Comparison of volume of blood processed on haemodialysis adequacy measurement sessions vs regular non-adequacy sessions
Bibliographic record
Abstract
BACKGROUND: Knowledge that adequacy measures such as the urea reduction ratio (URR) or Kt/V(urea) are being measured on haemodialysis may influence the behaviour of patients or staff such that the treatment may be better on those days. This study therefore tested the hypothesis that mean volume of blood processed (VBP), utilized as a surrogate for adequacy, is higher on adequacy measurement days than non-measurement days. METHODS: Patients were identified who had been on haemodialysis over the preceding 8 months. Primary outcome was the difference in the mean VBP (in litres) on URR measurement compared with non-URR measurement days (DeltaVBP(U)(-N)). Univariate and multivariate correlates of mean VBP and DeltaVBP(U)(-N) were also determined. RESULTS: Eighty-nine patients were identified who met inclusion and exclusion criteria. Linear regression demonstrated a weak relationship between VBP and URR (r=0.24, P<0.02). This relationship was much stronger when VBP was adjusted for patient weight (mean VBP/weight; r=0.78, P<0.0001). The overall mean VBP was 87.4 l (+/-1.2 l) and the average DeltaVBP(U)(-N) was 1.1 l (+/-0.3 l) (P=0.001). Twenty per cent of patients had a clinically relevant DeltaVBP(U)(-N) of >3.6 l. Patients with a graft or fistula had a significantly higher DeltaVBP(U)(-N) than patients with a tunnelled catheter. CONCLUSIONS: This study demonstrates that the average VBP is less on non-URR than on URR measurement days; this difference was clinically important in >20% of patients. Univariate analysis indicated that the use of a fistula or graft correlated with a higher DeltaVBP(U)(-N). This implies that our current method of assessing dialysis adequacy does systematically overestimate the average delivered dose of dialysis in a subset of patients.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".