Cardiovascular Disease in Patients With Chronic Kidney Disease: Polish Kidney- Heart Project

Study Overview
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Brief Summary
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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.

Detailed Description
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This is a prospective, observational study seeking to collate demographic, laboratory, and clinical data from patients with CKD hospitalized at two academic centres: the Department of Internal Medicine, Diabetology and Nephrology in Zabrze, Silesia, and the Clinic of Nephrology, Hypertension and Internal Medicine in Olsztyn, Warmia and Mazury. Patients will receive telephone check-ups annually post-discharge and will be proposed to attend on-site follow-up health checks. Patients will be followed up annually for 10 years or until death if occurs earlier, in order to collect information related to new onset cardiovascular events and progression to macroalbuminuria and/or doubling of serum creatinine with decrease of eGFR to less than 45 ml/min./1.73m2 (compared to baseline) or the onset of end stage renal disease (ESRD) or renal death. ESRD is defined as initiation of maintenance dialysis or kidney transplantation. All procedures, except eye fundus imaging for hospitalized patients align with standard nephrology ward care that patients agree for upon hospitalization. The Medical University of Silesia and the University of Warmia and Mazury, Collegium Medicum will obtain study approvals from the respective independent university- or chamber of physicians-based bioethics committees for performing fundus imaging during hospital stay and annual telephone contacts as well as on- site health checks for the longitudinal patient follow-up observation. With patient consent, annual on-site visits will entail blood and urine assessments, ECG, retinal imaging via the fundus camera, and examinations for peripheral and cardiac autonomic neuropathy among those with diabetes. Biochemical analyses will focus on assessing serum creatinine, lipid profile, HbA1c for diabetic patients, and the urine albumin-creatinine ratio (UACR). With a decade-long prospective follow-up focused on documenting new cardiovascular and renal events, the primary objective is to identify patients with CKD at the highest risk of cardiovascular disease and CKD progression. This goal will be achieved by implementing machine learning techniques to analyze clinical parameters that are easy to obtain in everyday clinical practice.

Official Title
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Cardiovascular Disease in Patients With Chronic Kidney Disease: Polish Kidney- Heart Project

Conditions
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Chronic Kidney Disease, Cardiovascular Diseases

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: 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) Exclusion Criteria: Death during hospital stay Terminal stage of cancer Lack of an informed consent

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Incident Coronary Artery Disease | New occurrence of coronary artery disease as diagnosed by standard medical procedures. | Annually, 10 years from enrollment | 
| Myocardial Infarction | New occurrence of myocardial infarction as confirmed by electrocardiogram and/or biomarkers. | Annually, 10 years from enrollment | 
| 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. | Annually, 10 years from enrollment | 
| Stroke or Transient Ischemic Attack | New occurrence of stroke as confirmed by neuroimaging or transient ischemic attack ascertained by typical symptoms. | Annually, 10 years from enrollment | 
| Peripheral Vascular Disease Peripheral Vascular Disease Peripheral Vascular Disease Peripheral Vascular Disease Peripheral Vascular Disease | New diagnosis of peripheral vascular disease confirmed by imaging studies. | Annually, 10 years from enrollment | 
| Atrial Fibrillation | Incident atrial fibrillation confirmed by electrocardiogram. | Annually, 10 years from enrollment | 
| Death Due to Cardiovascular Cause | Death where the primary cause is attributed to cardiovascular disease. | Annually, 10 years from enrollment | 
| Progression of Chronic Kidney Disease | Progression to macroalbuminuria or doubling of serum creatinine with a decrease of eGFR to less than 45 ml/min/1.73m^2 compared to baseline. | Annually, 10 years from enrollment | 
| End-Stage Renal Disease or Renal Death | Onset of end-stage renal disease requiring initiation of maintenance dialysis or kidney transplantation, or death due to renal causes. | Annually, 10 years from enrollment | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Machine-learning predictors of outcomes, including ECG predictors and retinal imaging predictors. | Using new statistical methods in predicting outcomes | 10 years from enrollment | 
| Cluster analyses. | Use of statistical cluster analysis to identify patterns within primary outcome measures. | 10 years from enrollment | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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chronic kidney disease, cardiovascular disease, artificial inteligence, predictors