Heightened Procoagulation after Post-Operative Thromboprophylaxis Completion in Patients with Metastatic Bone Disease from Primary Colorectal Cancer
Bibliographic record
Abstract
BACKGROUND: Platelets play a role in venous thromboembolism (VTE) and in mediating colorectal cancer (CRC) progression. Still, platelets' role in hypercoagulability after surgical intervention for metastatic bone disease (MBD) is ill-defined. METHODS: In this quantitative observational study, we utilized a high-resolution imaging approach to temporally examine platelet procoagulant membrane dynamics (PMD) in four patients with MBD from primary CRC (CRC/MBD), before and after surgical intervention, over a 6-month period. We coupled this investigation with thrombelastography, quantitative plasma shotgun proteomics, and biochemical analysis. RESULTS: The plasma of CRC/MBD patients was enriched in ADAM1a, ADAMTS7, and physiological ligands for platelet glycoprotein-VI/spleen tyrosine kinase (GPVI/Syk) activation. Thromboprophylaxis attenuated procoagulation upon its initial prescription (post-operative day one, POD1); however, all patients experienced rebound procoagulation between POD3 and POD14, which was associated with Syk activation (Y525/Y526) in all patients, and a VTE event in two patients. Plasma levels of DNA-histone complexes increased steadily after surgery and remained elevated throughout the study period. Additionally, we increasingly sighted both homotypic and heterotypic platelet microaggregates after surgery in CRC/MBD patients, but not in healthy control participants' plasma. CONCLUSIONS: Our data elucidates the cell biology of a prothrombo-inflammatory state caused by disease and vascular injury, and recalcitrant to thromboprophylaxis. New mechanistic insights into hypercoagulability in CRC/MBD patients may identify novel drug targets for effective thromboprophylaxis type and duration after orthopaedic surgery.
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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) | 0.001 | 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".