Inhibition of Streptokinase‐Induced, Antibody‐Mediated Platelet Aggregation with Tirofiban After Exposure to Streptokinase or Streptococcal Infection
Bibliographic record
Abstract
STUDY OBJECTIVE: To evaluate the effect of tirofiban (a glycoprotein IIb-IIIa inhibitor) in preventing streptokinase-induced, antibody-mediated platelet aggregation after administration of streptokinase or development of a streptococcal infection. DESIGN: Prospective analysis. SETTING: Research center of a Canadian hospital. PARTICIPANTS: Forty-five healthy volunteers, 45 patients who had received streptokinase within the past 3 years, and 13 patients who had a severe streptococcal infection also within the past 3 years. INTERVENTION: Blood samples were drawn to measure the extent of inhibition of streptokinase-induced, antibody-mediated platelet activation and aggregation by tirofiban. MEASUREMENTS AND MAIN RESULTS: Platelet aggregation was measured by using a turbidimetric method. The extent of inhibition by tirofiban was measured by incubating tirofiban for 2 minutes before adding streptokinase 5000 U/ml. Also, tirofiban was added 2 minutes before adding adenosine 5'-diphosphate (ADP) 2 microM/L into the last tube as a comparison. Strepto-kinase-induced, antibody-mediated platelet aggregation was observed in 10 (22%) of the 45 patients treated with streptokinase, in 3 (23%) of the 13 patients with streptococcal infection, and in none of the 45 healthy volunteers. Tirofiban inhibited streptokinase-induced, antibody-mediated platelet aggregation by 89 +/- 14% (p<0.001). Similarly, ADP-induced platelet aggregation was inhibited by 92 +/- 6% (p<0.001) with tirofiban. CONCLUSION: Streptokinase-induced, antibody-mediated platelet aggregation occurred in 13 (22%) of 58 patients who received streptokinase or were exposed to a streptococcal infection in the past 3 years. Such patients may not benefit from streptokinase therapy. In these patients, tirofiban significantly decreased the extent of antistreptokinase antibody-mediated platelet aggregation. Hence, patients undergoing streptokinase therapy may benefit from tirofiban as adjunctive therapy.
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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 | 0.000 | 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) | 0.000 | 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".