiz, A, Rauchman, M, Zhang, Z, Gopalakrishnan, R, et al. Early nephrologist involvement in hospital-acquired acute kidney injury: a pilot study. Am J Kidney Dis 2011;57:228–34. https://doi.org/10.1053/j.ajkd.2010.08.026.Search in Google Scholar PubMed

4. Colpaert, K, Hoste, EA, Steurbaut, K, Benoit, D, Van Hoecke, S, De Turck, F, et al. Impact of real-time electronic alerting of acute kidney injury on therapeutic intervention and progression of RIFLE class. Crit Care Med 2012;40:1164–70. https://doi.org/10.1097/ccm.0b013e3182387a6b.Search in Google Scholar

5. Kidney Disease Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int Suppl 2012;2:1–138. https://doi.org/10.1038/kisup.2012.2.Search in Google Scholar PubMed PubMed Central

6. Bellomo, R, Ronco, C, Kellum, JA, Mehta, RL, Palevsky, P. Acute Dialysis Quality Initiative Workgroup. Acute renal failure – definition, outcome measures, animal models, fluid therapy and information technology needs: the second international consensus conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care 2004;8:R204–12. https://doi.org/10.1186/cc2872.Search in Google Scholar PubMed PubMed Central

7. Waikar, SS, Bonventre, JV. Creatinine kinetics and the definition of acute kidney injury. J Am Soc Nephrol 2009;20:672–9. https://doi.org/10.1681/asn.2008070669.Search in Google Scholar PubMed PubMed Central

8. Endre, ZH, Kellum, JA, Di Somma, S, Doi, K, Goldstein, SL, Koyner, JL, et al. Differential diagnosis of AKI in clinical practice by functional and damage biomarkers: workgroup statements from the tenth acute dialysis quality initiative consensus conference. Contrib Nephrol 2013;182:30–44. https://doi.org/10.1159/000349964.Search in Google Scholar PubMed

9. US Food and Drug Administration. Letter to Astute Medical September 5, 2014. Available from: http://www.accessdata.fda.gov/cdrh_docs/pdf13/den130031.pdf [Accessed 19 July 2016].Search in Google Scholar

10. Kashani, K, Al-Khafaji, A, Ardiles, T, Artigas, A, Bagshaw, SM, Bell, M, et al. Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit Care 2013;17:R25. https://doi.org/10.1186/cc12503.Search in Google Scholar PubMed PubMed Central

11. Hoste, EA, McCullough, PA, Kashani, K, Chawla, LS, Joannidis, M, Shaw, AD, et al. Derivation and validation of cutoffs for clinical use of cell cycle arrest biomarkers. Nephrol Dial Transplant 2014;29:2054–61. https://doi.org/10.1093/ndt/gfu292.Search in Google Scholar PubMed PubMed Central

12. Bihorac, A, Chawla, LS, Shaw, AD, Al-Khafaji, A, Davison, DL, Demuth, GE, et al. Validation of cell-cycle arrest biomarkers for acute kidney injury using clinical adjudication. Am J Respir Crit Care Med 2014;189:932–9. https://doi.org/10.1164/rccm.201401-0077oc.Search in Google Scholar PubMed

13. Di Leo, L, Nalesso, F, Garzotto, F, Xie, Y, Yang, B, Virzì, GM, et al. Predicting acute kidney injury in intensive care unit patients: the role of tissue inhibitor of metalloproteinases-2 and insulin-like growth factor-binding protein-7 biomarkers. Blood Purif 2018;45:270–7. https://doi.org/10.1159/000485591.Search in Google Scholar PubMed

14. Zhang, D, Yuan, Y, Guo, L, Wang, Q. Comparison of urinary TIMP-2 and IGFBP7 cut-offs to predict acute kidney injury in critically ill patients: a PRISMA-compliant systematic review and meta-analysis. Medicine 2019;98:e16232. https://doi.org/10.1097/md.0000000000016232.Search in Google Scholar PubMed PubMed Central

15. National Institute for Health and Care Excellence. NICE guidance. Available from: https://www.nice.org.uk/guidance/dg39/chapter/3-Evidence [Accessed 17 June 2020].Search in Google Scholar

16. Lameire, NH, Vanholder, RC, Van Biesen, WA. How to use biomarkers efficiently in acute kidney injury. Kidney Int 2011;79:1047–50. https://doi.org/10.1038/ki.2011.21.Search in Google Scholar PubMed

17. Bagshaw, SM, Uchino, S, Bellomo, R, Morimatsu, H, Morgera, S, Schetz, M, et al. Septic acute kidney injury in critically ill patients: clinical characteristics and outcomes. Clin J Am Soc Nephrol 2007;2:431–9. https://doi.org/10.2215/cjn.03681106.Search in Google Scholar PubMed

18. Kellum, JA, Chawla, LS, Keener, C, Singbartl, K, Palevsky, PM, Pike, FL, et al. The effects of alternative resuscitation strategies on acute kidney injury in patients with septic shock. Am J Resp Crit Care Med 2015;193:281–7. https://doi.org/10.1164/rccm.201505-0995oc.Search in Google Scholar

19. Honore, PM, Nguyen, HB, Gong, M, Chawla, LS, Bagshaw, SM, Artigas, A, et al. Urinary tissue inhibitor of metalloproteinase-2 and insulin-like growth factor-binding protein 7 for risk stratification of acute kidney injury in patients with sepsis. Crit Care Med 2016;44:1851–60. https://doi.org/10.1097/ccm.0000000000001827.Search in Google Scholar

20. Martensson, J, Bell, M, Oldner, A, Xu, S, Venge, P, Martling, CR. Neutrophil gelatinase-associated lipocalin in adult septic patients with and without acute kidney injury. Intensive Care Med 2010;36:1333–40. https://doi.org/10.1007/s00134-010-1887-4.Search in Google Scholar PubMed

21. Parikh, CR, Abraham, E, Ancukiewicz, M, Edelstein, CL. Urine IL-18 is an early diagnostic marker for acute kidney injury and predicts mortality in the intensive care unit. J Am Soc Nephrol 2005;16:3046–52. https://doi.org/10.1681/asn.2005030236.Search in Google Scholar PubMed

22. Brandt, MM, Falvo, AJ, Rubinfeld, IS, Blyden, D, Durrani, NK, Horst, HM. Renal dysfunction in trauma: even a little costs a lot. J Trauma Inj Infect Crit Care 2007;62:1362–4. https://doi.org/10.1097/ta.0b013e318047983d.Search in Google Scholar

23. Bagshaw, SM, George, C, Gibney, RT, Bellomo, R. A multi-center evaluation of early acute kidney injury in critically ill trauma patients. Ren Fail 2008;30:581–9. https://doi.org/10.1080/08860220802134649.Search in Google Scholar PubMed

24. Harrois, A, Libert, N, Duranteau, J. Acute kidney injury in trauma patients. Curr Opin Crit Care 2017;23:447–56. https://doi.org/10.1097/mcc.0000000000000463.Search in Google Scholar PubMed

25. Eriksson, M, Brattström, O, Mårtensson, J, Larsson, E, Oldner, A. Acute kidney injury following severe trauma: risk factors and long-term outcome. J Trauma Acute Care Surg 2015;79:407–12. https://doi.org/10.1097/ta.0000000000000727.Search in Google Scholar

26. Podoll, AS, Kozar, R, Holcomb, JB, Finkel, KW. Incidence and outcome of early acute kidney injury in critically-ill trauma patients. PLoS One 2013;8:e77376. https://doi.org/10.1371/journal.pone.0077376.Search in Google Scholar PubMed PubMed Central

27. Makris, K, Markou, N, Evodia, E, Dimopoulou, E, Drakopoulos, I, Ntetsika, K, et al. Urinary neutrophil gelatinase-associated lipocalin (NGAL) as an early marker of acute kidney injury in critically ill multiple trauma patients. Clin Chem Lab Med 2009;47:79–82. https://doi.org/10.1515/cclm.2009.004.Search in Google Scholar PubMed

28. Robert, R, Reignier, J, Tournoux-Facon, C, Boulain, T, Lesieur, O, Gissot, V, et al. Refusal of intensive care unit admission due to a full unit: impact on mortality. Am J Respir Crit Care Med 2012;185:1081–7. https://doi.org/10.1164/rccm.201104-0729oc.Search in Google Scholar PubMed

29. Heung, M, Ortega, LM, Chawla, LS, Wunderink, RG, Self, WH, Koyner, JL, et al. Common chronic conditions do not affect performance of cell cycle arrest biomarkers for risk stratification of acute kidney injury. Nephrol Dial Transplant 2016;31:1633–40. https://doi.org/10.1093/ndt/gfw241.Search in Google Scholar PubMed PubMed Central

30. Breidthardt, T, Christ-Crain, M, Stolz, D, Bingisser, R, Drexler, B, Klima, T, et al. A combined cardiorenal assessment for the prediction of acute kidney injury in lower respiratory tract infections. Am J Med 2012;125:168–75. https://doi.org/10.1016/j.amjmed.2011.07.010.Search in Google Scholar PubMed

31. Ostermann, M, McCullough, PA, Forni, LG, Bagshaw, SM, Joannidis, M, Shi, J, et al. Kinetics of urinary cell cycle arrest markers for acute kidney injury following exposure to potential renal insults. Crit Care Med 2018;46:375–83. https://doi.org/10.1097/ccm.0000000000002847.Search in Google Scholar

Received: 2020-05-07
Accepted: 2020-09-11
Published Online: 2020-09-28
Published in Print: 2021-02-23

© 2020 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 18.4.2024 from https://www.degruyter.com/document/doi/10.1515/cclm-2020-0670/html
Scroll to top button