PB0141 Characterizing the Transcriptomic Profile of Acquired Hemophilia Using RNA-Seq
Bibliographic record
Abstract
Background: Preoperative use of platelet function tests contributes to the decrease of re-intervention rate due to bleeding and the necessity of transfusion in coronary artery bypass grafting (CABG) patients.Aims: The aim was to investigate the predictive value and to justify routine preoperative use of impedance aggregometry (multiplate electrode test) in these patients.Methods: A prospective observational trial which included 416 consecutive patients subjected to elective isolated CABG was conducted.The Multiplate ® test was used to assess platelet function.Platelet function test results, postoperative blood loss, and transfusion requirements were compared between high and low bleeding risk patients.Receiver operating characteristic analysis was performed to assess the sensitivity and specificity of the arachidonic acid (ASPI) and adenosine di-phosphate high sensitive (ADP HS) test.Results: ADPHS and ASPI test results significantly predicted total bleeding > 1000 ml (AUC, 0.685, p < 0.001; 0.695, p = 0.039).Sensitivity and specificity were 62.9% and40.0%,for ADPHS ≤6 02, and 70.8% and 41.8%, for ASPI ≤ 453.The sensitivity and specificity of cut-off values recommended by the manufacturer were 84.2% and 40.0% for ADPHS ≤ 500, while for ASPI < 600 the values were 54.7% and 62.2%.More platelets and cryoprecipitate were transfused in patients with ADPHS ≤ 602.5 ( p < 0.001; p = 0.035).Patients with ADPHS ≤ 500 had a higher rate of red blood count, platelet and cryoprecipitate transfusion ( p < 0.001p<0.001;p = 0.013).The manufacturer's ASPI test cut-off values showed no statistically significant prediction for a higher transfusion rate.Conclusion(s): Preoperative platelet function tests should be conducted systematically for all elective CABG patients who were on dual antiplatelet therapy after adjusting test cut-off values for each population.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 0.001 |
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.
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".