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Record W4383057489 · doi:10.1093/ndt/gfad142

Sepsis-associated acute kidney injury—treatment standard

2023· review· en· W4383057489 on OpenAlexfundno aff
Alexander Zarbock, Jay L. Koyner, Hernando Gómez, Peter Pickkers, Lui G. Forni, Mitra K. Nadim, Samira Bell, Michael Joannidis, Kianoush Kashani, Neesh Pannu, Melanie Meersch, Thiago Reis, Thomas Rimmelé, Sean M. Bagshaw, Rinaldo Bellomo, Akash Deep, Silvia De Rosa, Xose Fernandez-Perez, Faeq Husain‐Syed, Sandra L. Kane‐Gill, Yvelynne P. Kelly, Ravindra L. Mehta, Patrick Murray, Marlies Ostermann, John R. Prowle, Zaccaria Ricci, Emily See, Antoine Schneider, Danielle E. Soranno, Ashita Tolwani, Gianluca Villa, Claudio Ronco

Bibliographic record

VenueNephrology Dialysis Transplantation · 2023
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsnot available
FundersFaculty of Medicine and Dentistry, University of AlbertaSphingotec GmbHHospices Civils de LyonCentre Hospitalier Universitaire VaudoisFresenius Medical Care North AmericaUniversità degli Studi di TrentoUniversità degli Studi di FirenzeCytoSorbents EuropeDeutsche ForschungsgemeinschaftUniversity of Southern CaliforniaUniversity College DublinUniklinikum Giessen und MarburgAlberta Health ServicesKing's College LondonFondation LeenaardsUniversità degli Studi di PadovaInstituto D'Or de Pesquisa e EnsinoSanofiAbiomedTrinity College DublinKing's College Hospital NHS Foundation TrustQueen Mary University of LondonB. Braun MelsungenUniversity of DundeeUniversity of PittsburghAstraZenecaSchool of Medicine, Indiana UniversityUniversity of AlbertaMonash UniversityUniversity of California, San DiegoAlexion Pharmaceuticals
KeywordsMedicineAcute kidney injurySepsisIntensive care medicineKidney diseaseInternal medicine

Abstract

fetched live from OpenAlex

Sepsis is a host's deleterious response to infection, which could lead to life-threatening organ dysfunction. Sepsis-associated acute kidney injury (SA-AKI) is the most frequent organ dysfunction and is associated with increased morbidity and mortality. Sepsis contributes to ≈50% of all AKI in critically ill adult patients. A growing body of evidence has unveiled key aspects of the clinical risk factors, pathobiology, response to treatment and elements of renal recovery that have advanced our ability to detect, prevent and treat SA-AKI. Despite these advancements, SA-AKI remains a critical clinical condition and a major health burden, and further studies are needed to diminish the short and long-term consequences of SA-AKI. We review the current treatment standards and discuss novel developments in the pathophysiology, diagnosis, outcome prediction and management of SA-AKI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.814
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.395
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations102
Published2023
Admission routes1
Has abstractyes

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