About this trial
This is an observational longitudinal study which will collect routine demographic, laboratory and clinical parameters of patients with chronic kidney disease (CKD) in the Silesian and Warmia and Mazury Regions (Poland) aimed at predicting incident cardiovascular disease and cardiovascular and renal events using machine learning and artificial intelligence approaches. There will be a subgroup analysis of patients with diabetes and CKD.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
CKD defined as estimated glomerular filtration rate (eGFR) < 60ml/min/1.73 m2 and/or urine albumin creatinine ratio ( UACR) > 30 mg/g lasting at least 3 months
CKD regardless of eGFR/albuminuria when documented otherwise (by means of imaging, renal biopsy result, genetic background, etc)
Disqualifiers
Death during hospital stay
Terminal stage of cancer
Lack of an informed consent
Trial population
Patients hospitalized in nephrology departments in Zabrze and Olsztyn.
Trial design
Cohort
Prospective
Treatments tested in this trial
Not listed
Trial groups
Trial outcomes
Primary outcomes
Incident Coronary Artery Disease
New occurrence of coronary artery disease as diagnosed by standard medical procedures.
Myocardial Infarction
New occurrence of myocardial infarction as confirmed by electrocardiogram and/or biomarkers.
New onset heart failure or exacerbation of heart failure
New-Onset Heart Failure: Diagnosis based on the ESC guidelines, which include symptoms such as breathlessness, ankle swelling, and fatigue; objective evidence of cardiac dysfunction or structural abnormality in echocardiography; and response to treatment directed towards heart failure. Hospitalization for decompensated heart failure: Requires unscheduled admission to a healthcare facility with heart failure as the primary reason for admission.
Stroke or Transient Ischemic Attack
New occurrence of stroke as confirmed by neuroimaging or transient ischemic attack ascertained by typical symptoms.
Secondary outcomes
Machine-learning predictors of outcomes, including ECG predictors and retinal imaging predictors.
Using new statistical methods in predicting outcomes
Cluster analyses.
Use of statistical cluster analysis to identify patterns within primary outcome measures.
Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Medical University of Silesia
Lead sponsor
University of Warmia and Mazury in Olsztyn
Collaborator
University of Liverpool
Collaborator