Real-time flow–pressure coupling under pulse contour monitoring in kidney transplantation: prospective algorithm and retrospective phenotype assignment

Purpose To prospectively evaluate a pulse contour–guided algorithm for real-time flow–pressure coupling to direct fluid versus vasoactive therapy during kidney transplantation, and to retrospectively assign circulation phenotypes from intraoperative hemodynamics and assess their association with fluid responsiveness. Methods We conducted a prospective, nonrandomized evaluation of 65 KT recipients (32 deceased donor, 33 living donor) managed with GDHM. Pulse contour monitoring (HemoSphere/Acumen IQ) provided mean arterial pressure (MAP), cardiac index (CI), systemic vascular resistance index (SVRI), arterial dP/dt, and dynamic arterial elastance (EaDyn = PPV/SVV). Standardized fluid challenges were repeated every 45–60 min. Phenotypes were assigned using CI–SVRI patterns with dP/dt as a contractility proxy. Flow-pressure coupling was predefined as ΔSV ≥ 10% with EaDyn > 1.0. Primary outcomes were circulatory phenotype (initial and averaged) and per-challenge FPC responsiveness modeled as a proportion with trial weights. Results Recipients received a mean 3.57 fluid challenges; phenotype shifts were infrequent. Most patients showed limited flow-pressure coupling (41.5% had 0 responsive challenges). In binomial generalized linear models (logit), modeling the proportion of positive FPC tests with the number of challenges as trial weights, phenotype predicted per-challenge flow-pressure coupling (Hyperdynamic had lower odds versus Normal); covariates were not associated. Intraoperative volume, vasoactive support and early outcomes were similar; no protocol-related adverse events. Conclusions Circulatory phenotypes were associated with flow-pressure coupling and supported real-time fluid/inotrope decisions under GDHM during KT. Phenotype-guided GDHM enabled individualized MAP control while limiting unnecessary fluid/vasoactive therapy. Findings establish feasibility and motivate multicenter trials to test clinical impact and cross-platform validation.