NCT07312929

Brief Summary

SMART DIALYSIS - Scaling Machine Learning and Artificial Intelligence AlgoRithms to OpTimize the Performance and Delivery of Acute DIALYSIS. Hypothesis: Can the investigators develop and implement Machine Learning and Artificial Intelligence Algorithms into Clinical Information Systems to Optimize the Prescription, Delivery, and Performance of Acute Dialysis? Objective(s):

  1. 1.Identify variables surrounding identified Key Performance Indicators that may be used by Machine Learning and Artificial Intelligence algorithms to optimize the prescription and performance of acute dialysis.
  2. 2.Develop Machine Learning and Artificial Intelligence algorithms to help guide the prescription and delivery of acute dialysis in the development of Clinical Decision Support tools and Best Practice Advisories and create a ML/AI Augmented SMART DIALYSIS Digital Dashboard.
  3. 3.Implement and evaluate the performance of the developed Machine Learning and Artificial Intelligence algorithms on patient-centered and health economic outcomes.
  4. 4.Validate and benchmark the performance of the evaluated Machine Learning and Artificial Intelligence algorithms across multiple jurisdictions.

Trial Health

63
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
7,500

participants targeted

Target at P75+ for all trials

Timeline
58mo left

Started Oct 2026

Longer than P75 for all trials

Geographic Reach
1 country

15 active sites

Status
not yet recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

December 17, 2025

Completed
14 days until next milestone

First Posted

Study publicly available on registry

December 31, 2025

Completed
9 months until next milestone

Study Start

First participant enrolled

October 1, 2026

Completed
3.7 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 30, 2030

Expected
1 year until next milestone

Study Completion

Last participant's last visit for all outcomes

June 30, 2031

Last Updated

September 24, 2026

Status Verified

September 1, 2026

Enrollment Period

3.7 years

First QC Date

December 17, 2025

Last Update Submit

September 22, 2026

Conditions

Keywords

DialysisArticfical InteligenceKey performance indicatorsMachine Learning

Outcome Measures

Primary Outcomes (3)

  • Identify Key Performance Indicators that may be used by Machine Learning algorithms.

    Key Performance Indicators

    12 month

  • Develop Artificial Intelligence and Machine Learning algorithms

    Artificial Intelligence and Machine Learning algorithms

    36 month

  • Evaluate the performance of the developed Artificial Intelligence and Machine Learning algorithms.

    ICU and hospital mortality; Renal Recovery at ICU and hospital discharge and 90 days; ICU and hospital lengths of stay; Hospital Costs

    60 month

Study Arms (1)

Critically ill patients requiring acute dialysis

Admitted to an intensive care unit; requiring acute dialysis

Device: intermittent OR continuous renal replacement therapies

Interventions

We will include any critically ill patient admitted to an intensive care unit requiring acute dialysis.

Critically ill patients requiring acute dialysis

Eligibility Criteria

Sexall
Healthy VolunteersNo
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

The study population will comprise critically ill patients admitted to an intensive care unit who require acute renal replacement therapy.

You may qualify if:

  • Patients admitted to an intensive care unit (ICU) who require acute renal replacement therapy, either intermittent or continuous.

You may not qualify if:

  • Receipt of renal replacement therapy for less than 24 hours.
  • Pre-existing end-stage kidney disease.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (15)

Peter Lougheed Center

Calgary, Alberta, T1Y 6J4, Canada

Location

Foothills Medical Center

Calgary, Alberta, T2N 2T9, Canada

Location

Rockyview General Hospital

Calgary, Alberta, T2V 1P9, Canada

Location

South Health Campus

Calgary, Alberta, T3M 1M4, Canada

Location

Royal Alexandra Hospital

Edmonton, Alberta, T5H 3V9, Canada

Location

Misericordia Community Hospital

Edmonton, Alberta, T5R 4H5, Canada

Location

Mazankowski Heart Institute

Edmonton, Alberta, T6G-2B7, Canada

Location

University of Alberta Hospital

Edmonton, Alberta, T6G-2B7, Canada

Location

Grey Nuns Community Hospital

Edmonton, Alberta, T6L 5X8, Canada

Location

Northern Lights Regional Hospital.

Fort McMurray, Alberta, T9H 1P2, Canada

Location

Grand Prairie Regional Hospital

Grand Prairie, Alberta, T8V 4B1, Canada

Location

Chinook Regional Hospital

Lethbridge, Alberta, T1J 1W5, Canada

Location

Medicine Hat Regional Hospital

Medicine Hat, Alberta, T1A 4H6, Canada

Location

Red Deer Regional Hospital

Red Deer, Alberta, T4N 4E7, Canada

Location

Sturgeon Community Hospital

St. Albert, Alberta, T8N 6C4, Canada

Location

MeSH Terms

Conditions

Kidney Diseases

Condition Hierarchy (Ancestors)

Urologic DiseasesFemale Urogenital DiseasesFemale Urogenital Diseases and Pregnancy ComplicationsUrogenital DiseasesMale Urogenital Diseases

Study Officials

  • Oleksa G Rewa, MD MSc

    University of Alberta

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Oleksa G Rewa, MD MSc FRCPC

CONTACT

Fadi Hammal, MD MSc

CONTACT

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Target Duration
90 Days
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

December 17, 2025

First Posted

December 31, 2025

Study Start

October 1, 2026

Primary Completion (Estimated)

June 30, 2030

Study Completion (Estimated)

June 30, 2031

Last Updated

September 24, 2026

Record last verified: 2026-09

Locations