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Record W2794619328 · doi:10.1159/000485598

Indications and Timing of Continuous Renal Replacement Therapy Application

2018· review· en· W2794619328 on OpenAlex
Sean M. Bagshaw, Ron Wald

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueContributions to nephrology · 2018
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsSt. Michael's HospitalUniversity of Alberta
FundersCanada Research Chairs
KeywordsMedicineRenal replacement therapyIntensive care medicineObservational studyCritically illConfoundingAcute kidney injuryClinical trialInternal medicine

Abstract

fetched live from OpenAlex

Renal replacement therapy (RRT) is increasingly utilized to support critically ill patients with severe acute kidney injury (AKI). The clinical dilemma of when to ideally start RRT in these patients has been a longstanding issue that is in need of higher quality evidence to guide clinical practice. When clinicians are confronted with patients with life-threatening complications of AKI, the decision to start RRT is straightforward. However, in the absence of clear indications, the ideal circumstances and timing that balance the perceived benefits and risks of early versus delayed RRT remain uncertain. Survey data have confirmed substantial practice variation in the timing of RRT initiation. Most observational data and small clinical trials have limitations related to confounding by indication, heterogeneity in case-mix and illness severity, and variation in defining timing thresholds for starting RRT. Recently published trials have further added to the clinical uncertainty. This concise review provides an overview of prevailing and evolving evidence on the optimal time to start RRT in critically ill patients with 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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.823
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.049
GPT teacher head0.423
Teacher spread0.374 · 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