Standard Kt/V thresholds to accurately predict single-pool Kt/V targets for children receiving thrice-weekly maintenance haemodialysis
Bibliographic record
Abstract
BACKGROUND: Urea standard Kt/V (stdKt/V) provides a tool to normalize weekly small solute clearance for patients dialysed at various intervals, but it has not been studied in the paediatric haemodialysis (HD) population. METHODS: Using retrospective monthly adequacy data from children with end-stage renal disease receiving chronic thrice-weekly haemodialysis (n = 30), single-pool (spKt/V), equilibrated (eKt/V) and standard Kt/V (stdKt/V) were calculated for each individual HD session. eKt/V was estimated using Goldstein's logarithmic extrapolation method. Standard Kt/V was calculated using Leypoldt's formula based on eKt/V, duration and dialysis frequency. A spKt/V vs stdKt/V dose/frequency table was then derived from our thrice-weekly data. RESULTS: Using spKt/V of >or=1.2 as the minimal acceptable HD dose, receiver operating characteristic curve analysis was used to determine the corresponding target stdKt/V across a number of potential cutoff values. Single-pool Kt/V >or=1.2 was delivered with near certainty [sensitivity: 93.5%, specificity: 96.7%, area under the curve (AUC): 0.98] when a stdKt/V >or=2.0 was targeted. For a spKt/V >or=1.4, a target of stdKt/V >or=2.2 provided sensitivity and specificity of 73.4 and 96.1%, respectively, with an AUC of 0.94. CONCLUSIONS: Our data demonstrate that one should deliver a stdKt/V >or=2.0 for thrice-weekly paediatric HD in order to achieve a spKt/V >or=1.2; and if one wishes to ensure a spKt/V >or=1.4, then the stdKt/V must be >or=2.2. For children receiving a spKt/V >or=1.6 more than thrice weekly, the currently published adult dose/frequency table will overestimate the stdKt/V dose delivered and should be replaced by paediatric derived values.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".