Indian Journal of Critical Care Medicine

Register      Login

SEARCH WITHIN CONTENT

FIND ARTICLE

Volume / Issue

Online First

Archive
Related articles

VOLUME 26 , ISSUE 3 ( March, 2022 ) > List of Articles

EDITORIAL

Guessing Game of Patient Outcomes in the Renally Injured Critically Ill: Is There a Perfect Score?

Gautham M Raju

Citation Information : Raju GM. Guessing Game of Patient Outcomes in the Renally Injured Critically Ill: Is There a Perfect Score?. Indian J Crit Care Med 2022; 26 (3):253-255.

DOI: 10.5005/jp-journals-10071-24177

License: CC BY-NC 4.0

Published Online: 30-03-2022

Copyright Statement:  Copyright © 2022; The Author(s).


Abstract

HTML PDF Share
  1. Uchino S, Kellum JA, Bellomo R, Doig GS, Morimatsu H, Morgera S, et al. Acute renal failure in critically ill patients: a multinational, multicenter study. Journal of the American Medical Association 2005;294(7):813–818. DOI: 10.1001/jama.294.7.813.
  2. Bouchard J, Acharya A, Cerda J, Maccariello ER, Madarasu RC, Tolwani AJ, et al. A prospective international multicenter study of AKI in the intensive care unit. Clin J Am Soc Nephrol 2015;10(8):1324–1331. DOI: 10.2215/CJN.04360514.
  3. Odutayo A, Wong CX, Farkouh M, Altman DG, Hopewell S, Emdin CA, et al. AKI and long-term risk for cardiovascular events and mortality. J Am Soc Nephrol 2017;28(1):377–387. DOI: 10.1681/ASN.2016010105.
  4. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med 1985;13(10): 818–829. PMID: 3928249.
  5. Kidney Disease Improving Global Outcomes (KDIGO) AKI Work Group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int Suppl 2012;2:1–138. DOI:10.1038/kisup.2012.7.
  6. Kapadia MP, Kamdar KP, Jha PR. A study of clinical profile of patients with acute kidney injury in a tertiary care centre. IJASR [serial online] 2016;2(8):160–166. DOI: 10.7439/ijasr.v2i8.3511.
  7. Chawla LS, Abell L, Mazhari R, Egan M, Kadambi N, Burke HB, et al. Identifying critically ill patients at high risk for developing acute renal failure: a pilot study. Kidney Int 2005;68(5):2274–2280. DOI: 10.1111/j.1523-1755.2005.00686.x.
  8. Alba AC, Agoritsas T, Walsh M, Hanna S, Iorio A, Devereaux PJ, et al. Discrimination and calibration of clinical prediction models: users’ guides to the medical literature. Journal of the American Medical Association 2017;318(14):1377–1384. DOI: 10.1001/jama.2017.12126.
  9. Pencina MJ, D'Agostino RB Sr. Evaluating discrimination of risk prediction models: the C statistic. Journal of the American Medical Association 2015;314(10):1063–1064. DOI: 10.1001/jama.2015.11082.
  10. Van Calster B, Nieboer D, Vergouwe Y, De Cock B, Pencina MJ, Steyerberg EW. A calibration hierarchy for risk models was defined: from utopia to empirical data. J Clin Epidemiol 2016;74:167–176. DOI: 10.1016/j.jclinepi.2015.12.005.
  11. Chu R, Li C, Wang S, Zou W, Liu G, Yang L, et al. Assessment of KDIGO definitions in patients with histopathologic evidence of acute renal disease. Clin J Am Soc Nephrol 2014;9(7):1175–1182. DOI: 10.2215/CJN.06150613.
  12. Costa e Silva VT, de Castro I, Liaño F, Muriel A, Rodríguez-Palomares JR, Yu L. Performance of the third-generation models of severity scoring systems (APACHE IV, SAPS 3 and MPM-III) in acute kidney injury critically ill patients. Nephrol Dial Transplant 2011;26(12):3894–3901. DOI: 10.1093/ndt/gfr201.
  13. Wang H, Kang X, Shi Y, Bai ZH, Lv JH, Sun JL, et al. SOFA score is superior to APACHE-II score in predicting the prognosis of critically ill patients with acute kidney injury undergoing continuous renal replacement therapy. Ren Fail 2020;42(1):638–645. DOI: 10.1080/0886022X.2020.1788581.
  14. Patel P, Gupta S, Patel H, Bashar MD. A. Assessment of APACHE II Score to Predict ICU Outcomes of Patients with AKI: A Single Center Experience from Haryana, North India. Indian J Crit Care Med 2022;26(3):276–281.
PDF Share
PDF Share

© Jaypee Brothers Medical Publishers (P) LTD.