Randomised controlled study investigating standard dose continuous renal replacement therapy (CRRT) versus low-dose CRRT in critically ill patients with acute kidney injury (AKI): study protocol for a prospective, randomised, controlled, international, multicentre trial (the ‘Ketzerei’ trial)
Bibliographic record
Abstract
INTRODUCTION: The only supportive therapy for patients with severe acute kidney injury (AKI), a common complication among the critically ill, is dialysis. Based on the literature and current guidelines, continuous renal replacement therapy (CRRT) with a total effluent dose of 20-25 mL/kg/hour and adjustments to ensure such dose is delivered despite down time (eg, due to surgical procedures) is recommended. However, experimental and clinical studies suggest that azotaemia, which can be induced by lowering the effluent dose, may accelerate renal recovery. This clinical study investigates whether a lower effluent dose (10-15 mL/kg/hour) for a maximum of 7 days or until successful (>24 hours) liberation of CRRT in critically ill patients with a dialysis-dependent AKI accelerates renal recovery and reduces time on CRRT compared with guideline-directed standard dose (25-30 mL/kg/hour). METHODS AND ANALYSIS: The Ketzerei trial is an international, multicentre randomised, controlled trial, designed to investigate if a lower effluent dose (10-15 mL/kg/hour) accelerates renal recovery and reduces the time on CRRT compared with the guideline directed standard effluent dose (25-30 mL/kg/hour). The study aims to enrol 150 critically ill patients with a dialysis-dependent AKI. Eligible patients will be randomised to receive either a standard effluent dose (control group, 25-30 mL/kg/hour) or lower effluent dose (interventional group, 10-15 mL/kg/hour). The primary endpoint is the number of days free from CRRT and alive (from randomisation through day 28). Key secondary endpoints include the number of (serious) adverse events due to potential uremia, the duration of RRT and intensive care unit survival. ETHICS AND DISSEMINATION: The Ketzerei trial has been approved by the Ethics Committee of the Chamber of Physicians Westfalen-Lippe (2023-343 f-s), the University of Muenster and subsequently by the corresponding Ethics Committee of the participating sites. Results will be disseminated widely and published in peer-reviewed journals, presented at conferences and will guide patient care and further research. TRIAL REGISTRATION NUMBER: clinicaltrials.gov (NCT06021288).
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.033 | 0.005 |
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".