High-volume hemofiltration for septic acute kidney injury: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: High-volume hemofiltration (HVHF) is an attractive therapy for the treatment of septic acute kidney injury (AKI). Small experimental and uncontrolled studies have suggested hemodynamic and survival benefits at higher doses of HVHF than those used for the high-intensity arms of the RENAL and ATN studies. Our aim was to evaluate the effects of high-volume hemofiltration (HVHF) compared with standard-volume hemofiltration (SVHF) for septic AKI. METHODS: A systematic review and meta-analysis of publications between 1966 and 2013 was performed. The review was limited to randomized-controlled trials that compared HVHF (effluent rate greater than 50 ml/kg per hour) versus SVHF in the treatment of sepsis and septic shock. The primary outcome assessed was 28-day mortality. Other outcomes assessed were recovery of kidney function, lengths of ICU and hospital stays, vasopressor dose reduction, and adverse events. RESULTS: Four trials, including 470 total participants, were included. Pooled analysis for 28-day mortality did not show any meaningful difference between HVHF compared with SVHF (OR, 0.76; 95% CI, 0.45 to 1.29). No included studies reported statistically significant differences between groups for any of the secondary outcomes. Adverse events, including hypophosphatemia and hypokalemia, were more commonly observed in HVHF-treated patients, although reporting was inconsistent across studies. CONCLUSIONS: Insufficient evidence exists of a therapeutic benefit for routine use of HVHF for septic AKI, other than on an experimental basis. Given the logistic challenges related to patient recruitment along with an incomplete understanding of the biologic mechanisms by which HVHF may modify outcomes, further trials should focus on alternative extracorporeal therapies as an adjuvant therapy for septic AKI rather than HVHF.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.028 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".