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Record W2062091289 · doi:10.1097/aln.0b013e31824f951b

Acute Kidney Injury and Extrarenal Organ Dysfunction

2012· review· en· W2062091289 on OpenAlexaff
Steven C. Yap, H. Thomas Lee, David S. Warner

Bibliographic record

VenueAnesthesiology · 2012
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsColumbia College
Fundersnot available
KeywordsMedicineAcute kidney injuryOrgan dysfunctionRenal replacement therapyPathophysiologyMultiple organ dysfunction syndromeIntensive care unitIntensive care medicineKidneyComplicationCardiorenal syndromeBioinformaticsInternal medicineSepsis

Abstract

fetched live from OpenAlex

Acute kidney injury (AKI) is a frequent complication in the intensive care unit with limited therapeutic modalities. Although survival from isolated AKI has improved with recent advancements in renal replacement therapy, mortality from AKI complicated by multiorgan dysfunction has remained unchanged and is estimated to be approximately 50%. Hence, defining and better understanding the pathophysiology of distant organ dysfunction associated with AKI is clinically important because it may lead to new treatment strategies. In animal models, it has become increasingly clear that AKI is not an isolated event but results in remote organ dysfunction involving the heart, lungs, liver, intestines, and brain through an inflammatory mechanism that involves neutrophil migration, cytokine expression, and increased oxidative stress. The purpose of this brief review is to summarize the human and basic science evidence for AKI and its detrimental effects on distant organs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.068
GPT teacher head0.379
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations183
Published2012
Admission routes1
Has abstractyes

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