Tandem dialyzers with dual monitors to meet Kt/V targets
Bibliographic record
Abstract
Objective: A large body mass and/or a poorly functioning vascular access predispose to inadequate Kt/V. Double dialyzers in parallel and tandem have been shown to enhance Kt/V to levels recommended by K/DOQI. We experienced difficulties with unintended excessive ultrafitration (UF), positive transmembrane pressure (TMP)‐triggered pump stoppage, need for large volume saline infusion (inflating Kt/V), and a high incidence of clotting of the second dialyzer in tandem. Since blood and dialysate flow rates are higher in the tandem configuration, Kt/V should be theoretically higher. We developed a technique of using the tandem configuration with two monitors in which all the UF could be limited to the second dialyzer, the TMP of the two dialyzers independently controlled, TMP reversal eliminated, and saline infusion and unintended UF minimized. Methods: 3 large male patients with AV grafts (AVG) and 2 with tunneled catheters (TC) had 7 treatments (with Kt/V and URR calculated using the stop‐flow technique in the last 5) sessions of each of single, double parallel, and tandem configurations. Blood (Qb) and dialysate‐flow (Qd) were halved with Y‐connectors in the parallel configuration. Qb through both dialyzers and Qd through the second were controlled with the first monitor and Qd (TMP set to near zero) through the first dialyzer controlled with the second monitor using recirculating saline through its blood pump (with the “venous” pressure adjusted using an air‐filled syringe) in the tandem configuration. The patient's blood did not circulate through the blood‐pump of the first machine. Qd was 500 ml/min through each dialyzer in the single and tandem and 250 ml/min in the parallel configurations. Processed blood volume (dialysis time) was exactly 85 L with AVG and 60 L with TC. Heparin dosage was constant. ANOVA, 2 × k tables, and Neuman‐Keuls test were used in analyzing data. Results: Mean Kt/V (%URR) increased from 1.15 (62) with single to 1.35 (68) with parallel (p < 0.02) and 1.48 (71) with tandem (p < 0.001) dialyzers in patients with AVG but not TC [1.05 (58), 1.02 (55), and 1.25 (64) with single, parallel, and tandem, respectively]. Tandem dialyzers met targets for URR (p < 0.001) and Kt/V ( p < 0.05) more frequently than parallel with AVG but not TC. Conclusions: Tandem dialyzers with 2 monitors are more successful than parallel dialyzers in delivering target Kt/V and URR when Qb is not compromised.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".