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Record W2127586489 · doi:10.2215/cjn.04821107

Delivery of Renal Replacement Therapy in Acute Kidney Injury

2008· article· en· W2127586489 on OpenAlexaff
Andrew Davenport, Catherine Bouman, Ashok Kirpalani, Peter Skippen, Ashita Tolwani, Ravindra L. Mehta, Paul M. Palevsky

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2008
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineRenal replacement therapyAcute kidney injuryIntensive care medicineKidneyObservational studyNephrologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: The prescription and delivery of renal replacement therapy for acute kidney injury is subject to a wide variation and is conditioned by a multiplicity of factors. A variety of renal replacement therapy modalities are now available to treat acute kidney injury; however, there are no standards for the dosage, choice of modality, and intensity and duration of these therapies. Although several observational and interventional studies have addressed these topics, there are no consensus recommendations in this field. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The available literature on this topic and draft consensus recommendations for research studies in this area were developed using a modified Delphi approach and an international multidisciplinary network. RESULTS: The following questions were most important: What is the "dosage" of renal replacement therapy delivered to patients with stage 3 acute kidney injury? What is the optimal "dosage" of renal replacement therapy to maximize patient and renal survival? Is there a minimal "dosage" of renal replacement therapy required in patients with single-organ failure? Does modality of renal replacement therapy selected have an effect on patient and/or renal survival? In cases of continuous renal replacement therapy, does citrate anticoagulation confer a benefit? CONCLUSIONS: This report summarizes the available evidence and elaborates on the key questions and the methods that should be used so that the goal of standardizing the care of patients with acute kidney injury and improving outcomes can be achieved.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.407
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 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

Citations57
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueClinical Journal of the American Society of NephrologySame topicAcute Kidney Injury ResearchFrench-language works237,207