The Effects of Thrombocytopenia on Clotting Profile in Whole Blood As Determined By Thromboelastography When Anticoagulant Is Present at Therapeutic or Prophylactic Concentration
Bibliographic record
Abstract
Abstract Background: Anticoagulant therapy for the treatment of venous thromboembolism in patients with concomitant thrombocytopenia has been based on anecdotal evidence. The platelet (PLT) threshold at which anticoagulant therapy should be withheld is still controversial. A PLT count of 50 × 109/L was recommended to be the threshold in the past, but newer reviews have lowered the threshold to 30 × 109/L. We previously used thromboelastography (TEG) to study clotting in plasma reconstituted with autologous PLT. Since red cells also play a significant role in hemostasis and coagulation, we hereby developed a TEG model with whole blood (WB) in order to better mimic in vivo conditions to evaluate the clot formation in thrombocytopenic blood. Objective: Using TEG to monitor clotting in whole blood samples containing unfractionated heparin (UFH) or dalteparin, we evaluated the differences in clotting profile when PLT in the samples were reduced to thrombocytopenic range. Methods: Whole blood was collected from healthy volunteers in syringes containing citrate phosphate dextrose adenine (CDPA-1, pH=5.5) and 30 μg/L corn trypsin inhibitor. Magnetic CD 61 antibody chromatography was used to deplete PLT in the blood to a count of ≤ 15 × 109/L. Platelet-depleted whole blood (PDWB) was then mixed with untouched blood from the same donor to obtain the predefined PLT counts. Clotting was initiated in the TEG cups with 10 mM CaCl2 and tissue factor (TF) in the presence of either UFH (0.3 U/mL or 0.1 U/mL) or dalteparin (1 IU/mL or 0.3 IU/mL). Due to the mechanistic differences between UFH and dalteparin, we optimized the amount of TF to maximize the sensitivity of TEG assay for individual anticoagulants; thus, 2.25 pM and 2.05 pM were used for UFH and dalteparin experiments, respectively. However, the same amount of TF was used to evaluate the clotting with the same anticoagulant at both therapeutic and prophylactic concentrations. Clotting was monitored using a Haemoscope TEG at 37 ºC for a maximum of 3 hr or until maximum amplitude (MA) had been achieved. Three parameters of clotting profile including R, MA and area under the curve within the first 15 min of clotting (AUC15) were used for further analysis. A p-value < 0.05 was considered statistically significant. Results: All3 parameters showed significant compromise of clotting when PLT decreased from 150 × 109/L to < 15 × 109/L in the presence of UFH or dalteparin at therapeutic range. When these anticoagulants were reduced to prophylactic concentration, the clotting was also significantly moderated, but to a lesser extent, comparing samples with PLT at 150 × 109/L and those with PLT < 15 × 109/L. These are in accordance with the bleeding tendency in vivo. At 30 × 109/L, the newer recommended PLT threshold at which anticoagulant should be withheld in thrombocytopenic patients, the clotting parameters did not show any significant difference as compared to those at the traditional threshold of 50 × 109/L when UFH and dalteparin were at therapeutic concentrations. Similarly, when UFH was reduced to a prophylactic concentration, we detected no significant difference in the clotting profile between 50 × 109 PLT/L and 30 × 109 PLT/L. In contrast, in samples with dalteparin at a prophylactic concentration, MA was significantly lower at 30 × 109 PLT/L when compared with that at 50 × 109 PLT/L although R and AUC15 had no statistical difference. Additionally, samples of PDWB containing either anticoagulant at prophylactic concentration had better clot formation than those samples of 50 × 109 PLT/L containing UFH or dalteparin at therapeutic concentration. Conclusion: The TEG profile of WB clotting in this in vitro model simulates bleeding tendency observed clinically. In the presence of UFH or dalteparin at therapeutic concentration, there was no statistical difference in the TEG parameters comparing thrombocytopenic blood with 50 × 109 PLT/L and 30 × 109 PLT/L, supporting the latter as the new threshold to hold anticoagulant in thrombocytopenic patients. In addition, instead of holding all anticoagulants in severe thrombocytopenic patients with PLT < 30 × 109/L, administering UFH or dalteparin at prophylactic doses may offer a safe alternative, as both imped clotting in TEG even less than those at therapeutic concentration with thrombocytopenic blood at 50 × 109 PLT/L. Fig 1. TEG profile of clots with UFH Fig 1. TEG profile of clots with UFH Fig 2. TEG profile of clots with dalteparin Fig 2. TEG profile of clots with dalteparin Disclosures No relevant conflicts of interest to declare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".