This patient is an 87 year-old man with NYHA class III heart failure with reduced left-ventricular ejection fraction (35-40%), and a history of hypertension, atrial fibrillation, and chronic kidney disease. ECF%TBW was markedly elevated (56.7%) upon study entry, and the patient was readmitted to the hospital on study day 5. After a skilled nursing facility (SNF) stay, home monitoring resumed on study day 30. His ECF%TBW remained very high (57.0%), and bumetanide dose increases between study days 30 and 49 had minimal effect on fluid volumes and weight. Metolazone was started on study day 64, and the patient responded with a reduction in ECF%TBW to 52.7% on study day 76. He then left the study briefly only to be re-enrolled after his second readmission for heart failure. When BIS measurements resumed on study day 87, his ECF%TBW had risen to 54.7%. Metolazone therapy was reinitiated, and clinical, fluid volume, and weight stability was finally achieved by study day 115. The ECF%TBW strata shown in Figure 3B are based on population data and should be interpreted in clinical context. This patient was almost exclusively >51% (fluid overloaded state); achieving normal fluid status (41.5-46.4%) is an unrealistic goal in this case. With unblinded, real-time BIS data, it's likely that his caregivers would have recognized persistent fluid overload at the time of study entry as his ECF%TBW was 56-57%, markedly elevated even for this patient. An ECF%TBW of 50% and an ECF volume of 16 liters turned out to be reasonable targets in this case; a future goal of fluid monitoring in HF would be to identify and maintain target fluid volumes more quickly than is currently possible with weight tracking alone.
Given that the BIS device used in this report (Figure 1) operates while the test subject is sitting or standing without contacting metal and/or electronic objects, use in the intensive care setting is impractical. For these patients, volume status can be monitored invasively via pulmonary artery catheterization, and for whom fluid intake and loss is carefully tracked. BIS technology, however, may play a role in the following settings: (a) emergency departments (EDs) and urgent care centers; (b) risk stratifying HF patients at the time of hospital discharge based on the extent of residual congestion; (c) longitudinal management in clinic and skilled nursing facilities; and (d) assessing at-risk HF populations for health care managers and chief medical officers.
Because the ED and urgent care settings rely upon rapid, quantitative measures, bioimpedance-based assessment of fluid status may help facilitate triage of patients presenting with dyspnea. BIS measurements obtained in the ED:by serving as a point of comparison:may assist in the next phase of care if admission is required.
HF patients, when admitted to the hospital, usually need diuresis, but knowing when sufficient decongestion has been achieved can be challenging. Currently, physical exams, weights, and echocardiographic measures are used to assess hydration; however, despite use of these methods, 30-day readmission rates remain high. BIS-measured ECF%TBW at the time of hospital discharge may help identify patients at high-risk of readmission owing to persistent congestion.
In the outpatient setting, providers currently struggle with quantifying the extent of congestion. BIS may help distinguish between patients that are managed appropriately from those who may need an adjustment to their medication regimen.. As shown in Figure 4, BIS measurements correlate strongly with ultrasound-measured inferior vena cava size which has been used in clinic to manage diuresis and identify early fluid overload. Unfortunately, ultrasound is labor-intensive, requires a skilled operator, and is not always available.
As more HF patients enter alternative payment models for care, objective measures of wellness are sought. A recent study of more than 500,000 patients identified leg impedance measures as an independent risk factor for clinical deterioration; hence, BIS measurements at a population level may eventually help identify at-risk individuals. By directing resources to patients who pose the greatest risk for decline, healthcare systems can better meet the demand for high-yield care.
The case study presented in this report (Figure 5) is intended to provide an example of how BIS-derived fluid volume measures may be used to aid in monitoring patients with HF. It shows that ECF%TBW and ECF volume targets can be identified for heart failure patients [point (c), above]. This case also shows that patients may be discharged from hospitalizations for decompensated HF with substantial residual congestion [point (b), above]; this occurred on three occasions for this patient on study day 1 (ECF%TBW of 56.7%), day 30 (57.0%), and day 87 (54.7%).