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Original Research

Application of Machine Learning Algorithms to Predict Acute Kidney Injury in Elderly Orthopedic Postoperative Patients

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Pages 317-330 | Published online: 31 Mar 2022

References

  • Baek SH, Lee SW, Kim SW, et al. Frailty as a predictor of acute kidney injury in hospitalized elderly patients: a single center, retrospective cohort study. PLoS One. 2016;11(6):e0156444. doi:10.1371/journal.pone.0156444
  • Bouloussa H, Alzakri A, Ghailane S, et al. Is it safe to perform lumbar spine surgery on patients over eighty five? Int Orthop. 2017;41(10):2091–2096. doi:10.1007/s00264-017-3555-6
  • Jämsä P, Jämsen E, Huhtala H, et al. Moderate to severe renal insufficiency is associated with high mortality after hip and knee replacement. Clin Orthop Relat Res. 2018;476(6):1284–1292. doi:10.1007/s11999.0000000000000256
  • Gharaibeh KA, Hamadah AM, Sierra RJ, et al. The rate of acute kidney injury after total hip arthroplasty is low but increases significantly in patients with specific comorbidities. J Bone Joint Surg Am. 2017;99(21):1819–1826. doi:10.2106/JBJS.16.01027
  • Stevens PE, Levin A. Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Ann Intern Med. 2013;158(11):825–830. doi:10.7326/0003-4819-158-11-201306040-00007
  • Wu Y, Rao K, Liu J, et al. Machine learning algorithms for the prediction of central lymph node metastasis in patients with papillary thyroid cancer. Front Endocrinol (Lausanne). 2020;11:577537. doi:10.3389/fendo.2020.577537
  • Zimmerman LP, Reyfman PA, Smith ADR, et al. Early prediction of acute kidney injury following ICU admission using a multivariate panel of physiological measurements. BMC Med Inform Decis Mak. 2019;19(Suppl 1):16. doi:10.1186/s12911-019-0733-z
  • Zhang Z. Machine learning method for the management of acute kidney injury: more than just treating biomarkers individually. Biomark Med. 2019;13(15):1251–1253. doi:10.2217/bmm-2019-0363
  • Luo XQ, Yan P, Zhang NY, et al. Machine learning for early discrimination between transient and persistent acute kidney injury in critically ill patients with sepsis. Sci Rep. 2021;11(1):20269. doi:10.1038/s41598-021-99840-6
  • Zhang Z, Ho KM, Hong Y. Machine learning for the prediction of volume responsiveness in patients with oliguric acute kidney injury in critical care. Crit Care. 2019;23(1):112. doi:10.1186/s13054-019-2411-z
  • Biteker M, Dayan A, Tekkeşin Aİ, et al. Incidence, risk factors, and outcomes of perioperative acute kidney injury in noncardiac and nonvascular surgery. Am J Surg. 2014;207(1):53–59. doi:10.1016/j.amjsurg.2013.04.006
  • Grams ME, Sang Y, Coresh J, et al. Acute kidney injury after major surgery: a retrospective analysis of veterans health administration data. Am J Kidney Dis. 2016;67(6):872–880. doi:10.1053/j.ajkd.2015.07.022
  • Slankamenac K, Beck-Schimmer B, Breitenstein S, et al. Novel prediction score including pre- and intraoperative parameters best predicts acute kidney injury after liver surgery. World J Surg. 2013;37(11):2618–2628. doi:10.1007/s00268-013-2159-6
  • Salmasi V, Maheshwari K, Yang D, et al. Relationship between intraoperative hypotension, defined by either reduction from baseline or absolute thresholds, and acute kidney and myocardial injury after noncardiac surgery: a retrospective cohort analysis. Anesthesiology. 2017;126(1):47–65. doi:10.1097/ALN.0000000000001432
  • Long TE, Helgason D, Helgadottir S, et al. Acute kidney injury after abdominal surgery: incidence, risk factors, and outcome. Anesth Analg. 2016;122(6):1912–1920. doi:10.1213/ANE.0000000000001323
  • Sun LY, Wijeysundera DN, Tait GA, et al. Association of intraoperative hypotension with acute kidney injury after elective noncardiac surgery. Anesthesiology. 2015;123(3):515–523. doi:10.1097/ALN.0000000000000765
  • Shander A, Knight K, Thurer R, et al. Prevalence and outcomes of anemia in surgery: a systematic review of the literature. Am J Med. 2004;116(Suppl 7A):58s–69s. doi:10.1016/j.amjmed.2003.12.013
  • Kheterpal S, Tremper KK, Heung M, et al. Development and validation of an acute kidney injury risk index for patients undergoing general surgery: results from a national data set. Anesthesiology. 2009;110(3):505–515. doi:10.1097/ALN.0b013e3181979440
  • Moore PK, Hsu RK, Liu KD. Management of acute kidney injury: core curriculum 2018. Am J Kidney Dis. 2018;72(1):136–148. doi:10.1053/j.ajkd.2017.11.021
  • Hulsen T, Jamuar SS, Moody AR, et al. From big data to precision medicine. Front Med (Lausanne). 2019;6:34. doi:10.3389/fmed.2019.00034
  • Ngiam KY, Khor IW. Big data and machine learning algorithms for health-care delivery. Lancet Oncol. 2019;20(5):e262–e273. doi:10.1016/S1470-2045(19)30149-4
  • Romagnoli S, Ricci Z. Postoperative acute kidney injury. Minerva Anestesiol. 2015;81(6):684–696.
  • Liu BC, Tang RN, Liu ZH. Current clinical research of acute kidney injury in China. Chin Med J (Engl). 2015;128(9):1268–1271. doi:10.4103/0366-6999.156148
  • Ali Vial IA, Babar T, Boutros I. Incidence and risk factors of acute kidney injury after total joint arthroplasty; a retrospective cohort study. J Clin Orthop Trauma. 2020;11(Suppl 2):S255–s259. doi:10.1016/j.jcot.2019.10.012
  • Bucaloiu ID, Kirchner HL, Norfolk ER, et al. Increased risk of death and de novo chronic kidney disease following reversible acute kidney injury. Kidney Int. 2012;81(5):477–485. doi:10.1038/ki.2011.405
  • Kheterpal S, Tremper KK, Englesbe MJ, et al. Predictors of postoperative acute renal failure after noncardiac surgery in patients with previously normal renal function. Anesthesiology. 2007;107(6):892–902. doi:10.1097/01.anes.0000290588.29668.38
  • Grams ME, Sang Y, Ballew SH, et al. A meta-analysis of the association of estimated GFR, albuminuria, age, race, and sex with acute kidney injury. Am J Kidney Dis. 2015;66(4):591–601. doi:10.1053/j.ajkd.2015.02.337
  • Bell S, Dekker FW, Vadiveloo T, et al. Risk of postoperative acute kidney injury in patients undergoing orthopaedic surgery–development and validation of a risk score and effect of acute kidney injury on survival: observational cohort study. BMJ. 2015;351:h5639. doi:10.1136/bmj.h5639
  • Weingarten TN, Gurrieri C, Jarett PD, et al. Acute kidney injury following total joint arthroplasty: retrospective analysis. Can J Anaesth. 2012;59(12):1111–1118. doi:10.1007/s12630-012-9797-2
  • Panitchote A, Mehkri O, Hastings A, et al. Factors associated with acute kidney injury in acute respiratory distress syndrome. Ann Intensive Care. 2019;9(1):74. doi:10.1186/s13613-019-0552-5
  • Liu L, Liang Y, Li H, et al. Association between diabetes mellitus and contrast-associated acute kidney injury: a systematic review and meta-analysis of 1.1 million contrast exposure patients. Nephron. 2021;145:1–11.
  • Li N, Qiao H, Guo JF, et al. Preoperative hypoalbuminemia was associated with acute kidney injury in high-risk patients following non-cardiac surgery: a retrospective cohort study. BMC Anesthesiol. 2019;19(1):171. doi:10.1186/s12871-019-0842-3
  • Fowler AJ, Ahmad T, Phull MK, et al. Meta-analysis of the association between preoperative anaemia and mortality after surgery. Br J Surg. 2015;102(11):1314–1324. doi:10.1002/bjs.9861
  • Karkouti K, Stukel TA, Beattie WS, et al. Relationship of erythrocyte transfusion with short- and long-term mortality in a population-based surgical cohort. Anesthesiology. 2012;117(6):1175–1183. doi:10.1097/ALN.0b013e318271604e
  • Karkouti K, Grocott HP, Hall R, et al. Interrelationship of preoperative anemia, intraoperative anemia, and red blood cell transfusion as potentially modifiable risk factors for acute kidney injury in cardiac surgery: a historical multicentre cohort study. Can J Anaesth. 2015;62(4):377–384. doi:10.1007/s12630-014-0302-y
  • Haase M, Bellomo R, Story D, et al. Effect of mean arterial pressure, haemoglobin and blood transfusion during cardiopulmonary bypass on post-operative acute kidney injury. Nephrol Dial Transplant. 2012;27(1):153–160. doi:10.1093/ndt/gfr275
  • Shander A. Preoperative anemia and its management. Transfus Apher Sci. 2014;50(1):13–15. doi:10.1016/j.transci.2013.12.006
  • Plataki M, Kashani K, Cabello-Garza J, et al. Predictors of acute kidney injury in septic shock patients: an observational cohort study. Clin J Am Soc Nephrol. 2011;6(7):1744–1751. doi:10.2215/CJN.05480610
  • Mathis MR, Naik BI, Freundlich RE, et al. Preoperative risk and the association between hypotension and postoperative acute kidney injury. Anesthesiology. 2020;132(3):461–475. doi:10.1097/ALN.0000000000003063
  • Park S, Cho H, Park S, et al. Simple Postoperative AKI Risk (SPARK) classification before noncardiac surgery: a prediction index development study with external validation. J Am Soc Nephrol. 2019;30(1):170–181. doi:10.1681/ASN.2018070757
  • Lei VJ, Luong T, Shan E, et al. Risk stratification for postoperative acute kidney injury in major noncardiac surgery using preoperative and intraoperative data. JAMA Netw Open. 2019;2(12):e1916921. doi:10.1001/jamanetworkopen.2019.16921
  • Baird DP, Rae F, Beecroft C, et al. Introducing an AKI predictive tool for patients undergoing orthopaedic surgery. BMJ Open Qual. 2019;8(1):e000306. doi:10.1136/bmjoq-2017-000306
  • Neyra JA, Leaf DE. Risk prediction models for acute kidney injury in critically ill patients: opus in progressu. Nephron. 2018;140(2):99–104. doi:10.1159/000490119
  • Trongtrakul K, Patumanond J, Kongsayreepong S, et al. Acute kidney injury risk prediction score for critically-ill surgical patients. BMC Anesthesiol. 2020;20(1):140. doi:10.1186/s12871-020-01046-2
  • Wilson T, Quan S, Cheema K, et al. Risk prediction models for acute kidney injury following major noncardiac surgery: systematic review. Nephrol Dial Transplant. 2016;31(2):231–240. doi:10.1093/ndt/gfv415
  • Malhotra R, Kashani KB, Macedo E, et al. A risk prediction score for acute kidney injury in the intensive care unit. Nephrol Dial Transplant. 2017;32(5):814–822. doi:10.1093/ndt/gfx026