Precision Continuous Renal Replacement Therapy and Solute Control
Bibliographic record
Abstract
Continuous renal replacement therapy (CRRT) remains the dominant form of renal support among critically ill patients worldwide. Current clinical practice on CRRT prescription mostly relies on high quality studies suggesting no impact of CRRT dose on critically ill patients' outcomes. Recent clinical practice guidelines have been developed based on these studies recommending a static prescribed CRRT dose of 20-25 ml/kg/h. There is a rationale for renewed attention to CRRT prescription/practice based on the concept of dynamic solute control adapted to the changing clinical needs of critically ill patients. In response, Acute Disease Quality Initiative convened a 17th consensus meeting centered on re-evaluation of CRRT. This work group developed 4 themes focused specifically on CRRT dose prescription, delivery and solute control that were summarized in a series of consensus statements, along with the identification of critical knowledge gaps. CRRT dose prescription and delivery can be based on effluent flow rate. Delivered dose should be routinely monitored to ensure coherence with prescribed dose. CRRT dose should be dynamic, in recognition of between- and within-patient variation in targeted solute control or unintended solute clearance. Quality measures specific for monitoring delivered CRRT dose have been proposed that require further validation, prior to implementation, into the practice of guiding optimal CRRT dosage.
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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.019 | 0.026 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".