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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

In brief

Changes in kinetic eGFR predict sepsis-related AKD with 76% accuracy by day 7

In a secondary analysis of 690 septic patients, dynamic kinetic eGFR measurements identified those who progressed to acute kidney disease, reaching an area under the curve of 0.76 at day 7, while baseline MR-proADM added little extra value. Multimarker models modestly improved early discrimination but offered no clear clinical advantage over kinetic eGFR alone, underscoring the importance of serial renal function tracking.

Journal
Journal of intensive care (Q1)
Published
19 August 2026
Study design
Randomized controlled trial
Evidence level
Level 1, High (CEBM 1b)
Authors
Caroline Neumann, Frank Bloos, Philipp Franken, Thomas Lehmann, Holger Bogatsch, Johannes Ruhe
PMID
42618952
DOI
10.1186/s40560-026-00926-y

Why clinicians should know about it

  • Picked for Critical Care and Intensive Care Medicine (top studies of the week, 23 August 2026): Secondary analysis, biomarkers predict AKD in septic ICU patients
  • Picked for Biochemistry (medical) (top studies of the week, 23 August 2026): Kinetic eGFR, MR‑proADM, and H3.1 nucleosomes predict AKD in sepsis
  • Picked for Nephrology (top studies of the week, 23 August 2026): Biomarkers for AKD prediction in sepsis secondary analysis

Abstract

BACKGROUND: Sepsis-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. METHODS: This 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. RESULTS: AKD 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. CONCLUSIONS: In 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.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.