Early Prediction of Acute Kidney Injury in High Risk Patients After Non-cardiac Surgery

Combination of Biomarkers, Urine Sedimentation and Renal Resistive Index for Early Prediction of Acute Kidney Injury in High Risk Patients After Non-cardiac Surgery: a Prospective Observational Cohort Study

Acute kidney injury (AKI) is a common complication after non-cardiac surgery with adverse short and long term morbidity and mortality. So far there have been no effective therapy for AKI treatment developed, possibly due to the heterogenicity of this syndrome. Therefore, prevention of AKI in high risk patients undergoing non-cardiac surgery, as emphasized by Kidney Disease Improving Global Outcomes (KDIGO), becomes the first priority. However, early prediction of AKI is the first step before taking preventive measures, which really make a great challenge to clinical practitioners because of such a limited time window and complex clinical scenarios. Recently, cumulative evidence have shown that biomarkers and renal ultrasound may play an important role in AKI prediction after non-cardiac surgery. The purpose of this study is to investigate the combination of biomarkers, urine sedimentation and renal resistive index for early prediction of AKI in high risk patients undergoing non-cardiac surgery.

Study Overview

• Status: Recruiting
• Conditions: Acute Kidney Injury

Detailed Description

Early prediction of AKI have long been a study hotspot. Various clinical prediction models, biomarkers, urine sedimentation scores and imaging tools are developed and validated in different clinical settings mainly focusing on contrast associated AKI, durg induced AKI and cardiac surgery associated AKI. Due to the heterogenicity of this syndrome, one parameter which fits all patients for prediction of AKI dose not possibly exist. As a result, searching for combination parameters that can well predict AKI after non-cardiac surgery become the first priority for prevention of AKI. Evidence in non-cardiac surgery population have been gradually accumulated in recent years. Biomarkers for G1 cell cycle arrest, e.g. tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin like growth factor binding protein-7 (IGFBP-7), have demonstrated robust predictive performance in high risk surgical patients. Renal resistive index as calculated by ultrasound have also showed its validity in AKI prediction in patients following orthopedic surgery. Hence, the investigators make an assumption that combination of biomarkers, urine sedimentation and renal resistive index may improve the predictive value of AKI after non-cardiac surgery. The purpose of this study is to investigate the combination of biomarkers, urine sedimentation and renal resistive index for early prediction of AKI in high risk patients undergoing non-cardiac surgery.

Adult patients undergoing non-cardiac surgery and then admitting to surgical intensive care unit (SICU) will be immediately screened for this study. After enrollment, blood and urine samples, in addition to clinical routine tests, will be collected for the tests of biomarkers and urine sedimentation, such as serum creatinine, TIMP-2, IGFBP-7, α-1 microglobulin, microalbumin, transferrin, granular cast and so on. Meanwhile, central venous pressure (CVP) will be measured by primary nurse. If the patients were enrolled at daytime between 8:00-16:00, experienced intensivists will also calculate the renal resistive index (RI) by ultrasound. Urine samples will be collected again for storage after 6 and 12 hours admitting to SICU, at which time urine sedimentation and CVP will be repeatedly measured at the discretion of physician in-charge. AKI is monitored by serum creatinine daily in SICU and on demand in general wards, and by urine output (UO) every 3 hours in SICU. Patients will be followed up for postoperative complications, renal recovery, survival, SICU/in hospital stay and total cost until the first thing that happens: discharge/death, 30d after operation or withdrawing the study. Perioperative data will be recorded by specialized researchers.

• Study Type: Observational
• Enrollment (Anticipated): 1000

Contacts and Locations

• Study Contact: Name: Shuangling Li, MD; Phone Number: +861083575263; Email: lishuangling888@hotmail.com
• Study Contact Backup: Name: Nan Li, MD; Phone Number: +861083572623; Email: iculinan@163.com

Study Locations

• China
  • Beijing
    • Beijing, Beijing, China, 010
      • Recruiting
      • Peking University First Hospital
      • Contact: Shuangling Li; Phone Number: +861083575263; Email: lishuangling888@hotmail.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

High risk patients undergoing non-cardiac surgery

Description

Inclusion Criteria:

• Age ≥ 18 years; Undergoing non-cardiac surgery; Admitted to SICU immediately after surgery

Exclusion Criteria:

• Chronic kidney disease stage 5 (CKD-5) or requiring long-term dialysis; Undergoing kidney-related surgery; AKI before admission to SICU; Without Foley catheter placement ;Written informed consent not obtained

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Incidence of acute kidney injury within 7 days after surgery	AKI is diagnosed according to KDIGO criteria	within 7 days after surgery

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Severity of acute kidney injury within 7 days after surgery	AKI is classified according to KDIGO criteria	within 7 days after surgery
Incidence of postoperative complications	Defined as newly onset medical conditions that are harmful to patients' recovery and required therapeutic intervention, including pulmonary infection, pleural effusion, atelectasis, respiratory failure, surgical bleeding, new onset arrhythmia, acute myocardial infarction, congestive heart failure, stroke, ileus, liver injury, digestive tract bleeding, wound infection, urinary tract infection, severe sepsis, acute kidney injury, pulmonary embolism and deep venous thrombosis.	30 days after operation or withdrawing the study ( the first thing that happens: discharge/death)
Rate of ICU or in-hospital mortality	ICU/In-hospital mortality	30 days after operation or withdrawing the study ( the first thing that happens: discharge/death)
Rate of dialysis dependent at discharge	Defined as requiring any modality of renal replacement therapy at discharge	Until the first thing that happens: discharge/death, 30 days after operation or withdrawing the study.
Rate of continuous decreased kidney function at discharge	Estimated glomerular filtration rate (eGFR) decreased more than 25% of baseline value at discharge	30 days after operation or withdrawing the study ( the first thing that happens: discharge/death)
Rate of major adverse kidney events (MAKE)	Defined as a composite of death, dialysis dependent or continuous decreased kidney function	30 days after operation or withdrawing the study ( the first thing that happens: discharge/death)

Collaborators and Investigators

• Sponsor: Peking University First Hospital

Publications and helpful links

General Publications

• Bihorac A, Chawla LS, Shaw AD, Al-Khafaji A, Davison DL, Demuth GE, Fitzgerald R, Gong MN, Graham DD, Gunnerson K, Heung M, Jortani S, Kleerup E, Koyner JL, Krell K, Letourneau J, Lissauer M, Miner J, Nguyen HB, Ortega LM, Self WH, Sellman R, Shi J, Straseski J, Szalados JE, Wilber ST, Walker MG, Wilson J, Wunderink R, Zimmerman J, Kellum JA. Validation of cell-cycle arrest biomarkers for acute kidney injury using clinical adjudication. Am J Respir Crit Care Med. 2014 Apr 15;189(8):932-9. doi: 10.1164/rccm.201401-0077OC.
• Kashani K, Al-Khafaji A, Ardiles T, Artigas A, Bagshaw SM, Bell M, Bihorac A, Birkhahn R, Cely CM, Chawla LS, Davison DL, Feldkamp T, Forni LG, Gong MN, Gunnerson KJ, Haase M, Hackett J, Honore PM, Hoste EA, Joannes-Boyau O, Joannidis M, Kim P, Koyner JL, Laskowitz DT, Lissauer ME, Marx G, McCullough PA, Mullaney S, Ostermann M, Rimmele T, Shapiro NI, Shaw AD, Shi J, Sprague AM, Vincent JL, Vinsonneau C, Wagner L, Walker MG, Wilkerson RG, Zacharowski K, Kellum JA. Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit Care. 2013 Feb 6;17(1):R25. doi: 10.1186/cc12503.
• Grams ME, Sang Y, Coresh J, Ballew S, Matsushita K, Molnar MZ, Szabo Z, Kalantar-Zadeh K, Kovesdy CP. Acute Kidney Injury After Major Surgery: A Retrospective Analysis of Veterans Health Administration Data. Am J Kidney Dis. 2016 Jun;67(6):872-80. doi: 10.1053/j.ajkd.2015.07.022. Epub 2015 Sep 1.
• Kashani K, Cheungpasitporn W, Ronco C. Biomarkers of acute kidney injury: the pathway from discovery to clinical adoption. Clin Chem Lab Med. 2017 Jul 26;55(8):1074-1089. doi: 10.1515/cclm-2016-0973.
• Gocze I, Koch M, Renner P, Zeman F, Graf BM, Dahlke MH, Nerlich M, Schlitt HJ, Kellum JA, Bein T. Urinary biomarkers TIMP-2 and IGFBP7 early predict acute kidney injury after major surgery. PLoS One. 2015 Mar 23;10(3):e0120863. doi: 10.1371/journal.pone.0120863. eCollection 2015.
• Gunnerson KJ, Shaw AD, Chawla LS, Bihorac A, Al-Khafaji A, Kashani K, Lissauer M, Shi J, Walker MG, Kellum JA; Sapphire Topaz investigators. TIMP2*IGFBP7 biomarker panel accurately predicts acute kidney injury in high-risk surgical patients. J Trauma Acute Care Surg. 2016 Feb;80(2):243-9. doi: 10.1097/TA.0000000000000912.
• Perazella MA. The urine sediment as a biomarker of kidney disease. Am J Kidney Dis. 2015 Nov;66(5):748-55. doi: 10.1053/j.ajkd.2015.02.342. Epub 2015 May 2.
• Becker GJ, Garigali G, Fogazzi GB. Advances in Urine Microscopy. Am J Kidney Dis. 2016 Jun;67(6):954-64. doi: 10.1053/j.ajkd.2015.11.011. Epub 2016 Jan 22.
• Marty P, Ferre F, Labaste F, Jacques L, Luzi A, Conil JM, Silva S, Minville V. The Doppler renal resistive index for early detection of acute kidney injury after hip fracture. Anaesth Crit Care Pain Med. 2016 Dec;35(6):377-382. doi: 10.1016/j.accpm.2015.12.013. Epub 2016 Apr 28.
• Marty P, Szatjnic S, Ferre F, Conil JM, Mayeur N, Fourcade O, Silva S, Minville V. Doppler renal resistive index for early detection of acute kidney injury after major orthopaedic surgery: a prospective observational study. Eur J Anaesthesiol. 2015 Jan;32(1):37-43. doi: 10.1097/EJA.0000000000000120.
• Li N, Zhou WJ, Chi DX, Yuan C, Xie M, Li Z, Wang R, Qu CX, Li XY, Li SL, Yang L. Association between urine microscopy and severe acute kidney injury in critically ill patients following non-cardiac surgery: a prospective cohort study. Ann Palliat Med. 2022 Jul;11(7):2327-2337. doi: 10.21037/apm-21-3085. Epub 2022 May 19.

Study record dates

Study Major Dates

• Study Start (Actual): May 20, 2019
• Primary Completion (Anticipated): October 31, 2021
• Study Completion (Anticipated): November 30, 2021

Study Registration Dates

• First Submitted: March 13, 2019
• First Submitted That Met QC Criteria: March 18, 2019
• First Posted (Actual): March 19, 2019

Study Record Updates

• Last Update Posted (Actual): June 30, 2021
• Last Update Submitted That Met QC Criteria: June 28, 2021
• Last Verified: June 1, 2021

More Information

Terms related to this study

• Keywords: Biomarker; Acute Kidney Injury; Non cardiac surgery; Early prediction; Renal resistive index; Urine sedimentation
• Additional Relevant MeSH Terms: Kidney Diseases; Urologic Diseases; Renal Insufficiency; Wounds and Injuries; Acute Kidney Injury
• Other Study ID Numbers: Early predicting AKI

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No