Prospective Validation of AKI Prediction

NCT ID: NCT06804200

Last Updated: 2025-10-09

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 800 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2025-12-31
• Study Completion Date: 2026-02-28

Brief Summary

The purpose of this prospective observational study is to implement, deploy, and quantify accuracy of an existing Pediatric Early AKI Risk Score algorithm. The implementation will be facilitated using a Health Level 7 (HL7) Fast Healthcare Interoperability Resource (FHIR)-based architecture. Investigators will deploy this model and store results in a manner not viewable to the clinical team caring for the patient. To determine the accuracy of the implemented prediction model, Investigators will prospectively identify patients with AKI at 72 hours following ICU admission. Investigators hypothesize that this model will prospectively detect AKI with a sensitivity >70% and a positive predictive value >20%, both chosen a priori as 10% improvement over the initial Pediatric AKI Risk Score tool.

Detailed Description

This is a single-center prospective observational study validating an AKI predictive model. Each model feature will be mapped to an appropriate FHIR-based resource. To mitigate the latency issues seen in other distributed CDS systems, Investigators have developed an asynchronous design where algorithm calculations are performed offline (e.g., not within the EHR) and risk scores are subsequently written back to the EHR. Importantly, in this deployment, model output and resulting clinical risk score will not be communicated to the treating clinicians.

During the study period, Investigators will review charts daily for all patients admitted to the Golisano Children's Hospital PICU, a 12-bed facility adjacent to our 15-bed Pediatric Cardiac Intensive Care Unit (PCICU). Using a standard protocol to screen and identify patients by chart review, Investigators will generate a list of patients who meet AKI KDIGO criteria by SCr and urine output, along with recorded clinical information about these patients. At the conclusion of the study period, this list will be used as the "gold standard" and compared to the automated screening tool to determine the tool's test characteristics.

Model assessment outcomes include sensitivity, positive predictive value (PPV), and number needed to alert (NNA) to prospectively identify AKI in a population of critically ill children. Additional outcomes include timeliness of identification based on model implementation (e.g., measured timestamps of algorithm prediction compared to manual, prospectively identified AKI development). Additionally, Investigators will report interventions and clinical outcomes of the prospectively identified patients with AKI, stratified by those predicted early by the model (within 24 hours of admission) versus not.

Conditions

Acute Kidney Injury

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Pediatric ICU Admissions

The study subjects are all patients admitted to the pediatric intensive care unit and the pediatric cardiac care unit at Golisano Children's Hospital at Strong. By virtue of admission to a pediatric hospital bed, all subjects will be children. The rationale for focusing on this population is that the developed algorithm focuses on identifying acute kidney injury among critically ill pediatric patients. The gender and age of subjects will not influence enrollment. To accurately determine algorithm test characteristics (sensitivity, PPV, NNA) pragmatically, Investigators must include all admitted patients. Missing patients may bias our results and invalidate the study.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• Patients admitted to the Pediatric Intensive Care Unit or Pediatric Cardiac Intensive Care Unit
• Age > 30 days and < 18 years

Exclusion Criteria

• Discharged less than 12 hours after admission
• AKI at 12 hours of admission by KDIGO Serum Criteria

• Minimum Eligible Age: 30 Days
• Maximum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

NIH

Sponsor Role: collaborator

Adam C Dziorny

OTHER

Sponsor Role: lead

Responsible Party

Adam C Dziorny

Associate Professor of Pediatrics

Responsibility Role: SPONSOR_INVESTIGATOR

Locations

Golisano Children's Hospital at Strong

Rochester, New York, United States

Countries

United States

Central Contacts

Adam C Dziorny, MD, PhD

Role: CONTACT

adam_dziorny@urmc.rochester.edu

585-276-3014

Other Identifiers

K23DK138299

Identifier Type: NIH

Identifier Source: secondary_id

View Link

STUDY00008612

Identifier Type: -

Identifier Source: org_study_id