Evidence map›Paper›PMID 40426163›Full record

ArticleCritical care (London, England)2025

Trajectories of fluid management after the initiation of renal replacement therapy in critically ill patients: a secondary analysis of the STARRT-AKI trial.

William Beaubien-Souligny, Ehsan Gamarian, Jean-Maxime Côté, Javier A Neyra, Frederic Baroz, Neill K J Adhikari, Kevin Thorpe, Sean M Bagshaw, Ron Wald

Abstract read
In one paragraph

Article in Critical care (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors.

William Beaubien-SoulignyDivision of Nephrology, Centre Hospitalier de l'Université de Montréal, Montreal, Canada. William.beaubien-souligny@umontreal.ca.
Ehsan GamarianApplied Health Research Centre (AHRC), Toronto, Canada.
Jean-Maxime CôtéDivision of Nephrology, Centre Hospitalier de l'Université de Montréal, Montreal, Canada.
Javier A NeyraDivision of Nephrology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.
Frederic BarozMcGill University, Montreal, Canada.
Neill K J AdhikariDepartment of Critical Care Medicine, Sunnybrook Health Sciences Centre, and Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
Kevin ThorpeDalla Lana School of Public Health, University of Toronto, Toronto, Canada.
Sean M BagshawDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Albert and Alberta Health Services, Edmonton, Canada.
Ron WaldDivision of Nephrology, St. Michael's Hospital, Toronto, Canada.

Funding

CIHR Canada Research Chair in Critical Care Outcomes and Systems EvaluationCIHR MOP142296, 389635, IPR 139081Fonds de Recherche du Québec - Santé JuniorNIDDK NIH HHS R01DK128208, R01DK133539, U01DK12998, and U54DK137307
6 · The paper itself

Abstract

backgroundFluid management is an essential component of renal replacement therapy (RRT) in critically ill patients. Both a positive cumulative fluid balance (CFB) and a high net ultrafiltration (NUF) rate have been reported to be associated with adverse outcomes in epidemiological studies, although the overall trajectory of fluid balance after RRT initiation is not well-described. We aimed to characterize trajectories of fluid management parameters during RRT and analyse the effect of CFB/NUF on outcomes as a trajectory rather than single or aggregated time points over the first week after initiation of RRT.

methodsThis is a secondary analysis using fluid balance data focusing on individuals enrolled in the standard-strategy arm of the STARRT-AKI trial who initiated RRT. Cumulative fluid balance (CFB) following RRT initiation and daily net ultrafiltration (NUF) adjusted for body weight during the first 7 days after initiation of RRT were the main independent exposures. We modeled the trajectory of fluid parameters using spline functions and used latent trajectory analysis methods to identify predominant trajectories to compare patients' characteristics and outcomes. We employed logistic regression and multivariable joint longitudinal models to compare the odds and determine the time-dependent association between fluid parameters (CFB and NUF) and 90-day mortality across and within the trajectory classes identified.

resultsWe included 855 patients in the primary analysis. After excluding erroneous fluid balance data, we identified two distinct CFB/NUF trajectories. Class A (82.8%) was characterized by a slight increase in CFB and low/stable NUF during the week following RRT initiation while class B (17.2%) was characterized by an increasingly negative CFB with initially higher daily NUF during the first 4 days followed by a stabilization after day 4. In an adjusted analysis, individuals classified in class B were at lower risk for 90-day mortality (aOR: 0.48 CI 0.32; 0.70) p < 0.001) compared to class A. Time-dependent analysis revealed higher CFB was associated with mortality only in those with a class A trajectory (aHR 1.29, 95% CI 1.03-1.55, p = 0.03).

conclusionsDistinct CFB/NUF trajectories convey prognostic information beyond single-day fluid balance or NUF values and should be considered when formulating or interpreting fluid management strategies.

Indexed as

Acute Kidney InjuryFluid TherapyRenal Replacement TherapyAgedCritical IllnessFemaleHumansLogistic ModelsMaleMiddle AgedWater-Electrolyte BalanceAcute kidney injuryFluid balanceRenal replacement therapyUltrafiltration

Identifiers

PMID40426163
PMCPMC12107945

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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.