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Record W1965018904 · doi:10.1097/mcc.0b013e328332f653

Fluid accumulation and acute kidney injury: consequence or cause

2009· review· en· W1965018904 on OpenAlexaff
Josée Bouchard, Ravindra L. Mehta

Bibliographic record

VenueCurrent Opinion in Critical Care · 2009
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineAcute kidney injuryCritically illKidneyIntensive care medicineFluid intakeInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Fluid accumulation and fluid overload are frequent findings in critically ill patients and in those suffering from severe acute kidney injury. This review focuses on the consequences associated with fluid overload in critically ill patients with or without associated acute kidney injury and discusses the potential mechanisms by which acute kidney injury can contribute to fluid overload and whether fluid overload can also contribute to kidney dysfunction. RECENT FINDINGS: Fluid overload has recently been linked to adverse outcomes in critically ill patients suffering from acute kidney injury. However, whether significant fluid accumulation can contribute to acute kidney injury has not been investigated. SUMMARY: Fluid overload is independently associated with increased mortality in patients with acute kidney injury and contributes to worsen outcomes in critically ill patients. Further studies are required to determine the influence of fluid overload on organ function and overall prognosis.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.481
GPT teacher head0.603
Teacher spread0.122 · 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

Citations55
Published2009
Admission routes1
Has abstractyes

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