Clinical consequences of heparin‐free hemodialysis
Bibliographic record
Abstract
Heparin-free hemodialysis (HF-HD) has been increasingly used in patients at risk for bleeding, especially in the intensive care unit (ICU). Lack of heparin can reduce solute clearances in continuous hemofiltration; the effect on HD is undefined. Failure to recognize an effect of the anticoagulation strategy upon delivered clearance could contribute to the known problem of underdialysis in the ICU. In addition, the consequences of "locking" dialysis catheters with concentrated heparin solutions are also unclear. This study was designed to define the clinically relevant consequences of HF-HD and catheter locking. In part I, we performed 200 HD treatments on inpatients, of which 100 were performed with heparin, and 100 were performed as HF-HD. We calculated prescribed and delivered Kt/V and dialysis efficiency. In part II, a separate group of 14 patients undergoing HF-HD via central venous catheters had measurement of activated partial thromboplastin time (aPTT) during the last hour of dialysis, as well as 15, 60, and 240 min after catheters were locked with 1:5000 heparin. The prescribed Kt/V was 1.74+/-0.31 for standard HD with heparin vs. 1.66+/-0.36 for HF-HD (p=ns). The delivered Kt/V was 1.42+/-0.32 vs. 1.36+/-0.38 (p=ns). Efficiency was 0.82 vs. 0.84 (p=ns). Baseline aPTT was 28+/-5 s, and increased to 126+/-54 s, 15 min after locking (p<0.0001) and to 71+/-50 s, 60 min after locking (p=0.005). By 240 min, the mean aPTT had fallen to 33+/-9 s (p=0.03), although individual values were still as high as 50 s. The HF technique does not compromise delivery of dialysis to inpatients. Increased treatment time is not necessary. Locking catheters with heparin after HF-HD resulted in prolonged unintentional anticoagulation.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".