Acute Kidney Injury Predictor Validation Study

NCT03574896 | Completed

• 1 other identifier: S61388
• Study Type: observational
• Target: 252
• Locations: 1 country
• Sites: 1

Brief Summary

Purpose: To evaluate the performance of AKIpredictor, a computer-based algorithm that predicts the development of AKI in the 7 days following ICU admission, by comparing it with similar predictions made by attending physicians. Primary objective: To compare the performances of AKIpredictor and physicians in predicting AKI stage 2 or 3 in the 7 days following ICU admission Secondary objective(s): To investigate the influence of the level of seniority of the physician on the accuracy of the predictions; feasibility of making predictions within a 3 hour window for physicians Trial Design: Monocentric, prospective, longitudinal, non-interventional Endpoints: Primary: comparing the area under the ROC curves of the AKIpredictor and physicians. Secondary: estimation of PPV, NPV, sensitivity and specificity of both predictors at different thresholds; evaluation of alternative negative endpoints (ICU readmission after discharge, death); subgroup analyses. Sample Size: This is a pilot study. Sample size calculations to obtain sufficient power are not feasible due to lack of previous studies. The investigation will be conducted with a preset end time on June 30th. The investigators expect to include approximately 150 patients. Summary of eligibility criteria: All adult patients admitted to UZ Leuven's surgical ICU in the period of the study, with the exclusion of those with end-stage renal disease or AKI already present at the time of admission

Conditions

Critical Illness; Acute Kidney Injury

Outcome Measures

Primary Outcomes (1)

• AUROC comparison

  Comparison of the area under the receiver-operator characteristic (ROC) curves between the predictions made by the AKIpredictor and the ones made by ICU physicians, to predict AKI 2-3.

  1 week

Interventions

Computer model predictions of acute kidney injury OTHER

Comparison of the performances of AKIpredictor and physicians in predicting AKI stage 2 or 3 in the 7 days following ICU admission

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

All adult patients admitted to UZ Leuven's surgical ICU in the period of the study, with the exclusion of those with end-stage renal disease or AKI already present at the time of admission

You may qualify if:

• All adult patients admitted to UZ Leuven's surgical ICU in the period of the study

You may not qualify if:

• Patients with end-stage renal disease or AKI already present at the time of admission

Sponsors & Collaborators

• Geert Meyfroidt, MD, PhD: lead

Study Sites (1)

Geert Meyfroidt

Kessel-Lo, 3010, Belgium

Location

Related Publications (1)

• Flechet M, Falini S, Bonetti C, Guiza F, Schetz M, Van den Berghe G, Meyfroidt G. Machine learning versus physicians' prediction of acute kidney injury in critically ill adults: a prospective evaluation of the AKIpredictor. Crit Care. 2019 Aug 16;23(1):282. doi: 10.1186/s13054-019-2563-x.

  PMID: 31420056 DERIVED

MeSH Terms

Conditions

Critical Illness; Acute Kidney Injury

Condition Hierarchy (Ancestors)

Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases

Study Officials

• Geert Meyfroidt, MD, Phd

  KU Leuven

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: June 21, 2018
• First Posted: July 2, 2018
• Study Start: May 2, 2018
• Primary Completion: June 30, 2018
• Study Completion: September 1, 2018
• Last Updated: September 23, 2022

Record last verified: 2019-05

Data Sharing

• IPD Sharing: Will not share

Locations

BE (1)