Derivation of a Personalized Congestion Score Using a Chronic Implantable Inferior Vena Cava Management System in...

Congestion is a principal driver of worsening heart failure (HF) and hospitalization. The large, compliant inferior vena cava (IVC) enables detection of congestion before increases in filling pressures. We developed a novel, patient-individualized congestion score (NORM Score) using daily ambulatory IVC measurements-area and collapsibility-from an implantable sensor.

Using clinical data from 2 early feasibility trials (FUTURE-HF [First in Human Clinical Investigation of the FIRE1 System in Heart Failure Patients; NCT04203576] and FUTURE-HF2 [Early Feasibility Study of the NORM™ System in Heart Failure Patients; NCT05763407]), a congestion score (range, 0-100) was derived from daily supine IVC area (breath hold and free breathing) and collapsibility in patients implanted with a novel IVC sensor. A clinical alert was triggered if the score exceeded 70% of a patient's maximum for 5 of 7 days. Performance was evaluated against adjudicated HF events (HFEs) and N-terminal prohormone of brain natriuretic peptide (NT-proBNP) levels.

Among 63 patients (mean age, 66 years; 75% New York Heart Association functional class III), 30 HFEs occurred in 18 individuals. Score predicted HFEs with 92.6% sensitivity, high predictive accuracy (C-statistic, 0.83), and a low unexplained alert rate (0.57 per patient-year). Breaching the alert threshold was associated with an odds ratio of 18 (95% confidence interval 3.5-93.8) for hospitalization within 7 days. The congestion score was significantly associated with log-transformed NT-proBNP (β = 5.64;95% confidence interval 3.23-8.05; P < .001).

This unique congestion score, derived from an ambulatory implantable IVC management system, was associated with NT-proBNP levels and predicted worsening HFEs with high sensitivity. These findings, once validated in a pivotal randomized trial, will support the use of this novel congestion score for early detection of HF decompensation, streamline clinical response, and enable personalized patient self-management.