Hemofiltration compared to hemodialysis for acute kidney injury: systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: The objective of this systematic review and meta-analysis was to determine the effect of renal replacement therapy (RRT), delivered as hemofiltration vs. hemodialysis, on clinical outcomes in patients with acute kidney injury (AKI). METHODS: MEDLINE, EMBASE and CENTRAL databases and conference abstracts were searched to June 2012 for parallel-group or crossover randomized and quasi-randomized controlled trials (RCTs) evaluating hemofiltration vs. hemodialysis in patients with AKI. Two authors independently selected studies and abstracted data on study quality and outcomes. Additional information was obtained from trial authors. We pooled data using random-effects models. RESULTS: Of 6,657 citations, 19 RCTs (10 parallel-group and 9 crossover) met inclusion criteria. Sixteen trials used continuous RRT. Study quality was variable. The primary analysis included three parallel-group trials comparing similar doses of hemofiltration and hemodialysis; sensitivity analyses included trials comparing combined hemofiltration-hemodialysis or dissimilar doses. We found no effect of hemofiltration on mortality (risk ratio (RR) 0.96, 95% confidence interval (CI) 0.73 to 1.25, P = 0.76; three trials, n = 121 (primary analysis); RR 1.10, 95% CI 0.88 to 1.38, P = 0.38; eight trials, n = 540 (sensitivity analysis)) or other clinical outcomes (RRT dependence in survivors, vasopressor use, organ dysfunction) compared to hemodialysis. Hemofiltration appeared to shorten time to filter failure (mean difference (MD) -7 hours, 95% CI (-19,+5), P = 0.24; two trials, n = 50 (primary analysis); MD -5 hours, 95% CI (-10, -1), P = 0.01; three trials, n = 113 (including combined hemofiltration-hemodialysis trials comparing similar doses); MD -6 hours, 95% CI (-10, -1), P = 0.02; five trials, n = 383 (sensitivity analysis)). Data primarily from crossover RCTs suggested that hemofiltration increased clearance of medium to larger molecules, including inflammatory cytokines, compared to hemodialysis, although almost no studies measured changes in serum concentrations. Meta-analyses were based on very limited data. CONCLUSIONS: Data from small RCTs do not suggest beneficial clinical outcomes from hemofiltration, but confidence intervals were wide. Hemofiltration may increase clearance of medium to larger molecules. Larger trials are required to evaluate effects on clinical outcomes.
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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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".