Evidence map›Paper›PMID 42618952›Full record

ArticleJournal of intensive care2026

Predictive performance of kinetic eGFR, midregional proadrenomedullin, and H3.1 nucleosomes for acute kidney disease in sepsis: a secondary analysis of a large multicentre randomized controlled trial.

Caroline Neumann, Frank Bloos, Philipp Franken, Thomas Lehmann, Holger Bogatsch, Johannes Ruhe, Sepnet Critical Care Trials Group

Registry-linked trialAbstract read
In one paragraph

Article in Journal of intensive care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00832039 (Prospective, Randomized Multicenter Trial of Adjunctive Intravenous Therapy With Sodium-selenite), which is not on this map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

NCT00832039 phase3completednot on this map

Prospective, Randomized Multicenter Trial of Adjunctive Intravenous Therapy With Sodium-selenite(Selenase®, Double-blinded) and a Procalcitonin Guided Causal Therapy (Open) of Severe Sepsis or Septic Shock.

TypeinterventionalSponsorKompetenznetz SepsisRan2009 to 2013Enrolled1,089ConditionsSevere Sepsis, Septic ShockArmssodium-selenite, Placebo, Procalcitonin guided therapy
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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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

7 authors.

Caroline NeumannDepartment of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany. caroline.neumann@med.uni-jena.de.ORCID https://orcid.org/0000-0002-9242-6505
Frank BloosDepartment of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.
Philipp FrankenCenter for Clinical Studies, Jena University Hospital, Jena, Germany.
Thomas LehmannCenter for Clinical Studies, Jena University Hospital, Jena, Germany.
Holger BogatschInstitute for Medical Informatics, Statistics and Epidemiology (IMISE) and Clinical Trial Centre Leipzig, University of Leipzig, Härtelstraße 16-18, 04107, Leipzig, Germany.
Johannes RuheDepartment of Internal Medicine III, Nephrology, University Hospital Jena - Friedrich Schiller University, Jena, Germany.
Sepnet Critical Care Trials Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis-associated acute kidney injury (SA-AKI) frequently progresses to acute kidney disease (AKD) and is linked to poor outcomes. We evaluated whether combining biomarkers reflecting complementary pathophysiological domains-histone H3.1 nucleosomes (cellular injury), midregional pro-adrenomedullin (MR-proADM; endothelial dysfunction), and kinetic estimated glomerular filtration rate (kinetic eGFR; dynamic renal function)-improves prediction of AKD and renal recovery.

methodsThis secondary analysis of the multicentre randomized SISPCT trial included 690 patients with sepsis after exclusion of patients with pre-existing renal replacement therapy or missing AKI data. Biomarkers and kinetic eGFR were assessed at baseline, day 2, and day 7. Multivariable logistic regression models adjusted for age, sex, and non-renal SOFA score were used to assess associations with AKD. Predictive performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). Calibration for the combined models for each day was evaluated using bootstrap-corrected calibration plots. Clinical utility was assessed using decision curve analysis with fivefold cross-validation.

resultsAKD occurred in 196 patients (28.4%). At baseline, only MR-proADM was independently associated with AKD (adjusted OR 1.17, 95% CI 1.08-1.28; p < 0.001), whereas H3.1 and kinetic eGFR were not. At day 2 and day 7, only changes in kinetic eGFR were independently associated with AKD (both p < 0.001). Discriminative performance increased over time, with AUCs for the combined model of 0.65 at baseline, 0.70 at day 2, and 0.76 at day 7. At later time points, kinetic eGFR consistently showed the highest discriminative performance based on the point estimates of the AUC. An overall good calibration performance was shown. Decision curve analysis demonstrated only modest and inconsistent additional clinical net benefit of the combined model compared with kinetic eGFR alone. AKD was associated with increased 90-day mortality (55% vs. 24%; risk ratio 2.3, 95% CI 1.9-2.9). Biomarkers showed limited and inconsistent performance for prediction of renal recovery.

conclusionsIn patients with sepsis, MR-proADM at baseline and dynamic changes in kinetic eGFR during the first week were independently associated with AKD, whereas histone H3.1 nucleosomes provided limited predictive value. Although multimarker models seemed to modestly improve baseline discrimination, this advantage was not sustained over time and added little clinical benefit beyond kinetic eGFR. These findings highlight the value of dynamic renal function assessment for risk stratification of SA-AKI progression to AKD. Trial registration ClinicalTrials.gov Identifier: NCT00832039.

Indexed as

Acute kidney diseaseH3.1 nucleosomesKinetic eGFRMidregional pro-adrenomedullinSepsis

Identifiers

PMID42618952
PMCPMC13488215

What Socratic holds

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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 Socratic graph.