B Hipszer1, T Miller2, N Fleming3, W Hand4, T Scheeren5, M Mythen5, F Hatib5 1Becton, Dickinson and Company, Advanced Patient Monitoring, Irvine, USA, 2Duke University Health System, Raleigh, USA, 3UC Davis School of Medicine, Sacramento, USA, 4University of South Carolina School of Medicine, Greenville, USA, 5Becton, Dickinson and Company, Irvine, USA

Critical Care 2025, 29(S1):P203

Introduction: Compliance to effective protocols can improve patient outcome [1]. For optimal perioperative fluid management, it is not only administering the appropriate amount of fluid but also delivering it at the right time. An ad-hoc analysis of data collected in the clinical validation of the Acumen Assisted Fluid Management (AFM) software was conducted to assess the impact of compliance to AFM fluid suggestions on patient hemodynamics. The AFM software is a clinical decision support system that resides on an advanced hemodynamic clinical monitor, and it notifies the caregiver when a patient may be in a fluid responsive state by providing a suggestion on the monitor screen.

Methods: In a pragmatic study across nine US sites, 330 subjects undergoing major non-cardiac surgery were included [2]. Caregivers were provided with AFM guidance during surgery, and it was their choice to give fluid in response to AFM suggestions. In the study, 289 cases had AFM fluid suggestions. These cases were grouped by compliance to AFM suggestions. High, Moderate and Low compliance were defined as delivering fluid in response to an AFM suggestion > 75%, > 25% and ≤ 75%, and ≤ 25% of the time.

Results: Whereas SV and MAP did not change consistently as compliance increased, SV variation trended lower as compliance increased (Table). There was also a trend to give more volume in response to AFM suggestions, and less volume as maintenance, as compliance increased while the overall amount of fluid administered was similar between all three groups.

Conclusions: The vigilance of a computerized clinical decision support system such as AFM has the potential to assist in patient care but the advice from these systems needs to be followed to be effective. Compliance with AFM suggestions is associated with more time in a fluid-independent state without giving additional volume.

References

1.

Boekel MF et al. J Clin Monit Comput. 2021;35:1193–1202

2.

Maheshwari K et al. Anesthesiology. 2021;135:273–283

Table (abstract P203) 1 Hemodynamics and administered fluid volume for the three compliance groupsP204 Bioelectrical impedance analysis, fluid balance, and capillary leak index in critically ill patientsH Abdulghafour1, A Wong2 1King´s College Hospital NHS, Intensive Care Medicine, London, UK, 2King´s College Hospital NHS, Intensive Care Medicine / Consultant, London, UK

Critical Care 2025, 29(S1):P204

Introduction: Fluid management is crucial in critically ill patients. Bioelectrical impedance analysis (BIA) measures total body water (TBW), intracellular water (ICW), and extracellular water (ECW). The Capillary Leak Index (CLI), derived from CRP and albumin, reflects endothelial permeability. This study examines their relationship with fluid balance.

Methods: This study included 15 critically ill patients with 62 BIA measurements over three days. BIA metrics were obtained at the bedside, and cumulative fluid balances were retrieved from electronic health records. CLI and BIA parameters were analyzed using Spearman’s rank correlation.

Results: Significant correlations were found between CLI and both TBW (ρ = 0.431, p < 0.001) and ECW (ρ = 0.435, p < 0.001) (Table), indicating that higher CLI values are associated with extracellular fluid accumulation. CLI did not significantly correlate with the ECW/ICW ratio (ρ = 0.089, p = 0.489) or ECW percentage (ρ = 0.089, p = 0.489). Cumulative net fluid balance positively correlated with TBW (ρ = 0.506, p < 0.001), ICW (ρ = 0.442, p < 0.001), and ECW (ρ = 0.495, p < 0.001). Delta changes in cumulative fluid balance and body water compartments showed weak, non-significant correlations, likely due to the challenges of detecting short-term fluid shifts with BIA or limitations in fluid balance data accuracy.

Conclusions: BIA-derived parameters, including TBW, ICW, and ECW, correlated with cumulative fluid balance, confirming their role in assessing fluid status and extracellular shifts in critically ill patients. Associations with CLI highlight BIA’s ability to capture systemic fluid changes linked to endothelial dysfunction. However, weaker correlations for changes in fluid balance and body water compartments reflect the complexity of short-term fluid dynamics. Unlike previous BIA studies, this research integrates CLI to enhance understanding of fluid shifts and systemic inflammation, offering new insights into fluid management and endothelial permeability in critical care.

Table (abstract P204) Spearman: correlation between Capillary Leak Index (CLI) and BIA-derived metrics (1–4) and correlation between cumulative fluid balance and BIA metrics (5–7); CLI is calculated as (CRP [mg/dL]/albumin [g/L]) × 100;—Cumulative fluid balance represents total intake minus total output recorded since ICU admission