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Record W2145254543 · doi:10.2215/cjn.04871107

Timing of Initiation and Discontinuation of Renal Replacement Therapy in AKI

2008· article· en· W2145254543 on OpenAlexaffabout
R. T. Noel Gibney, Eric A. J. Hoste, Emmanuel A. Burdmann, Timothy E. Bunchman, Vijay Kher, Ravindran Viswanathan, Ravindra L. Mehta, Claudio Ronco

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2008
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineRenal replacement therapyDiscontinuationAcute kidney injuryIntensive care medicineNephrologyReimbursementInternal medicineHealth care

Abstract

fetched live from OpenAlex

Patients with acute kidney injury (AKI) often require initiation of renal replacement therapy (RRT). Currently, there is wide variation worldwide on the indications for and timing of initiation and discontinuation of RRT for AKI. Various parameters for metabolic, solute, and fluid control are generally used to guide the initiation and discontinuation of therapy; however, there are currently no standards in this field. Members of the recently established Acute Kidney Injury Network, representing key societies in critical care and nephrology along with additional experts in adult and pediatric AKI, participated in a 3-d conference in Vancouver in September 2006 to evaluate the available literature on this topic and draft consensus recommendations for research studies in this area. Key questions included the following: what are the indications for RRT, when should acute RRT support be initiated, and when should RRT be stopped? This report summarizes the available evidence and describes in detail the key questions, and some of the methods of answering them that will need to be addressed with the goal of standardizing the care of patients with AKI and improving outcomes.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.127
GPT teacher head0.431
Teacher spread0.304 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations148
Published2008
Admission routes2
Has abstractyes

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