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.
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.
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Who cites it
4 citing papers in PubMed.
- Article
- Joint trajectories of nutritional risk and fluid balance and prognosis in critically ill adults: a dual-trajectory modeling study using MIMIC-IV and eICU.Frontiers in nutrition · 2026Article
- Association between fluid balance trajectories and prognosis in older patients with malnutrition: a group-based trajectory model analysis.Frontiers in nutrition · 2026Article
- Association between serum osmolality trajectories and mortality in sepsis patients: a retrospective multi-cohort study.European journal of medical research · 2025Article
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9 authors.
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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.
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