Effects of Renal Replacement Therapy on Renal Recovery after Acute Kidney Injury
Bibliographic record
Abstract
Recovery of kidney function following an episode of acute kidney injury (AKI) is now acknowledged as a vital patient-centered outcome with clear health economic implications. In approximately 5-8% of critically ill patients with more severe forms of AKI, support with renal replacement therapy (RRT) is provided. Recent data have suggested that rates of RRT utilization in AKI are increasing. Despite advances in our understanding of how best to prescribe acute RRT in critically ill patients with AKI, additional aspects remain uncertain, predisposing to suboptimal delivery and variation in practice. Importantly, if, when, how, and by what principles we apply acute RRT for AKI are all treatment decision-related factors that are modifiable and may interact with recovery of kidney function. Limited data, mostly from observational studies and secondary analyses, have explored the specific association between acute RRT and recovery. Available data are not able to clarify whether providing any RRT in otherwise eligible patients with AKI impacts recovery. They are also unable to inform whether the timing or circumstance under which RRT is started impacts recovery. No studies have evaluated whether there is an optimal time to start RRT to maximize the probability of recovery. Accumulated evidence, mostly derived from observational studies, suggests initial therapy in critically ill patients with AKI with continuous RRT, compared with intermittent modalities, improves the probability of recovery to dialysis independence. Evidence from high-quality randomized trials failed to show any association between delivered dose intensity of RRT and recovery. The use of biocompatible membranes for acute RRT may improve recovery in AKI; however, data are inconsistent. Limited data have evaluated the impact of membrane flux properties on recovery. Preliminary data have suggested that circuit anticoagulation with citrate, which results in a reduction in membrane-induced oxidative stress and leukocyte activation, may be associated with improved recovery; however, further corroborative data are needed. Additional evidence, ideally from randomized trials, is clearly needed to inform best practice in the delivery of acute RRT to optimize probability of recovery of kidney function for survivors of AKI.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".