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Clinical Trials/NCT04705064
NCT04705064
Unknown
Not Applicable

Development and Prospective Validation of an Artificial Intelligence Model to Predict Postoperative Acute Kidney Injury

Seoul National University Hospital1 site in 1 country2,000 target enrollmentMarch 1, 2021

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Non-cardiac Surgery
Sponsor
Seoul National University Hospital
Enrollment
2000
Locations
1
Primary Endpoint
the incidence of postoperative acute kidney injury
Last Updated
5 years ago

Overview

Brief Summary

The main objective of this study is to develop and validate an artificial intelligence model that predicts postoperative acute kidney injury.

Detailed Description

Postoperative acute kidney injury is known to increase the length of hospital stay and healthcare cost. A lot of risk prediction models have been developed for identifying patients at increased risk of postoperative acute kidney injury. Recent advances in artificial intelligence make it possible to manage and analyze big data. Prediction model using an artificial intelligence and large-scale data can improve the accuracy of prediction performance. Furthermore, the use of an artificial intelligence may be a useful adjuvant tool in making clinical decisions or real-time prediction if it is integrated into the electrical medical record systems. However, before implementing an artificial intelligence model into the clinical setting, prospective evaluation of an artificial intelligence model's real performance is essential. However, to our knowledge, there was no artificial intelligence model for prediction of postoperative acute kidney injury, which was prospectively evaluated. Therefore, we aimed to develop an artificial intelligence model which predicts postoperative acute kidney injury and evaluate the model's performance prospectively.

Registry
clinicaltrials.gov
Start Date
March 1, 2021
End Date
February 1, 2022
Last Updated
5 years ago
Study Type
Observational
Sex
All

Investigators

Responsible Party
Principal Investigator
Principal Investigator

Hyung-Chul Lee

Assistant professor

Seoul National University Hospital

Eligibility Criteria

Inclusion Criteria

  • Adults patients undergoing non-cardiac surgery

Exclusion Criteria

  • Age under 18 years
  • Surgery duration \< 1 hour
  • Transplantation surgery
  • Nephrectomy
  • Cardiac surgery
  • Patients who had severe kidney dysfunction preoperatively as follows:
  • Serum creatinine ≥ 4 mg/dl
  • Estimated glomerular filtration rate \<15 ml/min/1.73m2
  • History of renal replacement therapy
  • Patients who had no results of preoperative or postoperative serum creatinine

Outcomes

Primary Outcomes

the incidence of postoperative acute kidney injury

Time Frame: during the postoperative seven days

postoperative acute kidney injury (diagnosed by KDIGO criteria using peak serum creatinine level) included all acute kidney injury events regardless of acute kidney injury severity

Study Sites (1)

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