Prospective assessment of platelet function in patients undergoing elective resection of glioblastoma multiforme
Bibliographic record
Abstract
This prospective study was aimed to test changes in hemostasis in patients with GBM, occurring at baseline (before surgery, time 0, T0) and 2 (T2), 24 (T24), and 48-hour (T48) after surgery. We enrolled consecutive patients subjected to GBM resection (GBR group; N = 60), laparoscopic colon cancer resection (comparative CCR group; N = 40), and healthy blood donors (HBD group; N = 40). We performed 1. conventional coagulation tests 2. ROTEM (rotational thromboelastometry) parameters and 3. platelet function tests, including PFA-200 closure time when stimulated by collagen/epinephrine (COL-EPI) and ROTEM platelet, using three different activators (arachnoid acid in ARATEM, adenosine diphosphate in ADPTEM, and thrombin receptor-activating peptide-6 in TRAPTEM). Variables associated with unfavorable 1-year clinical outcome were investigated, too. We observed in GBR patients that platelet aggregometry, as assessed by ROTEM platelet parameters, was significantly impaired along with a shortened closure time. These changes were evident from T0 to T48. A decreased area under the aggregation curve in TRAPTEM was associated with improved survival (adjusted odd ratio (95% CI), 1.03 (1.01–1.06)). This study suggests that patients with GBM presented a decreased platelet aggregation from before surgery and thorough the postoperative period. Decreased platelet aggregation improved clinical outcome.
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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 | 0.001 |
| 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".