Real-Time Acute Kidney Injury Perioperative Prediction Clinical Trial (NCT07604662)
Prediction of Acute Kidney Injury (AKI) After Surgery: A Pragmatic Three-Arm Cluster-Randomized Trial
🩺 Plain-English Summary (8th-Grade Level)
This investigator-initiated, pragmatic trial evaluates whether displaying a machine learning (ML)- derived perioperative AKI risk score-alone or paired with an interruptive Best/Our Practice Advisory (BPA/OPA)-improves kidney-protective care and reduces kidney injury after non-obstetric surgery at UCSF. Approximately 75-100 attending anesthesiologists (clusters) are randomized 1:1:1 to: (a) Control (risk score hidden), (b) Score Only (visible preoperative AKI risk probability with passive KDIGO bundle recommendation), or (c) Score + BPA (visible risk plus interruptive KDIGO prompt for high-risk patients). CRNAs/residents follow their attending' s assignment. Adult inpatients (age ≥18) with expected overnight stay and eGFR ≥15 mL/min/1.73 m² are included; obstetrics, chronic dialysis, and kidney transplant patients are excluded. The underlying preoperative model was prospectively validated at UCSF and outperforms anesthesiologist risk estimation reported in the literature. The model was reviewed and approved by the AI Oversight Committee at UCSF. Primary endpoint is the continuous change in serum creatinine (mg/dL) from baseline to POD 1-2. Secondary outcomes include KDIGO-defined AKI, adherence to bundle elements (hemodynamics, balanced fluids, nephrotoxin avoidance, glycemic control), intraoperative hypotension time, fluid volumes, nephrotoxin exposure, perioperative hyperglycemia, length of stay, unplanned ICU transfer, readmission, dialysis, and in-hospital mortality. Data are obtained from the EHR; analysts are blinded. No direct subject interaction is planned; the investigators will request a waiver of patient consent. The study aims to demonstrate that ML-enabled, workflow-embedded decision support can safely and feasibly improve guideline concordant care and decrease early postoperative kidney injury.
Who can join: Review the eligibility criteria below.
Location: University of California, San Francisco — San Francisco, California
Age range: 18 Years
🧪 Interventions in This Study
📋 "Do I Qualify?" — 1-Minute Self Screener
Instant ChecklistFull eligibility criteria are available on the official NIH protocol. View the criteria ↗
📍 All Participating Trial Locations (1 Sites)
- University of California, San Francisco — San Francisco, California
📞 Contact the Study Coordinator
Phone: (415) 502-5880
Email: andrew.bishara@ucsf.edu
Coordinator details come directly from the registered NIH protocol. Confirm the study is still recruiting before traveling.
💰 Cost, Insurance & Patient Rights
- 100% Free Items: The investigational treatment and protocol-required procedures are supplied at zero cost by the sponsor.
- Routine Patient Care: Under federal law (ACA § 2709) and many state statutes, routine care costs are covered during participation.
- Voluntary Participation: You may withdraw at any time without affecting your standard medical care.
More studies in Acute Kidney Injury
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- Acute Kidney Injury Genomics and Biomarkers in TAVR Study — Dallas, Texas
- Evaluation of UDP-glucose as a Urinary Biomarker for Early Detection of Cardiac Surgery-associated Pediatric Acute Kidney Injury — Boston, Massachusetts
- Theophylline Prophylaxis During Hypothermia to Limit Neonatal Nephron Damage — Oklahoma City, Oklahoma
- Proactive Prescription-based Fluid Management vs Usual Care in Critically Ill Patients on Kidney Replacement Therapy — Montreal, Quebec
- A Study of Auxora in Patients With AKI and Injurious Lung "Crosstalk" — Birmingham, Alabama
Explore by condition: All Acute Kidney Injury clinical trials
💡 How to Participate
- Check the checklist above to see if you may qualify.
- Contact the study coordinator using the phone/email above.
- Ask about the visit schedule, what is covered at no cost, and any travel support.
- Confirm with your own doctor before making a decision.