Timing of Initiation and Discontinuation of Renal Replacement Therapy in AKI
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".