Heparin albumin priming in a clinical setting for hemodialysis patients at risk for bleeding
Bibliographic record
Abstract
INTRODUCTION: Intermittent hemodialysis (IHD) is sometimes necessary in patients with a bleeding risk, i.e., before/after surgery or brain hemorrhage. In such case IHD has to be modified to limit the conventional anticoagulation used to avoid clotting of the extracorporeal circuit (ECC). We evaluated if priming using a heparin and albumin (HA) mixture could minimize the exposure to heparin. METHODS: Retrospective data from 1995 to 2013 were collected from 1408 acute dialysis treatment protocols that included 321 patients. Comparisons were made between IHD patients that had increased risk for bleeding and were treated by standard anticoagulation (Group-S), and patients at increased risk of bleeding (Group-HA). The ECC in Group-HA was primed with a solution of unfractioned heparin (UFH) (5000 Units/L) and albumin (1 g/L) in saline that was discarded after priming. There were 16 different dialyzers in the material. FINDINGS: Comparing Group-S (n = 883) with Group-HA (n = 221), the mean age was 61.6 vs. 62.2 years (P = 0.8), dialysis time was 197 vs. 190 minutes (P = 0.002), and total dose of intravenous anticoagulant/IHD was at median 5000 Units vs. 1200 Units (P = 0.001). Twenty-four percent of patients were treated without any additional heparin. Clotting resulting in interrupted dialysis was similar in both groups (0.8% for Group-S vs. 1.0% for Group-HA, P = 0.8). No secondary bleeding was reported in either group. DISCUSSION: HA priming minimized the risk of clotting and enabled acute IHD in vulnerable patients without increased bleeding, thus allowing completion of IHD to the same extent as for standard HD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".