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Record W2968552050

Performance Characteristics of a Novel Platelet Viability Assay for Heparin-Induced Thrombocytopenia

2017· article· en· W2968552050 on OpenAlexaff
Nikola Ivetic, James W. Smith, Angela Huynh, John G. Kelton, Donald M. Arnold, Ishac Nazy

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldMedicine
TopicHeparin-Induced Thrombocytopenia and Thrombosis
Canadian institutionsCanadian Blood ServicesMcMaster University
Fundersnot available
KeywordsPlateletHeparinPlatelet factor 4Heparin-induced thrombocytopeniaPlatelet activationSerotoninChemistryAnticoagulantMedicineAntibodyImmunologyPharmacologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Background: Heparin-induced thrombocytopenia (HIT) is an adverse drug reaction that causes platelet activation, leading to thrombocytopenia and a high risk of thrombosis. Platelet activation is induced by antibodies that bind to the complex of platelet factor 4 (PF4), a platelet α-granule protein, and heparin, a common blood anticoagulant. The 14C-serotonin release assay (SRA) is considered the gold standard functional assay for HIT testing due to its high sensitivity and specificity. Positive results in the SRA correlate strongly with clinical HIT; however, the SRA also requires radioactive serotonin as an endpoint marker and this limits its availability for use in diagnostic testing. In this study, we developed a platelet viability assay (PVA) using Calcein-AM, a fluorescent viability dye, as a marker to identify platelet-activating antibodies in patients with HIT. Methods: Patient sera were tested in parallel in the SRA and PVA and the results were compared and correlated for sensitivity and specificity. The SRA was performed using 14C-serotonin-labelled donor target platelets (350,000/µL; 75µL per test) incubated with 20µL of test serum and 5µL of heparin (0.1 U/mL).1 Following the reaction (60 minutes, room temperature), 100 µL of 5mM PBS/EDTA was added and the amount of 14C-serotonin released in the supernatant was measured. In our novel PVA, following the initial incubations with serum and heparin, platelets were stained with 2 µl of Calcein-AM (2 µg/mL final concentration) for 30 minutes at 37⁰C. 150 µl of 5mM PBS/EDTA was added and the fluorescence intensity of platelets was measured via flow cytometry (488nm excitation; Cytoflex). Platelet viability was reported as the percentage of platelets that maintained Calcein-AM fluorescence intensity relative to control. In total, 35 SRA-positive and 43 SRA-negative sera were tested. Results: In the PVA, the percentage of viable platelets were 91±4% for sera that were negative in the SRA (n=43); and 39±14% for sera that were positive in the SRA (n=35) (figure 1). Using a cut off defined as two-standard deviations from the mean of negative sera, sensitivity of the PVA was 100% and specificity was 93%. These results were consistent across different donor platelets. An inverse linear correlation (R=0.93) was observed between platelet viability in the PVA and serotonin release in the SRA. Conclusions:The PVA can accurately differentiate SRA positive from SRA negative HIT sera. Advantages of the PVA are that the assay is flow-cytometry based, and uses an inexpensive, easy to handle and a readily available endpoint marker for measuring platelet activation. Further prospective studies are needed to optimize the assay to develop a useful functional assay for HIT diagnosis. Disclosures Arnold: Dova: Consultancy; Amgen: Consultancy, Research Funding; Rigel: Consultancy; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Research Funding; UCB: Consultancy.

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)0.002
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.063
GPT teacher head0.316
Teacher spread0.253 · 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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Citations0
Published2017
Admission routes1
Has abstractyes

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