CRRTnet: a prospective, multi-national, observational study of continuous renal replacement therapy practices
Bibliographic record
Abstract
BACKGROUND: Continuous renal replacement therapy (CRRT) is the recommended modality of dialysis for critically ill patients with hemodynamic instability. Yet there remains significant variability in how CRRT is prescribed and delivered, and limited evidence-basis to guide practice. METHODS: This is a prospective, multi-center observational study of patients undergoing CRRT. Initial enrollment phase will occur at 4 academic medical centers in North America over 5 years, with a target enrollment of 2000 patients. All adult patients (18-89 years of age) receiving CRRT will be eligible for inclusion; patients who undergo CRRT for less than 24 h will be excluded from analysis. Data collection will include patient characteristics at baseline and at time of CRRT initiation; details of CRRT prescription and delivery, including machine-generated treatment data; and patient outcomes. DISCUSSION: The goal of this study is to establish a large comprehensive registry of critically ill adults receiving CRRT. Specific aims include describing variations in CRRT prescription and delivery across quality domains; validating quality measures for CRRT care by correlating processes and outcomes; and establishing a large registry for use in quality improvement and benchmarking efforts. For initial analyses, some particular areas of interest are anticoagulation protocols; approach to fluid overload; CRRT-related workload; and patient safety. TRIAL REGISTRATION: Registered on ClinicalTrials.gov 1/10/2014: NCT02034448.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".