Normalization of Clearances in Peritoneal Dialysis Using a Formula for Body Water Derived from an End-Stage Renal Disease Population
Bibliographic record
Abstract
OBJECTIVE: To compare body water (V) estimates from the Chertow formula (Vc), which was derived in an end-stage renal disease population, to V estimates from the Watson formulas (Vw) in continuous ambulatory peritoneal dialysis (CAPD) patients. To identify CAPD patients in whom Vc is preferred to Vw for clearance studies. DESIGN: Retrospective analysis of clearance studies. SETTING: Dialysis units of four academic medical centers. PARTICIPANTS: 302 subjects on CAPD. INTERVENTION: 613 clearance studies by standard methods. MAIN OUTCOME MEASURES: Comparisons between Vc and Vw, and between urea clearance normalized by Vc [(KtVc)ur] and Vw [(Kt/Vw)ur]. RESULTS: Vc exceeded Vw by 3.5 +/- 1.6 L (p < 0.001), or 9.6% on average. This degree of overestimation of Vw is in the range of body water estimates found in CAPD subjects with severe volume overload (> 5% of body weight) in previous studies. Total (Kt/Nw)ur exceeded total (Kt/Vc)ur by 8.6%. By linear regression, Vc = -0.589 + (1.112 x Vw), r = 0.983. Vw exceeded Vc in only 12 studies. Young age, short height, low body weight, and low prevalence of diabetes characterized the studies with Vw > Vc. Total (Kt/Vw)ur was adequate (> or = 2.0 weekly) in 276 studies. Among these, 74 studies had inadequate total (Kt/Vc)ur (< 2.0 weekly). By logistic regression, the predictors of inadequate (Kt/Vc)ur, when (Kt/Vw)ur was adequate, included the presence of diabetes, great height, and long duration of CAPD. CONCLUSIONS: Vc provides estimates of body water exceeding those provided by Vw in a great majority of CAPD patients. Consequently, approximately 25% of the clearance studies that are adequate when Vw is used as the normalizing parameter may be inadequate when Vc is used. Vc may provide a more appropriate estimate of body water than Vw in CAPD patients with volume overload.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".