In one paragraphArticle in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
13 authors.
Matthieu LegrandDepartment of Anesthesia and Perioperative Care, Division of Critical Care Medicine, University of California San Francisco, San Francisco, CA, USA. Matthieu.legrand@ucsf.edu.ORCID 0000-0001-9788-5316 Hanh Nguyen *Department of Anesthesia and Perioperative Care, Division of Critical Care Medicine, University of California San Francisco, San Francisco, CA, USA.
Carolyn S Calfee *Department of Medicine and Anesthesia, Division of Pulmonary, Critical Care Medicine, University of California, San Francisco, San Francisco, CA, USA.
Yingying Lu *Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-7187-1511 Michael HarhayDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-0553-674X Kathleen LiuDepartment of Medicine, Division of Nephrology, University of California, San Francisco, San Francisco, CA, USA.
David ChenDepartment of Anesthesia and Perioperative Care, Division of Critical Care Medicine, University of California San Francisco, San Francisco, CA, USA.ORCID 0000-0002-9413-8152 Juliane BernholzAM-Pharma B.V, Utrecht, the Netherlands.
Michael MatthayDepartment of Medicine and Anesthesia, Division of Pulmonary, Critical Care Medicine, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0003-3039-8155 Alexandre MebazaaDépartement d'Anesthésie-Réanimation, Hôpital Lariboisière, Assistance Publique-Hôpitaux de Paris (AP-HP), Université Paris Cité, Paris, France.ORCID 0000-0001-8715-7753 Peter PickkersDepartment of Intensive Care Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.
Ernesto RojasDepartment of Anesthesia and Perioperative Care, Division of Critical Care Medicine, University of California San Francisco, San Francisco, CA, USA.ORCID 0000-0002-6837-7678 Alexendar R PerezDepartment of Anesthesia and Perioperative Care, Division of Critical Care Medicine, University of California San Francisco, San Francisco, CA, USA.ORCID 0009-0003-3238-4643 Funding
Advancing Precision Medicine for ARDS and SepsisR35HL177135 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Carolyn Calfee · 2025 to 2026
$2.3MThe choice of vasopressor to prevent postoperative acute kidney injury after major non-cardiac surgery: a multicenter pragmatic cluster cross-over randomized trial (the VEGA-2 trial)R01DK139484 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SACHIN KHETERPAL, Matthieu Legrand · 2024 to 2026
$2.0MIdentification of sub-phenotypes of severely ill burn patients and risk for secondary sepsis: SEPSISBURNR01GM151494 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Matthieu Legrand · 2023 to 2026
$1.5MNHLBI NIH HHS R35 HL177135NIDDK NIH HHS R01 DK139484NIGMS NIH HHS R01 GM151494U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R01-GM151494-01
6 · The paper itselfAbstract
Sepsis is the leading cause of acute kidney injury in critically ill patients, and this complication carries a high risk of death. The biology underlying it varies between patients, which may explain why treatments have not succeeded. Here we show, using an ensemble method that groups patients by patterns across hundreds of blood proteins in three independent groups of patients, that sepsis-associated acute kidney injury comprises two reproducible subphenotypes. One subphenotype shows widespread activation of inflammation, metabolism, and oxidative stress; the other shows a quieter profile. Patients in the inflammatory subtype have higher mortality, more complications, and fewer days alive and out of the intensive care unit. A simple seven-protein test reproduces these groupings and identifies them accurately in separate cohorts. In a randomized trial, the drug ilofotase alfa appears to benefit the inflammatory subtype but not the other, suggesting that this classification could guide future treatment.
Indexed as
Acute Kidney InjuryBlood ProteinsProteomicsSepsisCritical IllnessFemaleHumansInflammationMaleOxidative StressPhenotypeBlood Proteins
Identifiers
PMID42844256
PMCPMC13646287
What OpenQuestion holds
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