Effect of unfractionated heparin and low molecular weight heparin on the clotting of platelet-reduced whole blood: an in-vitro study utilizing thromboelastography
Bibliographic record
Abstract
Treatment of venous thromboembolism with concomitant thrombocytopenia is challenging. The platelet threshold for safe administration of anticoagulants is under debate, with minimum platelet count of 50 × 109/l being recommended as the safe cutoff. However, some evidence suggests administration of anticoagulants may still be safe at platelet levels of 30 × 109/l. Therefore, we developed an in-vitro thromboelastography (TEG) study to examine the effect of therapeutic or prophylactic levels of unfractionated heparin (UFH) and low molecular weight heparin (LMWH) on the clotting profile of platelet-reduced whole blood. Using magnetic bead-based antibody chromatography, platelets were removed to achieve platelet-depleted blood (<10 × 109/l of platelets). Platelet-depleted blood was then mixed with whole blood to produce blood samples with platelet counts of 30 × 109, 50 × 109 and 150 × 109/l. These blood samples were incubated with therapeutic or prophylactic levels of UFH or LMWH in disposable TEG cups. Clotting was initiated with 10 mmol/l calcium and optimized tissue factor levels for each anticoagulant used (2.25 pmol/l for UFH and 2.05 pmol/l for LMWH). Clotting was monitored by TEG at 37 °C for 180 min. The following TEG parameters were evaluated: R (time to clot), maximum amplitude (strength of clot) and area under the curve in 15 min (overall speed and strength of the clot at 15 min of clotting). No statistically significant differences were observed between platelet counts of 30 × 109 and 50 × 109/l for R, maximum amplitude or area under the curve in 15 min for most of the therapeutic and prophylactic doses of UFH and LMWH tested in this study. Use of anticoagulants compromised all of the TEG parameters relative to a normal platelet count of 150 × 109/l, in a dose dependent manner. The current study demonstrates that in-vitro clotting is impaired with use and increasing doses of anticoagulants. Despite this observation, we did not observe a significant difference in clotting between platelet levels of 30 × 109 and 50 × 109/l. Overall, this work provides further insight in the debated use of anticoagulants in patients with venous thromboembolism and concomitant thrombocytopenia, and provides support for possible use of anticoagulants at lower platelet thresholds.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".