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<p>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. 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&#xa0;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 &gt; 1.0. Primary outcomes were circulatory phenotype (initial and averaged) and per-challenge FPC responsiveness modeled as a proportion with trial weights. 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. 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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月10日

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  • Jennifer Cutler,
  • Leon Wang,
  • Hooman Golfeiz,
  • Eric McDaniel,
  • Ryan Barnette,
  • Wesley Glick,
  • Avner Gereboff,
  • Leah Breen,
  • Blake Simon,
  • Robert Kariger

摘要

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. 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. 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. 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.