Decoding portal vein pulsatility: hemodynamic determinants in a post-hoc analysis of a prospective observational trial

Annals of Intensive Care volume 15, Article number: 81 (2025) 

Background

The portal vein pulsatility index (PVPI) reflects systemic congestion and is influenced by both volume status and right ventricular (RV) function. The mean systemic filling pressure analogue (Pmsa), derived from a mathematical model, estimates the interaction between stressed blood volume and systemic vascular compliance, serving as surrogate marker of volume status. This post-hoc analysis of an observational trial investigates the combined role of Pmsa and RV function as determinants of PVPI using echocardiography. Fifty-five mechanically ventilated patients with circulatory failure were included within 6 h of ICU admission following elective open-heart surgery. Fluid-tolerant patients (PVPI < 50%) underwent a passive leg raising (PLR) test; fluid-responsive patients subsequently received 7 mL/kg of Ringer’s lactate. PVPI and Pmsa were measured at five timepoints: baseline (T1), after PLR (T2), upon returning to baseline (T3), after fluid administration (T4), and 20 min post-infusion (T5). RV function parameters, including RV to LV end-diastolic area ratio (RVEDA/LVEDA), tricuspid lateral annular systolic velocity (RV S’), RV fractional area change (RVFAC), pulmonary acceleration time (PAT), and right myocardial performance index (RIMP)—were assessed at T1, T4, and T5. Only fluid-responsive patients were evaluated beyond T3.

Results

At T1, robust multilinear regression including all patients identified RVEDA/LVEDA (β = 10.38; p < 0.001), RIMP (β = − 6.54; p = 0.002), and RV S’ (β = − 0.60; p = 0.002) as significant determinants of squared PVPI. In all patients, repeated measures correlation between Pmsa and PVPI was strong across T1-to-T3 (ρ = 0.785; p < 0.001), increasing from a non-significant correlation at T1 (ρ = 0.215; p = 0.115). Generalized estimating equations conducted only in fluid-responsive patients across T1, T4, and T5 identified Pmsa (β = 4.19; p < 0.001), RV S’ (β = − 5.84; p < 0.001), RVEDA/LVEDA (β = 34.85; p = 0.018), and RIMP (β = − 35.28; p = 0.039) as significant determinants of PVPI.

Conclusion

RV function and Pmsa are key determinants of PVPI. Their combined assessment may support an individualized congestion management by guiding interventions toward volume status, RV function, or both.