Assessment of AI Prediction Models in Prediction of Acute Kidney Injury in Critical Patients
NCT06857188 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000
Last updated 2025-05-16
Summary
The assessment of AI -based prediction models in detecting AKI early in critically ill patients. Specifically, the aim is to evaluate the model's ability to predict the onset of AKI before it clinically manifests allowing for early interventions
Conditions
- Acute Kidney Failure
- Artificial Intelligence (AI)
Sponsors & Collaborators
-
Assiut University
lead OTHER
Principal Investigators
-
Alaa El-Dein ElMoneim Sayed, professor · Assiut University
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2025-05-14
- Primary Completion
- 2026-03-01
- Completion
- 2026-03-01
More Related Trials
-
The Effect of Automated Electronic Alert for Acute Kidney Injury on the Outcomes of Hospitalized Patients
NCT03736304 ·Status: COMPLETED ·Phase: NA
-
Machine Learning Predict Renal Replacement Therapy After Cardiac Surgery
NCT04977687 ·Status: COMPLETED
-
Evaluation of U-AKIpredTM for Predicting AKI in Critically Ill Patients Within 12 Hours: a Multicenter Prospective Cohort Study
NCT06496555 ·Status: RECRUITING
-
Machine Learning Predict Acute Kidney Injury in Patients Following Cardiac Surgery
NCT04966598 ·Status: COMPLETED
-
Preventing Acute Kidney Injury and Improving Outcome in Critically Ill Patients Utilising Risk Prediction Score
NCT03178435 ·Status: COMPLETED ·Phase: NA
-
Transition of Acute Kidney Injury to Chronic Kidney Disease
NCT04101110 ·Status: COMPLETED
-
Acute Kidney Injury - Epidemiology in Intensive Care Unit Patients 2: an International Multicenter Cohort Study
NCT07207031 ·Status: ENROLLING_BY_INVITATION
-
Role of Neuronal Guidance Proteins as Diagnostic Markers for Acute Kidney Injury (AKI)
NCT05924269 ·Status: NOT_YET_RECRUITING
-
Clinical Findings and Albuminuria as Predictors of Acute Kidney Injury in Patients With Acute Heart Failure
NCT06621862 ·Status: NOT_YET_RECRUITING
-
Risk Factors and Deep Learning Model for CI-AKI
NCT06596785 ·Status: ACTIVE_NOT_RECRUITING
-
Platelets to Albumin Ratio for Prediction of Acute Kidney Injury in Patients Admitted to the Intensive Care Unit
NCT06554977 ·Status: NOT_YET_RECRUITING
-
Clinical Values of Automated Electronic Alert for Acute Kidney Injury
NCT02793167 ·Status: COMPLETED ·Phase: NA
-
Early Prediction of Acute Kidney Injury in High Risk Patients After Non-cardiac Surgery
NCT03880110 ·Status: UNKNOWN
-
Acute Kidney Injury in Neonatal ICU in Assuit University
NCT07083284 ·Status: NOT_YET_RECRUITING
-
Prevalence , Risk Factors and Outcomes of AKI in ICU Patients
NCT04264507 ·Status: UNKNOWN
-
Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery
NCT06146829 ·Status: COMPLETED
-
Acute Kidney Injury and Renal Outcomes for COVID-19 Patients in Intensive Care Units
NCT04459975 ·Status: UNKNOWN
-
Role of Renal Artery Doppler in Critically Ill Children With Acute Kidney Injury
NCT06202326 ·Status: NOT_YET_RECRUITING
-
Outcomes of Acute Kidney Injury in Critically Ill Patients
NCT03338127 ·Status: UNKNOWN
-
Renal Outcome of Acute Kidney Disease
NCT03597854 ·Status: UNKNOWN
-
Acute Kidney Injury Predictor Validation Study
NCT03574896 ·Status: COMPLETED
-
Incidence and Spectrum of Acute Kidney Injury in Cirrhotics and Assessment of New Biomarkers as Early Predictors of Acute Kidney Injury
NCT02016053 ·Status: COMPLETED
-
Acute Kidney Attack in Severe Traumatized Patients
NCT03877978 ·Status: COMPLETED
-
A Machine Learning Prediction Model for Postoperative Acute Kidney Injury in Non-Cardiac Surgery Patients
NCT07030166 ·Status: RECRUITING
-
Serum Cysteine Rich Protein 61 and Cystatin C for Early Detection of Acute Kidney Injury in Patients With Heart Diseases
NCT05242705 ·Status: UNKNOWN