Intensity of Continuous Renal Replacement Therapy in Acute Kidney Injury in the Intensive Care Unit: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Acute kidney injury is a common finding among patients in the intensive care unit (ICU) and is an independent predictor of mortality. The optimal intensity and timing of continuous renal replacement therapy (CRRT), in critically ill patients remain unclear. The purpose of this study was to conduct a systematic review and meta-analysis of all prospective randomized controlled trials (RCTs) to determine the effect of intensity of CRRT on the survival of patients with acute renal failure (ARF) in ICU setting. METHODS: Search strategy and data source. Electronic databases were searched on MEDLINE (through February 2010), ISIWeb of Science, and Cochrane Central Register of Controlled Trials (2010); Pub Med ''Related articles.'' Trial authors were also contacted for additional information. Study selection and data abstraction. All prospective clinical trials comparing the intensity of CRRT in adult patients with ARF and with explicit reporting of mortality were included. Three authors independently evaluated articles for eligibility and extracted data on study quality and outcomes. Meta-analysis used a random-effects model. RESULT: Of the 322 citations, 5 trials (n = 2402) were included in the meta-analysis, which met all the inclusion and exclusion criteria. Meta-analysis showed that in critically ill patients with acute kidney injury, the high-dose CRRT did not reduce mortality at 28 days. (risk ratio [RR], 0.88; 95% confidence interval [CI], 0.70-1.11; P = 0.28). CONCLUSION: In critically ill patients with acute kidney injury, the high-dose CRRT did not reduce mortality at 28 days.
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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 | 0.023 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.043 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".