Acute Heart Failure (AHF), Congestion, Venous
Conditions
Keywords
decongestion, diuretics, algorithm, acute heart failure
Brief summary
The aim of this study is to evaluate the effectiveness of loop diuretic adaptative algorithm that is based on machine learning, urine output prediction tool, in decongestion of acute heart failure patients. A total of 90 patients will be enrolled in the study. Of these, 45 will be assigned to the algorithm-based intervention group, while the remaining 45 will serve as the control group. In the control group, all decisions regarding diuretic therapy will be made solely by the attending physician, without the use of the algorithm. Patients will receive intravenous furosemide, with the initial dose determined by the attending physician. Two hours after administration of the diuretic, a spot urine sample will be collected to measure sodium and creatinine concentrations. Based on these values, the 6-hour urine output will be estimated using the machine learning, urine output prediction tool (http://diuresis.umw.edu.pl). This estimate will guide the diuretic therapy plan for the first 24 hours of hospitalization. On the second day, the procedure will be repeated using the same methodology.
Interventions
DIAGNOSTIC_TESTStandard of Care (SOC)
Diuretic treatment per attending physician.
DIAGNOSTIC_TESTAlgorithhm-based decongestion
Patient will receive standarized furosemide dosing based on the result of the algorithm-estimated 6h urine output (profiles of diuretic response).
Sponsors
Wroclaw Medical University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
SINGLE (Subject)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Adult patients over 18 years of age who provide informed consent * Ability to enroll in the study within the first 24 hours of hospitalization * Primary reason for hospitalization is acute heart failure with signs of congestion (at least moderate lower extremity edema) * NT-proBNP \> 1500 pg/ml * Anticipated need for diuretic therapy for at least 48 hours from the time of study enrollment
Exclusion criteria
* End-stage kidney disease requiring renal replacement therapy * Hemodynamic instability requiring inotropic support * Active infection requiring intravenous antibiotic therapy
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Cumulative diuresis over 48 hours. | 48 hours | Total urine output during the 48-hour duration of the study. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Cumulative diuresis during first 24h of the study. | 24 hours | The total urine output during the first 24 hours of the study. |
| Cumulative diuresis on the second 24h of the study. | 48 hours | The total urine output during the second 24 hours of the study. |
| Cummulative natriuresis over 48 hours of the study. | 48 hours | The total amount of sodium excreted in the urine during the 48-hour duration of the study. |
| Total length of hospitalization. | Up to 60 days | This refers to the total length of the hospital stay, measured in days, from admission to discharge. |
| Weight change at 24 hours. | 24 hours | The difference in body weight measured at 24 hours compared to baseline. |
| Weight change at 48 hours. | 48 hours | The difference in body weight measured at 48 hours compared to baseline. |
| Percentage of patients accurately red-flagged. | 48 hours | Patients with an estimated 6-hour urine output of less than 900 ml will be red-flagged. This outcome indicates the proportion of patients who were correctly identified (red-flagged) as poor diuretic responders. |
| Diuresis calculated per dose of loop diuretic over 48 hours of the study. | 48 hours | The volume of urine output relative to the total dose of loop diuretic administered during the study period. |
Countries
Poland
Contacts
Primary ContactJan Biegus, MD, PhD
Backup ContactGracjan Iwanek, MD
Outcome results
None listed