Acute Kidney InjuryNCT06804200
Prospective Validation of AKI Prediction
An observational study of Acute Kidney Injury, run by Adam C Dziorny at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 30 days to 18 years
- Conditions the study is for
- Acute Kidney Injury
- How many people
- 800 participants
- Where
- 1 siteUnited States
- Study dates
- 25 Jun 2025to 1 Aug 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 30 days to 18 years
- All sexes
- No healthy volunteers
- Child, Adult
Study population: All medical and surgical patients admitted to the pediatric intensive care unit and pediatric cardiac intensive care unit.
Who may be able to join
- Patients admitted to the Pediatric Intensive Care Unit or Pediatric Cardiac Intensive Care Unit
- Age > 30 days and < 18 years
Who cannot join
- Discharged less than 12 hours after admission
- AKI at 12 hours of admission by KDIGO Serum Criteria
Trial locations and contacts
1 site in 1 country.
United States1 site
Golisano Children's Hospital at Strong
Rochester, New York, 14642
About this study
Official title: Prospective Validation of AKI Prediction Algorithm
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.
Read the 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
- Keywords
- Machine Learning, Pediatrics, Critical Care
- Medical subject headings
- Acute Kidney Injury
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Acute Kidney Injury (AKI) within the first 72 hours of 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.
Measured: Within 72 hours following ICU Admission
Secondary outcomes (2)
Prediction Accuracy and Timeliness of AKI Risk using a Predictive Model
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.
Measured: Within 12 hours of ICU Admission
Risk of Mortality in Patients with Acute Kidney Injury (AKI)
Investigators will assess for AKI independent risk of mortality at 28 days after adjusting for confounders.
Measured: 28 Days following ICU admission
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Feb 2025
- Study start25 Jun 2025
- Primary completion1 Aug 2026
- Study completion1 Aug 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute Kidney InjuryStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 800 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Adam C Dziorny
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Adam C Dziorny, University of Rochester
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06804200
- Sponsor's protocol ID
- STUDY00008612
- Other IDs
- K23DK138299
- Status last verified
- Aug 2026
- First submitted
- 27 Jan 2025
- Last updated
- 18 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: Non-PHI data elements may be made available by request, per data sharing plan.
Study at a glance
From the registry record, last updated by the sponsor on 18 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Validation of AKI Prediction Algorithm
- ClinicalTrials.gov ID
- NCT06804200
- Acronym / sponsor ID
- STUDY00008612
- Conditions
- Acute Kidney Injury
- Keywords
- Machine Learning, Pediatrics, Critical Care
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 800 participants (estimated)
- Lead sponsor
- Adam C DziornyUniversity, hospital or other
- Collaborators
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
- Study start
- 25 Jun 2025 (actual)
- Primary completion
- 1 Aug 2026 (actual)
- Study completion
- 1 Aug 2027 (estimated)
- First posted
- 3 Feb 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| 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. |
Who may qualify
- Ages
- 30 days to 18 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult
- Study population
- All medical and surgical patients admitted to the pediatric intensive care unit and pediatric cardiac intensive care unit.
Key inclusion criteria (2 listed)
- Patients admitted to the Pediatric Intensive Care Unit or Pediatric Cardiac Intensive Care Unit
- Age > 30 days and < 18 years
Key exclusion criteria (2 listed)
- Discharged less than 12 hours after admission
- AKI at 12 hours of admission by KDIGO Serum Criteria
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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.
2 secondary outcomes
Prediction Accuracy and Timeliness of AKI Risk using a Predictive Model
Time frame: Within 12 hours of ICU Admission
Risk of Mortality in Patients with Acute Kidney Injury (AKI)
Time frame: 28 Days following ICU admission
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Aug 2026.
- Individual participant dataSharing planned: Undecided. Non-PHI data elements may be made available by request, per data sharing plan.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Acute Kidney Injury, run by Adam C Dziorny at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 18 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Acute Kidney Injury (AKI) within the first 72 hours of ICU admission (time frame: Within 72 hours following ICU Admission). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 Aug 2026.