Cystatin C in critically ill patients treated with continuous venovenous hemofiltration
Bibliographic record
Abstract
Assessment of residual renal function in critically ill patients with acute renal failure (ARF) treated with continuous venovenous hemofiltration (CVVH) is difficult. Cystatin C (CysC) is a low-molecular-weight protein (13.3 kDa) removed from the body by glomerular filtration. Its serum concentration has been advocated for assessment of renal function in patients with kidney disease. To investigate whether the removal of CysC by CVVH is likely to influence its serum concentration, concentrations of CysC were measured in 3 consecutive samples in 18 patients with oliguric ARF treated with CVVH (2 L/hr). Samples were taken from the afferent and efferent blood lines and from the ultrafiltrate line. Concentrations of CysC did not change during the time interval studied. The mean serum concentrations of CysC were 2.25+/-0.45 mg/L in the afferent and 2.19+/-0.56 mg/L in the efferent samples (NS); ultrafiltrate concentrations of CysC were 1.01+/-0.45 mg/L. The sieving coefficient of CysC was 0.52+/-0.20; the clearance of CysC was 17.3+/-6.6 mL/min; and the quantity of CysC removed averaged 2.13 mg/hr. During CVVH (2 L/hr), the quantity of CysC removed is less than 30% of its production and no rapid changes in its serum concentration are observed. Therefore, CVVH (2 L/hr) is unlikely to influence serum concentrations of CysC significantly, which suggests that it can be used to monitor residual renal function during CVVH.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".