Trial for the Early Identification of Acute Kidney Injury

NCT04200950 | Withdrawn Phase 2 DMC

• 1 other identifier: 07012020
• Study Type: interventional
• Target: N/A
• Locations: 0 countries
• Sites: N/A

Brief Summary

Previse is a novel, software-based clinical decision support (CDS) system that predicts acute kidney injury (AKI). Previse uses machine learning methods and information drawn from the electronic health record (EHR) to identify the early signs of acute kidney injury; by doing so before the clinical syndrome of AKI is fully developed, Previse can give clinicians the time to intervene with the goals of preventing further kidney damage, and decreasing the sequelae of AKI. It has been demonstrated in retrospective work that Previse can predict AKI with high accuracy at long prediction horizons, but the tool has yet to be validated in prospective settings; therefore, in this project, the clinical utility of Previse will be assessed through an individually randomized controlled multicenter trial.

Conditions

Acute Kidney Injury

Outcome Measures

Primary Outcomes (1)

• Incidence of adverse kidney events as assessed by Major Adverse Kidney Event within 30 days (MAKE30) criteria

  The proportion of patients meeting one or more criteria for the Major Adverse Kidney Events within 30 days (MAKE30) composite of death, new renal replacement therapy, or persistent creatinine elevation ≥ 200% of baseline, all censored at the first of hospital discharge or 30 days

  Through study completion, an average of twelve months

Study Arms (2)

Intervention

EXPERIMENTAL

Previse alert arm

Device: Previse

Control

NO INTERVENTION

No alert

Interventions

Previse DEVICE

Machine learning algorithm for early acute kidney injury (AKI) prediction.

Intervention

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adult ≥ 18 years admitted to a participating study hospital

You may not qualify if:

• ﹤18 years of age
• ESRD diagnosis code
• Stage 4 or Stage 5 CKD diagnosis code
• Initial creatinine ≥4.0mg/dl
• Nephrectomy during admission
• Admission to hospice service
• Admission to observation status
• Any organ transplant (including kidney transplant) within 6 months
• Dialysis order prior to AKI onset
• Dialysis order within 24 hours of admission
• Prior admission in which patient was randomized

Sponsors & Collaborators

• Dascena: lead

Related Publications (1)

• Mohamadlou H, Lynn-Palevsky A, Barton C, Chettipally U, Shieh L, Calvert J, Saber NR, Das R. Prediction of Acute Kidney Injury With a Machine Learning Algorithm Using Electronic Health Record Data. Can J Kidney Health Dis. 2018 Jun 8;5:2054358118776326. doi: 10.1177/2054358118776326. eCollection 2018.

  PMID: 30094049 BACKGROUND

MeSH Terms

Conditions

Acute Kidney Injury

Condition Hierarchy (Ancestors)

Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases

Study Design

• Study Type: interventional
• Phase: phase 2
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 11, 2019
• First Posted: December 16, 2019
• Study Start: July 1, 2020
• Primary Completion: June 1, 2021
• Study Completion: June 1, 2021
• Last Updated: September 24, 2021

Record last verified: 2021-09