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NCT Number: NCT06804200

Prospective Validation of AKI Prediction

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.

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Key information

Conditions

Acute Kidney Injury Female Urogenital Diseases Female Urogenital Diseases and Pregnancy Complications Kidney Diseases Male Urogenital Diseases Renal Insufficiency Urogenital Diseases Urologic Diseases

Age range

30 day–18 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Golisano Children's Hospital at Strong

Rochester, New York, 14642, United States

Location status: Recruiting

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Primary outcomes

  1. Acute Kidney Injury (AKI) within the first 72 hours of ICU admission

    Time frame: Within 72 hours following ICU Admission

    Acute Kidney Injury (AKI) defined by KDIGO stages 1, 2, or 3, based on changes in serum creatinine levels or urine output (UOP), assessed within the first 72 hours of ICU admission. Stage 1 is defined by a 1.5 to 1.9 times baseline serum creatinine or an increase of ≥0.3 mg/dL. Stage 2 is a 2.0 to 2.9 times baseline increase, and Stage 3 is a 3.0 times baseline increase or a serum creatinine ≥4.0 mg/dL.

Secondary outcomes

  1. Prediction Accuracy and Timeliness of AKI Risk using a Predictive Model

    Time frame: Within 12 hours of ICU Admission

    Predictive model results generated prospectively (at 12 hours following admission) will be used to generate a 2x2 confusion matrix with prospectively identified AKI by serum creatinine or urine output changes based on KDIGO criteria. Investigators will calculate sensitivity, PPV, and NNA for the prospective identification of AKI. Investigators will report the time of AKI prediction compared to admission date and the onset date of AKI.

  2. Risk of Mortality in Patients with Acute Kidney Injury (AKI)

    Time frame: 28 Days following ICU admission

    Investigators will assess for AKI independent risk of mortality at 28 days after adjusting for confounders.

Study contacts

Contact information is provided by the study sponsor or research team.

Adam C Dziorny, MD, PhD

CONTACT

[email protected]

585-276-3014

Sponsors and collaborators

Lead sponsor

Adam C Dziorny

Other

Collaborators

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

Registry information

Official study title

Prospective Validation of AKI Prediction Algorithm

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Feb 3, 2025
Registry last updated
Apr 8, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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