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An in-Vitro Model Using Thromboelastography to Evaluate the Effects of Anticoagulants On Clot Formation in Plasma Enriched with Autologous Platelets

2012· article· en· W2588139273 on OpenAlexaff
Jorell Gantioqui, Ivan Stevic, Paul Y. Kim, Keith K. Lau, Anthony K.C. Chan, Howard H.W. Chan

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMcMaster UniversityThrombosis and Atherosclerosis Research InstituteMcMaster University Medical Centre
Fundersnot available
KeywordsThromboelastographyPlateletFondaparinuxAntithromboticRivaroxabanPlatelet-poor plasmaDabigatranTissue factorChemistryClotting timeThrombelastographyRecombinant factor VIIaPharmacologyAnticoagulantPlatelet-rich plasmaThromboplastinHeparinMedicineThrombosisAnesthesiaCoagulationInternal medicineWarfarinBiochemistry

Abstract

fetched live from OpenAlex

Abstract Abstract 1091 Background: In the presence of thrombocytopenia, antithrombotic therapy in patients with thrombosis is a challenge for the managing physicians. Current guidelines are based on anecdotal data and expert opinion. Hereby, we used an in-vitro model with thrombelastography (TEG) to study the interactions of anticoagulants with plasma clotting proteins and varying concentrations of platelets. The objective of this study is to better elucidate the range of platelet concentrations in plasma which will permit clot formation in the presence of anticoagulant. Methods: Fresh human platelet-rich plasma and platelet-poor plasma were obtained from the same donors to produce plasma samples with predefined platelet counts. For each experiment, these samples were incubated with a reaction mixture containing 30 μg/mL corn trypsin inhibitor and one of the following anticoagulants at therapeutic concentrations: heparin (0.3 IU/mL), dalteparin (1.0 IU/mL), fondaparinux (1.25 mg/L), rivaroxaban (150 ng/mL) or dabigatran (180 ng/mL). Clotting was initiated with 10 mM CaCl2 and tissue factor (TF) (Thromborel® S). The amount of tissue factor for each anticoagulant was pre-optimized so that the plasma did not clot in the absence of platelets but the clotting time would return to baseline when platelet count increased to 150 x109/L, corresponding to the expected clinical profile. All parameters for TEG (R,a, MA, TMA) were monitored for 180 min. The area under the curve for each TEG tracing in the first 15 min (AUC15) after clot initiation was estimated as it represents a global measurement of clot strength during its formation. Williams' t-test was used to compare multiple data points with its corresponding baseline control. A p < 0.05 was considered statistically significant. Results: The TF concentration in Thromborel S® was 3140 pM as determined by ELISA. We found that the optimal TF concentrations required for each anticoagulant were 1.2 pM, 0.7 pM, 0.07 pM for heparin, dalteparin, and fondaparinux respectively. No extrinsic tissue factor was required for rivaroxaban and dabigatran. In the presence of an anticoagulant, clot formation was significantly delayed when platelet counts were below 50 x109/L (fig.1). In contrast, when platelet counts were between 50–150 x109/L, there were no significant differences in all TEG parameters. The AUC15 linearly decreased when platelet counts fell below 150 x109/L. In the presence of heparinoids, the overall AUCs are reduced by an average of 6-fold comparing to the controls without anticoagulants (fig.2). In the presence of rivaroxaban or dabigatran the reduction in the overall AUCs was minimal compared to the heparinoids. The slopes of AUC15 against platelet count in the heparinoids were similar, with an average slope of 15. In contrast, the direct factor specific anticoagulants had distinctly different slopes that averaged at 56. Conclusion: Our findings suggest that, in the presence of therapeutic concentration of an anticoagulant, coagulation is delayed when platelet count is below 50 x109/L and clot formation is globally attenuated with lower platelet counts. Due to the fact that the clotting time is significantly prolonged when platelet counts fall below the threshold of 50 x109/L, we recommend withholding or reducing anticoagulants when patients with thrombocytopenia have platelet counts lower than this level. This data is consistent with the current clinical practice in adult population. Furthermore, since rivaroxaban and dabigatran required no extrinsic TF to initiate clot formation in our model, these new anticoagulants may have a wider safety margins for the treatment of thrombosis in thrombocytopenic patients. Yet, without the availability of specific antidote for these new anticoagulants, their use in patients with high bleeding risk warrants further evaluation. 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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.288
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations1
Published2012
Admission routes1
Has abstractyes

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