Evidence map›Paper›PMID 39116013›Full record

Trial reportAnesthesia and analgesia2025

Assisted Fluid Management and Sublingual Microvascular Flow During High-Risk Abdominal Surgery: A Randomized Controlled Trial.

Sean Coeckelenbergh, Marguerite Entzeroth, Philippe Van der Linden, Moritz Flick, Maxim Soucy-Proulx, Brenton Alexander, Joseph Rinehart, Tristan Grogan, Maxime Cannesson, Jean-Louis Vincent and 3 more

Registry-linked trialAbstract readRandomized Controlled TrialEquivalence Trial
In one paragraph

Trial report in Anesthesia and analgesia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07301307 (The Use of the Hypotension Prediction Index), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07301307 narecruitingnot on this mapstarted 2026, after this paper: background citation

The Use of the Hypotension Prediction Index (HPI) Combined With the Assisted Fluid Management (AFM) Software for Perioperative Hemodynamic Optimization in Patients Undergoing General Anesthesia.

TypeinterventionalSponsorNational and Kapodistrian University of AthensRan2026 to 2027Enrolled100ConditionsIntraoperative HypotensionArmsAcumen IQ sensor with Hypotension Prediction Index (HPI) and Assisted Fluid Management (AFM) software, Conventional Intraoperative Hemodynamic management
3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Sean CoeckelenberghFrom the Department of Anaesthesiology and Intensive Care, Hôpitaux Universitaires Paris-Saclay, Université Paris-Saclay, Hôpital Paul-Brousse, Assistance Publique Hôpitaux de Paris (AP-HP), Villejuif, France.
Marguerite EntzerothFrom the Department of Anaesthesiology and Intensive Care, Hôpitaux Universitaires Paris-Saclay, Université Paris-Saclay, Hôpital Paul-Brousse, Assistance Publique Hôpitaux de Paris (AP-HP), Villejuif, France.
Philippe Van der LindenUniversité Libre de Bruxelles, Brussels, Belgium.
Moritz FlickDepartment of Anaesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Maxim Soucy-ProulxFrom the Department of Anaesthesiology and Intensive Care, Hôpitaux Universitaires Paris-Saclay, Université Paris-Saclay, Hôpital Paul-Brousse, Assistance Publique Hôpitaux de Paris (AP-HP), Villejuif, France.
Brenton AlexanderDepartment of Anaesthesiology & Perioperative Care, University of California San Diego, La Jolla, California.
Joseph RinehartDepartment of Anaesthesiology & Perioperative Care, University of California Irvine, California, Irvine, California.
Tristan GroganDepartment of Medicine Statistics Core, David Geffen School of Medicine, University of California Los Angeles, California, Los Angeles, California.
Maxime CannessonDepartment of Anaesthesiology & Perioperative Medicine, David Geffen School of Medicine, University of California Los Angeles, California, Los Angeles, California.
Jean-Louis VincentDepartment of Intensive Care, Erasme Hospital, Université Libre de Bruxelles, Brussels, Belgium.
Eric VicautUnité de Recherche Clinique, Lariboisière University Hospital, Paris 7 Diderot University, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France.
Jacques DuranteauFrom the Department of Anaesthesiology and Intensive Care, Hôpitaux Universitaires Paris-Saclay, Université Paris-Saclay, Hôpital Paul-Brousse, Assistance Publique Hôpitaux de Paris (AP-HP), Villejuif, France.
Alexandre JoostenDepartment of Anaesthesiology & Perioperative Medicine, David Geffen School of Medicine, University of California Los Angeles, California, Los Angeles, California.

Funding

Personalized Risk Prediction for Prevention and Early Detection of Postoperative Failure to RescueR01EB035028 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Maxime Cannesson · 2023 to 2026
$2.3M
NIBIB NIH HHS R01 EB035028
6 · The paper itself

Abstract

backgroundImplementation of goal-directed fluid therapy (GDFT) protocols remains low. Protocol compliance among anesthesiologists tends to be suboptimal owing to the high workload and the attention required for implementation. The assisted fluid management (AFM) system is a novel decision support tool designed to help clinicians apply GDFT protocols. This system predicts fluid responsiveness better than anesthesia practitioners do and achieves higher stroke volume (SV) and cardiac index values during surgery. We tested the hypothesis that an AFM-guided GDFT strategy would also be associated with better sublingual microvascular flow compared to a standard GDFT strategy.

methodsThis bicenter, parallel, 2-arm, prospective, randomized controlled, patient and assessor-blinded, superiority study considered for inclusion all consecutive patients undergoing high-risk abdominal surgery who required an arterial catheter and uncalibrated SV monitoring. Patients having standard GDFT received manual titration of fluid challenges to optimize SV while patients having an AFM-guided GDFT strategy received fluid challenges based on recommendations from the AFM software. In all patients, fluid challenges were standardized and titrated per 250 mL and vasopressors were administered to maintain a mean arterial pressure >70 mm Hg. The primary outcome (average of each patient's intraoperative microvascular flow index (MFI) across 4 intraoperative time points) was analyzed using a Mann-Whitney U test and the treatment effect was estimated with a median difference between groups with a 95% confidence interval estimated using the bootstrap percentile method (with 1000 replications). Secondary outcomes included SV, cardiac index, total amount of fluid, other microcirculatory variables, and postoperative lactate.

resultsA total of 86 patients were enrolled over a 7-month period. The primary outcome was significantly higher in patients with AFM (median [Q1-Q3]: 2.89 [2.84-2.94]) versus those having standard GDFT (2.59 [2.38-2.78] points, median difference 0.30; 95% confidence interval [CI], 0.19-0.49; P < .001). Cardiac index and SVI were higher (3.2 ± 0.5 vs 2.7 ± 0.7 l.min -1 .m -2 ; P = .001 and 42 [35-47] vs 36 [32-43] mL.m -2 ; P = .018) and arterial lactate concentration was lower at the end of the surgery in patients having AFM-guided GDFT (2.1 [1.5-3.1] vs 2.9 [2.1-3.9] mmol.L -1 ; P = .026) than patients having standard GDFT strategy. Patients having AFM received a higher fluid volume but 3 times less norepinephrine than those receiving standard GDFT ( P < .001).

conclusionsUse of an AFM-guided GDFT strategy resulted in higher sublingual microvascular flow during surgery compared to use of a standard GDFT strategy. Future trials are necessary to make conclusive recommendations that will change clinical practice.

Indexed as

AbdomenFluid TherapyMicrocirculationMouth FloorAgedFemaleHumansMaleMiddle AgedMonitoring, IntraoperativeProspective StudiesStroke VolumeTreatment Outcome

Identifiers

PMID39116013
PMCPMC12621645

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.