Abstract

Abstract Funding Acknowledgements Type of funding sources: None. Background Positive fluid balance has been associated with adverse outcomes in patients admitted to intensive care units (ICU). Urine output (UO) is used both to assess deterioration of renal function as well as for management of fluid balance in patients admitted to the general ICU. In the cardiac ICU, patients admitted for acute decompensated heart failure (ADHF) are at high risk for type I cardio-renal syndrome and increased morbidity and mortality. Studies have shown that poor fluid management in these patients contributes to worse outcomes in this patient population (1). Aim To investigate the possible effect of real-time monitoring of UO trends on the individualized pharmacologic management, fluid balance, and clinical outcomes of patients admitted to the cardiac ICU with ADHF. Methods We performed a case series of 35 patients admitted to the cardiac ICU from July 2021 and January 2022 with ADHF. Their standard Foley catheter was connected to an electronic monitoring system (Clarity-RMS sensor kit) that continuously monitors UO in real-time. Its technology is described elsewhere (2). The UO monitoring system displays UO trends on the consoles that are updated in real-time. UO trends were utilized to detect dynamic changes in urine output and guide an individualized approach for the pharmacologic management of each patient, based on blood pressure, hourly UO and total fluid balance. Daily and accumulated fluid balance was registered at up to 72 hours following admission. Patient outcomes included incidence of acute kidney injury (AKI), as defined by the KDIGO criteria for changes in serum creatinine (SCr), and 30-day mortality. The case series group was than compared to a historical group of 35 matched controlled patients admitted between 2018-2019. Patients were matched according to cause of admission, age and glomerular filtration rate. Results Mean age was 71 ± 11 years and 49 (70%) were men. Patients in the electronic urinary monitoring cohort demonstrated significantly more negative daily and cumulative fluid balance as compared to the historical cohort, (P<0.001 for all, Figure 1). Incidence of AKI and AKI combined with 30-day mortality was significantly lower in the electronic UO monitoring cohort (23% vs. 57%, p<0.001, and 34% vs. 63%, p<0.001, respectively). These changes were more prominent in the subgroup of patients with chronic kidney disease (CKD) (Figure 2). Conclusion We demonstrated that real time monitoring of UO trends may be used for goal-directed care for the prevention of fluid overload and adverse outcomes in patients with ADHF. Further studies on larger populations are required to validate the potential utility of UO trending in the management of critically ill patients with ADHF.

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