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

NCT ID: NCT03880110

Last Updated: 2021-06-30

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

1000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-05-20

Study Completion Date

2021-11-30

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Acute Kidney Injury

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Peking University First Hospital

OTHER

Sponsor Role lead

Responsible Party

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Li Yang

Principal Investigator, Clinical Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Peking University First Hospital

Beijing, Beijing Municipality, China

Site Status RECRUITING

Countries

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China

Central Contacts

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Shuangling Li, MD

Role: CONTACT

+861083575263

Nan Li, MD

Role: CONTACT

+861083572623

Facility Contacts

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Shuangling Li

Role: primary

+861083575263

References

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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.

Reference Type BACKGROUND
PMID: 26337133 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 28076311 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 23388612 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 24559465 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 25798585 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 26816218 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 25943719 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 26806004 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 27133237 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 25014511 (View on PubMed)

Li N, Wang J, Zhou W, Li S, Yang L. External Validation of the Simple Postoperative Acute Kidney Injury Risk Index in Patients Admitted to the Intensive Care Unit After Noncardiac Surgery. Anesth Analg. 2025 May 1;140(5):1140-1148. doi: 10.1213/ANE.0000000000007320.

Reference Type DERIVED
PMID: 39919018 (View on PubMed)

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.

Reference Type DERIVED
PMID: 35610195 (View on PubMed)

Other Identifiers

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Early predicting AKI

Identifier Type: -

Identifier Source: org_study_id

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